The effects of soluble silicon fertilization on monocots and dicots have been widely studied. However, little is known regarding its effects on protecting epiphytes against insect and fungal pests. The efficacy of silicon fertilizer to reduce damage by thrip pest complexes, namely: Thrips palmi Karny, Frankliniella occidentalis Pergande, Chaetanaphothrips orchidii Moulton, and Chaetanaphothrips signipennis Bagnall (Thysanoptera: Thripidae), and fungal pathogens: Botrytis cinerea Persoon (Helotiales: Sclerotiniaceae) and Fusarium spp. Link (Hypocreales: Nectriaceae) was examined during a nine-month greenhouse trial in Hawaii. The trial assessed yield, quality, and pest damage across three common varieties of dendrobiums. All replicates received additional soluble silicon fertilizer applications alternating weekly between soil drench and foliar (50 mg Si/plant) applications. Yield, quality, and spray length, pest damage, plant vigor, SPAD, and leaf temperature were measured. Data were analyzed using a generalized linear model (glm) with repeated measures followed by post-hoc pair-wise comparisons in R, version 4.3.1. Treatment effects were significant at P

This data descriptor summarizes the process applied and data gathered from 50 publications/papers reporting on the use of photography generated by tourists, tour operators and members of the public, with a particular focus on the crowdsourcing of photographs through online platforms and social networking sites (SNSs) as a method of research for wildlife conservation and ecotourism. The papers were collected in a systematic literature review to inform a pilot study of the feasibility of using SNSs to crowdsource georeferenced photographs of endangered Bornean Pygmy Elephants (Elephas maximus borneensis) taken by ecotourists along the Lower Kinabatangan River region of Sabah, Malaysia. Papers were sourced using the Murdoch University Findit online-search tool to search over 100 databases, including Proquest, Scopus and Web of Science. The criteria for a paper to be included in the review (and shared via the dataset attached to this this data descriptor) were that it was peer-reviewed, published in English, between 1997 and the 31 December 2017, had the full text accessible online and reported on a study or studies that utilized photographs that tourists, tour operators and/or members of the public generated and shared via SNSs or online platforms.

Background: This study aimed to develop and evaluate a dietary self-care promotion program for hemodialysis patients based on Hurley's self-efficacy model. Methods: The needs of hemodialysis patients were identified, and an online community-based dietary self-care promotion program was developed with expert evaluations. 44 hemodialysis patients were randomly assigned to an experimental group (n=22) and a control group (n=22). The program was applied to the experimental group for four weeks. Before and after the intervention, as well as four weeks after the intervention, dietary self-efficacy, dietary self-care behavior, interdialytic weight gain, serum phosphorus, and serum potassium were assessed in both groups. Results: Significant differences over time and between groups were observed in dietary self-efficacy, interdialytic weight gain, serum phosphorus, and serum potassium. The interaction between time and group was also significant. While no significant differences were found over time in dietary self-care behavior, significant group differences and interaction effects between time and group were identified. Conclusions: The results indicate that the dietary self-care promotion program using an online community for hemodialysis patients is more effective in enhancing dietary self-efficacy and dietary self-care behavior compared to conventional treatment. This suggests the clinical applicability of the proposed dietary self-care promotion program.

Objective: Diabetes disproportionately affects African Americans leading to higher morbidity and mortality. This study explores the experiences of African Americans adults who successfully self-manage their type 2 diabetes (called Peer Ambassadors) and provided phone-based peer support in a 6-month culturally tailored diabetes self-management program for African Americans guided by the Information-Motivation-Behavioral skills model. Design: A group discussion using a semi-structured discussion guide was conducted. Qualitative content analysis was used to identify the facilitators and barriers to completing the role of a Peer Ambassador, and to develop strategies for overcoming possible challenges in the future. Setting: Key informant discussions were conducted in a community location to gain insights into Ambassadors’ motivations and challenges in delivering peer support. Participants: Three Peer Ambassadors completed ethics training, peer mentor training and received a phone call guide before providing support to their peers. Results: There were four core themes related to Peer Ambassador experiences: (1) Motivation to be a Peer Ambassador, (2) Program elements that supported Peer Ambassador role, (3) Key elements of achieving engagement, and (4) Challenges related to being a Peer Ambassador. Conclusions: This study showed Peer Ambassadors in a culturally tailored peer-supported self-management program found fulfillment in sharing experiences and supporting peers. They highly valued educational group sessions for knowledge updates and sustaining their health-related goals, suggesting the potential benefits of recognizing milestones or providing advanced training for future program sustainability. Findings suggest the importance of recruiting motivated patients and providing effective facilitation for peer support roles, including addressing barriers such as time commitment and lack of socialization opportunities.

Education is expected to support the development of a more sustainable way of thinking, working, and living. Although there is a broad range of literature on Education for Sustainable development (ESD), the role of principals in the implementation of sustainability and ESD in schools has rarely been taken into consideration. However, based on the results of school effectiveness research, one can assume that school principals exert a significant influence on ESD. Sustainability is a leadership issue. When a school aims at integrating sustainability and ESD, the principal plays a pivotal role. She or he has to support the endeavor wholeheartedly and credibly, organize a participative process of school development, push ahead sustainability and ESD in the daily life of the school, support teaching staff in the application of ESD, involve students and offer them opportunities to launch their own initiatives. This article seeks to support principals in leading their schools towards sustainability. Four stages of the integration of Sustainability and ESD in a school are defined. For each of these stages, a number of actions and management strategies are suggested and explained in detail.

This research delves into a detailed exploration of the thermal decomposition behavior of bio-based polymers, specifically Thermoplastic Starch (TPS) and Poly(lactic acid) (PLA). The study focuses on the impact of three different heating rates under a nitrogen atmosphere, providing comprehensive insights into the thermal stability of these eco-friendly polymers. In particular, the TPS kinetic model is examined, encompassing the decomposition of three distinct fractions. In contrast, PLA exhibits a simplified kinetic behavior requiring only a fraction described by a zero-order model. The kinetic study involves a systematic investigation into the individual contributions of key components within TPS, including starch, glycerin, and polyvinyl alcohol (PVA). This nuanced analysis contributes to a comprehensive understanding of the thermal degradation process of TPS and PLA, enabling the optimization of processing conditions and the prediction of material behavior across varying thermal environments. Furthermore, the incorporation of different starch sources and calcium carbonate additives in TPS enhances our understanding of the polymer's thermal stability, offering insights into potential applications in diverse industries.

Directive 2018/844/EU on energy efficiency claims almost 80% of final energy consumption in EU is used within the buildings. Subsequent Directive (EU) 2023/1791 introduced in 2023 expected 68% of the World population living in urban areas. Both Directives enhanced the role of energy management (EM) applied on the city buildings. The study introduces the development of energy management in Czech municipalities between the years 2009 and 2023. The main goal of this article is to present selected results of the unique national survey focused on the energy management in Czech municipalities conducted in 2023 and compare it with results of national surveys implemented in 2009 and 2018. The main method is the evaluation of deep survey conducted among the municipal representatives or energy managers in the past with the new survey conducted in 2023. The results show that EM became notably more important issue for the most Czech municipalities. The number of cities implementing EM significantly grew and the number of city energy managers increased too. On the other hand, the used potential of energy savings triggered by establishing EM is insufficient. This article should be applied to stress power of municipal EM in performing energy efficiency and RES projects and encouraging government to support municipal energy managers in their complex role.

Decision tables have been used for many years in data processing and business applications to simulate complex rule sets. Several computer languages have been developed based on rule systems and they are easily programmed in several current languages. Land management and river-reservoir models simulate complex land management operations and reservoir management in highly regulated river systems. Decision tables are a precise yet compact way to model the rule sets and corresponding actions found in these models. In this study, we discuss the suitability of decision tables to simulate management in the river basin scale Soil and Water Assessment Tool (SWAT+) model. Decision tables are developed to simulate automated irrigation and reservoir releases. A simple auto irrigation application of decision tables was developed using plant water stress as a condition for irrigating corn in Texas. Sensitivity of the water stress trigger and irrigation application amounts were shown on soil moisture and corn yields. In addition, the Grapevine Reservoir near Dallas, Texas was used to illustrate the use of decision tables to simulate reservoir releases. The releases were conditioned on reservoir volumes and flood season. The release rules as implemented by the decision table realistically simulated flood releases as evidenced by a daily NSE (Nash-Sutcliffe Efficiency) of 0.52 and a percent bias of -1.1%. Using decision tables to simulate management in land, river and reservoir models was shown to have several advantages over current approaches including: 1) mature technology with considerable literature and applications, 2) ability to accurately represent complex, real world decision making, 3) code that is efficient, modular and easy to maintain, and 4) tables that are easy to maintain, support, and modify.

Traceability is the ability to determine the path of a product from purchase to consumption to determine when and where it originated. This paper aimed to determine the factors that influence fishers’ decision-making to participate in tuna traceability program, it also explores the determinants of fish catch for small-scale fishers and the feasibility of implementing tuna traceability in the Davao Gulf, Philippines. The result of the interview showed that the significant factors that highly affected the decision-making of fishers in implementating tuna traceability program: boat capacity, fishing hours and communication of fishers (P≤0.05). Household size, years in community, fishing hours, volume of fish sold, and the fishers' communication in the fishing ground (P≤0.05) were other factors that determined the daily catch of the fishers. The results of this study showed that fishers from the Davao Gulf were willing to be part of traceability program that would sustain and increase the value of their fish catch. Moreover, communication was shown to be critically needed in such programs adjusting it for the fish catch to remain fresh or of good quality. Our study will help in deterring and mitigating illegal, unregulated and unreported fishing (IUU) through fish catch traceability.

Self-report measurement is frequently used in human sports to assess training adaptations [1, 2]. This is a technique novel to the equestrian sport. The aim of this study was to describe how elite event riders of Germany evaluate their own fitness as well as that of their horses for the entire duration of an eventing season. Additionally, correlations with possible influencing external factors such as type of training or duration of grazing were also investigated. Short online questionnaires were used to allow eight riders to describe the training of their horses. Five criteria (general performance, ability to concentrate, general state of mind, general muscular condition and emotional wellbeing) were used to assess both, their horse's, as well as their own wellbeing. A 1-10 rating scale was used to score each criterion resulting in an average of 38 points out of 50 (maximum wellbeing) for horse (Std. dev. 0.55) and rider (Std. dev. 0.65) respectively. A total of 120 questionnaires were analysed. A correlation could be demonstrated (Spearman's correlation coefficient = 0.5) between rider and horse score, whereby it only became a linear correlation above 30 points. In addition, the horse score correlates positively with its success at competitions. While the horses were rated similarly throughout the season, the riders’ perceived welfare was higher in the middle of the season compared with the beginning and end of the season. Regularly turned-out horses resulted in higher horse scores (Linear mixed model, p=0,04, n=120). It can be concluded that the self-report measurement of fatigue and wellbeing can be a useful tool for trainers and riders to better determine the horse’s fatigue and recovery. It should be noted that external factors influence both, rider and horse assessment.

Soybean (Glycine max L.) is a vital leguminous crop known for its rich nutritional profile, includ-ing high protein and oil content, making it a valuable resource in global agriculture and human nutrition. In Pakistan due to regulatory issues non-GMO soybean is grown therefore, the universal herbicide control method is not applicable. Similarly, for other crops, specific herbicides are avail-able but for soybean no crop specific herbicide is present. A comprehensive study was conducted over two growing seasons, in 2022 and 2023, at Agronomic Research Farm University of Agri-culture Faisalabad. The research involved 16 different treatments, including both six pre-emergence and eight post-emergence herbicides as well as a control group and weedy check. Findings of this study showed that critical importance of weed management in soybean cultiva-tion, as unchecked weed infestation can lead to substantial yield losses. Among the pre-emergence herbicide S-Metolachlor + Pendimethalin performed best and showed higher plant height (54.33 cm & 53.67 cm), 100 grain weight (11.57 g & 12 g), seed yield plant-1 (13.07 g and 12.87 g), lower Susceptibility Index (10%), higher weed control percentage (91.21% & 95.65%) higher weed con-trol efficiency (92.02% & 93.43%), herbicide efficiency index (27.54% & 32.48%) and lower weed index (18.16% & 21.70%) during 2022 and 2023 respectively. However, in post emergence herbi-cide the Fluizefop-p-butyl is most effective herbicide due to less crop injury 10% Susceptibility In-dex, higher plant height (42.67 cm & 44 cm), whole plant weight (93.33 g & 95 g), 100-grain weight (11.40 g & 11.77 g), seed yield plant-1 (12.87 g & 13.13 g), higher weed control percentage (91.12% & 91.03%) higher weed control efficiency (89.73% & 92.36%, herbicide efficiency index (21.18% & 30.41%) and lower weed index (19.42% & 20.08%) in both 2022 and 2023 respectively. Notably, herbicides such as S-Metolachlor + Atrazine + Mesotrione, Topramezone, Mesosulfu-ron-methyl + Iodosulfuron-methyl sodium and Mesotrione + Atrazine led to complete plant mor-tality, resulting lethal to soybean. The findings of this study support the hypothesis that screened the best suitable herbicides with less plant injury, and higher efficiency index. So, it is recom-mended that the application of S-Metolachlor + Pendimethalin as PRE and Fluizefop-p-butyl as POST showed the least injury and best weed control results with higher grain yield.

