The livestock sector can be a major contributor to the mitigation of greenhouse (GHG) emissions. Within the sector, beef production produces the largest proportion of the livestock sector’s direct emissions. The objective of this study was to assess the on-farm GHG emissions in semi-arid rangelands in Argentina and to identify the relationships between emissions and current farm management practices. A survey recorded detailed information on farm management and characteristics. Assessments of GHG emissions were based on the IPCC Tier 2 protocols [1]. The relationships between farm management and GHG emissions were identified using General Linear Models. Cluster analysis was used to identify groups of farms that differed from others in emissions and farm characteristics. Emissions per product sold were low on farms that had improved livestock care management, rotational grazing, received technical advice, and had high animal and land productivities. Emissions per hectare of farmland were low on farms that had low stocking rates, low number of grazing paddocks, little or no land dedicated to improved pastures and forage crops, and low land productivity. Our results suggest that the implementation of realistic, relatively easy-to-adopt farming management practices has considerable potential for mitigating GHG emissions in semi-arid rangelands of central Argentina.

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.

Weight loss solutions are on the rise, and there is growing interest in natural alternatives to the pharmaceuticals in the market, which are not devoid of relevant side effects. To this end, the objective of the current study is to assess the effects of a botanical-based blend comprised of lemon verbena and hibiscus extracts in weight management, body fat, appetite, lipid, and glucose profiles, in an overweight population, for 90 days. As a result, the volunteers presented significant weight loss in absence of diet, which coincided with decreased body fat. Body fat was assessed by anthropometry, electrical bioimpedance and DEXA scan. Cholesterol levels were also significantly decreased. Satiety assessment revealed that the product contributed to increased feeling of fullness and satisfaction after a meal, compared to the placebo group, which could contribute to the weight loss observed. Blood glucose and blood pressure levels remained unchanged, which was expected as the volunteers were normoglycemic and their blood pressure was in the healthy range. In conclusion, daily supplementation of a botanical-based blend contributes to weight loss in overweight individuals, in absence of diet, while not affecting other parameters that are in the healthy range. This product could be a candidate alternative or add-on to other weight loss products, as part of a healthy lifestyle.

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.

Stormwater drainage and urban flooding are the popular issues in policy agendas and academia. Although the research on these title increases steadily an integrated review on stormwater drainage and urban flood with a focus on pluvial flooding has yet to be produced. This paper presents a critical review on stormwater drainage and urban flood based on 78 selected journal papers published over the period of 1990 to 2018. The review focus on pluvial flooding to relate urban stormwater drainage management and urban flood disaster management and to show the links between the two. The methods taken to manage urban stormwater drainage and urban flooding as well as the complexity of achieving a comprehensive urban flood disaster management are evaluated and discussed. To better understand the concepts behind urban flood and improve the urban flood risk management strategies, recommendation of future research directions are also provided.

In this article we have estimated the value of “Opportunity Driven Entrepreneurship” in Europe. We use data from European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, Pooled OLS, and Dynamic Panel. Our results show that “Opportunity Driven Entrepreneurship” is positively associated, among others, to “Innovation Friendly Environment” and “Turnover Share Large Enterprises”, while it is negatively associated, among others, to “Sales Impacts” and “R&D Expenditure Business Sectors”.

Anemia is a condition of decreased red blood cell number or hemoglobin concentration, or of disturbance in their function, ultimately leading to decreased oxygen transport to tissues. Many factors and diseases may lead to anemia, with wide manifestations systemically as well as orally. Therefore, a sound understanding of this condition is essential for the dental practitioner, with emphasis on alerting signs, dental management and proper communication with patient’s physician.

Rapid technological advancements in information communication technologies have enabled water resource data collection at greater spatial and temporal scale. However, this water data is often limited to the purposes of its primary collection, and limits decisions made by stakeholders towards sustainable urban water management. This empirically focused research paper examines how water practitioners involved in strategic planning can capture additional values from integrating different water data. Furthermore, the perception of 22 urban water practitioners across Australia are presented, regarding the importance of and difficulty in using water data for strategic planning, and the necessary steps for achieving integrated water management practices. Interviewees perception revealed gaps in available water resource data (i.e. water quality, ground water, stormwater, and urban water use), and limitations of industry guidelines for operating within existing governance frameworks. Overall, the research highlights the Australian urban water sector’s perception of water data’s crucial role in representing stakeholders interest; however, changes made in water data’s collection are required for an integrated water management approach. Implications for future open water data standard are discussed.

Food systems will need to undergo considerable transformation. To be better prepared for and resilient to uncertainty and disturbances in the future, resource users and managers need to further develop knowledge about the food and farming system, with its dominating feedback structures and complexities, and to test robust and integrated system-based solutions. This paper investigates how participatory system dynamics modeling can be adapted to groups at the community level with low or no formal educational background. The paper also analyzes the refinement of workshop participants’ mental models as a consequence of a participatory system dynamics intervention. For this purpose, we ran two workshops with small-scale farmers in Zambia. Analysis of workshop data and post-workshop interviews shows that participatory system dynamics is well adaptable to support an audience-specific learning-by-doing approach. The use of pictures, objects and water glasses in combination with the basic aspects of causal loop diagramming makes for a well-balanced toolbox. Participants acquire understanding that is also relevant beyond systems thinking in that is offers a range of practical insights such as a critical evaluation of common food security strategies.

The establishment of thresholds is integral to environmental management. This paper introduces the use of thresholds in the context of deep-seabed mining, a nascent industry for which an exploitation regime of regulations, standards and guidelines is still in the process of being developed, and for which the roles and values of thresholds have yet to be finalised. There are several options for integrating thresholds into the International Seabed Authority’s regulatory regime, from being stipulated in regulations to being part of a mining contract, each option having its own advantages and disadvantages. Here we explore the range of ways that thresholds can be derived, set out the challenges in translating ecological and management data into thresholds, highlight factors for acceptance and operationalisation of thresholds in deep-seabed mining, and explain the necessity of refining thresholds as knowledge on impacts to features improves. Some comparable marine industries already use thresholds and these could potentially be used as starting points for the development of thresholds for deep-seabed mining. In order to be acceptable to the wide range of deep-seabed mining stakeholders, thresholds need to strike a balance among levels of harm acceptable by society, levels of environmental precaution justifiable by governments, scientific robustness, and operational practicality.

This paper aims to provoke fundamental thinking and action around the value and importance of socially-equitable development to the economic advancement, resilience, and prosperity of communities, as we contend with the 21^st Century grand challenge of the changing climate and disasters. As local communities and the global community have experienced an increased frequency, intensity and duration of natural and man-made disasters over the past several decades, opportunities have also grown to identify and reap the benefits of socially-equitable economic development. Reflecting on the COVID-19 pandemic, we discuss the critical importance of socially-equitable economic development to the resilience and sustainability of communities and the infrastructure that supports them. To this end, we: (1) examine what constitutes socially-equitable economic development at different spatial scales of community; (2) explore whether socially-equitable development can occur at different scales of community; (3) explicate the importance of formally considering the inputs, processes, outputs and outcomes for socially-equitable development; (4) explain why the pursuit of equal distribution of the benefits and burdens of development is a necessary but not sufficient endeavor for socially-equitable economic development; (5) analyze the relationships between socially-equitable development, and resilient and sustainable infrastructure and communities; (6) explain why socially-equitable development should be a key component of infrastructure and community resilience strategies in the 21^st Century; and, (7) explain why socially-equitable development can ultimately be viewed as a long-term strategy for prosperity.

Solid-state lighting has been replacing conventional lighting in the market, raising concerns for implementing an efficient end-of-life management system. Since LED waste streams have not been quite dominant, characterization studies (product-level characteristics, component-wise information, bill of materials, diversity, and differences) are inconsistent and having substantial gaps. This study investigates the end-of-life LED lamp literature, focusing on the bill-of-materials, and reveals that the characterization procedure suffers from a severe lack of sample representativeness. Consequently, characterization results are widely varied and not generalizable. Moreover, most of the studies did not inform and document the detailed sample characteristics, precluding the possibility of identifying reasons for variation. Combining available information from the recent studies, we present a mass distribution at the component level, exemplifying the prospect for meeting EU regulatory limit and the need for more insight at the lamp and component level. To fill the disconnection between lamp level characteristics and component and material content, we propose a characterization protocol that carefully documents lamp, component, and material level information by establishing a lamp-component–material composition nexus. The protocol may help researchers, policymakers, and industrial stakeholders conduct a systematic characterization, analyze complexities and prepare for a sustainable solution.

All departments in a business work separately, but for the same purpose.In this article, a system that allows not only the mechanical design department but also the manufacturing, storage, process planning, quality control, electrical design, purchasing departments, etc. to have access to the required information has been developed. Initially, current manufacturng result informations is collected from the project attandees. Secondly, a workflow is designed dependent on the current data flow. All the project stakeholders are introduced to join and use product data management system. In the absence of this kind of system, loss of time, scraps and loss of engineering time would be investigated. This allowed the company owners to be sure that no faulty revision of design will be produced after the system started. On the other hand automation of bill of materials generation provided the purchasing department correct and up to date information about outsourced parts. Allowing different engineering disciplines to work together provided more suitable environment. Gradually this conditions allowed all the departments work faster and market the new product much faster than before the system. Tracing the workflows for management purposes would be handled by the system. A ‘Validation of Design’ process is modelled for the company.

The emergence of digital twins (DTs) represents a recent advancement in technological processes that support the planning, construction, and oversight of constructed assets. A DT is essentially a digital model that facilitates simulations and two-way information exchange with its real-world counterpart (a physical twin), creating opportunities for data-driven decision-making. Despite the promising prospects of DTs, both the technology and the methodologies for developing them, as well as their potential applications, remain not fully understood in both academic and industrial contexts. This research explores the applications of DTs for the management of existing assets within the AEC/FM industry. The study presents the results of a comprehensive literature review that explores existing knowledge in this domain. The findings reveal that procedures for creating DTs are still in their early stages, emphasizing potential applications in asset management throughout their lifespan, facilitating sustainability upgrades, and supporting the maintenance and restoration of heritage assets. The review concludes by providing recommendations for future research in this evolving field.

Fungal pathogens pose a major threat to food production worldwide. Traditionally, chemical fungicides have been the primary means of controlling these pathogens, but many of these fungicides have recently come under increased scrutiny due to their negative effects on the health of humans, animals, and the environment. However, the use of fungicides with less of an environmental impact tends to result in the development of resistance in populations of phytopathogenic fungi. Therefore, new environmentally friendly alternatives that provide adequate levels of disease control are needed to replace chemical fungicides—if not completely, at least partially. A number of alternatives to conventional chemical fungicides have been developed, including plant defence elicitors (PDEs), biological control agents (fungi, bacteria and mycoviruses), biofungicides, RNA interference (RNAi) methods, and resistance breeding. This article reviews the conventional and alternative methods available to manage fungal pathogens, discusses their strengths and weaknesses, and identifies potential areas for future research.

