Free and open source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH like a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice it is applied as a case study to the current criminal military aggressor nation, who is also a fossil fuel exporter. The results show there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil fuel energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations.

The main source of electricity worldwide stems from fossil fuels, contributing to air pollution, global warming, and associated adverse effects. This study explores wind energy as a potential alternative. Nevertheless, the variable nature of wind introduces uncertainty in its reliability. Thus, it is necessary to identify an appropriate machine learning model capable of reliably forecasting wind speed under various environmental conditions. This research compares the effectiveness of artificial neural networks (ANN) and convolutional neural networks (CNN) in predicting wind speed across three locations in South Africa, characterised by different weather patterns. Empirical results show that CNN outperforms ANN in accurately forecasting wind speed under different weather conditions. This superiority is likely due to the inherent architectural attributes of CNNs, including feature extraction capabilities, spatial hierarchy learning, and resilience to spatial variability. These results could be useful to decision-makers in the energy sector.

In the study of relativistic jets one of the key open questions is their interaction with the environment on the microscopic level. Here, we study the initial evolution of both electron–proton (e^- - p⁺) and electron–positron (e^±) relativistic jets containing helical magnetic fields, focusing on their interaction with an ambient plasma. We have performed simulations of "global" jets containing helical magnetic fields in order to examine how helical magnetic fields affect kinetic instabilities such as the Weibel instability, the kinetic Kelvin-Helmholtz instability (kKHI) and the Mushroom instability (MI). In our initial simulation study these kinetic instabilities are suppressed and new types of instabilities can grow. In the e^- - p⁺ jet simulation recollimation-like instability occurs and jet electrons are strongly perturbed. In the e^± jet simulation a recollimation-like instability occurs at early times followed by a kinetic instability and the general structure is similar to a simulation without helical magnetic field. Simulations using much larger systems are required in order to thoroughly follow the evolution of global jets containing helical magnetic fields.

This article seeks to provide an improved and more comprehensive understanding of the concept and theories on wasteland. It achieves this by focusing on the Indian context allowing us to unpack the importance of including multiple perspectives of wasteland narratives; this means including more positive narratives of the potential of wasteland to inform and improve prospects for land policies in the global south. Wasteland is commonly recognized as an underutilized category of land that may transform into a valuable resource base with proper management measures. The term waste has multiple angles that carry different notions ranging from fallow to agroforestry land in the global south and Brownfield to green space in the global north. We conduct a narra-tive review approach to qualitatively analyze the concept wastelands studied in pre-existing lit-erature from 1970 to present. The unsystematic literature review approach incorporates multiple elements of wasteland discourse, like understanding the meaning of the term on a global scale, setting out the meaning of the term waste into multiple perspectives explicitly in the Indian con-text, along with different classes and management approaches of wasteland from a national per-spective. The multiple perspectives of wasteland not only generate misconception on land resource but spawn difficulties in land use policy particularly for Indian scenario. For sustainable land use policy, reclaiming wasteland would be the best possible way for India and other countries in Global South, which requires a comprehensive methodological overview on wasteland narrative.

Abstract: Recent years demonstrate the increased attention to radon from two scientific directions. After neglecting radon as earthquake precursors in 1990-th it becomes again the subject of earthquake-forecast papers discussions due to growing networks of the radon monitoring in different countries, especially, the technologies of real-time radon measurements where the gamma-spectrometers become the leader of interest as the sources of 222Rn identification. The second fast developing direction is including the radon in the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) models as a source of the boundary layer ionization. And here we encounter with second direction which is not connected with the earthquake forecast problems. It is the role of air ionization by radon as a source of the Global Electric Circuit (GEC) modification. In this publication we try to unite all these problems to present more complex view on radon as important element of our environment.