A recent publication defined lockdown “revisionism” as “the spread of misinformation on lockdowns and other public health measures.” We used this publication to analyze the claim that questioning lockdowns or other public health interventions and mandates amounts to lockdown “revisionism” and “misinformation”. We suggest that the term ‘revisionism’, like the term ‘misinformation’ contained in its definition, were merely labels used to denigrate evidence-based contrary conclusions so as to avoid having to critically appraise the best evidence itself. We aim to describe how, by glossing over topics without fully engaging with the best evidence available, the assertions made do not withstand critical scrutiny. We suggest that, to ensure lessons are learned for the future, we must be willing to engage in rigorous and open debate – calling reasonable critical scrutiny of evidence ‘misinformation’, ‘disinformation’, or ‘revisionism’ is not supportive of this goal. Finally, we suggest that a main lesson from the COVID-19 pandemic is not to have an increased focus on so-called ‘misinformation’ and ‘revisionism’, but rather to re-discover the emergency management process of making decisions that ensure multidisciplinary representation, transparency, cost-benefit analyses of courses open using the best evidence available, and that protects against censorship and groupthink.

The ongoing COVID-19 pandemic has profoundly affected millions of lives globally, with some individuals experiencing persistent symptoms even after recovering. Understanding and managing the long-term sequelae of COVID-19 is crucial for research, prevention, and control. As a result, to monitor the health of individuals affected by these conditions, they must maintain up-to-date health records using digital health informatics apps for surveillance. In this review, we provide an overview of the existing literature on identifying long COVID manifestations through hierarchical classification and the characterization of long COVID by different hierarchical groups based on the Human Phenotype Ontology (HPO). We outline the aspects of the National COVID Cohort Collaborative (N3C) and Researching COVID to Enhance Recovery (RECOVER) in artificial intelligence (AI) to identify long COVID. Knowledge exploration, using the concept map for the clinical pathways of long COVID presented in this paper, provides an overview of the data needed to explore tackling the long-term effect of COVID-19 by integrating innovative cohesive frameworks and designing health informatics-based applications. To the best of our knowledge, this is the first paper to explore the potential incorporation of long COVID as a variable risk factor within a digital health informatics application.

The shrimp industry in the Philippines play a vital role in the local and national economy through exports with markets abroad such as in South Korea, Japan, the USA, and others. This study aimed to describe the various cultural and operational characteristics of small-holder and commercial shrimp farms (P. vannamei) in the Davao region. It also evaluated the current risks and challenges faced by the shrimp farmers. A semi-structured questionnaire that focused on shrimp farmers, and operators in the region was used to collect data with N=41 farmers and operator. The results showed that respondents were engaged in small-holder farming activities which had an average yield of 10 tons/ha. On the other hand, the commercial farms that operate intensively had an average yield of 24 tons/ha. Most small-holder operators used electric generator machines to conduct aeration in their farms using paddlewheels and blowers. For the commercial farms, more paddlewheels and blowers were employed per pond compared to small-holder farms. Generally, the income of a farm was related to the yield of farms or the number of fries rather than social factors or size of farms cultivated. In terms of input costs, feeds were found to have the highest input costs, followed by the fry, fuel, labor, and others (fertilizers and water treatment chemicals). Most of the farmers mentioned that they are affected by diseases such as white spot syndrome (60%), black gills (35%), and red tail (5%). They perceived that the main contamination come from the water source (31%). The main threats mentioned are declining shrimp prices in the market, source of fry, water disposal, and overstocking, and water quality. Based on this study, farmers should follow good shrimp aquaculture practices and there is a need for them to regularly monitor their water quality.

Insecticidal toxins from Bacillus thuringiensis (Bt) are valuable tools for pest management worldwide, contributing to the management of human disease insect vectors and phytophagous insect pests of agriculture and forestry. Here, we report the effects of dual and triple Bt toxins expressed in transgenic cotton cultivars on the fitness and demographic performance of Helicoverpa zea (Boddie), a noctuid pest known as cotton bollworm and corn earworm. Life-history traits were determined for individuals of three field populations from a region where H. zea overwintering is likely. Triple-gene Bt cotton cultivars expressing Cry and Vip3Aa toxins killed 100% of the larvae in all populations tested. In contrast, dual-gene Bt cotton expressing Cry1Ac+Cry1F and Cry1Ac+Cry2Ab2 allowed population growth with the intrinsic rate of population growth (rm) 38% lower than on non-Bt cotton. The insects feeding on Bt cotton plants expressing Cry1Ac+Cry2Ab2, Cry1Ac+Cry1F, or Cry1Ab+Cry2Ae exhibited reduced larval weight, survival rate, and increased development time. Additionally, fitness parameters varied significantly among the insect populations, even on non-Bt cotton plants, likely because of their different genetic background and/or previous Bt toxin exposure. This is the first report of the comparative fitness of H. zea field populations on dual-gene Bt cotton after the recent reports of field resistance to certain Bt toxins. These results document the population growth rates of H. zea from an agricultural landscape with 100% Bt cotton cultivars. Our results will help to refine models designed to predict resistance evolution and improve insect resistance management for Bt crops.

Enhancing energy efficiency within the building sector is imperative to curbing energy losses, given that this sector alone contributes to over 34% of global energy consumption. Employing a building management system, along with its regular updates, presents a strategic avenue to decrease energy usage, enhance building energy efficiency, and more. Tailored control strategies, aligned with the unique characteristics and usage patterns of each building, are essential for achieving energy savings. This article presents an evaluation of HVAC system efficiency in office buildings, utilizing a data-driven approach coupled with simulations conducted in IDA ICE software. The research explores the control strategy of an office building equipped with a constant air volume HVAC system, featuring a regularly controlled air handling unit. The objective is to boost energy efficiency while striking a balance between occupant comfort and energy consumption. Findings indicate that by analyzing measured data and adjusting configurable parameters, building energy consumption can be significantly reduced. Close monitoring of indoor parameters by building operators and corresponding adjustments to the HVAC system can yield energy savings of up to 16%. Leveraging these insights, the paper suggests integrating data-driven and dynamic simulation methods into building management system models to optimize HVAC systems, enhance energy efficiency, and advance ambitious carbon neutrality objectives.

This research presents alternative solutions for an Energy Efficiency Management System (EEMS) serving as a framework for optimizing the energy consumption algorithm and lowering energy consumption. First, a monitoring Wireless Sensor and Actuator Network (WSAN) is used for sensing, measuring, gathering data, and modeling all the dynamic disturbance parameters of the rooms in the building. Second, integrated software for metering and controlling the processes of digital data flow is used. Third, an alternative solution is proposed to reduce energy consumption. The primary benefits of this system are real-time monitoring; rapid, alternative solutions; and the ability to make a prudent decision on how to lower energy consumption. The system shows instant and accumulated solutions for short and long-term time planning. The solutions identified can be implemented in the same buildings under the same circumstances. The universities of Majmaah and Philadelphia have buildings with similar infrastructure. The system was applied to the buildings at Philadelphia University. The results were generalized to both universities. After implementation, the energy consumption of the EEMS using WSAN (based on the monitoring was reduced up to 23% when compared to that of the initial state.

Continuous discovery and update of applications or their boundaries running in cloud environments in an automatic way is a highly required function of modern data center ops solutions. Prior attempts to address this problem within various products or projects were/are applying rule-driven approaches or machine learning techniques on specific types of data − network traffic as well as property/configuration data of infrastructure objects, which all have their drawbacks in effectively identifying roles of those resources. The current proposal (ADLog) leverages log data of sources, which contain incomparably richer contextual information, and native constructs of VMware Aria Operations for Logs in terms of Event Types and their distributions to group those entities, potentially automatically enrich with indicative tags, and recommend for further management tasks and policies. Our methods discriminate not only diverse kinds of applications, but also their specific deployments thus providing hierarchical representation of the applications in time and topology. For several applications under Aria Ops management in our experimental test bed, we discover those in terms of similarity behavior of their components with a high accuracy. The validation of the proposal paves the path for an AI-driven solution in the cloud management scenarios.

The implementation of management systems has become a strategic advantage in achieving business goals, especially in industrial organizations, but the implementation of social responsibility requirements is especially ethical. Large multinational companies have long been developing and, in particular, implementing their own codes of conduct, which include their suppliers, to demonstrate their commitment to Corporate Social Responsibility (CSR). The compliance with CSR requirements from stakeholders is thus extended or intertwined with requirements in established management systems (MSs). The objectives of the study were to (1) analyze the different approaches to CSR in internationally recognized cross-industry and industry-specific standards and codes in different industries; (2) select the most appropriate framework for assessing the degree of applicability of CSR in the selected management systems and develop a methodology for its assessment; (3) apply the proposed methodology (referred to as SRIMS) in the selected areas: automotive industry, research organization, and metallurgical industry; (4) through ANOVA, validate its use for assessing the overall level of CSR applicability in an organization's established management systems. The application of the Bonferroni method confirmed the hypotheses that the developed SRIMS model is a sufficiently appropriate tool for assessing the overall level of applicability of CSR requirements to established MSs.

The sustainable use of precious water resources requires effective water management. In the European Union, water management is mainly regulated by the Water Framework Directive (2000/60/EC), introducing an integrated river basin management approach. As EU directive, the legislation needs to be implemented in the Member States, entailing not only legal transposition, but also application and enforcement in Member States. One major instrument introduced by the Water Framework Directive is the environmental goal achievement obligation of art. 4 WFD, containing also a deterioration ban with several exemptions. This study compares transposition, application and enforcement of the exemption of permanent deterioration (art. 4 (7) WFD) in the context of the environmental goal achievement obligation regime in Lower Saxony (Germany) and the Netherlands. The study rests on a legal analysis of literature, policy documents and jurisprudence. Although based on the same EU directive wording and case law of the European Court of Justice, the deterioration ban and the exemption of permanent deterioration are implemented rather differently: While the deterioration ban is predominantly understood as planning obligation in the Netherlands, it became an important permit requirement in Lower Saxony since the Weser-ruling of the European Court of Justice.

The water resources policy under climate change impacts water security, which should ensure enough water of good quality for humans and nature. Integrated water management is the state-of-the-art policy support model that, after 20 years in use, failed to achieve in many countries its primary goal of water bodies' good ecological status. Here, we show that this is due to the substantial externalities the anthropocentric character of the model generates. From the historical analysis, three main results are obtained: 1) the nature-human interplay is always composed of the coexistence of two opposite behaviors of conflict and cooperation; 2) this contradiction is a dialectical, general ontological attribute; 3) on the balance of power between nature and humans, three clusters are identified: i) naturalistic; ii) dualistic; iii) anthropocentric. A novel behaviorist dialectical conflict resolution model can resolve the differences between stakeholders and natural laws. The harmonic symbiosis of humans with nature removes environmental externalities and can lead to sustainable water security. Three case studies from the literature illustrate the merits of the new dialectical model.

This study focuses on understanding how global auto parts companies manage innovation by analyzing keywords in CEO messages from their reports. The study involved three key phases: (1) extraction of innovation-related keywords emphasized in CEO messages, (2) comparison of innovation-related keyword usage between high-performing (upper group) and low-performing (lower group) companies, and (3) analysis of the characteristics of innovation management via internal meaning and the structural interpretation of keywords. A comparison between the upper and lower groups revealed distinct differences in the emphasized keywords. The mapping of open innovation success factors, based on keywords extracted according to eigenvector centrality, identified Provision of Resources and Governance as central to innovation management in the upper group. These findings serve as a benchmark for establishing the direction, vision, and strategy of innovation management in the lower group.

Households and businesses are generating unprecedented levels of electrical and electronic wastes (e-waste), fueled by modernisation and rapid obsolescence. While the challenges imposed by e-waste are similar everywhere in the world, disparities in progress to deal with it exists; with developing nations such as South Africa lagging. The increase in e-waste generation increases the need to formulate strategies to manage it. This paper presents an overview of e-waste management on a global and South African scenarios with a specific case for Cathode Ray Tube (CRT) waste management practices in South Africa. CRTs present the biggest problem for recyclers and policy makers because they contain hazardous elements such as lead and antimony. Common disposal practices have been either landfilling or incineration. The research into the South African practices with regards to CRT waste management showed that there is still more to be done to effectively manage this waste stream. This is despite clear waste regulatory frameworks in the country. However, recent developments have placed e-waste as a priority waste stream, which should lead to intensified efforts in dealing with it. Overall, these efforts should aim to maximise diversion from landfilling and to create value-addition opportunities, leading to social and environmental benefits.

This study addresses the prediction of recurring failures in water supply networks, a complex and costly task, but essential for the effective maintenance of these vital infrastructures. Using historical failure data provided by Companhia de Água e Esgotos da Paraíba (CAGEPA), the research focuses on predicting the time until the next failure at specific points in the network. The authors divided the failures into two categories: Occurrences of New Faults (ONF) and Recurrences of Faults (RF). To make the predictions, they used predictive models based on Machine Learning, more specifically on MLP (Multi Layer Perceptron) neural networks. The study revealed that, by analyzing data from past failures and considering factors such as altitude, number of failures on the same street and days between failures, it is possible to achieve an accuracy greater than 80% in predicting failures within a 90-day interval. This demonstrates the feasibility of using fault history to predict future water supply outages with significant accuracy. These forecasts allow water utilities to plan and optimize their maintenance, minimizing inconvenience and losses. The article contributes to the field of water infrastructure management by suggesting that the data-driven approach can be applied in other cities or in networks of different types, such as energy or communication networks. The conclusions highlight the importance of data collection and analysis in preventing failures and optimizing water utilities’ resources.