Dementia is a major issue for healthcare systems worldwide, necessitating the development of creative and effective strategies for its management. This paper examines the use of Artificial Intelligence (AI) technologies in caring for and managing people with dementia. AI-driven solutions can improve diagnosis, personalize care, optimize medication management, and reduce the burden on caregivers. This paper discusses the implementation of an AI-based framework for creating videos related to people’s memories to support train-therapy or travel- therapy, a non-pharmacological intervention for Alzheimer’s disease patients

Full-order state-space models represent the starting point for the development of advanced control methods for wind turbine systems (WTSs). Regarding existing control-oriented WTS models, two research gaps must be noted: (i) There exists no full-order WTS model in form of one overall ordinary differential equation that considers all dynamical effects which significantly influence the electrical power output; (ii) all existing reduced-order WTS models are subject to rather arbitrary simplifications and are not validated against a full-order model. Therefore, in this paper, two full-order nonlinear state-space models (of 11th and 9th-order in the (a, b, c)- and (d, q)-reference frame, resp.) for variable-speed variable-pitch permanent magnet synchronous generator WTSs are derived. The full-order models cover all relevant dynamical effects with significant impact on the system’s power output, including the switching behavior of the power electronic devices. Based on the full-order models, by a step-by-step model reduction procedure, two reduced-order WTS models are deduced: A non-switching (averaging) 7th-order WTS model and a non-switching 3rd-order WTS model. Comparative simulation results reveal that all models capture the dominant system dynamics properly. The full-order models allow for a detailed analysis covering the high frequency oscillations in the instantaneous power output due to the switching in the power converters. The reduced-order models provide a time-averaged instantaneous power output (which still correctly reflects the energy produced by the WTS) and come with a drastically reduced complexity making those models appropriate for large-scale power grid controller design.

Acute pancreatitis (AP) is a leading gastrointestinal disease that cause hospitalization. Initial management in the first 72 h after the diagnosis of AP is pivotal, which can influence the clinical outcomes of the disease. Initial management, including fluid resuscitation, pain control, nutritional support, antibiotic use, and endoscopic retrograde cholangiopancreatography (ERCP) in gallstone pancreatitis, plays a fundamental role in AP treatment. Recent updates for fluid resuscitation, including treatment goals, the type, rate, volume, and duration, have triggered a paradigm shift from aggressive hydration with normal saline to goal-directed and non-aggressive hydration with lactated Ringer’s solution. Evidence of the clinical benefit of early enteral feeding is becoming definitive. Routine use of prophylactic antibiotics is generally limited, and the procalcitonin based algorithm of antibiotic use has recently been investigated to distinguish between inflammation and infection in patients with AP. Although urgent ERCP (within 24 h) should be performed for patients with gallstone pancreatitis and cholangitis, urgent ERCP is not indicated in patients without cholangitis. Furthermore, convalescent treatment, including cholecystectomy in gallstone pancreatitis and alcohol intervention in alcoholic pancreatitis, is also important for improving the prognosis and prevent recurrence in patients with AP. This review focuses on recent updates on the initial and convalescent management strategies for AP.

Recent advances in quantum computing systems attract tremendous attention. Commercial companies, such as IBM, Amazon, and IonQ, have started to provide access to noisy intermediate-scale quantum computers. Researchers and entrepreneurs attempt to deploy their applications that aim to achieve a quantum speedup. Grover’s algorithm and quantum phase estimation are the foundations of many applications with the potential for such a speedup. While these algorithms, in theory, obtain marvelous performance, deploying them on existing quantum devices is a challenging task. For example, quantum phase estimation requires extra qubits and a large number of controlled operations, which are impractical due to low-qubit and noisy hardware. To fully utilize the limited onboard qubits, we develop a distributed application with a key-value data structure based on Grover’s algorithm called IQuCS . Consider a database with duplicates. By encoding each element to a binary type with a unique key and forming a key-value pair, we can count the number of occurrences of each element in the database based on quantum computing. We have optimized the operation process by filtering data points to make it more efficient. To determine the effect of this optimization, we evaluate it with datasets of different sizes and with different numbers of duplicates. With the assistance of classical computers, IQuCS can reduce the problem set for each query. Due to this reduction, IQuCS requires fewer qubits. Through the iterative management, IQuCS achieves a reduction of qubit virtualized consumption, up to 66.2%, with reasonable accuracy.

Sustainability is the core concern of every business; The exploration of avenues to maintain sustainability while staying competitive with high level of productivity remains a vital endeavor. Production flexibility is a key area that can enhance the sustainability of manufacturing industries as it can ensure product availability, scalability, agility/fault tolerance as well as disaster recovery potentials. Technological advancements have provided avenues where companies can enhance virtually all aspects of their operations for efficiency, effectiveness, and productivity. This paper uses both quantitative and qualitative research approach to identify the capability requirements for smart and effective production management and subsequent analysis is done using Multi-Criteria Decision-Making methodology to identify and rank various industry 4.0 technologies and concepts that can provide these smart capabilities in in manufacturing industries to aid the businesses to achieve sustainability with production flexibility. The paper identifies over 12 smart capabilities and 9 Industry 4.0 Technologies which are applicable to production management. It also compares results from the analytics of historical I4.0 implementation as discussed in literatures with the current state as deduces from survey feedbacks from various manufacturing industries.

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.

Storing scientific data on the file system in a meaningful and transparent way is no trivial task. In particular when the data have to be accessed after their originator has left the lab the importance of a standardized file structure cannot be underestimated. It is desirable to have a structure that allows for the unique categorization of all kinds of data from experimental results to publications. It has to be accessible to a broad variety of workflows, e.g., via graphical user interface as well as via command line, in order to find widespread acceptance. Furthermore, the inclusion of already existing data has to be as simple as possible. We propose a three-level structure to organize and store scientific data that incorporates the full chain of scientific data management from data acquisition to analysis to publications. Metadata are saved in a standardized way and connect original data to analyses and publication as well as to their originators. A simple software tool to check a file structure for compliance with the proposed structure is presented.

In this review, the effect of colostrum on immune system development in buffalo calves was examined. The neonatal period is critical for buffalo calves and is characterized by a high mortality rate (more than 40%); the intake of colostrum improves the immune system of calves, increasing their chances of survival. Mainly in intensive farms, the availability of good quality colostrum is necessary, thus, good quality colostrum is often stored to provide newborn calves which cannot be fed by their mothers. The buffalo breeding is constantly expanding in Italy, mainly thanks to the Mozzarella cheese production that represents an excellence of the “Made in Italy” and is exported worldwide. High calf mortality rates directly affects the profitability of the business. Compared with other species, researches on buffalo colostrum are scarce; nevertheless it is fundamental to improve colostrum characteristics and management to guarantee buffalo calves health and reduce their mortality rate.

The complexity of analysis pipelines in biomedical sciences poses a severe challenge for the transparency and reproducibility of results. Researchers are increasingly incorporating software development technologies and methods into their analyses, but this is a quickly evolving landscape and teams may lack the capabilities to set up their own complex IT infrastructure to aid reproducibility. Basing a reproducible research strategy on readily available solutions with zero or low set-up costs whilst maintaining technological flexibility to incorporate domain-specific software tools is therefore of key importance. We outline a practical approach for robust reproducibility of analysis results. In our examples, we rely exclusively on established open-source tools and free services. Special emphasis is put on the integration of these tools with best practices from software development and free online services for the biostatistics domain.

Warming of the climate system is unequivocal, and many of the observed changes are unprecedented over five decades to millennia. Globally the atmosphere and ocean is increasingly getting warmer, the amount of ice on the earth is decreasing over the oceans, and the sea level has risen. According to Intergovernmental Panel on Climate Change, the total increasing temperature globally averaged combined land and surface between the average of the 1850-1900 period and the 2003 to 2012 period is 0.78 °C (0.72 to 0.85). But should we prepare for such the relatively small change? The importance is not the mean of the warming but the considerable likelihood of climate change that could trigger extreme natural hazards. The impact and the risk of climate change associated with railway infrastructure have not been fully addressed in the literature due to the difference in local environmental parameters. On the other hand, the current railway network in Malaysia, over the last decade, has been significantly affected by severe weather conditions such as rainfall, lightning, wind and very high temperatures. Our research findings point out the extremes that can lead to asset system failure, degraded operation and ultimately, delays to train services. During the period of flood, the embankment of the track can be swept away and bridge can be demolished, while during drought, the embankment of the track can suffer from soil desiccation and embankment deterioration, high temperature increases the risk of track buckling and high winds can result in vegetation or foreign object incursion on to the infrastructure as well as additional quasi-static burden exerted. This review is of significant importance for planning and design of the newly proposed high speed rail link between Malaysia and Singapore.

In recent years, Malaysia has faced environmental challenges caused by municipal solid waste, especially household waste, during the Covid-19 pandemic. Among all the household waste, plastic and paper are the most prominent waste that causes environmental hazards. Several recycling associations in Malaysia have carried out their practices for better waste sustainability and management to curb the increasing amount of household waste. However, the effectiveness is still vague in achieving smart and effective household waste management. Therefore, this paper aims to investigate Malaysia’s household waste management, mainly in three significant municipalities in Malaysia for Kuala Lumpur, Penang and Melaka, in becoming a resilient and sustainable city by addressing two main research questions 1) What are the key factors for ensuring the more success move for future household waste management in cities? and 2) How will the 3 municipalities address their waste issues based on the key factors from RQ1, respectively? This paper reviewed 13 waste management articles and explores the potential of the four factors of waste management from the perspective of technology and data, economy, social and governance. The discussed factors and models contributed to an integrated future-proofing framework that focuses on smart waste tracking, an gamified awareness education, and strict policies to control waste management are the way forward for the future of smart cities household waste management.

Buildings are subject to intrinsic and extrinsic failures at all stages of the construction process, i.e., design to occupancy (i.e., use) as several failure types can affect them. There are three basic steps for researching building failures: listing, cataloging, and solving/deciding whether highlighting the least invasive and lowest cost intervention. Therefore, this research presents some methods used in construction for the intervention prioritization and seeks to illustrate the most suitable methodology for different settings failure x diagnosis x intervention. Therefore, the most traditional tools are shown: BASICO, SWIFT, FEMEA, AAF, and GUT matrix, where a critical assessment of the strengths and weaknesses is carried out. After that, a case study on maintenance services for the moisture on the building facades was performed. Finally, the GUT matrix and the FMEA method are the best results

Medically underserved communities have limited access to effective disease management resources in the U.S. Mobile health applications (mHealth apps) offer patients a cost-effective way to monitor and self-manage their condition and to communicate with providers; however, current diabetes self-management apps have rarely included end-users from underserved communities in the design process. This research documents key stakeholder-driven design requirements for a diabetes self-management app for medically underserved patients. Semi-structured survey-interviews were carried out with 97 patients with diabetes and 11 healthcare providers from medically underserved counties in South Texas to elicit perspectives and preferences regarding a diabetes self-management app, and their beliefs regarding such an app’s usage and utility. Patients emphasized the need for accessible educational content and for quick access to guidance on regulating blood sugar, diet, and exercise and physical activity using multimedia rather than textual form. Healthcare providers indicated that glucose monitoring, educational content, and graphical visualization of diabetes data were among the top-rated app features. These findings suggest that specific design requirements for the underserved may improve the adoption, usability, and sustainability of such interventions. Designers should consider health literacy and numeracy, linguistic barriers, data visualization, data entry complexity, and information exchange capabilities.