Worldwide, among older adults, infection is the leading mortality cause; chronic nutritional deficits confer significant mortality risk and increase healthcare costs. The association of the Global Leadership Initiative on Malnutrition (GLIM)-defined malnutrition with infection-related mortality, especially with renal dysfunction in older patients, remains unevaluated. In older patients hospitalized with infection, stratified by renal function, we investigated the association of malnutrition severity with mortality. This single-center, retrospective cohort study of 1220 participants (age ≥65 years) admitted to Aichi Medical University from 2019 to 2020 used a multivariate Cox proportional hazards model to determine the association of GLIM-defined nutritional status (no, moderate, or severe malnutrition) with all-cause mortality. Compared to no malnutrition, moderate and severe malnutrition conferred significantly higher mortality (adjusted hazard ratio [confidence interval ]: 1.00 [reference], 1.76 [1.28-2.42], and 2.44 [1.78-3.33], respectively), with the highest all-cause mortality in malnutrition with a low estimated glomerular filtration rate (eGFR <30 mL/min/1.73m2; 7.35 [4.57-11.8]) compared to no malnutrition and normal eGFR (≥60 mL/min/1.73m2). GLIM-defined malnutrition confers higher all-cause mortality risk in older adults with infection, especially those with renal dysfunction. This information enables the identification of high-risk older patients with infection and targeted clinical management of those with malnutrition, renal dysfunction, and infection.

AbstractBackground: The World Health Organization (WHO) said the situation in India was a "devastating reminder" of what the coronavirus could do. COVID-19 cases suddenly spiked across India. Union Health Minister Harsh Vardhan has said that one of the major reasons for the spike in coronavirus cases was people not following COVID-appropriate behaviour. The Union minister noted that the sudden rise in cases is largely or maybe event-driven comprising local body elections, grand weddings, and farmers' protest. These events may cause asymptomatic covid-19 carriers to spread wide covid-19 to others. Malaysia is also facing a surge in Covid-19 may due to the spread of covid-19 by asymptomatic covid-19 carriers. Therefore, it is important to develop an application that can publicize information on asymptomatic covid-19 carriers. The purpose of this application is to provide sufficient information and scientific research evidence to ensure that prevention strategies for asymptomatic covid-19 carriers must be implemented. The app is also open to anyone who uses it to educate others so that information can be shared more quickly to prevent other countries from becoming "Second India or Malaysia".Method: The homepage of the app shows that asymptomatic covid-19 carriers may have a lower viral load, the same viral load, or a higher viral load than symptomatic covid-19 carriers. When the user app is pressed by each category, they will see sufficient information and scientifically based research evidence about each category. These apps also show the evidence that on January 13, 2021 - Malaysian Health Department Director Dr Noor Hisham Abdullah instructs test Only those Close Contacts With Symptoms and The Malaysian Medical Association (MMA) has urged the Health Ministry to urgently improve the management of mild Covid-19 cases and revert to its policy of testing all close contacts. In addition, These apps also show App raise public awareness of the importance of COVID-19 vaccination(version 4) [Peter Chew, 2021] can intuitively see that countries with high vaccination rates can solve the problem of asymptomatic transmission of covid-19 carriers.Result: This application displays sufficient information and scientifically based research evidence to prove asymptomatic covid-19 carriers are the main key to the outbreak of covid-19. Some countries are using covid-19 symptom prevention strategies. They are only testing the symptomatic closed contact of covid-19 patients, because they may think that asymptomatic covid-19 carrier is just a low viral load and a low transmission rate, which is wrong. Some asymptomatic covid-19 carriers of covid-19 have high viral loads. The accumulation of asymptomatic covid-19 carriers with high viral load is the main cause of the covid-19 outbreak. Conclusion: Three apps have been developed to educate the public about the importance of asymptomatic covid-19 carriers. The asymptomatic covid-19 carrier education app (1) will provide sufficient information and scientific research evidence to educate citizens of any country to ensure that preventive strategies must be implemented for asymptomatic carriers to prevent the country’s Covid-19 outbreak. App, Game Base Learning to Prevent Infection from COVID-19 (version 3) [Peter Chew, 2020 ]. The app allows anyone to intuitively see that when the second wave covid-19 arrives, the accumulation of a large number of asymptomatic carriers in some countries has led to the high infection rate of covid-19. This is what is happening in India now. App raise public awareness of the importance of COVID-19 vaccination(version 4) can intuitively see that countries with high vaccination rates can solve the problem of asymptomatic transmission of covid-19 carriers. This is what is happening in Israel now.

The stability and optimal control for an SIS epidemic model with demographics and heterogeneous control strategies (immunization and quarantine) on complex networks are investigated. The epidemic threshold, disease-free and endemic equilibria are derived. Then, global asymptotical stability about the two equilibria are studied based on different methods. Furthermore, the optimal control issue about the system is also considered. We obtain the existence and uniqueness of the optimal control and optimal control tactics. Some numerical simulations were conducted to illustrate and supplement the theoretical results. Meanwhile, the effects of the combination of various immunization and quarantine schemes are studied and also compared with the optimal control strategies.