Plant N concentration (PNC) has been commonly used to guide farmers in assessing maize (Zea mays L.) N status and making in-season N fertilization decisions. However, PNC varies based on the development stage and therefore a relationship between biomass and N concentration is needed (i.e., critical N dilution curves; CNDC) to better understand when plants are N deficient. A few CNDC have been developed and used for plant N status diagnoses, but have not been tested in the US Midwest. The objective of this study was to evaluate under highly diverse soil and weather conditions in the US Midwest the performance of CNDCs developed in France and China for assessing maize N status. Maize N rate response trials were conducted across eight US Midwest states over three years. This analysis utilized plant and soil measurements at V9 and VT development stages and final grain yield. Results showed that the French CNDC (y=34.0x-0.37, where y is critical PNC, x is aboveground biomass) was better with a 91% N status classification accuracy compared to only 62% with the Chinese CNDC (y=36.5x-0.48). The N nutrition index (NNI), which is the quotient of the measured PNC and the calculated critical N concentration (Nc), based on the French CNDC was significantly related to soil nitrate-N content (R2=0.38-0.56). Relative grain yield on average reached a plateau at NNI values of 1.36 at V9 and 1.21 at VT, but for individual sites ranged from 0.80 to 1.41 at V9 and from 0.62 to 1.75 at VT. The NNI threshold values or ranges optimal for crop biomass production may not be optimal for grain yield production. It is concluded that the CNDC developed in France is suitable as a general diagnostic tool for assessing maize N status in US Midwest. However, the threshold values of NNI for diagnosing maize N status and guiding N applications vary significantly across the region, making it challenging for guiding specific on-farm N management. More studies are needed to determine how to effectively use CNDC to make in-season N recommendations in the US Midwest.

The ecotoxic effect of glyphosate, a commonly used Parthenium control herbicide, was evaluated in laboratory on biological and fitness attributes of Zygogramma bicolorata. Bioassay of glyphosate was carried within a minimum range of field recommended dose. Indirect exposure experiment reveals that glyphosate caused maximum mortality of 3^rd larval instars, extends the development stages of larvae, pre pupation and pupation. Significant negative effect was observed on sex ratio, fecundity, egg viability and on other fitness attributes. The study demonstrated the non-compatibility of glyphosate and unsafe with Zygogramma bicolorata. The study concludes that owing to acute toxicity of glyphosate at recommended field dose may be used in combination with Z. bicolorata for successful control of Parthenium weed, but needs to be evaluated under natural field conditions.

Development of the continental shelf has accelerated significantly as nations around the world seek to harness offshore renewable energy. Many areas marked for development align with submerged palaeolandscapes. Poorly understood and difficult to protect, these vulnerable, prehistoric landscapes provide specific challenges for heritage management. Indeed, there now appears to be a schism between what underwater cultural heritage policy intends and what it is achieving in practice. Shortcomings in international and national legislature ensures that large parts of the continental shelf, including areas under development, may have little or no legal protection.

Studies of Phytophthora impacts in forests generally focus on individual species without recogni-tion that Phytophthora occur in multispecies communities. We investigated community structure of Phytophthora species in the rhizosphere of Agathis australis (kauri) in Te Wao Nui o Tiriwa / Waitākere Ranges, New Zealand, in the context of kauri dieback disease expression. Soil sampling and tree health monitoring was conducted on 767 randomly selected mature kauri trees. Phy-tophthora species were detected using both soil baiting and DNA metabarcoding of eDNA. Four species were detected with soil baiting (P. agathidicida, P. cinnamomi, P. multivora, and P. pseudo-cryptogea) and an additional three species with metabarcoding (P. kernoviae, P. cactorum/P. aleatoria and an unknown clade 7 species). Phytophthora cinnamomi was the most abundant species and was distributed throughout the forest. Both P. multivora and P. agathidicida were limited to forest edges, suggesting more recent arrivals. P. agathidicida presence was strongly correlated with declining canopy health, confirming its role as the main river of kauri dieback. The limited distribution of P. agathidicida and infrequent detections (11.0% samples) suggests that that this species is spreading as an introduced invasive pathogen and provide hope that with strategic management uninfected areas of the forest can be protected. The frequent detections of P.cinnamomi and P. multivora, from symptomatic trees in the absence of P. agathidicida suggest more research is needed to understand their roles in kauri forest health.

In this paper I take the book by Michel Serres “Thumbelina” as the occasion for a reflection on the conceptual basis of knowledge management, as it was built by Ikujiro Noanka and co-workers. The direct access to knowledge that Thumbelina practices together with her peers is, in fact, for me, a god observation point to bring the reflection of Nonaka further, towards the discovery of a new understanding of knowledge and knowing processes. If the digital revolution is third step after writing and printing, in the soft changes in the relations between human beings and knowledge, then it poses in an urgent manner the problem to deepen our understanding of what knowledge and intelligence are and to change our practice at the education level and to design new digital tools to support our knowledge management processes.

Multi-rotor drones, a kind of unmanned equipment which is widely used in military, commercial consumption and other fields, has been developed very rapidly in recent years. However, their short flight time has hindered the expansion of their application range. This can be addressed by utilizing hydrogen fuel cells, which exhibit high energy density, strong adaptability to ambient temperature, and no pollution emissions, as the power source. Accordingly, the application of hydrogen fuel cells as the power source in multi-rotor drones is a promising technology that has attracted significant research attention. This paper summarizes the development process of hydrogen fuel cell mul-ti-rotor drones and analyzes the key obstacles that need to be addressed for the further development of hydrogen fuel cell multi-rotor drones, including structural lightweight, hydrogen storage methods, energy management strategies. Additionally, prospects for the future development of hydrogen fuel cell multi-rotor drones are presented.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

Keywords: Energy harvesting, Hybrid, Medical Wearable Sensor Nodes, Health Monitoring, Power Management

Water recycling and reuse are corner stones in the water management that may be compromised by the presence of pollutants. Among them, pharmaceuticals can overcome the standard water treatments and require sophisticated approaches to remove them. Sorption is an economically affordable alternative limited by the need of sorbents that exhibit sorption coefficient (Kd) higher than 500 L/kg to be useful in wastewater treatment plants (WWTPs). We report that th cross-linking of dextrin (Dx) with divinyl sulfone (DVS) in presence of 1 mmol or 5 mmol of ibuprofen (IBU) yields the insoluble polymers pDx1 and pDx5 with improved affinity for IBU, Kd higher than 600 L/kg for ciprofloxacin (CIP) and ofloxacin and an outstanding Kd higher than 4000 L/kg for erythromycin (ERY), when assayed against a cocktail of 6 drugs. The characterization of the polymers by XRPD, TGA and SEM reveals that both pDx1 and pDx5 share similar features, with an ERY Kd of 13 x 103 for pDx1 and 6.4 x 103 for pDx5. The facts that new affinities and improvements in Kd can be achieved by cross-linking Dx in presence of other molecules that promote a pre-organization, broaden the applications of DVS cross-linked polysaccharide as sustainable and eco-friendly sorbents.

This conceptual, interdisciplinary paper will start by introducing the commencement of a new era in which human society faces continuously accelerating technological revolutions, named for short ‘Padkos’. In this context, a conceptual model of sustainable development with a focus on knowledge sharing and management will be proposed. The construct of knowledge management will be unpacked into a three-layer model with a focus on the knowledge-human and data-machine spheres. Then, each sphere will be discussed with concentrating on the learning and decision- making processes, the digital supporting systems and the human actors’ aspects. Moreover, the recombination of new knowledge development and contemporary knowledge management into one amalgamated construct will be proposed. The holistic conceptual model of knowledge sharing for sustainable development is comprised by time, cybersecurity and two alternative humanistic paradigms (Homo Technologicus and Homo Sustainabiliticus). Two additional particular models are discussed in depth. First, a recently proposed model of quantum organizational decision-making is elaborated. Next, a boundary management and learning process is particularized. The paper ends with several implications for the future based on the deliberations in the paper and the models discussed.

Increasing agricultural productivity is indispensable to meet future food demand. Crop im-provement programs rely heavily on genetic diversity. The success of weeds in the ecosystem can be attributed to genetic diversity and plasticity. Weedy rice, a major weed of rice, has diverse morphology and phenology, implying wide genetic diversity. Study was conducted to genotype weedy rice accessions (n =54) previously phenotyped for herbicide tolerance and allelopathic potential using 30 SSR markers. Cultivated rice (CL163, REX) and allelopathic rice (RONDO, PI312777, PI338047) were also included in the study. Nei’s genetic diversity among weedy rice (0.45) was found to be higher than cultivated rice (0.24) but less than allelopathic rice (0.56). The genetic relationship and population structure based on herbicide tolerance and allelopathic po-tential were evaluated. Herbicide-tolerant and susceptible accessions formed distinct clusters in the dendrogram, indicating their genetic variation, whereas no distinction was observed between allelopathic and non-allelopathic weedy rice accessions. Weedy rice accession B2, which was previously reported to have high allelopathy and herbicide tolerance, was genetically distinct from other weedy rice. Results from the study will help leverage weedy rice for rice improvement programs as both rice and weedy rice are closely related, thus having a low breeding barrier.

No-show appointments in healthcare is a problem faced by medical centers around the world, and understand the factors associated with the no-show behavior is essential. In the last decades, artificial intelligence took place in the medical field and machine learning algorithms can work as a efficient tool to understand the patients behavior and to achieve better medical appointment allocation in scheduling systems. In this work, we provide a systematic literature review (SLR) of machine learning techniques applied to no-show appointments aiming at establishing the current state-of-the-art. Based on a SLR following the Kitchenham methodology, 24 articles were found and analyzed, in which the characteristics of the database, algorithms and performance metrics of each studies were synthesized. Results regarding which factors have a higher impact on missed appointment rates were analyzed too. The results indicate that the most appropriate algorithms for building the models are decision tree algorithms. Furthermore, the most significant determinants of no-show were related to the patients age, whether the patient missed a previous appointment, and the distance between the appointment and the patients scheduling.

Foliar fungal diseases in tomatoes include early blight (Alternaria linariae), Septoria leaf spot (Septoria lycopersici), and late blight (Phytophthora infestans) which is oomycetes. These are one of the significant production constraints in tomatoes. We describe the etiology, host range, distribution, symptoms, and disease cycle to understand the biology followed by management practices emphasizing the resistance breeding approach for these diseases. In crop improvement efforts, we provide an analytical review, including conventional and molecular methods for improving this disease resistance. Modern breeding tools, including genomics, genetic transformation, and genome editing, can be used to improve these traits. There is a good possibility of using these tools in the future to improve these traits.

This paper explores indigenous perspectives on the understanding and management of cultural heritage within the Mapungubwe and Makgabeng Cultural landscapes in South Africa. State-based management system paid little attention to indigeneity resulting in contested interpretation of the archaeological past. This by-passing of indigenous input is a product of colonial and apartheid policies that glorified Western practices at the expense of black African heritage stakeholders. World heritage mechanisms are also skewed in favor of modern practice which is overly designed to be sensitive to tangible aspects of the past than the intangible elements that make up much of indigenous African heritage. We used the archaeology of Mapungubwe and Makgabeng Cultural landscapes as a test case for the impact of indigenous voices on heritage, but the results have wider applicability. We employed semi-structured interviews and focus group discussions to gather qualitative data that we calibrated with our lived experiences as products of Tsonga-speakers from this broader landscape. The results expose that indigenous people use physical manifestation of sites, ethnographic inquiry, names, oral history, spirit mediums, landscape memory, genealogy, and praise poetry to identify, interpret, evaluate, and manage their cultural heritage. Additionally, indigenous perspectives which rely on collective memory, ritual practices, and indigenous knowledge systems have huge potential for enriching our understanding of the archaeological heritage. We propose a more inclusive archaeology and heritage management practice that involve indigenous groups in the identification, interpretation, grading, and presentation of the African past.

Vehicle routing is a critical factor in municipal solid waste (MSW) collection planning and operations. Poor routing can introduce inefficiencies and cause targeted levels of services or performance to be missed irrespective of the level of resource application. Trial and error approaches have been proven to be not the best in the planning and prediction of expected performance. This study explores various Geographic Information System (GIS) tools and analysis techniques, and how they can be applied to optimizing vehicle routes in light of challenging site conditions. Using Adentan West residential area, suburb of Accra Ghana as a case study, current performance of the trial and error method was measured and a GIS computer model was used to evaluate various optimization scenarios to determine the level of savings that can be made. Field measurements were taking with Global Positioning System (GPS) devices for waste collection activities in areas with varying characteristics and conditions, and data analysed for one selected vehicle operating four days per week. It was found that, for a scenario where only the bin collection order was optimized while route selection was restricted by the ArcGIS Network Analyst, 2.6% of travel distance and 2.21% of travel time were saved. For the second scenario where only the route selection was optimized while order of bin collection was restricted, 4.1% and 1.5% of travel distance and time respectively were saved. For a third scenario where both the order of collection and route selection were together optimized, 10.9% and 3.7% of travel distance and time respectively were saved. Lastly, by regrouping all the bins for daily collection, 4.5% and 1.2% of travel distance and time respectively were saved. The results demonstrated that there is always room for optimization of solid waste collection routing irrespective of site constraints and other challenges that the nature of bin distribution pose to drivers. In developing countries like Ghana, where there is high demand for services in the face of limited road network access, application of GIS in optimization of routes will guide providers in planning and subsequently make more savings in fuel consumption, vehicle maintenance and cost of man-hours.