Amidst the recent energy crisis, the pivotal role of resource efficiency and renewable energy sources (RES) for sustainable development has become apparent. Transition to sustainability involves decentralized energy solutions empowering local communities to generate, store, and utilize their energy, diminishing reliance on centralized systems and potentially transforming them into power flexibility resources. This is particularly crucial in non-interconnected island systems that primarily rely on imported oil for electricity generation. Such reliance not only implies high production costs but also threatens energy security and adds to the environmental footprint of local economic activities. Addressing the above necessitates, amongst other elements, the adoption of advanced energy management with sophisticated forecasting and demand-side management (DSM) strategies. In response, we introduce a versatile algorithm investigating the impact of DSM at the community scale, designed to maximize the utilization of renewable energy produced from local installations. Integrated as an ancillary module in an advanced energy management platform, the algorithm undergoes testing using datasets collected from end-consumers and a small-scale RES installation on the island of Tilos, Greece. This study not only offers insights for energy stakeholders but also establishes theoretical parameters that can inform subsequent decision-making processes.

Ubiquitous computing comprises scenarios where networks, devices within the network, and software components change frequently. Market demand and cost-effectiveness are forcing device manufacturers to introduce new-age devices. Also, the Internet of Things (IoT) is transitioning rapidly from the IoT to the Internet of Everything (IoE). Due to this enormous scale, effective management of these devices becomes vital to support trustworthy and high-quality applications. One of the key challenges of IoT device management is automatic device classification with the logically semantic type and using that as a parameter for device context management. This would enable smart security solutions. In this paper, a device classification approach is proposed for the context management of ubiquitous devices based on unsupervised machine learning. To classify unknown devices and to label them logically, a proactive device classification model is framed using a k-Means clustering algorithm. To group devices, it uses the information of network parameters such as Received Signal Strength Indicator (rssi), packet_size, number_of_nodes in the network, throughput, etc. Experimental analysis suggests that the well-formedness of clusters can be used to derive cluster labels as a logically semantic device type which would be a context for resource management and authorization of resources. This paper fulfills an identified need of proactive device classification for device management.

Continuity of activities and projects are important for sustainably developing organizations, especially universities. The purpose of this research study is to find university development guidelines regarding waste management according to the green university ranking criteria for sustainable developments by studying and collecting the data covering the last five years (2019 - 2023) of Mahasarakham University. We also analyzed and synthesized lessons learned from the details of the operations and the factors involved in successes while comparing and providing suggestions for the operations in the next year. It was found that waste management that resulted in continuous developments that achieved the goals of Mahasarakham University consisted of the five guidelines. (1) Making green university policies and using them as the (key performance index) KPI of the divisions and also announcing the university's waste management policies by applying the principles of 3R (Reuse-Reduce-Recycle). (2) Allocating the budgets supporting the projects' activities according to the evaluation criteria. (3) Student and personnel participation as well as the mechanisms used by the committees from various administrative divisions such as Student Council, Student Association and clubs to drive the operations. (4) Identifying the main responsible individuals and committees for the green university who communicated and drove the operations while collecting, analyzing and preparing the data. (5) Follow-ups and evaluations of the project's activities with the Plan-Do-Check-Act (PDCA) processes for continuous and sustainable developments and improvements leading to the green university. With the above operations, Mahasarakham University's waste management scores of the six indices during 2019 - 3023 increased annually as follows: 900, 900, 1050, 1275 and 1350.

This article explores the results of a study on the improvement of the swiftlet house business with the goal of making appropriate legal measures for it. Area surveys, focus groups, and in-depth semi-structured interviews were among the data collection methods used. Swiftlet house entrepreneurs; central and local government officials; and citizens surrounding swiftlet houses significantly contributed to the research. Currently, the swiftlet house business is still illegal in Thailand because swiftlets are considered protected wildlife – protected by the Wildlife Preservation and Protection Act B. E. 2562 (2019). Additionally, it is not permitted to collect, damage, or occupy swiftlet nests without appropriate legal authority to do so. Moreover, there is still no legislation that specifically applies to the swiftlet house business. This study can guide the Thai Government and local governments to develop appropriate laws to govern the swiftlet house industry in Thailand.

Waste management is a significant issue that Indonesia must face. The presence of waste will always exist as long as life continues. One of the main challenges in waste management is the proper separation of organic and inorganic waste. As a solution to address this issue, the Ministry of Environment has made efforts to develop Waste Banks. However, it also creates new problems related to manual data collection, lack of monitoring by the community in implementing waste management activities, and a lack of specific reports regarding waste management conducted by officers. We propose the creation of a website using the Agile Development SDLC method. This website involve several steps and incorporate functions for data digitalization and expedited data collection, such as the addition of QR Code functionality, Monthly Reporting Function, and enhanced data security. The method used in this research is Agile Development. The application has been developed with a user-friendly interface and the latest web development technologies to ensure smooth performance. Overall, the web-based application for organic and inorganic waste using Laravel is an important step to promoting sustainable waste management practices.

This paper presents quantitative research results regarding the influence of demographic factors on the earthquake risk perception of the citizens of Belgrade. This research aims to determine how much the citizens of Belgrade are aware of the risk and prepared to react in the event of an earthquake. The relationship between gender, age, level of education, and facility ownership with risk perception was examined. T-test, One-way ANOVA, and Pearson correlation coefficient were used to examine the relationship between the variables and the earthquake risk perception. The survey was conducted using a questionnaire that was given and then collected online among 235 Belgrade respondents during September 2020. The questions were divided into three categories. The first part of the questionnaire was consisted of general questions about the demographic characteristics of the respondents, then the questions that would determine the level of awareness of the respondents about earthquakes, and finally, the questions for determining the respondents' preparedness. The results of the research show that women have a higher perception of risk. It has been proven that the youngest respondents from the age category of 18-30 have the lowest risk perception. The influence of education level in no case showed a statistically significant correlation with risk perception.

This narrative review aims to summarize evidence regarding the current utilization and future applications of neuromodulation in patients with headaches, with special attention paid to migraine and chronic cluster headache. We performed a narrative review of the literature to identify studies that detail the effectiveness of neuromodulation therapies in the treatment of headache syndromes. The literature was refined to predominantly focus on systematic reviews published in the last year that have the most robust reporting of research done on this topic. Patients with headache face several challenges, including medication overuse, cost burden, non-compliance to medications due to inability to tolerate side effects, or treatments that are ineffective. Neuromodulation is an emerging field that encompasses implantable and non-implantable technologies that intervene on the signaling and perception of pain. In recent years, this technology has been used as an analgesic, and has been shown to be effective for treatment-resistant headache, particularly when used in patients with migraine and chronic cluster headache.

Project managers should balance a variety of resource elements in building projects while taking into account many major concerns, including time, cost, quality, risk, and the environment. This study presents a framework for resource trade-offs in project scheduling based on the Building Information Modeling (BIM) methodology and metaheuristic algorithms. First, a new metaheuristic algorithm called Fire Hawk Optimizer (FHO) is used. Using project management software and the BIM process, a 3D model of the construction is created. In order to maximize quality while minimizing time, cost, risk, and CO2 in the project under consideration, an optimization problem is created, and the FHO's capability for solving it is assessed. A predefined stopping condition is taken into account while doing 30 independent optimization runs to obtain the statistical metrics, such as the mean, standard deviation, and the required number of objective function evaluations. The results show that the FHO algorithm is capable of producing competitive and exceptional outcomes when it comes to trade-off various resource options in projects.

The Ministry of Health evaluates hospital management in accordance with the standard of quality of service. The concept of Shariah hospitals offers management services that exceed the standard of quality of hospital care. The study aims to illustrate the concept of Shariah hospitals in Indonesia. We collect related literature from various media via online search with the keywords “Shariah hospitals,” “implementation of Shariah hospitals,” and “application of Shariah hospitals.” Main findings: The study finds that the Shariah hospitals built by the philosophy of Islam are willing to provide the best health-care services to patients. A code of conduct must be fulfilled by the hospital management in Shariah hospitals: (1) general liability, (2) obligations to society and the environment, (3) obligations to patients, (4) obligations to the leaders, staff, and employees, and (4) relationships with related institutions. The foremost challenges include the improvement of health personnel performance and the quality of services in addition to perceptions that are not inclusive of the system of Shariah hospitals. This implementation should run consistently and with the commitment of all parties. Such insight, in turn, can be counted as an input to an approach to health services, particularly in increasing the performance rates, such as hospital. This study is the first to provide new insight into discussion about shariah hospital by presenting its focuses on Islamic approaches in meeting the quality standards of health services in hospitals so as to obtain more value. However, exclusive principles—Islamization, heterogeneity, and the performance of health workers—challenge the implementation of this hospital system.

In the past decade, we have witnessed a dramatically increasing volume of data collected from varied sources. The explosion of data has transformed the world as more information is available for collection and analysis than ever before. To maximize the utilization, various machine and deep learning models have been developed, e.g. CNN [1] and RNN [2], to study data and extract valuable information from different perspectives. While data-driven applications improve countless products, training models for hyperparameter tuning are still time-consuming and resource-intensive. Cloud computing provides infrastructure support for the training of deep learning applications. The cloud service providers, such as Amazon Web Services [3], create an isolated virtual environment (virtual machines and containers) for clients, who share physical resources, e.g., CPU and memory. On the cloud, resource management schemes are implemented to enable better sharing among users and boost the system-wide performance. However, general scheduling approaches, such as spread priority and balanced resource schedulers, do not work well with deep learning workloads. In this project, we propose SpeCon, a novel container scheduler that is optimized for shortlived deep learning applications. Based on virtualized containers, such as Kubernetes [4] and Docker [5], SpeCon analyzes the common characteristics of training processes. We design a suite of algorithms to monitor the progress of the training and speculatively migrate the slow-growing models to release resources for fast-growing ones. Specifically, the extensive experiments demonstrate that SpeCon improves the completion time of an individual job by up to 41.5%, 14.8% system-wide and 24.7% in terms of makespan.