This study assesses the feasibility of hepatitis B and C elimination, using an analysis of trends of epidemiology data (1990-2019) from the global burden of disease. Joinpoint regression analysis was used to identify significant changing points in trends of Age-standardizes Prevalence Rate (ASPR) and Age-standardizes Mortality Rate (ASMR) and to estimate the annual percentage changes (APC) and the average annual percentage changes (AAPC) for the period. Sociodemographic Index (SDI) was used to analyze trends between countries. The total percentage change of the ASPR (2019/1990) was -31.4% and -12.8% for HBV and HCV worldwide respectively, the rate ratio (HBV/HCV) was 2.5. Mortality has decreased for HBV but not for HCV. The total percentage change for the ASMR (2019/1990) was -26.7% and 10.0%, for HBV and HCV respectively. While ASMR of HBV decreased, HCV increased during this period. The percentage change in ASMR of HBV was highest in countries with high-middle SDI and lowest in countries with high SDI. For HCV, the percentage change in ASMR was highest in countries with High SDI (increase) and only in countries with low SDI decreased. The global HBV and HCV rates have fallen with different AAPC associated with the SDI. Despite the advances, there is still a long way forward to achieve the 2030 elimination goals. An important challenge is related to finding a way to speed up the yearly rate at which the decline is happening.

This comprehensive review examines the critical issue of antimicrobial resistance (AMR), a growing global concern with profound societal implications. This article presents an overview of the causes of AMR, including the misuse and overuse of antibiotics in healthcare, agriculture, and veterinary practices. Various conventional and advanced detection methodologies have been explored, highlighting the importance of the accurate and timely identification of resistant strains. The challenges associated with tackling AMR, encompassing scientific, economic, and regulatory aspects have been discussed in depth. In addition, this article sheds light on the far-reaching societal implications of AMR, including increased healthcare costs, treatment complexities, and potential disruptions to healthcare systems. This emphasizes the urgency of adopting proactive strategies to combat AMR and underscores the need for global cooperation, policy interventions and public awareness campaigns. By unraveling the multifaceted dimensions of AMR, this review aims to enhance our understanding, stimulate further research, and promote concerted efforts to mitigate the threat of antimicrobial resistance.

With enhanced life expectancy and ageing global populations, the prevalence of multimorbidity continues to increase. However, there is a dearth of evidence linked to multimorbidity diagnoses, treatments and health outcomes which remains a concern for future proofing optimal healthcare services. Generating evidence is critical to managing multimorbidity, promoting public health and minimizing health inequalities via effective healthcare policies that improve quality of life for vulnerable populations. This study assessed meta-epidemiology of multimorbidity to report the gaps in scientific knowledge and clinical practice. A systematic methodology was designed and published in PROSPERO (CRD42022347308) to report meta-epidemiology analyses using databases including PubMed, Web of Science, ScienceDirect, EMBASE, The Cochrane Gynaecology and Fertility Group Specialised Register of Controlled Trials and MEDLINE for studies published between the 1^st of January 1980 - 31^st December 2022. A random-effects model was used to estimate the pooled proportion of multimorbidity in adults. Forest plots, pooled odds ratios and statistical heterogeneity metrics were used to assess the association between multimorbidity and investigated factors. Funnel plots and Egger’s regression were used to detect and correct for publication bias. Our findings identified women to be 0.32 times more likely to have multimorbidity in comparison to males. In regard to ethnicity, white people were 0.47 times less likely to develop comorbidities than black people. People who identified as a drinker or unmarried were more likely to develop comorbidities than those who are non-drinkers or married, respectively. Regardless of smoking status, people were equally likely to have comorbidity. In terms of environmental influences, people in rural areas were found to be 0.2 times less likely to have comorbidity in comparison to those living in urban areas. Interestingly, people with a higher education level were 0.57 times more likely to develop comorbidities than those with only a high school education. It is evident that multimorbidity has a significant burden globally and impacts the provision of care necessitated across populations given its association with several social determinants of health. Robust research and healthcare policies are required to better manage multimorbidity in patients. An example of such intervention includes employing prevention programs to reduce risk and incidence of multimorbidity within at-risk populations.