Software stands as one of the most rapidly evolving technologies in the present era, characterized by its swift expansion in both scale and complexity which leads to challenges in quality assurance. Software Defect Prediction (SDP) emerges as a methodology crafted to anticipate undiscovered defects, leveraging known defect data from existing codes. This methodology serves to facilitate software quality management, thereby ensuring overall product quality. Machine Learning (ML) and Deep Learning (DL) methodologies exhibit superior accuracy and adaptability compared to traditional statistical approaches catalyzing active researches in this domain. However, it makes us hard to generalize not only because of the disparity between open-source project and commercial project but also the difference on each industrial sectors. Consequently, further research utilizing datasets sourced from diverse real-world sectors becomes imperative to bolster the applicability of these findings. In this study, we utilized embedded software for telecommunication systems of SAMSUNG ELECTRONICS, supplemented by the introduction of nine novel features to train the model, and subsequent analysis of results ensued. Experimental outcomes revealed that the F-measurement metric has been enhanced from 0.58 to 0.63 upon integration of the new features, thereby signifying a performance augmentation of 8.62%. This case study is anticipated to contribute to bolster the application of SDP methodologies within analogous industrial sectors.

In Australia, traditional methods of cat management by local government (councils) animal management officers (AMO) have been ineffective, with cat-related calls and cat impoundments continuing to increase, resulting in many healthy cats being euthanized. This has detrimental effects on the mental health of AMOs, pound and shelter staff and veterinarians. The City of Banyule, Victoria implemented a free cat sterilization, microchipping and registration (licensing) program in 2013-14. Initially targeted to three low socioeconomic suburbs with the highest cat-related calls and intake, where enforcement action had little effect. An average of 4.1 cats/1000 residents per year were sterilized over eight years. The program was available to all cats in the area, including stray cats being fed by caregivers, provided they took ownership of the cats. There were no limitations on the number of cats enrolled per household and free transport was provided if required. The program was later expanded city-wide. Over eight years, city-wide cat intake decreased by 66%, euthanasia by 82%, with an increase in proportion of cats reclaimed by owners from a baseline of 6% of intake (2012-13) to 16% (2020-21). Cat-related calls decreased in the target area by 51% and city-wide by 36%. The council’s financial outlay was $84,000, which resulted in decreased costs as-sociated with cat-related calls of $266,225.00. Instead of traditional trap-adopt- kill, proactive management of urban cats based on targeted sterilization should be utilized by government and animal welfare agencies in Australia and internationally. These types of programs are effective at reducing intake and euthanasia and are cost-effective.

The Philippines is an archipelagic country composed of different indigenous cultural communities (ICCs) spread across various islands. Many of these Indigenous Peoples (IP) are marginalized and do not have access to common resources enjoyed in the lowland areas. An initial assessment focusing on the evaluation of their available livelihood and resources was conducted, in order to find common solutions to existing problems. The assessment took place at the office of the tribal council of Matigsalog in barangay Datu Salumay, Marilog District, Davao City from April 11 to 13, 2023. There were about 42 participants in total for Matigsalog tribes (26 men and 16 women) who attended the meeting and there were 15 participants from the Ata tribe (7 men and 8 women). Validation of the study separately took place through a brief presentation of the results before 15 members of the tribe and a hiking visit in their farmlands. The study determined the existing livelihoods in the two areas which are mainly agricultural, farming of crops (rice, corn, cassava, sweet potato) and fruit trees (coconut, banana, durian, jackfruit, pomelo) and the resources as well as the community’s knowledge, systems, and practices with regards to agricultural crops including climate change. Their sustainable farming practices include intercropping, seed-saving, and exchange practices, preserving these crop varieties and ensuring their availability for future planting seasons, no usage of chemical fertilizers and pesticides. To conclude, the tribe’s aspirations and resulting recommendations are summarized, to facilitate more directed and effective governmental assistance.

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

Purpose: Expanded carrier screening (ECS) informs couples of their risk of having offspring affected by certain genetic conditions. Limited data exists assessing the actions and reproductive outcomes of at-risk couples (ARCs). We describe the impact of ECS on planned and actual pregnancy management in the largest sample of ARCs studied to date. Methods: Couples who elected ECS and were found to be at high risk of having a pregnancy affected by at least one of 176 genetic conditions were invited to complete a survey about their actions and pregnancy management. Results: Three hundred ninety-one ARCs completed the survey. Among those screened before becoming pregnant, 77% planned or pursued actions to avoid having affected offspring. Among those screened during pregnancy, 37% elected prenatal diagnostic testing (PNDx) for that pregnancy. In subsequent pregnancies that occurred in both the preconception and prenatal screening groups, PNDx was pursued in 29%. The decision to decline PNDx was most frequently based on the fear of procedure-related miscarriage, as well as the belief that termination would not be pursued in the event of a positive diagnosis. Conclusions: ECS results impacted couples’ reproductive decision-making and led to altered pregnancy management that effectively eliminates the risk of having affected offspring.

Presently power control and management play a vigorous role in information technology and power management. Instead of non-renewable power manufacturing, renewable power manufacturing is preferred by every organization for controlling resource consumption, price reduction and efficient power management. Smart grid efficiently satisfies these requirements with the integration of machine learning algorithms. Machine learning algorithms are used in a smart grid for power requirement prediction, power distribution, failure identification etc. The proposed Random Forest-based smart grid system classifies the power grid into different zones like high and low power utilization. The power zones are divided into number of sub-zones and map to random forest branches. The sub-zone and branch mapping process used to identify the quantity of power utilized and the non-utilized in a zone. The non-utilized power quantity and location of power availabilities are identified and distributed the required quantity of power to the requester in a minimal response time and price. The priority power scheduling algorithm collect request from consumer and send the request to producer based on priority. The producer analysed the requester existing power utilization quantity and availability of power for scheduling the power distribution to the requester based on priority. The proposed Random Forest based sustainability and price optimization technique in smart grid experimental results are compared to existing machine learning techniques like SVM, KNN and NB. The proposed random forest-based identification technique identifies the exact location of the power availability, which takes minimal processing time and quick responses to the requestor. Additionally, the smart meter based smart grid technique identifies the faults in short time duration than the conventional energy management technique is also proven in the experimental results.

Floods, recognized for their erratic behavior and devastating effects, are a significant threat as a natural disaster. In Brunei Darussalam, the impact of climate change is becoming increasingly evident through higher temperatures and an expected increase in annual rainfall (5.0mm per year from 2021 to 2050), highlighting the critical need for updated flood risk management techniques. In line with the climate resilience and adaptation objectives of WAWASAN 2035, this paper introduces an innovative approach—a cutting-edge flood risk management framework that utilizes the capabilities of big data analytics, sophisticated machine learning algorithms, and smart Internet of Things (IoT) sensors. Traditional methods, which rely on numerical and physical data modeling, often do not provide precise short-term flood forecasts. Our suggested framework uses machine learning to analyze real-time flood forecasting, sensor data and enhance warning systems, addressing the shortcomings of traditional approaches. The key advantage of this approach is its potential to drastically decrease flood-related damages, protect lives, and boost infrastructure resilience. This proposal is not only in aligns with Brunei's vision for a safe and climate-adaptable future but also marks a significant step forward in adopting innovative and sustainable flood risk management solutions amidst an evolving climate.

The purpose of this paper is to propose a tool to measure the performance of a Strategic Asset Management Plan (SAMP) based on a Balanced Scorecard (BSC). The SAMP converts organizational objectives into asset management objectives, also specifies the role of the asset management system and brings support to achieve asset management objectives. The SAMP becomes the heart of the organization and integrates with long-term, medium-term, and short-term financial plans integrated with same term activity plans. In the SAMP, the balance among performance, costs and risks is also taken into consideration in order to achieve the organization’s objectives. On the other side, the SAMP is a guide to set the asset management objectives while describing the role of the Asset Management System (AMS) in meeting those objectives. While SAMP is the central figure of AMS, it is important to measure its performance and needs to be build and improved through an iterative process, what means that is not just a document, it is “the document”, and should be treated as a “living being” that needs to adapt to internal and external changes quickly. The BSC is an excellent tool where, through the appropriate Key Performance Indicators (KPIs), the progress can be measured, and is supported by four perspectives: Financial; Customer; Internal Process; and Learning and Growth.

Research focused on understanding wider systemic factors driving behavioral change is limited with a dominant focus on the role of individual farmer and psychosocial factors for farming practice change, including reducing fertilizer application in agriculture. Adopting a wider systems perspective, the current study examines change and the role that supporting services have on fertilizer application rate change. A total of 238 sugarcane growers completed surveys reporting on changes in fertilizer application along with factors that may explain behavior change. Logistic regressions and negative binomial count-data regressions were used to examine whether farmers had changed fertilizer application rates and if they had, how long ago they made the change, and to explore the impact of individual and system factors in influencing change. Approximately one in three sugarcane growers surveyed (37%) had changed the method they used to calculate fertilizer application rates for the cane land they owned/managed at some point. Logistic regression results indicated growers were less likely to change the basis for their fertilizer calculation if they regarded maintaining good relationships with other local growers as being extremely important, they had another source of off-farm income, and if they had not attended a government-funded fertilizer management workshop in the five years preceding the survey. Similar drivers promoted early adoption of fertilizer practice change; namely, regarding family traditions and heritage as being unimportant, having sole decision-making authority on farming activities and having attended up to 5 workshops in the five years prior to completing the survey. Results demonstrated the influence of government-funded services to support practice change.

The Fruit Harvest Helper, a mobile application developed by Northwest Nazarene University’s (NNU) Robotics Vision Lab, aims to assist farmers in estimating fruit yield for apple orchards. Currently, farmers manually estimate the fruit yield for an orchard, which is a laborious task. Fruit Harvest Helper seeks to simplify their process. While prior research efforts at NNU concentrated on developing an iOS app for blossom detection, this current research aims to adapt that smart farming application for apple detection across multiple platforms, iOS and Android. The old and new applications were designed with an intuitive user interface that is easy for farmers to use, allowing for quick image selection and processing. Unlike before, the adapted app utilizes a color ratio-based image segmentation algorithm implemented in OpenCV C++ to detect apples in apple tree images selected for processing. The results of testing the algorithm with a dataset of images indicate an 8.52% Mean Absolute Percentage Error (MAPE) and a Pearson correlation coefficient of 0.6 between detected and actual apples on the trees. These findings were obtained by evaluating the images from both the east and west sides of the trees, which was the best method to reduce the error of this algorithm. Although the Fruit Harvest Helper shows promise, there are many opportunities for improvement. These opportunities include exploring alternative machine-learning approaches for apple detection, conducting real-world testing without any human assistance, and expanding the app to detect various types of fruit. The Fruit Harvest Helper mobile application is among the many mobile applications contributing to precision agriculture, nearing readiness for farmers to use in yield monitoring and farm management.

In graduate programs such as social work, field education is the signature pedagogy of education. As such, student placement with an appropriate field education agency is critical to ensure academic success and career readiness. A variety of Learning Management System (LMS) and Integrated Planning and Advising Service (IPAS) technologies have been developed to fully integrate technology into the educational system and streamline and improve the learning experience for students, educators, and administrators. Few (if any) of the existing solutions have capabilities to match students with field educators on the basis of an individual student’s completed coursework and area of specialization, as well as field educator needs and opportunities. This paper describes our experience developing a custom LMS/IPAS system—the School of Social Work information System (SSWiS)—that was designed specifically for student learning, faculty advising, and academic administration within our social work graduate program. We present the challenges that motivated the design of the SSWiS before describing the architecture and functionality of our solution. We then discuss our preliminary evaluation results. We conclude with a discussion of the benefits and limitations of our system in the context of today’s technical needs in graduate education in social work and other fields.

Exploring the determinants of biological community structure is important not only for understanding the formation of the community, but also for promoting its biodiversity conservation. We monitored butterfly communities in a grassland and woodland area of Mount Fuji, Japan, and explored the environmental factors that influenced them. Multivariate regression tree (MRT) analysis generated a 3-leaved MRT (G1, G2, and G3) and showed the total explained variation of 64.4% in the species composition. The explanatory variables discriminating between the two branches in the first node and in the second node of the MRT were neighbouring plant community and management status, respectively. The neighbouring plant community was related to the distribution of butterfly dietary resources and contributed much in determining the species composition of the community. While the management status was largely related to the amount of their dietary resources, affecting the species richness and diversity. The PCA results revealed that the three key groups (G1, G2, and G3) were formed along the gradients of these two factors. Consequently, to maintain mowing management and the diversity of neighbouring vegetation is very important for the continuance of butterfly community diversity and composition and the conservation of Red Listed species in the area.