With the evolution of technology over the years, it has become possible to develop intelligent environments based on the concept of the Internet of Things, distributed systems, and machine learning. Such environments are incorporated with various solutions to solve user demands from services. One of these solutions is UBIPRI middleware, whose central concept is to maintain privacy in smart environments and to receive notifications as one of its services. However, this service is freely performed, disregarding the privacy that the environment employs. Another consideration is that based on the researched related works, it was possible to identify that the authors do not use statistical hypothesis tests in their solutions developed in the presented context. This work proposes an architecture for notification management in smart environments, composed by a notification manager named PRIPRO to assign it to UBIPRI and to aim to perform tests and comparisons between classification algorithms to delimit which one is most feasible to implement in the PRINM decision-making mechanism. The experiments showed that the J48 algorithm obtained the best results compared to the other algorithms tested and compared.

Obesity is one of the greatest health challenges facing today’s adolescents. Dietary interventions are the foundation of obesity prevention and management. As adolescents are digital frontrunners and early adopters of technology, digital health interventions appear the most practical modality for dietary behaviour change interventions. Despite the rapid growth in digital health interventions, effective engagement with adolescents remains a pertinent issue. Key strategies for effective engagement include co-designing interventions with adolescents, personalisation of interventions, and just-in-time adaptation using data from wearable devices. The aim of this paper is to appraise these strategies, which may be used to improve effective engagement and thereby improve the dietary behaviours of adolescents now and in the future.

This report presents a framework for analysing the risk of alien taxa under South Africa's National Environmental Management: Biodiversity Act of 2004, and the Alien and Invasive Species Regulations of 2014. While the report was initially designed to meet a specific South Africa need, the risk analysis processes developed can, we believe, be transferred to any specified geographic region. In outlining a series of questions related to a taxon’s likelihood of invasion and the consequences thereof, i.e. the potential impacts, the report provides a structure for collating data relevant to the process of listing taxa as well as a process for developing recommendations that is both mathematically sound, transparent, and that explicitly takes uncertainty into account. The framework is based on collating information according to international standards in biological invasions (specifically the IUCN Environmental Impact Classification of Alien Taxa Scheme, the CBD's scheme for classifying invasion pathways, and the Unified Framework for Biological Invasions proposed by Blackburn et al. 2011). The risk analysis framework is currently being implemented in South Africa in an effort to underpin national regulatory lists of invasive species.

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.

One of the most concerning global environmental issues is the pollution of agricultural soils by heavy metals (HMs), especially cadmium (Cd), which not only affects human health by taking Cd-containing foods but also impacts the quality of rice. The soil's nitrification and denitrification processes, coupled with the release of volatile organic compounds by plants, raise substantial concerns. The understanding of three aspects of paddy soil under conditions of heavy-metal pollution and water management is currently limited. In this review, we summarized recent literature related to the deleterious effects of Cd on both soil processes related to the N cycle and rice quality, particularly aroma, in different water management practices. Under both continuous flooding (CF) and alternate wetting and drying (AWD) conditions, cadmium (Cd) has been observed to reduce both nitrification and denitrification processes. The adverse effects are more pronounced in continuous flooding (CF) compared to alternate wetting and drying (AWD). Similarly, the alteration in rice aroma is more significant in AWD than in CF. The precise modulation of volatile organic compounds (VOCs) by Cd, remains unclear based on the available literature. Nevertheless, HM accumulation is higher in AWD conditions compared to CF, leading to a detrimental impact on volatile organic compounds (VOCs). The literature concluded that AWD practices should be avoided in Cd contaminated fields to decrease accumulation and maintain the quality of rice. In the future, rhizospheric engineering and plant biotechnology can be used to decrease the transport of HMs from the soil to the plant’s edible parts.

The advent of deep learning has completely reshaped our world. Now, our daily life is fulfilled with many well-known applications that adopt deep learning techniques, such as self-driving cars and face recognition. Furthermore, robotics developed more forms of technology which share the same principle with face recognition, such as hand pose recognition and fingerprint recognition. Image recognition technology requires a huge database and various learning algorithms, such as convolutional neural network and recurrent neural network, that requires lots of computational power, such as CPUs and GPUs. Thus, clients could not be satisfied with the computational resource of the local machine. The cloud resource platform emerged at a historic moment. Docker containers play a significant role of microservices-based applications in the next generation. However, it could not guarantee the quality of service. From clients’ perspective, they have to balance the budget and quality of experiences (e.g. response time). The budget leans on individual business owners and the required Quality of Experience (QoE) depends on usage scenarios of different applications, for instance, an autonomous vehicle requires real-time response, but, unlocking your smartphone can tolerate delays. Plenty of on-going projects developed user-oriented optimization resource allocation to improve the quality of the service. Considering the users’ specifications, including accelerating the training process and specifying the quality of experience, this thesis proposes two differentiate containers scheduling for deep learning applications: TRADL and DQoES .

The exponential growth in the consumption of electronics, in combination with the reduction in their useful life, leads to a significant increase in the volume of electronic material discarded. Printed Circuit Boards (PCBs) are modules composed of ceramic, polymer and metallic materials of high economic value and with a great potential for damage to biotic and anthropic environments when inadequately discarded. The aims of this work was to study the main environmental impacts and the efficiency of mechanical operations in the electronic waste recycling process in optimizing the concentration of metallic copper. For this, the samples obtained were characterized according to their morphology and chemical composition, and subjected to physical and mechanical treatments: dismantling, grinding, separation by granulometry, density and magnetic property. The environment impacts were estimated by the Life Cycle Assessment of the pre-treatment processes, associated with copper extraction operations in WPCBs. According to the results obtained, it is possible to infer that the NM +1mm Concentrated product presents in its metallic composition around 78% of copper, which contributes to the efficiency of the hydrometallurgical extraction processes. It is noteworthy that the Concentrated class represents about 14% of copper (wt) taking into account the amount of 3.789 kg of PCB waste input material. The potential for reinsertion of the dust in the material recovery process is highlighted, given that the chemical composition of this particulate has a significant presence of metals. In general, it was found that due to the higher concentration (wt %) of the sample being allocated in the range of - 0.15mm + 0.05mm, the elements Fe (18.30%), Si (10.73%), Ca (9.21%) and Cu (8.89%) stand out regarding the participation of the elemental composition of this fraction and also regarding the general composition of the sample. Furthermore, the generation of dust during the fragmentation process, can be associated with occupational respiratory diseases when not managed. About the Life Cycle Assessment, in seven of the nine categories evaluated, crushing and screening activities accounted for more than 90% of the recorded impact values. In general, it is estimated that in the pre-treatment phase be generated 15.4 kg CO2 eq.

Background There is increasing awareness of problems associated with global warming but a lack of a systematic approach on how to deliver more environmentally sustainable dental care. A sustainable world aims to ensure that basic needs and quality of life of everyone are met, now and for future generations. The carbon footprint is an indicator of environmental sustainability. Aim The aim is to suggest an environmental management change for the dental practice focusing on the objective of carbon footprint reduction. Environmental management change design The management change is based on the concept of “Plan-Do-Check-Act”, as recommended by the International Organisation for Standardisation (ISO) and described through the environmental aspects of the dental practice. The approach focuses on establishing and implementing environmental objectives, followed by monitoring results and taking actions to improve continually. The environmental aspects considered for the dental practice are activities causing an impact on the carbon footprint: energy use, travel, product purchasing, waste production, emission to air, water use, and contamination of land. Conclusions The “Plan-Do-Check-Act” ISO 14100-2015 model can be effectively integrated into the dental practice setting for its environmental management. A reduction of the carbon footprint of the dental practice is achieved by applying the environmental management change described for each activity.

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.

The best business relationships are built as relationships between people and organizations that work together to achieve common goals. In the current digital era, B2B collaboration relationships are essential for business success. The response time to customer requests can be a key factor in maintaining these relationships and obtaining a competitive advantage. The use of VBA automation for repetitive tasks can help speed up this process, but it is important that computer operators have medium knowledge about using VBA macros. This work deals with issues related to improving response times to requests received by email, using a macro program for repetitive tasks. The empirical study was conducted on an average of 50 daily emails for order confirmation, with an average writing time of 68 s per email, resulting in a potential reduction in working time for the operator of approximately 1 h/day, only for order confirmation. The results show a significant improvement in working time for computer operators, using VBA buttons for repetitive tasks.

Design changes seem inevitable in engineering, procurement and construction EPC projects. Such changes create a need for a proactive approach to adjusting project scope, cost and time (the triple constraints) for efficiency and effectiveness in overall delivery. This study investigates the causes and implications of design changes in order to improve design change management practices. Data for the study was obtained through online interviews with New Zealand industry practitioners. Thematic analysis was used to collate the results into meaningful data. The study found that design changes were predominantly caused by clients' inadequate strategic planning, insufficient attention to design, EPC contractors' inadequate design ability, and on-site variations. There were three categories of such design changes: direct impact on the project, the reciprocal and complementary effect on stakeholders, and the far-reaching impact on the community. The study concludes by suggesting improvements, such as strengthening the integration of project teams to enhance design quality, strategic alignment of stakeholders at the planning stage, early contractor involvement (ECI) between the planning and design phases, and improving collaboration between design and construction teams. Further, a combination of high technical skills (e.g. design ability) and soft skills (can-do attitude, interpersonal skills, problem-solving skills, documentation skills, etc.) are needed to effect the desired improvement in design change management.

This study presents virtual reality (VR) videos as an effective technique for delivering extension educational materials on manure and mortality management. Virtual reality is a technology that can enable immersive distance learning. Using VR tours can enable the public to learn manure and mortality management technologies without in-person farm visits, thus saving traveling time and money and avoiding exposure to pathogens and noxious odors in farms. As the first part of this project, 360° VR tours were created on multiple aspects of manure management, including composting, anaerobic digestion, and preliminary wastewater treatment. These videos were presented to a diverse audience of agricultural producers, extension specialists, and researchers through in-person and online extension events and the Texas Manure YouTube channel. The effectiveness of videos was evaluated using surveys, which measured the audience's awareness of the topics before and after watching VR videos. Statistical analysis revealed that the increase in awareness after watching the videos was statistically significant, with a p-value of less than 0.0001. Statistical analysis also revealed that job classification and professional experience significantly impacted the change in awareness. Researchers, extension specialists/agents, and participants with less experience in manure and mortality management experienced a greater change in awareness than agricultural producers and participants with more experience. Interest and impression of the audience on the VR videos was also evaluated. According to survey data, the majority of the audience rated these videos as an effective technique for educating the public about manure and mortality management, found the VR videos interesting, were willing to learn more content through VR videos, and were likely to recommend them to their colleagues. A statistically significant correlation could be observed between the awareness change and the effectiveness rating given to the videos by the participant.