Broadband noise reduction over the low-mid frequency range in the building and transportation sectors requires compact lightweight sound absorbers of typical sub-wavelength size. The use of multi-layered closely-spaced (micro-)perforated membranes or panels, if suitably optimized, contribute to these objectives. However, their elasticity or modal behaviors often impede the final acoustical performance of the partition. The objective of this study is to get insights into the vibrational effects induced by elastic limp membranes or panels volumetric modes on the optimized sound absorption properties of acoustic fishnets and functionally-graded partitions (FGP). Cost-efficient global optimization of the partition total frequency-averaged dissipation is achieved from simulated annealing with vibrational effects included through an impedance translation method. Critical coupling analysis reveals how the membranes or panels vibrations redistribute the locations of the Hole-Cavity resonances as well as their cross-coupling with the panels first volumetric mode. It is found that elastic limp micro-perforated membranes broaden the first pass-band of acoustic fishnets while smoothing out the dissipation ripples over the FGP optimiza-tion bandwidth. Moreover, the resonance frequency of the first panels mode sets an upper limit to the broadband optimization of FGPs, up to which high dissipation, low reflection and low trans-mission can be achieved.

Digital health has gained widespread adoption across various disciplines. Within the field of sport science, there is growing interest in digital health, leading to a surge in research activities. The objective of this study is to conduct a comprehensive bibliometric and visualization analysis, tracing the evolutionary trajectory, identifying research hotspots, and uncovering emerging trends in digital health within the domain of sport science. By doing so, this research aims to offer scholars a systematic and comprehensive understanding of the dynamic landscape in this field. To achieve this, the Web of Science core collection was chosen as the primary database. A thorough literature search was performed, focusing on digital health and sport science, resulting in the screening of 1870 English-language documents. The findings revealed a consistent upward growth trend in the annual publication count from 2010 to 2023. Notably, the United States, specifically the Commonwealth of Pennsylvania System of Higher Education, and John B. Cronin, emerged as the most prolific contributors in terms of publications. Collaborative efforts among countries, institutions, and authors were also observed. The research hotspots identified encompassed several areas, including the evaluation of digital health technologies' effectiveness, exploration of the relationship between digital health technologies and physical activity/exercise performance, and the use of digital health technologies in assessing and rehabilitating sports injuries. Among the prominent digital health technologies employed in these studies were virtual reality, social media, and wearable devices. The predominant types of studies utilized meta-analysis, randomized controlled trials, and cross-sectional studies. Looking towards the future, the study identified several key research trends. These include the exploration of telemedicine, artificial intelligence-based machine learning, therapeutic interventions, and physical therapy within the realm of digital health. These emerging areas signify promising directions for future investigation and development in the field of digital health within sport science.

Dealing with randomness is a crucial aspect that cost-effectiveness analysis (CEA) tools need to address, but existing stochastic CEA tools have rarely examined risk and return from the perspective of global benefits. This paper proposes a stochastic CEA tool that supports medical decision-making from the perspective of global benefits of risk and return, the risk-adjusted incremental cost-effectiveness ratio (ICER). The tool has a traditional form of ICER but uses the risk-adjusted expected cost. Theoretically, we prove that the tool can provide marginal medical decisions that promote the risk-return level on global benefits within any intervention structure and can also serve as a discriminating condition for the optimal intervention structure. Numerical simulations within a framework of mean-variance support the conclusions in this paper.

Fuel consumption, subsequent emissions and safe operation of class 8 vehicles are of prime importance in recent days. It is imperative that the vehicle operates in its true optimal operating region given a variety of constraints such as road grade, load, gear shifts, Battery State of charge (for hybrid vehicles), etc. In this paper a research study is conducted to evaluate the fuel economy and subsequent emission benefits when applying predictive control to a mild hybrid line haul truck. The problem is solved using a combination of dynamic programming with back tracking and model predictive control. The specific fuel saving features that are studied in this work are dynamic cruise control, gear shifts, vehicle coasting and torque management. These features are evaluated predictively as compared to a reactive behavior. The predictive behavior of these features are a function of road grade. The result and analysis shows significant improvement in fuel savings along with NOx benefits. Out of the control features dynamic cruise (predictive) control and dynamic coasting showed the most benefits while predictive gear shifts and torque management (by power splitting between battery and engine) for this architecture did not show fuel benefits but provided other benefits in terms of powertrain efficiency.