The creation of a Europe-wide electricity market combined with the increased intermittency of supply from renewable sources calls for an investigation into the risk of aggregate peak demand. This paper makes use of a risk model to assess differences in time-use data from residential end-users in five different European electricity markets. Drawing on the Multinational Time-Use Survey database, it assesses risk in relation to the probability of electrical appliance use within households for five European countries. Findings highlight in which countries and for which activities the risk of aggregate peak demand is higher and link smart home solutions (automated load control, dynamic pricing and smart appliances) to different levels of peak demand risk.

Abstract: Safety issues related to the electrification of more electric aircraft (MEA) need to be addressed because of the increasing complexity of aircraft electrical power systems and the growing number of safety-critical sub-systems that need to be powered. Managing the energy storage systems and the flexibility in the load-side plays an important role in preserving the system’s safety when facing an energy shortage. This paper presents a system-level centralized operation management strategy based on model predictive control (MPC) for MEA to schedule battery systems and exploit flexibility in the demand-side while satisfying time-varying operational requirements. The proposed online control strategy aims to maintain energy storage (ES) and prolong the battery life cycle, while minimizing load shedding, with fewer switching activities to improve devices lifetime and to avoid unnecessary transients. Using a mixed-integer linear programming (MILP) formulation, different objective functions are proposed to realize the control targets, with soft constraints improving the robustness of the model. Besides, an evaluation framework is proposed to analyze the effects of various objective functions and the prediction horizon on system performance, which provides the designers and users of MEA and other complex systems with new insights into operation management problem formulation.

Atmospheric pollution arising from diesel-powered engines can result in acute and chronic diseases of the respiratory and cardiovascular systems. The annual carnival festival that takes place in the city of Salvador, Bahia-Brazil, is a large-scale event that gathers approximately 2 m revelers and 170,000 workers who accompany dozens of sound-trucks, or trios elétricos, for a period of seven days. These slow-moving sound-trucks run on diesel fuel, constantly exposing those around them to exhaust fumes. The present study aimed to evaluate air quality along the approximately 10km-long carnival parade circuit and determine possible impacts on human health. We applied a three-phase risk analysis strategy from 2007–2009: 1) hazard identification, 2) risk characterization and 3) risk management. Our quantification of atmospheric particulate matter 2.5 (PM2.5) and nitrogen dioxide (NO₂) concentrations revealed variable levels of PM2.5 ranging from 19 µg/m³ to 580 µg/m³, with peaks of up to 800 μg/m³ at sound-truck concentration areas. We then assessed the effects of air pollution on human health using ophthalmologic parameters obtained from 28 carnival volunteers, who often presented symptoms of eye irritation. Finally, we established strategies to communicate the study’s objectives and obtained results to the population through media outlets and open discussions with government agencies. According to our risk analysis, carnival sound-trucks represent the main source of atmospheric PM2.5 and NO₂ pollution during the annual 7-day carnival festival. As a consequence of our research, the municipal government of Salvador issued an addendum to its carnival legislation mandating organizers to monitor atmospheric pollution, and, subsequently, all large-scale public events. Municipal government authorities have also promoted a shift from petroleum-based diesel fuel to biodiesel, a less-polluting fuel, for all adapted carnival sound-trucks. Our approach, which employed easily accessible and inexpensive methodology, provided substantial scientific evidence to support improvements in the regulation of air quality during large-scale public events held in the city of Salvador.Keywords: environmental

Introduction: In recent years, platelets have been in short supply and high demand. Approximately one in five cardiac surgery patients require platelets. In our safety-net hospital, however, the incidence is over 40%. Renal dysfunction, long cardiopulmonary bypass (CPB) times, and absence of tranexamic acid (TXA) are common risk factors for requiring platelet transfusions. Methods: Our hypothesis was fewer platelets would be transfused within two hours after bypass under these three conditions: creatinine is low, predicted surgery duration is short, and TXA is uniformly administered. Our anesthesia department designed this retrospective before-and-after observational study when the surgery department decided to narrow preoperative criteria respective to these three elements. The Institutional Review Board of Louisiana State University Health Sciences Center Shreveport approved of the protocol and waived individual informed consent. We compared timing of platelet transfusions (within 7 days) in consecutive patients who had CPB during the first ninety days of 2022 to those in 2023 using t-tests in SAS 9.3. Confounders included age, weight, anticoagulants, gender, and the platelet counts and hemoglobin immediately prior to platelet transfusion. Secondary outcomes were postoperative day two creatinine and other components transfused. Results: Preoperatively creatinine tended to be higher in 2022 at 1.5 vs 1.1, reaching significance postoperatively at 1.9 vs 1.1 (p=0.02). Bypass times decreased from 174 to 124 minutes (p=0.06). TXA use increased from 18 of 28 to 26 of 29 patients. Platelet counts increased on bypass from 142 to 173 (p=0.06). Platelet and hemoglobin nadirs were higher (day 3: 8g/dL vs 8.8, p=0.04; 98 vs 138, p=0.005). Platelet units transfused per patient tended to increase (0.75+/-1 vs 0.93+/-1.5); if exposed, patients tended to receive more units (2.1+/-1.3 vs 2.5+/-1.4) sooner. Changes in transfusions for red cells were nonsignificant at 1.97 per patient to 1.21, cryoprecipitate 0.36 to 0.69, and FFP 0.93 to 0.83. Conclusions: This is the first study examining timing of platelet transfusions after bypass. In the present investigation, we measured platelet count during bypass and prothrombin hours after arrival in the intensive care. Platelets were often administered in sets of two because of scarce immediate supply, partly from lack of an agitator table. More importantly, these data support a need for point-of-care thromboelastograms intraoperatively, but the cost has been prohibitive. Some centers’ algorithms list triggers for transfusion by fibrinogen and prothrombin times, available immediately after separation from bypass.

The importance of conflict analysis and safety considerations during work zone intervals at signalized intersections cannot be overstated, as these periods pose unique challenges and safety risks for both motorists and pedestrians. Work zones introduce temporary changes to traffic patterns, lane configurations, and signal timings, which can disrupt the flow of traffic and increase the likelihood of conflicts between vehicles and pedestrians. By conducting comprehensive conflict analysis, it is possible to identify potential conflict points, such as merging areas, pedestrian crossings, and lane transitions, and implement targeted safety measures to mitigate risks. Additionally, considering safety considerations during work zone intervals is paramount to safeguarding the well-being of road users and minimizing the occurrence of conflicts or collisions. Measures such as enhanced signage, temporary traffic control devices, and increased enforcement efforts can help promote compliance with traffic regulations and ensure the safe passage of vehicles and pedestrians through work zones. This study investigates the dynamics of traffic behavior and safety implications within work zones at signalized intersections, aiming to address key challenges and enhance intersection management strategies. Through comprehensive analysis, varying frequencies of Vehicle-to-Vehicle (V2V) conflicts were observed across different movement directions, with significant occurrences identified in specific phases of the traffic signal cycle. Specifically, 69 V2V conflicts in phase #1, 181 in phase #2, 31 in phase #3, 207 in phase #4, 1 in phase #5, 274 in phase #6, 93 in phase #7, and 186 in phase #8 were recorded. Furthermore, the examination of Vehicle-to-Pedestrian (V2P) conflicts underscored the importance of prioritizing pedestrian safety, with notable occurrences observed in phases associated with pedestrian crossing movements. Meanwhile, despite the closure of left-turn movements, instances of red light running persisted, with 69 red light running events in phase #1, 181 in phase #2, 31 in phase #3, 207 in phase #4, 1 in phase #5, 274 in phase #6, 93 in phase #7, and 186 in phase #8.To mitigate these safety concerns during work zone intervals, proactive measures are essential. Strategies include improving communication through clear signage and advanced warning systems, enhancing enforcement efforts with red light cameras and increased police presence, and investing in infrastructure improvements such as temporary pedestrian facilities. Integration of real-time data from sensors, particularly LiDAR technology, offers significant advantages in detecting conflicts and red light runners during work zone intervals. LiDAR's precise, real-time data on vehicle and pedestrian movements, combined with its 360-degree coverage and high spatial resolution, facilitates accurate detection and tracking of potential conflict scenarios, contributing to enhanced intersection safety and traffic management efficiency. This study endeavored to conduct a traffic safety analysis during work zone intervals at a signalized intersection in Baltimore City, known for its high rate of traffic crashes, utilizing LiDAR sensor technology.

The purpose of this article is to investigate and analyze the practices of scientific management within the County Departments of Sports and Youth (CDYS) in Romania. Conducted through a comprehensive research endeavor spanning from January to June 2022, the study utilized a standardized questionnaire as its primary instrument for data collection, distributed among CDYS directors. A notable finding from the study indicates that a significant proportion of respondents (44.9%) perceive notable disparities in the normative-functional elements governing the National Sports System in Romania compared to international standards. Moreover, the majority (51%) consistently adhere to regulatory acts, while a substantial portion (69.4%) underscore the importance of strict adherence to internal regulations in strategy formulation. Furthermore, an overwhelming majority (88.9%) acknowledge the substantial influence of available resources on strategy development, with collaboration with authorities primarily occurring through direct communication channels. Respondents prioritize multiple objectives (44.9%), affirm the necessity of various competencies (53.1%), and identify a lack of human and financial resources (59.2%) as the most significant obstacle. Notable achievements highlighted in the study include the improvement of the county's sports performance (53.1%). Respondents also believe that setting clear and realistic objectives (38.8%) is pivotal to enhancing CDYS management, while considerations in formulating strategies emphasize trends in the sports domain (42.9%) and the specific needs of the local sports community (42.9%). Overall, this research contributes to the understanding and promotion of more efficient practices in managing sports and youth departments within Romania's counties.

Considering the increasing rate of energy consumption and its environmental detrimental effects, as well as considering the use of non-renewable energy sources such as fossil fuels, energy management issues have become more important. Given the 40% share of the building industry's total energy consumption, as well as the 80% share of energy consumed during the operation period, attention to the areas of energy management and optimization during the operation period of the buildings can have a major impact on buildings’ energy performance. In this research, through identifying building energy management tools and studying previous studies and assessing the effects of building energy management systems, the economic and environmental impacts of using building energy management systems on the annual energy consumption in an office building in Tehran as a case study has been investigated. The results indicate a 32 percent reduction in energy consumption and a significant reduction in the release of the environmental pollutants in smart mode compared to the base mode. Moreover, considering the social costs associated with the emitted pollutants as well as the return period, it has been attempted to identify the factors contributing to the economic justification of using smart heating and cooling systems. According to the results, the use of smart energy management systems can be considered as an effective step in optimizing and managing energy consumption in the construction sector.

The paper addresses the ongoing and continuous interest in photovoltaic energy systems (PESs). In this context, the study focuses on an isolated photovoltaic system with hybrid bat-tery-supercapacitor storage (HBSS). The integration of supercapacitors (SCs) in this system is of particular importance because of their high specific power density. In photovoltaic (PV) systems, multi-storage systems use two or more energy storage technologies to enhance system perfor-mance and flexibility. When batteries and supercapacitors are combined in a PV system, their benefits are maximized and offer a more reliable, efficient, and cost-effective energy storage op-tion. In addition, effective multi-storage power management in a PV system needs a solid grasp of the energy storage technologies, load power demand profiles, and the whole system architecture. In this work, battery-supercapacitor storage system (HBSS) is established by combining batteries and supercapacitors. The primary objective is to devise a novel management algorithm that ef-fectively controls the different power sources. The algorithm's purpose is to regulate the charge and discharge cycles of the HBSS, ensuring that the state of charge (SOC) of both batteries and supercapacitors remains within the desired range. The proposed management algorithm is de-signed to be simple, efficient, and light on computational resources. It efficiently handles the energy flow within the HBSS, optimizing the usage of both batteries and supercapacitors based on real-time conditions and energy demands. By maintaining the SOC of these energy storage components within the specified limits, the proposed method ensures their longevity and max-imizes their performance. Simulation results obtained from applying the management strategy are found to be satisfactory. These results show that the proposed algorithm maintains the SOC of batteries and supercapacitors within the desired range, leading to improved energy management and enhanced system efficiency.

The hyper-arid environment is characterized by high inter-annual climatic fluctuations. The yearly average rainfall can change substantially for several years, forming wet or dry sub-periods. Observing rainfall trends over a sub-period can lead to a false perception of a change in the trend but may in fact represent a periodic cycle when examined on a larger time scale. We aimed to better characterize the rainfall regime prevailing in the hyper-arid Arava Valley (Israel/Jordan), and to examine the response of vegetation to annual rainfall. We hypothesized that annual and perennial vegetation would respond differently to wet and dry sub-periods, and that grazing activities will impact vegetation growth. We used a time series of monthly rainfall, from which we calculated Standard Precipitation Index (SPI), and calculated proxies of perennial and annual vegetation over the last four decades using Landsat-derived Normalized Difference Vegetation Index (NDVI). We found no clear trend in rainfall amounts during this period, however we did identify wet and dry sub-periods which were statistically distinct in rain and in vegetation patterns from each other. The highest levels of correlation between rainfall and the NDVI derived proxies were found when examining average rainfall over a period of two- three years for the annual vegetation and over four years for perennial vegetation. Using the Mann-Kendall test, we identified a time lag of two to four years, with the proxies of annual vegetation responding faster than the proxies of perennial vegetation, to shifts between wet and dry sub-period. In addition, we found a consistent difference between natural vegetation cover in Jordan (grazed) and Israel (non-grazed), favoring the development of natural vegetation on the Israeli side. We conclude that integrating between long-term remote sensing satellite imagery and climatic records revealed the greater resilience of perennial vegetation in the hyper-arid region to climatic fluctuation, and enabled us to identify the vegetation’s sensitivity to anthropogenic impact.