Given the importance of the development of urban infrastructure and environmental impacts produced by the civil construction waste (CCW), it is important to correct the handling of CCW with objective solutions that are more environmentally friendly. In that sense the present study aimed to determine indicators that make it possible to estimate the amount of CCW generated from construction sites in the city of Londrina, Parana State, Brazil. The generation of CCW was estimated in a general way, regarding the composition of its mixture, correlated to the gross areas of the buildings studied and their generated volumes of RCC. This generating rate was evaluated in a general way and specifies two types of sites: the new residential and new non-residential constructions. The data required for the development of these indicators was obtained through extensive survey and interviews carried out at the environment secretariat of the City Hall. The generating rate of CCW obtained for non-residential buildings was 0.2052m3/m2 or 170.44kg/m2, for new residential sites was 0.2054m3/m2 or 170.60kg/m2 and for new commercial or non-residential construction sites, it was 0.20453 m3/m2 or 169.85kg/m2. It was also possible to estimate the amount generated annually per inhabitant in the municipality, which is 0.60m3/inhabit.year or 498.55kg/inhabit.year.

The UK aviation industry is committed to achieving net zero emissions by 2050 through sustainable measures, and one of the key aspects of this effort is the implementation of Unmanned Traffic Management (UTM) systems. These UTM systems play a crucial role in enabling the safe and efficient integration of unmanned aerial vehicles (UAVs) into the airspace. As part of the Airspace of the Future (AoF) project, the development and implementation of UTM services have been prioritized. The paper aims to create an environment where routine drone services can operate safely and effectively. To facilitate this, a digital twin of the National Beyond Visual Line of Sight Experimentation Corridor has been created. This digital twin serves as a virtual replica of the corridor and allows for the synthetic testing of unmanned traffic management concepts. The implementation of the digital twin involves both simulated and hybrid flights with real drones. Simulated flights allow for the testing and refinement of UTM services in a controlled environment. Hybrid flights, on the other hand, involve the integration of real drones into the airspace to assess their performance and compatibility with the UTM systems. By leveraging the capabilities of UTM systems and utilizing the digital twin for testing, the AoF project aims to advance the development of safer and more efficient drone operations. Experimentation Corridor has been developed to simulate and test concepts related to managing unmanned traffic. The paper provides a detailed account of the implementation of the digital twin for the AoF project, including simulated and hybrid flights involving real drones.

In this research, a new conceptual framework introduced to analysis of water security. Using the exponential, logistic growth model, and employing the historical population of Tabriz city from 1956 to 2016, the future period (2022-2100) population predicted. Pearson Correlation, Spearman's Rho and Kendall's rank coefficients were used for analyzing correlation between population and water consumption. In addition, the amount of city water demand in the future period predicted using the ordinary least square model. Then, water stress and water scarcity indices calculated for Tabriz city in the future period. Results indicated that the mathematical population growth models are very suitable for prediction of city population. There was a significant positive correlation between the city population and water demand. In addition, the amount of water demand will proportionally increase with rising number of population. Finally, linear and quadratic equations presented for city water demand based on the city population number. It can be concluded that Tabriz city will be faced with severe water stress in the future period. The proposed new method in this study can be used for other different cities of the world. Also, Results will be helpful for decision makers in optimum management of urban water resources.

This paper provides a new management method (MM) to optimally operate standalone direct current (DC) photovoltaic water pumping system (PVWPS) and synchronize its hydraulic performance to variable daily irradiance. The proposed approach well considers the issues from PV generator and a positive displacement pump mismatching to deserve a hydraulic network. Accordingly, Management Method uses small pumps mounted in parallel scheme to displace the hydraulic power point (HPP) in order to satisfy the mal adequacy between supply and load. Based on experimental Study; this approach showed a yielded standalone system, possibility of running pumping system using only photovoltaic supply (Without use of capacitance), and possibility to design more economical PV systems as the maximum peak power demand for each month can be satisfied using small power pumps in parallel and adjusting their switch with accordance to varying daily irradiance. Moreover, an analytical model was developed with reference to the obtained experimental results. This model based on a daily occurring irradiance as inputs in order to predict optimal performance outputs. It can be considered as a decision tool to track power point resulting from optimal electrical and hydraulic performances of the pumping system according to changes of the daily irradiance.

Distribution System Operators (DSOs) are adapting to changing energy demands and the shift toward renewable and decentralized energy. Circularity is increasingly relevant for DSOs as their distribution systems age and need replacing. Taking circular action, however, is generally regarded as challenging as the current circular economy (CE) landscape is highly fragmented and rarely touches the implementation level. A longitudinal case study at Dutch DSO Liander on the circu-larity of distribution transformers was used to understand empirical success factors for taking circular action and to generate prescriptive knowledge on the operationalization of circularity. Six design propositions for circular action were formulated that suggest to 1) initiate small-scale cir-cularity experiments, 2) involve technical and strategic experts, 3) synergize circularity with more urgent, primary goals 4) translate circular initiatives bottom-up and top-down, 5) collaborate with other DSOs, and 6) create multidisciplinary teams. At DSO Liander, selecting the right interventions depending on the changing context contributed to operationalizing circularity for distribution transformers and achieving circularity targets. The generalizable design propositions could assist other DSOs in optimizing their strategy toward circular action.

A claim management office (CMO) is a new intra-organisation fit based on an organisational project management (OPM) approach and deals specifically with improving claim performance. However, CMO is either misunderstood or often overlooked in construction companies, mainly due to ignorance of the OPM context but further exacerbated by a lack of real case study research on how to adopt CMO in these organisations. This study addresses this prevailing knowledge gap by investigating the nature of the construction industry from the CMO viewpoint and developing an extensive framework through which to improve organisational claims performance. Organisational ambidexterity theory integrated with X-inefficiency theory is adopted for claims performance outcomes, due to organisation intra-firm irrational decisions when managing such claims. Data was obtained and analysed from a international large construction company (which used CMOs) and its internal focus group discussion (as a multi-method approach). The reference framework provides new perspectives on how construction-related companies can adopt a CMO structure, which enables them to improve claims performance by planning in three interrelated activities viz. function-, process- and performance-based-. Furthermore, findings contribute to researchers and practitioners by providing a true understanding of the CMO-related mechanism and plausible roadmap for future work.

Background: Hurricanes and other wind events are significant disturbances that affect coastal urban forests around the world. Past research has led to the creation of wind resistance ratings for different tree species which can be used in urban forest management efforts to mitigate the effects of these storms. While useful, these ratings have been limited to species common to one global region (Florida, USA).Methods: Drawing on past ratings and data from a global literature review on tropical storm research, we created a machine learning model to broaden both the geographic coverage and the variety of species currently assessed for their resistance to wind.Results: We were able to assign wind resistance ratings to 281 new species based on the available data and our modelling efforts. The model accuracy and agreement with the original ratings when applied to the testing data set was high with 91% accuracy.Conclusions: The resulting list of wind resistance ratings has been adapted into a spreadsheet-based decision aid for managers, allowing them to assess the overall susceptibility of their urban forest to wind events like hurricanes.

Aquaculture assumes a pivotal role in meeting the escalating global food demand, and shrimp farming, in particular, holds indispensable significance for the global economy and food security, providing a rich source of nutrients for human consumption. Nonetheless, the industry faces formidable challenges, primarily attributed to disease outbreaks, and the diminishing efficacy of conventional disease management approaches, such as antibiotic usage. Consequently, there is an urgent imperative to explore alternative strategies to ensure the sustainability of the industry. In this context, the burgeoning field of epigenetics emerges as a promising avenue for combating infectious diseases in shrimp aquaculture. Epigenetic modulations entail chemical alterations in DNA and proteins, orchestrating gene expression patterns without modifying the underlying DNA sequence by utilizing DNA methylation, histone modifications, and non-coding RNA molecules. Exploiting epigenetic mechanisms presents an opportunity to enhance immune gene expression and bolster disease resistance in shrimp, thus revolutionizing disease management strategies and optimizing shrimp health and productivity. Additionally, the concept of epigenetic inheritability in marine animals holds immense potential for the future of the shrimp farming industry. To this end, this comprehensive review thoroughly explores the dynamics of epigenetic modulations in shrimp aquaculture, with a particular emphasis on its pivotal role in disease management. It accentuates the significance of harnessing advantageous epigenetic changes to ensure the long-term viability of shrimp farming while deliberating on the potential consequences of these interventions. Overall, this appraisal highlights the promising trajectory of epigenetic applications, propelling the field toward strengthening sustainability in shrimp aquaculture.

Identifying and assessing risk is one of the most important processes in managing complex systems and requires careful consideration. The need for an effective, efficient approach to risk management is considerably more important for defense industries, because they are exposed to risk already in early stages of development. This paper uses Heterogeneity and Homogeneity analysis between risk factors with Cochran’s Q test and Multidimensional scaling in order to present the complexity of the risk factors relevant to defense SoS, and proposes a methodology for identifying, analyzing and monitoring the risks that they face. Findings from an in-depth analysis of 46 classified defense SoS shows a need to focus on three main risks faced by defense projects: insufficient human resources, changes in the original specifications, and lack of other (non-human) resources. The paper also presents some recommendations for minimizing risk factors in defense SoS.

The explosion of data has transformed the world since much more information is available for collection and analysis than ever before. To extract valuable information from the data in different dimensions, various deep learning models have been developed in the past years. Although these models have demonstrated their strong capability on improving products and services in various applications, training them is still a time-consuming and resource-intensive process. Presently, cloud, one of the most powerful computing infrastructures, has been used for the training. However, how to manage cloud computing resources and to perform the training efficiently is still challenging current techniques. For example, general resource scheduling approaches, such as spread priority and balanced resource schedulers, actually do not work well with deep learning workloads. Besides, the resource allocation problem on a cluster can be divide into two subproblems: (1) local resource optimization: improve resource configuration for a single machine; (2) global resource optimization: improve the cluster-wide resource allocation. In this thesis, we propose two novel container schedulers, FlowCon and SpeCon, that are designed to address these two subproblems respectively and specifically to optimize performance of short-lived deep learning applications in the cloud. FlowCon focuses on resource configuration of single-node in a cluster, as show that it efficiently improves deep learning tasks completion time and resource utilization, and reduces the completion time of a specific job by up to 42.06\% without sacrificing the overall system time. SpeCon targets on cluster-wide resource configuration that speculatively migrate slow-growing models to release resources for fast-growing ones. Based on our experiments, SpeCon improves makespan for up to 24.7\%, compared to current approaches.

Nerve hydrodissection (HD), a technique used when treating nerve entrapments, involves using an anesthetic or solution such as saline or 5% dextrose solution to separate the nerve from the surrounding tissue, fascia, or adjacent structures. This technique aims to treat neuropathic pain, or pain caused by the nerve. Ultrasound-guided HD of peripheral nerves has gained significant attention in the medical profession and pain management fields in recent years. This is due to a number of high impact publications of randomized control trials demonstrating the efficacy and safety of this technique for the treatment of carpal tunnel syndrome. Even the 20th edition of Harrison’s Principles of Internal Medicine textbook lists injection of 5% dextrose as an alternative local treatment that does not have the side effects of corticosteroids. At present, there is no review of the current literature on this technique. This manuscript will summarize and discuss the following: 1) the different approaches to doing ultrasound-guided HD of nervous structures, 2) its usages in different clinical situations, 3) its clinical pearls, 4) the solution used, and 5) the postulated mechanisms of action.

Knowledge management gains space within the school organization and can contribute satisfactorily to the quality of teaching. In everyday life the school manager intuitively uses knowledge management practices without exploiting the potentials they offer or allow. In this context, the purpose of this work is to identify the level of implementation of knowledge management practices aimed at structuring the organizational processes used by the public school manager. The methodology adopted was exploratory, with a qualitative and quantitative approach. For data collection, an already validated instrument with twenty-seven questions was used. Respondents to the questionnaires, one hundred and eleven managers of the basic education schools that make up the public school system in a city in the northwestern region of Paraná, Southern Brazil. In analyzing the results, it was only at this point that we investigated only those practices that were related to the structuring of organizational processes. This decision is justified because of the responsibilities of the school manager in the execution of his work. The results indicated that the school in its daily life, makes use of practices of Knowledge Management related to the structuring of the organizational processes and that many are already applied by the managers.

We describe a dataset that contains job description published on a popular online website in the information and technology sector. As the website focus mainly on United Kingdom based jobs, the data have a specific focus on this country. It contains 11.501 job vacancies and 13 related meta data information. The dataset is suitable for HR analysis using machine learning techniques such as natural language processing and neural networks.

The cultivation systems of Coffea spp in a cooperative society in Puebla, Mexico, include rustic, traditional polyculture, commercial polyculture, unshaded monoculture and shaded monoculture. In this work, the properties of the soil were analyzed through physical, chemical, and biological analysis to determine its nutritional status. Composite sample analyses were conducted to determine physical, chemical and microbiological parameters (fungi, actinomycetes, mesophilic bacteria, nitrifying and denitrifying bacteria). Leaf nutrients were determined. Rustic was the cropping system with the highest amount of K (0.76 cmol kg-1) in soil and nutrient assimilation in leaf (N= 2.79%, P= 660.01, K= 17297.22 and Fe= 271.24 mg kg-1) (p= 0.001); in addition to presenting high populations of mesophilic bacteria, fungi and actinomycetes (30.16, 0.59 and 0.83 respectively, x10 6 CFU g-1 soil) and very low nitrification and denitrification rates. The principal component analysis (PCA) (>3.25%) indicated that actinomycetes and K in soil favor the assimilation of Fe, K and P. This Coffea spp cultivation system had a lower impact on soil health than the rest of the systems and favored forest ecosystem conservation.

Purpose: To explore parents’ perceptions of the educational intervention programme regarding their children’s postoperative pain management. Design and Methods: A qualitative descriptive study was conducted. Thirty-two parents whose children underwent inpatient elective surgery were recruited from the two intervention groups (received an educational booklet and a video, with or without an hour of face-to-face teaching session) for this qualitative evaluation of the intervention. Participants were asked to comment on the content and delivery methods of the intervention via individual face-to-face semi-structured interviews. Thematic analysis was used to identify themes from the data. Results: Three themes were generated from 32 participants’ interview data: current pain management practices, experiences and benefits of the educational intervention, and suggestions to improve pain management. Conclusions: Our findings suggested that the educational intervention in children’s postoperative pain management was helpful for parents and their children. However, it is necessary to improve educational materials and equip healthcare professionals with non-pharmacological pain relief methods. Practice Implications: Our findings reveal the current challenges in extensively adopting non-pharmacological pain relief methods. Healthcare professionals can do more to routinely integrate pharmacological and non-pharmacological pain management strategies in relieving pain effectively. Future research could develop technology-based programmes to increase ease of access. Trial Registration Number: ISRCTN24910957.

There is increasing demand from stakeholders for tools to support outcome-based approaches in environmental management. For such tools to be useful, understanding user requirements is key. In Scotland, UK, stakeholders were engaged in the development of an Environmental Decision Support System (EDSS) to support the management of land and freshwater resources for multiple policy outcomes. A structured participatory engagement process was employed to determine stakeholder requirements, establish development principles to fulfil these requirements and road-test prototypes. The EDSS specification that emerged from this bottom-up process was spatially-explicit, free at the point of use, and touch and mobile device compatible. This application, which is under development, does not closely resemble most existing published EDSS. We suggest that there is a mismatch between the way scientists typically conceptualise EDSS and the kinds of applications that are likely to be useful to decision-makers on the ground. Interactive mobile and web-based geospatial information services have become ubiquitous in our daily lives, but their importance is not reflected in current literature on EDSS. The current focus in environmental management on adaptive, stakeholder-centred strategies based on outcomes offers an opportunity to make better use of these new technologies to aid decision-making processes.

Over the last few decades, many countries, especially Caribbean island ones, have been challenged by the devastating consequences of natural disasters, which pose a significant threat to human health and safety. Timely information related to the distribution of vulnerable population and critical infrastructure are key for an effective disaster relief. OpenStreetMap (OSM) has repeatedly been shown to be highly suitable for disaster mapping and management. However, large portions of the world, including countries exposed to natural disasters, remain unmapped. In this study, we propose a methodology that relies on remotely sensed measurements (e.g. VIIRS, Sentinel-2 and Sentinel-1) and derived classification schemes (e.g. forest and built-up land cover) to predict the completeness of OSM building footprints in three small island states (Haiti, Dominica and St. Lucia). We find that the combinatorial effects of these predictors explain up to 94% of the variation of the completeness of OSM building footprints. Our study extends the existing literature by demonstrating how remotely sensed measurements could be leveraged to evaluate the completeness of OSM database, especially in countries at high risk of natural disasters. Identifying areas that lack coverage of OSM features could help prioritize mapping efforts, especially in areas vulnerable to natural hazards and where current data gaps pose an obstacle to timely and evidence-based disaster risk management actions.

This research was carried out with the objective of analyzing the principles of social and solidarity economy in the community funds of the rural sector of Pichincha, Ecuador. Small organizations promote microcredits for local, social and economic development, representing an alternative to those managed by traditional banks. The research was descriptive, non-experimental field research. The population analyzed consisted of 220 community funds, and the size of the representative sample was 49 community organizations that practice solidarity finance. The data were collected through online questionnaires using a Likert scale, and the validity of this approach was judged by experts; the reliability of the instrument obtained was 0.95 using the Cronbach’s alpha method. The results highlight that in these organizations, the following traits prevail: associativity, self-management and organization. However, autonomy and solidarity have a negative valuation, which shows that strategies must be rethought to achieve the empowerment of the financial service. This will allow them to be sustainable and to expand with more benefits that promulgate financial activity and promote structures in rural community networks that promote local development and strengthen deficient principles as a basis for generating a greater benefit to the partners.

Electronic Word of Mouth (eWOM) has been widely used by the majority of consumers in different digital platforms. This exploratory study was conducted with the aim to get further insights about online consumer behavior through social networking sites and online reviews sites in order to help tourism businesses develop sustainable eWOM strategies. In order to carry out this objective, an exploratory study has been developed to analyze the existing literature of eWOM strategies and online consumer behavior. The systematic literature review analysis establishes two main topics: (i) tourism (ii) eWOM. The scientific database of Web of Science has been used to collect relevant literature of the subject matter. The search term “Tourism” and “eWOM” were applied. The database of Web of Science produced a total of 124 articles and with the different filters applied during the PRISMA 2009 Flow diagram the process resulted in a selection of 13 studies. The results of the research will provide a broader knowledge for scholars of social sciences and businesses for adopting sustainable strategies of the increasing influence of eWOM in tourism.

Here we present a blockchain-backed token recognition system to reward the contributions that academics make to the scientific ecosystem. Recognition is important in science but current methods, systems and incentives are limited. Specifically, the traditional focus on narrow publication metrics means diverse contributions are not captured, while bias toward senior, established scientists is common. To tackle this challenge, we explore the potential of harnessing blockchain’s collaborative, decentralised and trust-brokering properties to develop a token reward system for use by research funders. Academics would be awarded tokens for undertaking common but vital tasks such as peer review, sitting on funding committees and submitting reports. These tokens would not be tradable or specifically monetisable but would serve as a validated record of scientific contribution. They would have value in professional recruitment and job placement, support grant and award applications, and inform performance appraisals and file reviews. Coordination and cooperation across multiple funding agencies in developing the platform would provide an opportunity to aggregate and standardise recognition, given academics often work with several funders. This system’s goals are to expand recognition metrics, promote efficiencies, improve the robustness of professional assessments and enable cross-funder collaboration, thereby optimising research processes and practices in a decentralised and democratised manner.

Severe cancer pain significantly diminishes patients' quality of life, leading to increased reliance on caregivers. Although opioid analgesics are effective, they may induce opioid-induced bowel dysfunction (OIBD) with symptoms such as nausea, vomiting, drowsiness, and constipation. While controlled-release oxycodone is a viable option, its prolonged use can lead to opi-oid-induced constipation (OIC). Addressing this, a relative novel formulation - a fixed 2:1 ratio of oxycodone and naloxone in prolonged release - aims to provide analgesia while alleviating OIC. This review critically assesses the evidence on the efficacy, safety, and patient experience of ox-ycodone/naloxone prolonged release in managing severe cancer pain, emphasizing the necessity for a targeted approach in this patient population.

This work investigates the utility of the National Oceanic and Atmospheric Administration’s National Water Model (NWM) for water management operations by assessing the total inflow into a select number of reservoirs across the Central and Western U.S. Total inflow is generally an unmeasured quantity, though critically important for anticipating both floods and shortages in supply over a short-term (hourly) to sub-seasonal (monthly) time horizon. The NWM offers such information at over 5,000 reservoirs across the U.S., however, its skill at representing inflow processes is largely unknown. The goal of this work is to understand the drivers for both well performing and poor performing NWM inflows such that managers can get a sense of the capability of NWM to capture natural hydrologic processes and in some cases, the effects of upstream management. We analyzed the inflows for a subset of Bureau of Reclamation (BoR) reservoirs within the NWM over the long-term simulations (retrospectively, seven years) and for short, medium and long-range operational forecast cycles over a one-year period. We utilize ancillary reservoir characteristics (e.g. physical and operational) to explain variation in inflow performance across the selected reservoirs. In general, we find that NWM inflows in snow-driven basins outperform those in rain-driven, and that assimilated basin area, upstream management, and calibrated basin area all influence the NWM’s ability to reproduce daily reservoir inflows. The final outcome of this work proposes a framework for how the NWM reservoir inflows can be useful for reservoir management, linking reservoir purposes with the forecast cycles and retrospective simulations.