This article describes the POTENTIALS project, which aimed to develop business models for the reuse of former industrial and mining sites in different regions. The project focused on the creation of eco-industrial parks as a result to enable sustainable energy production and reduce waste and pollution. A key aspect was the Territorial Impact Assessment (TIA), a new and complex policy assessment tool. Therefore, the TEQUILA (Territorial Efficiency Quality and Identity Layer Assessment) approach is used to describe the TIA and emphasizes its application in assessing the impact of EU policies and projects on territorial cohesion. It underlines the need for a differentiated understanding of the regional characteristics and potential impacts of policies; and stresses the importance of regionalized impact models for the assessment. Furthermore, the process and results of applying the TEQUILA methodology to assess the territorial impact of different scenarios of business models within the POTENTIALS project is given.

Urbanization and climate change have increased the need for stormwater management and nature-based solutions. Decisions made at project level impact the emergence of systemic traits of the stormwater network and the functionality of the catchment areas in urban planning. To that end, it is vital to introduce the decision-making tools for analyzing both the utilities and amenities of nature-based solutions (NBS) to increase their adoption to reduce the peak loads in the stormwater system, and to that end, mitigate the impacts of climate change. This paper demonstrates a workflow using drone-based photogrammetry, 3D modeling, and simulation software to generate visual and functional models assisting in informed decision-making in the design of stormwater systems as functional landscape architecture. Using aerial data from drones and modeled design solutions, the proposed workflow simulates rain events, infiltration, evaporation, water flow, and accumulation of stormwater in a way that allows the visual and quantified analysis of detailed landscape architecture designs. The paper provides an example of a rooftop site simulation demonstrating the infiltration and flow of water to the drainage. The visual decision-making method provided can aid in investment decisions for functional landscape design in support of stormwater management.

The background of this work is related to the scheduling of household appliances, taking into account variations in energy costs during the day, due to official Brazilian domestic tariffs: constant and white. The white tariff can reach an average price of around 17\% lower than the constant, but charges twice its value at peak hours. In addition to cost reduction, we propose a methodology to reduce user discomfort due to time shifting of controllable devices, presenting a balanced solution through the analytical analysis of a new method here called tariff space, derived from white tariff posts. To achieve this goal, we explore the geometric properties of the movement of devices through the tariff space (geometric locus of the load), over which we can define a limited region in which the cost of a load under the white tariff will be equal to or less than the constant tariff. As a trial for the efficiency of this new methodology, we collected some benchmarks (such as execution time and memory usage) against a classic multi-objective algorithm (Hierarchical) available in the language portfolio in which the project has been executed (Julia language). As a result, both methodologies achieve similar results, but the one presented in this article shows a significant reduction in processing time and memory usage, which could lead to the future implementation of the solution in a simple, low-cost embedded system like an ARM cortex M.

The aim of this paper is to study the main areas in which Artificial Intelligence (AI) will impact the field of project management that relates to cost, risk and scheduling. The research model was based on a previous study of the ten project management knowledge areas presented in the PMI’s PMBOK 6th edition where project schedule-, cost- and risk management knowledge areas were identified as being the ones most likely to be affected by the development of AI. A group of experts that participated in the study agreed that AI will affect the project management profession in the future. Different elements of the three knowledge areas were considered to be affected more by AI than others. The schedule baseline is the element believed to be affected the most out of the project schedule management elements. For project cost management, the estimation of resource cost is believed to be affected the most. In the case of project risk management, the application of AI will have the strongest impact on the probability and impact format.

As non-operative management (NOM) of esophageal and rectal cancer is becoming more prevalent, blood-biomarkers such as circulating tumor DNA (ctDNA) may provide clinical information in addition to endoscopy and imaging to aid in treatment decisions following chemotherapy and radiation therapy. In this feasibility study, we prospectively collected plasma samples from locally advanced esophageal (n=3) and rectal cancer (n=2) patients undergoing multimodal neoadjuvant therapy to assess the feasibility of serial ctDNA monitoring throughout neoadjuvant therapy. Using the DIDA-Seq error-correction method, we serially interrogated plasma cell-free DNA at 28-41 tumor-specific genomic loci throughout therapy and in surveillance with an average limit of detection of 0.016% mutant allele frequency. In both rectal cancer patients, ctDNA levels were persistently elevated following total neoadjuvant therapy with eventual detection of clinical recurrence prior to salvage surgery. Among the esophageal cancer patients, ctDNA levels closely correlated with tumor burden throughout and following neoadjuvant therapy, which was associated with a pathologic complete response in one patient. In this feasibility study, patient and tumor-specific ctDNA levels correlated with clinical outcomes throughout multi-modality therapy suggesting that serial monitoring of patient ctDNA has the potential to serve as a highly sensitive and specific biomarker to risk-stratify esophageal and rectal cancer patients eligible for NOM. Further prospective investigation is warranted.

This investigation delves into an examination of the growth dynamics observed in Central Taiwan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs This investigation delves into an examination of the growth dynamics observed in Central Tai-wan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs in Taiwan and Scotland, respectively, attracting numerous high-tech and startup enterprises. Various means facilitate the growth of industries and foster innovations in different industrial spheres. Important factors contributing to this growth include policy support, availability of research materials, and provision of infrastructure. This research paper compares the successful case studies of two industrial parks, along with their environmental and economic management strategies. It explores the management principles that ensure the sustainable development and economic growth of industrial parks, aiming to assist decision-makers and relevant stakeholders in evaluating the sustainable development planning of industrial parks.

Keywords: conservation; cultural pluralism; environmental regulation; community-based natural resource management; Indigenous law

Managers are often faced with the task of improving the management of the production 17process in order to maintain the sustainability of production efficiency in a highly competitive en-18vironment. The submitted contribution deals with the design of a system that will support them in 19the selection of progressive methods and technologies in order to improve the management of pro-20duction processes. Managers often follow new trends in this issue, but it is not easy to work on the 21knowledge that proven progressive technologies can bring them higher efficiency. The presented system is based on the use of knowledge of existing solutions of manufacturers of automotive components, where companies solve similar problems in production management. The mix of methods and technologies used in the management of production processes brings companies different results in the achieved efficiency. The proposed system for supporting the selection of the production management method and technology is designed from blocks of data collection, benchmarking of the performance of production processes of industrial enterprises, and further from data mining technology to obtain knowledge about the effect on efficiency from already implemented technologies. The last blocks help to examine the differences in the implementation of the same methods and technologies and allow to present the obtained results to the manager in the form of recommendations for choosing a suitable progressive method and technology.

This study provides a detailed investigation into the pathways through which microplastics from urban sources are transported to marine ecosystems, their distribution across different environments, and their impacts on marine life. Utilizing a combination of water and sediment sampling across urban, riverine, and marine environments, the research quantitatively assesses the concentration and types of microplastics present, and evaluates the ecological consequences of their accumulation in marine ecosystems. The findings reveal a significant concentration of microplastics in all examined environments, with the highest levels detected in urban areas, closely linked to industrial activities and inadequate waste management practices. The study documents a variety of microplastic polymers, with polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET) being the most prevalent. A substantial impact on marine organisms was observed, including evidence of microplastic ingestion across a wide range of species and indications of stress and physical damage to coral reefs. Seasonal variations indicate that microplastic concentrations peak during periods of high rainfall, suggesting urban runoff as a critical pathway for microplastic transport. The study concludes with recommendations for improving waste management practices, enhancing public awareness and engagement in plastic recycling efforts, and implementing policies aimed at reducing the production and use of single-use plastics. This research underscores the urgent need for coordinated actions to mitigate the pervasive issue of microplastic pollution, highlighting the role of urban management and policy interventions in safeguarding marine ecosystems.

Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. The results show that the strategies derived from the general heuristic are very interesting, all of them deploying roadside units in a circle pattern around the traffic epicenter.

The present study aims to identify tomato (Solanum lycopersicum L.) cultivars with weed-suppressive ability against target weed species in the tomato growing season. A greenhouse study was conducted with 17 tomato cultivars and target weeds Palmer amaranth (Amaranthus palmeri S. Wats), yellow nutsedge (Cyperus esculentus L.), and large crabgrass (Digitaria sanguinalis L.). Tomato plants and weed species were grown in the same pot. The height, chlorophyll, and dry weight biomass of the weeds were measured 28 days after sowing. The largest effect of tomato interference was on Palmer amaranth. Cultivar 15 reduced Palmer amaranth height, chlorophyll, and biomass by 58, 28, and 83%, respectively. Chlorophyll percentage of yellow nutsedge seedlings was suppressed by 15% by cultivar 64, whereas 13% of its height was reduced by cultivar 20. Cultivar 15 reduced biomass of yellow nutsedge by 40%. The percentage of chlorophyll of large crabgrass was reduced by 22% with cultivar 5, whereas the height and biomass were reduced by 35 and 44% with cultivars 38 and 63, respectively. Factoring all parameters evaluated, cultivars 38, 33, and 7 were most suppressive against the problematic weed species in tomato.

Analytical data platform have been used for decades for improving the organizational performance. Starting from the data warehouses used primarily for structured data processing, through the data lakes oriented for raw data storage and post-hoc data analyses, to the data lakehouses − a combination of raw storage and business intelligence pre-processing for improving the platform efficacy. But in recent years a new architecture called Data Mesh has emerged. The main promise of this architecture is to remove the barriers between operational and analytical teams in order to boost the overall value extraction from the big data. A number of attempts has been made to formalise and to implement it in existing projects. Although being defined as a socio-technical paradigm, data mesh still lacks the technology support for enabling its widespread adoption. To overcome this limitation, we propose a new view of the platform requirements alongside the formal governance definition that we believe can help in successful adoption of the data mesh. It is based on fundamental aspects such as decentralized data domains and federated computational governance. In addition, we also present a blockchain-based implementation of a mesh platform as a practical validation to our theoretical proposal. Overall, this article demonstrates a novel research direction of the information system decentralization technologies.

The contribution deals with the selection of progressive methods and technologies to improve the management of production processes in the industrial area. The first chapter of the contribution summarises the theoretical starting points for the management of production processes and their progressive concepts. Chapter 2 deals with the analysis of the current state of play in the use of methods and technologies in production management and summarise its problem areas. Chapter 3 presents the design of a system for selecting the appropriate method and technology to improve the management of the production process. The system presented is designed from data collection blocks, a benchmark for the performance of industrial enterprises' production processes, and data mining to gain knowledge of the impact of the methods and technologies used on the performance of production processes. The last block of the system allows the presentation of the obtained results, which sets out the recommendation for the choice of progressive method and technology. The system is partially verified in the last chapter of the contribution.

During the Covid-19 pandemic in Taiwan, analytical tools of PEST (political, economic, social-cultural, and technological), SWOT (strength, weakness, opportunity, threat), nine building blocks of a business model canvas, and knowledge management were combined to develop a theoretical framework, and used to assess business, smart and sustainable management of two case companies: Tung Sheng Company Limited and its subsidiary, Strong Basic Enterprise Limited. A heuristic inquiry research design was adopted. In addition to secondary data from the two case companies, major top managers were interviewed to reveal constructive questions about the existing business models and to re-interpret strategy. The results showed that case companies own capabilities of R & D (research and development) as a foundation to further apply new smart ICT (information and communication technology) and execute green manufacturing. Additionally, strong key partnerships are used to diversify business investment for leveraging on limited resources given current insufficient qualified employees. Resilient practices adopted new and green technology to help mitigate the negative impacts of the Covid-19 pandemic. This study provides a useful framework and practical information about how to examine business models, smart and sustainable management processes of the two case companies and to make adjustments in strategies for the future.

Diabetes mellitus (DM) and obesity account for the highest burden of non-communicable diseases. There is increasing evidence showing therapeutic patient education (TPE) as a clinically and cost-effective solution to improve biomedical and psychosocial outcomes among people with DM and obesity. The present systematic review and meta-analysis presents a critical synthesis of development of TPE interventions for DM and obesity and the efficacy of these interventions across a range of biomedical, psychosocial and psychological outcomes. A total of 54 of these RCTs were identified among patients with obesity and diabetes and were thus, qualitatively synthesized. Out of these, 47 were included into quantitative synthesis. There was substantial heterogeneity in reporting of these outcomes (I²= 88.35%, Q= 317.64), with significant improvement (SMD=0.36, 95% CI: 0.23 to 0.49) noted in biomedical outcomes in the intervention group. The effect sizes were comparable across interventions delivered by different modes and delivery agents. These interventions can be delivered by allied health staff, doctors or electronically as self-help programs, with similar effectiveness (P < 0.001). These interventions should be implemented in healthcare and community settings to improve health of patients suffering from DM and obesity.

Large datasets that enable researchers to perform investigations with unprecedented rigor are growing increasingly common in neuroimaging. Due to the simultaneous increasing popularity of open science, these state-of-the-art datasets are more accessible than ever to researchers around the world. While analysis of these samples has pushed the field forward, they pose a new set of challenges that might cause difficulties for novice users. Here, we offer practical tips for working with large datasets from the end-user’s perspective. We cover all aspects of the data life cycle: from what to consider when downloading and storing the data, to tips on how to become acquainted with a dataset one did not collect, to what to share when communicating results. This manuscript serves as a practical guide one can use when working with large neuroimaging datasets, thus dissolving barriers to scientific discovery.