The Internet of Things (IoT) is experiencing exponential growth, revolutionizing various industries with its ability to connect devices and enable advanced applications. In the realm of energy production, IoT offers significant potential for optimizing processes and improving efficiency. This study presents a comprehensive monitoring and energy management strategy for the University of Cuenca's microgrid photovoltaic (PV) system, utilizing IoT and ThingSpeak as key technologies. The proposed strategy leverages intelligent environments and utilizes ThingSpeak as a robust platform for data presentation and analysis. By integrating IoT devices and sensors, real-time monitoring of PV system parameters such as solar radiation and temperature is achieved. The collected data is then analyzed using advanced algorithms and visualized through ThingSpeak, enabling effective energy management and decision-making. The developed monitoring system was rigorously tested in a laboratory microgrid setting, where the PV system is interconnected with other generation and storage systems, as well as the electrical grid. Through the seamless integration of these components, the monitoring system provides enhanced visibility and control over the microgrid's energy production. The results demonstrate the successful implementation of the monitoring system, showcasing its ability to improve the supervision, automation, and analysis of daily energy production. By leveraging IoT technologies and ThingSpeak, stakeholders can access real-time data, analyze performance trends, and optimize energy resources.

This study delves into the dynamics of relational energy (RE) within organizational context, examining some of its antecedents and decedents. Specifically, it investigates the influence of psychological capital (PsyCap) and humor on RE, and subsequently, the latter’s impact on job performance (JB) mediated by job engagement (JE). A research model based on structural equation modelling carried out with 481 employees in private service industries demonstrates several key relationships. It reveals that both PsyCap and affiliative humor positively affect RE, while aggressive humor exerts a negative influence. Furthermore, RE shows positive association with JE and JP, with JE serving as a mediator. To the authors’ knowledge, this is the first study to present an integrated model encompassing this exact combination of influencers and consequences of RE as well as to be investigated within Western Balkans cultural context. Therefore, it represents a novel approach. Additionally, the research addresses crucial questions regarding the existence and strategic significance of RE within organizational interactions. The findings offer valuable insights for organizations seeking to enhance employee engagement, performance, and wellbeing – even during health crises such as COVID-19 – by fostering RE. The study advances the understanding of RE in organizational settings and provides a foundation for future research in this domain.

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

This study evaluates for the first time the plastic litter occurrence in Posidonia spheroids of four Mediterranean sandy beaches at different anthropogenic impact. A total of 80 spheroids was analyzed and 202 plastic items were found. Spheroids entangled a high number of plastic litter (132 plastic items/kg) with significant differences between beaches. Our results highlight the importance to implement the beach cleaning plan for the removal of all spheroids in order to prevent them from flaking and releasing the marine litter trapped inside them again in the environment. Spheroids should be manually removed in order to protect the banquettes. The removal should be involved all spheroids, independently from their size. This study adds data for the implementation of the monitoring program of marine litter and contributes to the development of specific management measures as well as implement Mediterranean action plans.

Improving the efficiency of the supply process in prefabricated components is challenging and requires accounting for a variety of risks involved in the management of the suppliers. The purpose of this study is to present a method to account for the systematic trade-offs between several supplier alternatives. A novel framework is presented for the whole assessment of supplier alternatives by taking advantage of the information extracted from customized building information modeling (BIM) and a database required for assessment of impacts. A data library related to assessment criteria for supply alternatives is built to facilitate the storage and sharing of information. Analytic hierarchy process (AHP) is used to select the optimal supplier that is able to provide the most satisfaction for the determined criteria. The proposed framework was also illustrated by the implementation in a mega project. The study implication is that BIM-enabled supplier selection can indeed lead to more benefits and higher values for all stakeholders.

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.

This paper presents how social media platforms and their components could be integrated into the KMS for the purpose of managing and sustaining Somali Indigenous knowledge (IK). The discovery of knowledge and its utilization is now fuelled by the advancement of technology, which connects users to external sources through using different platforms. The rapidly increasing use of SM and mobile technologies create opportunities to form knowledge networks that can facilitate the process of creating, preserving, and sharing knowledge and skills that are unique to communities in the Somali context. Somali society being an oral society with rich IK and other cultural practices lacked a framework in place to organize the existing knowledge in various methods. The paper refers to existing methodology E-learning and KM functions. This method first identifies functional similarities between SM, E-Learning, and KM systems and their interactions if they are properly integrated. The proposed framework consists of two functional parts; KM and SM. The KM part involves knowledge capturing, validation, formatting, storing, and distribution. SM part of the framework involves knowledge presentation, sharing, and application. Since the Somalis are said to be an oral society, this framework helps to capture and disseminate IK residing in knowledge holders.

This paper examines the relationship between GDP per capita and waste generated in European Union countries, highlighting the importance of this relationship for understanding the environmental consequences of economic growth and formulating waste management policies. The analysis findings demonstrate that, in most cases, higher GDP is associated with higher amounts of waste, although there are exceptions to this trend. A smaller number of countries are also found where no such relationship exists. These are primarily high-income countries in the lower part of the EKC or countries in transition. Cluster analysis reveals regional differences in the relationship between GDP and waste that the economic factors and the level of development in the regions concerned can explain. Bulgaria is among the European countries with the lowest economic growth associated with a large amount of waste. The analysis, therefore, focuses on Bulgaria. The impact of GDP per capita, Human Development Index and Population Density on municipal waste in Bulgaria is studied. The aim is to identify significant relationships and dependencies between these factors and the amount of waste. Based on the results of multiple regression analysis and the findings from municipal waste management data in Bulgaria, specific actions are proposed for municipal waste management in the country. Recommendations are made for developing sustainable waste management policies and sharing best practices between regions.

Introduction and Objective: Caudal block has been used in children for many years and is considered the gold standard for multimodal analgesia in the pediatric age group. Caudal block belongs to the category of central neuraxial blocks, which can provide both visceral and somatic analgesia. With the introduction of ultrasound into the clinical practice of anaesthesia, the caudal block is now performed under USG guidance. In our study, we aimed to compare the efficacy of a single caudal block in postoperative acute pain management, the need for additional analgesics, the incidence of side effects, the timing of initial analgesic administration, and the need for rescue analgesic administration (paracetamol 10 mg/kg) in circumcision surgery. Materials and Methods: 120 patients undergoing circumcision surgery were divided into 3 groups. The caudal block was performed in all cases under USG guidance. Only the caudal block was applied for cases in the Caudal group (Group C). The Caudal + paracetamol group (Group CP) received paracetamol 10 mg/kg intravenously (i.v.) and the caudal block. Patients in the Caudal + meperidine group (Group CM) received 1 mg/kg meperidine intravenously. The caudal block was performed in each case with a 0.5 ml/kg volume of 0.125% bupivacaine. Results: As a result of our study, it was found that the least postoperative pain occurred in 12.50% of the CM group (p=0.011). Significant results were obtained when weight and age variables were analyzed according to the groups (p-values p=0.011 and p=0.003, respectively). Significant differences were found between the input pulse values, 5-minute pulse values, 15-minute pulse values, and input SpO2 values (p values p < 0.001, p < 0.001, p=0.011, p=0.037, respectively). Only Wong-Baker pain scores at the 24th hour differed significantly from the periods measured after the groups (p < 0.001). There was no significant difference between the FLACC and Wong-Baker pain scores in the other periods. There was no difference between the groups regarding the time when postoperative analgesics were administered and the total amount of analgesics administered (rescue analgesic 10 mg/kg oral paracetamol) (p=0.408, p=0.238). Conclusion: Caudal block can be safely applied during circumcision. Ultrasound guidance increases the chances of success and reduces the complication rate. Caudal block can be safely used in pediatric surgery since it does not cause serious complications, has low postoperative pain scores, and reduces the number of postoperative analgesics.

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.

Firefighters Protective Clothing consist of several layers of different properties and functions. The layers create barriers against dangerous outer factor. However, they are also barriers to transport of sweat produced by human organism. It causes that very often sweat in the form of vapor is not transferred effectively from the human organism through the FPC to environment. This leads to sweat condensation on the skin of the FPC user causing his discomfort. In order to ensure as good as possible physiological comfort of firefighter while firefighting and other rescue actions it is necessary to take into consideration the transport of condensed sweat in the multilayer textile set creating the FPC. In the presented work four variants of multilayer textile sets for the FPC have been tested in the aspect of liquid moisture transport. Measurement was performed by means of the Moisture Management Tester (MMT290) – innovative instrument manufactured by the SDL Atlas. Obtained results showed that the transfer of sweat in liquid form occurs only in the inner, next to skin layer of the multilayer sets for the FPC.

Battery Management System helps to improve the transient performance and life of electro-chemical rechargeable batteries like a Li-ion, lead–acid, etc. The investigation here was focused on the crucial part of the Battery Management System that is, Cell balancing, State of charge of the battery, etc. By analyzing the different control strategies a new optimal control strategy is developed to improve the battery performance according to application. The Control strategy is developed using an active and passive cell balancing model with the help of AVL Cruise and MATLAB/SIMULINK software. For the active cell balancing technique, a switched capacitor technique is chosen. To have longer battery life, the time required for the cell balancing must be as low as possible for which many control logics have been defined. The effect of these cell balancing techniques on the performance of battery packs is investigated and it is observed to produce a promising result.

Micro turbojets are used for propelling radio-controlled aircraft, aerial targets and personal air vehicles. When compared to full-scale engines, they are characterized by relatively low efficiency and durability. In this context, the degraded performance of gas path components could lead to an unacceptable reduction in the overall engine performance. In this work, a data-driven model based on a conventional Artificial Neural Network (ANN) and an extreme learning machine (ELM) was used for estimating the performance degradation of the micro turbojet. The training datasets containing the performance data of the engine with degraded components were generated using the validated GSP model and the Monte Carlo approach. In particular, compressor and turbine performance degradation were simulated for three different flight regimes. It was confirmed that component degradation had a similar impact in flight than at sea level. Finally, the datasets were used in the training and testing process of the ELM algorithm with four different input vectors. Two vectors had an extensive number of virtual sensors, and the other two were reduced to just fuel flow and Exhaust Gas Temperature. Even with the small number of sensors, the high prediction accuracy of ELM was maintained for takeoff and cruise but was slightly worse for variable flight conditions.

Risk management of electric power transmission lines requires knowledge from different areas such as environment, land, investors, regulations, and engineering. Despite the widespread availability of databases for most of those areas, integrating them into a single database or model is a challenging problem. Instead, in this paper, we use a single source, the Brazilian National Electric Energy Agency’s (ANEEL) weekly reports, which contains decisions about the electrical grid, comprising most of the areas. Since the data is unstructured (text), we employed NLP techniques such as stemming and tokenization to identify keywords related to common causes of risks provided by an expert group on energy transmission. Then, we used models to estimate the probability of each risk. Our results show that we were able to estimate the probability of 97 risks out of 233.