This study investigates the complex role of financial risks in the context of public–private partnerships (PPPs) in India and their relationship to the amount and extent of investments made by private partners (s). We hypothesize that subsidies, bid criteria, and risk have a positive relationship with investments made by private partners. A project’s leverage moderates these relationships. Regression was used to analyze the hypotheses using SPSS 24 and PROCESS Macro. Data from the World Bank were collected from 2009 to 2019 for the study variables. Interestingly, our research finds support for these relationships that may seem contrary to some commonly-held notions of risk relationships, such as – the government using ‘viability gap’ funding to attract private investment and ‘leverage’ does not moderate the relationship between risk assumed and private investment. This study is among the first to recognize and elaborate on financial risk relationships, specifically in the context of Indian PPPs. These findings are significant for both private and public participants in terms of financial considerations in PPP projects, especially in emerging markets.

The aim of this study was to develop, implement, and evaluate a new auxiliary enterprise risk management framework and process to serve as an enabler to the global ISO 31000 risk framework and ISO 31010 processes. This framework has been designed particularly for use within high-risk environments and those characterized by volatility, uncertainty, complexity, and ambiguity (VUCA). This paper proposes a methodology for optimization of structured sharing and grass-roots management of all available risk-sentience information with the assessed potential to develop into an identifiable risk in the future. The author introduces new risk terminology including risk-sentience, risk-sentience information, and risk-sentience management. The process involved the development of the Theory of Risk-Sentience (ToRS), Risk-Sentience Auxiliary Framework (RSAF) and a risk-sentience management process referred to as LUOMEAR (Learning from Uncertainties, Others Mistakes, Experiences and Anecdotal Reporting). Manchester Patient Safety Framework (MaPSaF), SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis, and a newly developed Risk-Sentience Fertility Checklist were used to conduct pre and post-trial evaluations. The findings include positive adjustments in safety culture, components of commitment to quality, communication and team-working around safety issues, access to evolving risk-information, and efficient sharing and management of recorded risk-information. Recommendations are made for more extensive application of both the proposed auxiliary risk framework and process within high-risk sectors to further explore its effectiveness and scope.

This study empirically analyzes the effectiveness of resource optimization utilizing artificial intelligence (AI) within cloud computing environments. It compares systems that have been transitioned from a Monolithic structure to Microservices Architecture (MSA) with those adopting a simple Rehost strategy, to validate the operational efficiency of two systems whose resource efficiency has been enhanced compared to traditional legacy systems. The research is based on systems that determined resource efficiency post-cloud migration using APM tools. It points out the limitations of traditional heuristic operation methods in resource optimization, which lead to issues such as application performance degradation, resource over-allocation, and increased operational costs. This study aims to overcome the conventional resource optimization standards that depended on the average peak usage of CPU and memory infrastructure, by introducing AI-based optimization tools, and applying on-premise standards to cloud and container environments to achieve resource optimization. The paper emphasizes the importance of resource optimization through AI-based automation tools, exploring the possibilities of resolving real-world application performance issues in cloud environments, reducing unnecessary resource usage costs, and cutting down on labor risks and operational expenses. Through this, it presents strategic directions on how AI technology can offer financial and operational advantages in managing cloud resources.

Risk management strategies protect the company as a whole as well as employees from unforeseen financial impacts. As in the case of personal finance, preparing for certain scenarios helps to face any difficulties that the company may encounter and allows it to get out of this impasse.For any project to be successful, the way the project executing agency will deal with potential risks must be determined so that it can identify, mitigate or avoid problems when it needs to do so. Successful project managers realize that risk management is important, because the achievement of project objectives depends on planning, preparation, results and evaluation that contribute to the achievement of strategic goals, especially the sustainable development of societies.Risk management strategies work to protect the company as a whole as well as employees from unexpected financial effects, and as is the case in personal finance, preparing for certain scenarios helps to face any difficulties that the company may face and allows it to get out of this impasse.To ensure the success of your project, determine how you will handle potential risks so that you can identify, mitigate or avoid problems when you need to do so. Successful project managers understand that risk management is important, because the achievement of project objectives depends on planning, preparation, results, and evaluation that contribute to the achievement of strategic objectives.

Lake Rawapening, Semarang Regency, Indonesia, has incorporated a holistic plan in its management practices. However, despite successful target achievements, some limitations remain that a review of its management plan is needed. This paper identifies and analyzes existing lake management strategies as a standard specifically in Lake Rawapening by exploring various literature, both legal frameworks and scholarly articles indexed in Google Scholar and published in Water by MDPI about lake management in many countries. There are two major types of lake management, namely pillar-based and object-based. While the former is the foundation of a conceptual paradigm that does not comprehensively consider the roles of finance and technology in the lake management, the latter indicates the objects to manage so as to create standards or benchmarks for the implementation of various programs. Overall, Lake Rawapening management should include more programs on erosion-sedimentation control and monitoring of operational performance using information systems.

Rice is consumed as a staple food by majority of the people in the world and failure in rice crop, due to any reason, poses a severe threat of starvation. Rice blast, caused by a fungus blast has been ranked among the most important plant diseases. It is by far the most threatening disease of ric crop and it is found wherever rice is grown. All of the rice blast disease management strategies that have been employed have limited success and rice blast has never been eliminated from a region in which rice is grown. Hence there is need to look for the best remedy in terms of effectiveness and organic nature of the method etc. This study was aimed to determine the plant growth promoting and biopesticidal effects of bioactive components present in a mixture of Piper caninum and Piper betle var. Nigra leaf extracts. . The extracts were applied in the field to determine their inhibition effects against blast disease, growth and yield improvement.. Extract of both the plants promoted plant growth and exhibited antifungal activity against rice blast fungus, Pyricularia oryzae. However the synergistic effect of the mixture of the two extracts exhibited greater effects than an effect of a single extract. . All treatments reduced the intensity of blast disease on week 15 with disease intensity by 7.90%. The extracts could increase plant height, the numbers of tillers, number of leaves, number of grains per panicle number of heads per panicle, and the full-grain weight hill.. The highest potential yield (t/ha) was observed in the 2% extract treatment, and all treatment results significantly differed from that of the control. The potential grain yield was 3.23 t/ha in the control, while that in the treatment ranged from 3.81 t/ha to 5.61 t/ha. The high grain yield observed with the treatment was caused by the low intensity of blast disease.

The restrictions imposed by the Covid-19 pandemic left many older adults isolated and confined. Under active aging theory, self-management is crucial for well-being among older adults coping with aging. The current study examines how (a) initial self-management, and (b) changes in self-management due to independent physical training, affect psychological outcomes in a sample of care home residents following outbreak of the pandemic. 64 older adults (53 females, 11 males), mean age is 82.23, reported on their self-management abilities, then embarked on six months of training in chair exercises (one session per week). The training exercises were halted after 22 sessions due to the pandemic, but some residents continued to practice independently. Eight weeks after the outbreak of the pandemic, residents who had continued to practice at least once per week (n = 35) and those who had not continued to practice (n = 29) were questioned again about their self-management, and about five psychological outcomes: anxiety, traumatic stress, satis-faction, general mood, and post-traumatic growth (PTG). Self-management improved among older adults who independently practiced the exercises, and declined among those who did not. Pre-pandemic self-management significantly predicted post-outbreak traumatic stress symptoms, anxiety, general mood, and satisfaction with life, but not PTG. However, the difference in self-management between the pre-pandemic and post-outbreak measures was associated with PTG, and made a unique contribution to prediction of the other effects. Self-management abilities among older adults can be seen as a protective factor against adverse psychological outcomes at times of trauma. Further, the improvement in self-management among older adults who independently practiced physical excises made a unique contribution beyond initial self-management abilities.

There has been a growing call for reform of the U.S. biomedical community in recent years. As a community, we face a growing list of issues including excessive waste, reproducibility, bias, inadequate training, and the absence of sustainable long-term planning that detract from the overall goal of advancing human health. In response to this debate, biomedical stakeholders have taken positive steps forward to remedy these issues. However, we must continually improve upon these steps to promote the long-term stability of the biomedical enterprise. Given the widespread interest of the scientific community in addressing these issues, there exists a unique opportunity to come together and create a new era of biomedical discovery. The completion of this exciting task requires reflection on our view and management of the system, and what the best route to sustainable change may be. Importantly, a coordinated approach that considers the collective make-up of the biomedical system and how processes and people influence collective output and create value for patients is needed. Here, these three areas and the concepts of systems theory, total quality management, and organizational development and their contribution to the management and effectiveness of biomedical discovery are discussed. Importantly recommendations are made concerning overall management strategy, process efficiency and quality research, administrative tasks, organizational cultural challenges, individual and team development, and funding strategy.

Industria 4.0 is present in smart and digital manufacturing, making manufacturing companies improve productivity, reducing delivery time and related costs. The objective of this work is to demonstrate through three integrated MPS Festo stations (Distribution, Pick \& Place and Sorting), using the Internet of Things and Google Analytics technologies, the benefits in relation to remote performance monitoring. The intended objective is achieved through the implementation of the monitoring system at the three MPS Festo stations. The data obtained through the integration of the Festo stations and their respective sensors are processed and analyzed in a cloud infrastructure, so that the main metrics are visualized and transmitted on a panel. This monitoring system improves the perception of process performance, as the main performance metrics are displayed, such as productivity, cycle time and parts produced. The cloud infrastructure allows remote viewing and monitoring of the system.

Conflicts are frequent within the complex professional environment of the construction industry. If claims cannot be overcome amicably, they result in disputes that lead to litigation. Identification of the causes of these claims and their impact on the duration, cost, and quality of the final project is expected to facilitate the prevention of unsuccessful performance of construction contracts. The novelty of this study is that after codifying the most common causes of construction contract claims derived from the extant literature, they are further investigated in terms of their probability of occurrence and the perceived impact they have on the project completion time, its total cost, and quality. Based on calculated relative importance indices from expert opinion, this paper proposes probability and severity of impact values for 39 common causes of claims in the construction industry. These can be applied to calculate their risk values for stakeholders in public construction contracts to plan mitigation measures of contractual claims. The findings show that the top five riskiest causes of contractual claims in the Greek construction industry are changes in quantities, work, or scope, design quality deficiencies or errors, payment delays, delays in work progress, and the financial failure of the contractor.

The purpose of this study is to find out the e-reputation management of the hotel industry, as well as the social media channels used as the tools of hotel e-reputation building. This study used a qualitative approach by analyzing the in-depth interviews with hotel marketing communication practitioners of 15 hotel companies in Bandung City. The findings identified that e-reputation is considered a crucial factor in determining hotel performance due to the change of customers’ behaviors today and identified also three types of e-reputation management activities implemented by hotel companies, such as online activities, offline activities, and online/offline activities. The results of this study have implications for the hospitality industry, as a reference for formulating their marketing strategies.

Grasslands are at risk of degradation due to unsustainable management practices and climate change. Sustainable grassland soil management can promote ecosystem service delivery and improve the resilience of the entire grassland ecosystem to anthropogenic change. Here, we re-view the principal soil quality indicators (SQIs) and how they have been used to evaluate the sustainability of different grassland management practices globally. We then discuss sustainable grazing management practices, before reviewing some novel grassland species which may im-prove grassland resilience with relevance for grassland management in Europe and the UK. We also give an overview of current sustainable grassland management methods and their assessment at field scale. From this, we suggest that sustainable Grazing Management Plans (GMPs), together with the testing of drought-resistant grass species and appropriate SQIs monitoring, is key to increasing resilience of grassland ecosystems to anthropogenic change.

Public green and open spaces fulfil various social, ecological, economic, and aesthetic roles, which complement each another, but can also compete with one another. COVID-19 pandemic catalysed multiple societal changes, including citizens’ perception, needs and expectations posed towards urban green spaces. This article discusses the extent to which the temporally and geographically changed patterns of experiencing these natural spaces also influenced users’ perception and behaviour as well as their appreciation of the conservation areas. The study is based upon two surveys carried out in the greater metropolitan region of Vienna, the capital city of Austria. A quantitative survey (representative online panel) among Viennese population (n=1012), as well as qualitive interviews with experts responsible for conservation areas, administrators of federal parks, along with NGOs representatives were carried out in spring and summer 2021. Our study shows the changed use of urban and suburban large green spaces and conservation areas: first, from the perspective of those responsible for the areas as well as the visitors. Both perspectives supplement one another. They highlight also changed perception of urban citizens towards green spaces during COVID-19 pandemic. An increased importance of time spent in nature (68%) and possibility to visit large green areas (67%) was reported by Viennese citizens. Also, higher recognition of green spaces located close to home was observed among 69% of the respondents. Thus, the presented study contributes to the ongoing international discussion on the transition of societal needs and its effects on urban green spaces induced by the pandemic. Presented results deliver solid arguments highlighting the need of urgent transformation towards a more sustainable, resilient and healthy urban space.

Risk protection and precaution are noticeable present, especially in times of a pandemic like Covid 19. However, it is not only in times of abruptly upcoming and unexpected situations like Corona that companies and economic entities are exposed to opportunities and threats. Internal and external developments that could influence the organization’s aims are defined as risks. Hence, it is important to emphasize that every operational activity is associated with risks and is consequently a challenge for companies. The purpose of this paper is to contribute to the identification and classification of individual risks. In this regard, the objectives and relevance of risk management are highlighted. Through the accomplishment of a classic literature review and the application of a comparative methodology the procedure of how hedging instruments are applied, is elaborated. The analysis indicates that various business concerns have a high awareness of risks inherent in business transactions, although they are still very hesitant to insert hedging instruments. Their uncertainties consist in defining and classifying the relevant risks plus identifying the appropriate hedging methods for them. Thus, this research can add new dimensions to hedging transactions and, particularly, express the benefits and opportunities of hedge accounting.

Ecosystemic services are those that provide material or immaterial benefits to the inhabitants of a landscape from its water, food, medicines and raw materials. They are classified into four types: provisioning, regulating, supporting and cultural. The latter can be defined as those non-material benefits that humans obtain through ecosystems. They include educational value, cultural diversity, sources of inspiration, spirituality and religious values, aesthetic value, social relations, rootedness or belonging, cultural heritage, recreational and ecotourism services, and scientific knowledge, among others. Characterising such diverse factors requires a systematisation in study facets for their management. We propose three: memory, image and socio-system, as differentiated spheres of approach to the urban landscape. The memory facet would include the ecosystemic services of belonging, cultural heritage and, in certain themes, cultural diversity, sources of inspiration and religious values. The image facet includes the aesthetic value and perceptual aspects of ecotourism. In the socio-system we would study the educational value, scientific knowledge and recreational or spirituality services, reflected in the endowments; but also social relations, rootedness and another vision of ecotourism.

Abstract: Panfacial fractures are complex injuries involving multiple regions of the facial skele-ton simultaneously, which may necessitate multiple surgeries over a relatively short period. They are often associated with polytrauma and other injuries including brain trauma, which re-quire either immediate airway management, prolonged intubation, or repeated intubations for staged surgeries. Given the frequent need for intermaxillary fixation and the potential involve-ment of the central nasal complex or skull base, conventional oro-tracheal or nasotracheal intu-bation often presents challenges. Submental intubation is the most reported method of airway management with the aim to avoid tracheostomy and its related complications. A review of the different techniques of airway management in the elective treatment of panfacial fractures was performed focusing on the advantages and disadvantages of each method. Most of the literature consisted of retrospective studies, with only one prospective study comparing submental intu-bation to tracheostomy in panfacial fractures. There is abundant literature that favours the sub-mental intubation for its rapid establishment and low complication rate. Other techniques less reported were retromolar intubation, nasotracheal to orotracheal switch, tracheostomy or crico-thyroidotomy. An algorithm for the management of the airway in panfacial fractures is pre-sented.

Humanity will soon define a new era for nature – one that seeks to correct decades of underwhelming responses to the global biodiversity crisis. Area-based conservation efforts, which include both protected areas and other effective area-based conservation measures, are likely to extend and diversify. But persistent shortfalls in ecological representation, management effectiveness and measurable biodiversity outcomes diminish the potential role of area-based conservation in stemming biodiversity loss. Here we show how protected area expansion by governments since 2010 has had limited success in increasing biodiversity coverage, and identify four emergent issues that –if addressed – will enhance the performance of area-based conservation post-2020. We close with recommendations for a broad biodiversity agenda that maximises the potential of area-based conservation. Parties to the Convention on Biological Diversity must recognise that area-based conservation primarily focuses on local threats to species and ecosystems, and needs enhanced emphasis on biodiversity outcomes to better track and fund its contribution to global conservation efforts.

Gelatin industry residues are increasingly used as fertilizer and soil conditioner. However, correct residue dosage is critical for grass development and minimizing environmental impacts. This randomized block design study determined adequate dosage of Mixed Gelatin Sludge (MGS) for Marandu grass production in wet/dry seasons in Brazil. Five MGS levels (0%–200% of required nitrogen) were compared to mineral fertilizer. Agronomic/productivity characteristics, bromatological composition, macro/micro-nutrient composition of leaves, and soil chemical attributes were evaluated. Agronomic/productivity characteristics were influenced by MGS dose in both dry/rainy seasons, except for leaf blade pseudostem ratio and percentage of leaves/pseudostem. Bromatological composition was influenced by MGS doses in dry/rainy seasons except for dry/mineral material quantities. Marandu leaf tissue chemical composition was significantly influenced by MGS dose, except for potassium, boron, and iron. Chemical composition of four soil layers between 0–50 cm influenced GMS dose, except for pH, organic matter, magnesium, copper, manganese, and zinc. GMS dose for Marandu production should be 200% of nitrogen (N) requirement. GMS application increased productivity/quality of Marandu grass. Macronutrients (N, phosphorus) and micronutrients (Ca, Mg, S, Cu, and Zn) increased in Marandu grass and in the soil (Ca, S, and Na). Increased sodium (Na) level was not limiting.

Background and Objectives: Chronic pain is a prevalent condition that is frequently complicated by mood and anxiety disorders. Purpose of the present article is to identify differences in the management of patients with chronic pain and anxiety/mood disorders depending on the physiotherapists’ gender. Materials and Methods: An ad-hoc questionnaire was developed and sent to 327 physiotherapists by e-mail. The two groups identified by gender were compared by unpaired sample t tests for continuous variables and χ2 tests for qualitative ones. A binary logistic regression was then performed with factors resulted statistically significant at univariate analyses as independent variables and gender as dependent one. Results: Female physiotherapists exhibited a higher level of confidence than male physiotherapists in administering continued physiotherapy for patients affected by Generalized Anxiety Disorder (GAD) (p=0.01), as well as for individuals who had previously engaged with a mental health professional (p=0.01). Furthermore, female physiotherapists believed that pharmacotherapy was less associated with motor side effects (p&lt;0.01) and more frequently recognized the importance of a training to identify affective disorders (p=0.01) and the need of more education in mental health (p=0.01). The binary logistic regression model confirmed that female professionals were less likely to work as freelance (p=0.015) and were more confident in the prosecution of physiotherapy by patients with GAD (p=0.05). Conclusions: Female physiotherapists compared to male ones seem to be more comfortable with patients affected by mental conditions and to be more aware of the need of training on mental health. Further studies are needed to confirm the results of the present study.

Background: Although Tuberculosis (TB) is one of the oldest diseases known to mankind, many practitioners are still unaware of various aspects of management of TB including drug resistant TB. To be able to make an impact on the disease burden we need to understand the knowledge, attitude and practices (KAP) of practitioners, both in government and private sector, towards TB case management. Methodology: A random cross-sectional survey of 99 respondents to assess the KAP towards TB case management using a digital semi-structured questionnaire which was pre-tested and administered to allopathic practitioners from across States in North and Central India. Results: 77% responders were government doctors and 23% were private practitioners. Chest physicians accounted for 61% of the responders. 26% of government and 78% of private doctors relied on sources which are difficult to validate for their knowledge on drug resistant TB management. There were large variations seen in knowledge on modes of transmission, standard precautions, extent of drug resistant TB, diagnostics as well as treatment regimen for drug resistant TB. Conclusion: The knowledge of both sector doctors especially amongst private practitioners with respect to the awareness of extent, diagnosis, and treatment and infection control measures for drug resistant TB is suboptimal which translates to poor diagnostic, therapeutic and infection control choices amongst private practitioners. If India has to achieve the targets for TB Elimination by 2025, serious work needs to be done to upgrade the knowledge of the private sector doctors on drug resistant tuberculosis. The Ministry of Health and Family Welfare, GoI needs to have regular educational programs for the private practitioners coupled with awareness campaigns and frequent surveys to assess the knowledge, attitude and practices being followed in the private sector for TB management including drug resistant TB.

Software project estimating (SPE) is a powerful but necessary step in the production of projects for software. Software project estimating includes several components, estimating software time, software resources, software costs, and software effort estimation (SEE). SEE seeks to estimate the number of "hours-person" and "months-person" of work required for developing or managing a software program. During the initial phase of the development of software, future efforts are impossible to predict. To estimate effort, many deep learning (DL) and machine learning (ML) models were previously created. For estimate, single-model techniques and ensemble methods were investigated in this research. Ensemble methods involve a combination of multiple separate models. Bagging, boosting, and voting were the ensemble methods looked into for estimation. Datasets considered for estimation were COCOMO81, COCOMONasa I, COCOMONasa II, Albrecht, Maxwell, China, Desharnais, Desharnais_1_1, Kitchenham, Boehm, and Belady. The evaluation criteria used MAE, RAE, RMSE, RRSE, and CC. The result from previous studies is that the total size of the set of data utilized is small in predicting the effort, as the largest size of the set of data used is the China dataset containing only 499 projects. So, in this study, the dataset has been merged to increase the total size of the set of data and increase the accuracy of prediction. The results indicated that the suggested merged dataset increased effort estimation accuracy.

The River Basin Management Plan (RBMP) is an essential component of the European Union Water Framework Directive that details an integrated approach required to protect, improve and sustainably manage water resources. RBMP were intended to be produced for the periods 2009-2015, 2016-2021 and 2022-2027. However, after two years of delays in the development processes, the Republic of Ireland produced its first RBMP in 2010. The second RBMP cycle was also implemented in 2018 and is expected to run until the end of 2021 to give way to the third RBMP, whose consultation processes have been ongoing since December 2019. This paper contributes to the forthcoming RBMP by assessing stakeholders’ perspectives on the second RBMP through a desk-based review and by conducting interviews with nine institutions (14 interviewees). The qualitatively analysed interviews reveal a broad spectrum of actors associated with water management and governance in the Republic of Ireland through a three-tier governance structure that has been delivered (with amendment) through the first two RBMPs. Organisations such as the An Fóram Uisce|The Water Forum, the Environmental Protection Agency, the Local Authority Waters, and the Agricultural Sustainability Support and Advisory Programme have responsibilities designated in the RBMPs to deliver improved water quality, integrated catchment management, community engagement and awareness-raising. Trust has also been building up among these organisations and other agencies in the water sector. Despite these responsibilities and progress, the interviews identified communication lapses, ineffective collaboration and coordination among stakeholders and late implementation to be hampering the successful delivery of the second RBMP, in addition to significant pressures acting on water bodies from agricultural activities and urban wastewater treatment. Towards the third RBMP, the paper concludes that optimised water sector finance, enhanced and well-resourced communications, and improved stakeholder collaboration are needed to foster effective and efficient water services delivery and quality. More so, given the cross-cutting impact of the Sustainable Development Goals on water resources and the interconnected relations among the goals, the paper further recommends the integration of the SDGs in the various plans of actions and a co-benefits approach to derive the triple benefits from biodiversity, climate change initiatives and water quality measures.

The efficient and sustainable management of hospitals is an increasingly relevant challenge in the healthcare sector. With limited financial resources, regulatory pressures and increasing demands for quality services, hospitals are faced with the want to approve sound policies to certify financial and operational sustainability. Management accounting is critical in this instance. In Portugal the DL nº 284, of July 26, 1999, allow us to confirm the need to reinforcement of profitability and efficiency in the provision of healthcare. Management accounting is an essential tool for monitoring and controlling costs, making strategic decisions, efficiently allocating resources and evaluating performance in the hospital environment. It allows a comprehensive view of financial and operational aspects, providing valuable information for management and strategic planning. However, the sustainability of hospital management accounting is a critical and complex topic that deserves special attention. Hospitals face several challenges, such as the complexity of hospital costs, the integration of information systems and the measurement of healthcare value. These challenges can compromise the effectiveness of management accounting and its ability to provide relevant and reliable information for decision making. As a result, it is required to address the sustainability of hospital management accounting by identifying the specific challenges faced in this area and exploring opportunities to overcome them. By addressing these challenges and seizing opportunities, hospitals can strengthen their position in the healthcare sector, improve their operational efficiency, optimize resource allocation and ensure the provision of quality services to patients. In this article, the challenges faced by hospital management accounting will be analysed, such as the complexity of costs, the integration of information systems and the measurement of value in healthcare. Additionally, opportunities to improve financial and operational management will be highlighted through the adoption of advanced technologies, an emphasis on value-based management and collaborative partnerships. By exploring these themes, this essay aims to make a contribution. to the advancement of hospital management accounting and the sustainability of hospitals in the current healthcare scenario.

In the semi-arid region of Brazil, it is common to use saline or brackish water for crop production. However, this practice can negatively affect the soil, nutrient balance, and fruit quality and production. From this perspective, this study aimed to evaluate the effect of fertilization combinations with nitrogen (N), phosphorus (P), and potassium (K) on the production and quality of West Indian cherry grown under salt stress in the second year of production. The study was conducted in a protected environment following a randomized block design with treatments distributed in a 2 x 10 factorial arrangement referring to two levels of electrical conductivity of irrigation water (ECw) (0.6 and 4.0 dS m-1) and 10 NPK fertilization combinations (80-100-100; 100-100-100; 120-100-100; 140-100-100; 100-80-100; 100-120-100; 100-140-100; 100-100-80; 100-100-120 e 100-100-140% of the recommendation in the second year of production), with three replicates and one plant per lysimeter. The results indicate that irrigation of West Indian cherry crop irrigation at the water salinity of 4.0 dS m-1 negatively affected all fruit production variables. The interaction between the ECw of 0.6 dS m-1 and the 100-80-120 NPK fertilization combination increased the total number of fruits and the total fruit weight of West Indian cherry.