In precision agriculture in fertigated crops it is necessary to optimize the use of water and chemicals, and enable efficient application of fertilizers in order to ensure the best yield and avoid risks of soil salinization and contamination. In this study, an intelligent system was developed with the objective of monitoring, in real-time, moisture and solute concentrations in soil cultivated with lisianthus (Eustoma grandiflorum, var. Casablanca) fertigated under a protected environment. During one crop cycle, moisture was monitored in soil solution using TDR100 reflectometer and solute concentrations were monitored with ceramic cup extractors. Plants were fertigated with a solution containing five potassium concentrations (50, 100, 150, 200, and 250 mg dm-3) applied when the soil reached moisture limits of 0.20, 0.15, 0.13, 0.11, and 0.09 cm3 cm-3. Experimental plots were arranged in a randomized block design in a 5 x 5 factorial scheme (moisture limits x potassium concentrations in soil solution), with four replicates. The proposed intelligent system enabled precise monitoring of moisture and electrical conductivity by TDR, and potassium, and other solute concentrations with extractors, being indicated for the management of lisianthus fertigation under greenhouse conditions with greater environmental safety and reduction of water consumption and risk of salinization.

Abstract: Purpose – In this article we lay out the change management practices adopted by financial firms in small states within the Eurozone. We determine whether these organisations have the ability to identify triggers for change (Red Flags) and subject them to eight thematic elements to understand whether management practices can continue to exist and support operational environments, even when unexpected circumstances affect their day to day operations and processes. In doing this we examine the extent to which the eight thematic elements from the model designed by Dalli Gonzi, (2019) (The Dali Model) can assist organisations in risk identification and business continuity planning. Design/methodology/approach – A self-administered questionnaire purposely designed for this study was administered to personnel working in internal controls within financial institutions of small Eurozone states. The participants were asked to grade statements using a 5-point Likert scale, ‘1’ being ‘totally disagree’ and ‘5’ being totally agree’ to the statement posed under the thematic elements forming the basis of the Dali Model. Findings – Factor analysis provided support for the eight hypothesised dimensions of the decision-making model: connection, capacity, governance, network, policy, training, process improvement, standards. Originality/value – The study provides a better understanding and support of “best practice” in change management through an understanding and assessment of the eight factors that are the basis of this model. It addresses practical recommendations to ensure application to a wider frame of use.

Flying-fox populations are increasingly threatened by heat events, starvation events and other stressors due to habitat clearing and human/flying-fox conflict.These factors are unlikely to resolve, meaning that a well-coordinated and timely approach to flying-fox disasters is imperative for the mitigation of further flying-fox population impacts.

There are uncertainties associated with every phase of the stock assessment process, ranging from the collection of data, assessment model choice, model assumptions and interpretation of risk to the implementation of management advice. The dynamics of fish populations are complex, and our incomplete understanding of those dynamics (and limited observations of important mechanisms) necessitate that models are simpler than nature. The aim is for the model to capture enough of the dynamics to accurately estimate trends and abundance and to provide advice to managers about sustainable harvests. The \textit{status quo} approach to assessment modelling has been to identify the `best' model, based on diagnostics and model selection criteria, and to generate advice from that model, mostly ignoring advice from other model configurations regardless of how closely they performed relative to the chosen model. We review the suitability of the ensemble modelling paradigm to more fully capture uncertainty in stock assessment model building and the provision of advice. We recommend further research to evaluate potential gains in modelling performance and advice from the use of ensemble modelling, while also suggesting revisions to the formal process for reviewing models and providing advice to management bodies.

Statistical management policy and system plays significant role in development of any nation as it guides the planner to analyze the gaps, design programs and allocate budget in efficient manner. Globally, design and usage of statistical management system varies relying on country specific ability and resources availability. Government of Nepal has been managing database in individual as well as thematic manner. Policy wise, thematic database is in operation based on Statistics Act 1958 and individual database is in operation based on Birth, Death and Other Personal Related Events Registration Act 1976. Though civil registration related policies have been either updated or newly formed, sectoral statistic management related policy has not been updated since its first promulgation period (1958). With no policy supporting the consolidated statistical management system, government as well as non-government agencies has been investing millions of dollars annually to collect, compile and analyze individual related data and fulfill their respective objectives. It has forced the government services and performance to be paper-based, time-consuming and tedious thus creating dis-trust among citizen each passing day. Though, formulation of legal instrument promoted digital movement and mandated shift towards e-government modality, the process has been low. Theoretically, Technology Acceptance Model (TAM) state the need of having advanced and efficient technology to be in place in current setting to improve governance, efficiency, accountability, transparency and trust. Also, the same theory state the requirement of strong willingness and motivation from the users (government, non-government and citizen) to adopt the technology based policy and system. As the integrated statistical management policy emphasizes on technology-based system or digital system, the perspectives of Technology Acceptance Model also termed as Information System Theory aid in understanding the context, conceptualizing and addressing the needs with an establishment and implementation of digital system or technology based system. This policy paper applied the Technology Acceptance Model (TAP) to examine the underlying opportunities and challenges associated with an integrated statistical management policy. With existing gaps in existing policy, system and practice alongside an overview of opportunities and challenges, this paper recommends the need of stand-alone integrated statistical management policy to consolidate sectoral as well as civil related information through single system based on recommended policy.

This research article aims to present implementation and evaluation of the HPPT design based on using multi-parallel pumps switching for yielding performance with reference to potential change of daily irradiance. After that, the curve fitting of the hydraulic performance scenarios is tested to compare the hydraulic energy growth behaviors with reference to exponential and power growth models.

Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations, as well as research. In order to make use of pathogen genomics data, it must be interpreted using contextual data (metadata). Contextual data includes sample metadata, laboratory methods, patient demographics, clinical outcomes, and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration, and its use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating, and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool’s web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission.In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.

This article examines how digitalisation is impacting the management of IT. Phase 1 of the re-search focuses on the German automotive industry, and adopts a qualitative inductive approach, based on feedback from 19 semi-structured interviews with IT managers and professionals. Five key aspects of digitalisation are identified, and a new model for the management of IT is devel-oped. Phase 2 then reviews the deployment of digital technologies in eight organisations from other industry sectors and assesses the overall impact on the management of IT. The results suggest that the transition to new IT management structures in the German automotive industry may be the forerunner of a change process that will impact more widely in other industries, in particular where digital technologies are now embedded in an organisation’s products or services. The results also provide some new perspectives on the conceptualisation of digitalisation and digital transformation, and represent a contribution to the developing theory around new tech-nology deployment and IT management in the digital era.

The present work analyzes university students' perceptions on cyberbullying. More specifically, the main objective was to understand the level of concern displayed by young students in teacher training programs regarding cyberbullying; our analysis includes their degree of self-confidence and their commitment when faced with this problem, their self-reported training on the subject, and the measures they consider adequate to approach it in the educational context. Using a survey research design, 408 students from Early Childhood Education, Primary Education Degrees, and the Master’s Degree in Secondary Education, and Vocational Training from national public universities participated. The results shed light upon the coexistence of three differentiated profiles of teachers in training when faced with cyberbullying. However, although there is clear evidence of the high level of concern regarding this problem in every case, they placed more importance on raising awareness of the issue with families, prevention, management and training as basic pillars for re-directing the worrisome reality experienced in educational centers. The need to include these contents in the initial training of future education professionals, for overcoming cyberbullying, and the importance of collaborative work between parents and educators are the conclusions of this research study that are in agreement with other studies.

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.

Overcrowding in the emergency department is a problem that generates several implications for bed management, which is deemed one of a hospital's most critical processes. Effective management of hospital production capacity includes bed management processes, which can be improved in order to leverage hospital performance. Thus, this study sought to understand how bed management works and identify the main factors that influence its management. The study was performed through a case study, with data collected from semi-structured interviews and bibliographic research, which were triangulated. Thematic content analysis of the interviews and cross-analysis were performed. As a result, the main factors that influence hospital Bed management were identified: communication between teams and units; definition of performance goals; decisions shared between units; occupation and discharge planning by the teams; length of stay; the role of the nurses; and COVID-19. The greatest difficulties in the management process are related to these factors. Additionally, suggestions are provided to mitigate such reported difficulties.

The issue of women’s participation in top management and boardroom positions has received increasing attention in the academic literature and the press. However, the pace of advancement for women managers and directors continues to be slow and uneven. The novel framework of this study organizes the factors at the individual, organizational and public policy level that affect both career persistence and the advancement of women in top management positions; namely, factors affecting 1) career persistence (staying at the organization) and 2) career advancement or mobility (getting promoted within the organization). In the study location, Chile, only 32 percent of women “persist”, or have a career without interruptions, mainly due to issues with work–family integration and organizational environments with opaque and challenging working conditions. Women who “advanced” in their professional careers represent 30 percent of high management positions in the public sector and 18 percent in the private sector. Only 3 percent of general managers in Chile are women. Women in Chile have limited access and are still not integrated into business power networks. Our findings will enlighten business leaders and public policy-makers interested in designing organizations that retain and promote talented women in top positions.

This study provides an insightful overview of community-participatory governance and conflict management as instruments for utilizing resources for development in Sub-Saharan Africa (SSA). SSA is a region rich in natural resources but prone to conflict. The study is conceptual and critically engages the application of community governance and conflict management strategies that SSA countries need to adopt. The study praises the notion that community governance is characterized by recognizing and accepting intercultural diversity and creating a democratic institution for promoting good governance and conflict management in SSA. The study recommends that good community governance is required to drive local communities' development, growth, and transformation into a sturdy, innovative, and productive society capitalizing on opportunities. The study voice for the amalgamation of appropriate models and theories of governance cogently in the context of SSA due to the heterogeneity of communities. Therefore, to resolve conflict, conflict management, resolution, and transformation strategies are necessarily needed to accomplish a viable peace to maintain and sustain development.

Electric Vehicles (EVs) are the need of the hour due to growing climate change problems linked with the transportation sector. Battery Thermal Management System (BTMS), which is accountable for certifying safety and performance of lithium-ion batteries (LiB), is the most vital part of an EV. LiB has auspicious gravimetric energy density but the heat generation due to chemical reactions inside a LiB during charging and discharging causes temperature rise which has a direct effect on LiB performance and safety. This study specifically focuses on aircooled BTMS, defines different types of air-cooled BTMS (active and Passive), discusses limitations associated with air-cooled BTMS, and investigates different optimization techniques and parameters to improve performance of air-cooled BTMS. Maintaining temperature within optimum range and uniform temperature distribution between cells of a battery pack are the major design parameters for improving the performance and efficiency of air-cooled BTMS. Various optimization techniques including cell arrangement with a battery pack, air-flow channel optimization, and air inlet/outlet position variations are discussed and each technique is thoroughly reviewed. Finally, it’s noted that passive air-cooled BTMS is not that effective for long-distance vehicles so most researchers shifted their focus toward active air-cooled BTMS. Active air-cooled BTMS requires a lot of power for effective performance. Lastly, the most recent field of air-cooled BTMS technology which is Air-Hybrid BTMS is discussed and declared a very promising solution for overcoming major limitations associated with air-cooled BTMS.