Phase synchronization of weakly coupled limit cycle oscillators are related to the stability of the zero solution of the reduced-order dynamics of phase differences, represented by a systems of differential equations on a hypertorus. Using Rantzer's density function, a dual form of Lyapunov function, we propose a method to certify almost global stability of an equilibrium on a hypertorus. We show that the proposed method can certify robustness of phase synchronization of all-to-all and weakly coupled limit cycle oscillators with respect to disturbances in phases. The method leverages sum of squares polynomial optimization to construct the certification function.

Global optimization is an imperative development of local optimization because there are many problems in artificial intelligence and machine learning requires highly acute solutions over entire domain. There are many methods to resolve the global optimization, which can be classified into three groups such as analytic methods (purely mathematical methods), probabilistic methods, and heuristic methods. Especially, heuristic methods like particle swarm optimization and ant bee colony attract researchers because their effective and practical techniques which are easy to be implemented by computer programming languages. However, these heuristic methods are lacking in theoretical mathematical fundamental. Fortunately, minima distribution establishes a strict mathematical relationship between optimized target function and its global minima. In this research, I try to study minima distribution and apply it into explaining convergence and convergence speed of optimization algorithms. Especially, weak conditions of convergence and monotonicity within minima distribution are drawn so as to be appropriate to practical optimization methods.

Infectious diseases, as COVID-19 is proving, pose a global health threat in an interconnected world. In the last 20 years, resistant infectious diseases such as SARS, MERS, H1N1, Ebola, Zika and now COVID-19 have been impacting global health defences, and aggressively flourishing within the rise of global travel, urbanization, climate change and ecological degradation. In parallel, this extraordinary episode in global human health highlights the potential for artificial intelligence (AI)-enabled disease surveillance to collect and analyse vast amounts of unstructured and real-time data to inform epidemiological and public health emergency responses. The uses of AI in these dynamic environments are increasingly complex, challenging the potential for human autonomous decisions. In this context, our study of qualitative perspectives will consider a responsible AI framework to explore its potential application to disease surveillance in a global health context. Thus far, there is a gap in the literature in considering these multiple and interconnected levels of disease surveillance and emergency health management through the lens of a responsible AI framework.

This paper presents an extension of the results obtained in previous work concerning the application of global optimization techniques to the design of finite strategic games with mixed strategies. In that publication the Fuzzy ASA global optimization method was applied to many examples of synthesis of strategic games with one previously specified Nash equilibrium, evidencing its ability in finding payoff functions whose respective games present those equilibria, possibly among others. That is to say, it was shown it is possible to establish in advance a Nash equilibrium for a generic finite state strategic game and to compute payoff functions that will make it feasible to reach the chosen equilibrium, allowing players to converge to the desired profile, con- sidering that it is an equilibrium of the game as well. Going beyond this state of affairs, the present article shows that it is possible to ”impose” multiple Nash equilibria to finite strategic games by following the same reasoning as before, but with a fundamental change: using the same fundamental theorem of Richard McKelvey, modifying the originally prescribed objective function and globally minimizing it. The proposed method, in principle, is able to find payoff functions that result in games featuring an arbitrary number of Nash equilibria, paving the way to a substantial number of potential applications.

People living in slums and other deprived areas in low- and middle-income country (LMIC) cities are under-represented in censuses, and subsequently in "top-down" gridded population estimates. Modelled gridded population data are a unique source of disaggregated population information to calculate local development indicators such as the Sustainable Development Goals (SDGs). This study evaluates if, and how, WorldPop-Global (WPG) -Unconstrained and -Constrained “top-down” datasets might be improved in a simulated realistic LMIC urban population by incorporating slum profile population counts into model training. We found that the WPG-Unconstrained model with or without slum training data grossly underestimated population in urban deprived areas while grossly overestimating population in rural areas. SDG 11.1.1, the percent of population living in slums, for example, was estimated to be 20% or less compared to a "true" value of 29.5%. The WPG-Constrained model, which included building auxiliary datasets, far more accurately estimated the population in all grid cells (including rural areas), and the inclusion of slum training data further improved estimates such that SDG 11.1.1 was estimated at 27.1% and 27.0%, respectively. Inclusion of building metrics and slum training data in “top-down” gridded population models can substantially improve grid cell-level accuracy in both urban and rural areas.

Particle swarm optimization (PSO) is an effective algorithm to solve the optimization problem in case that derivative of target function is inexistent or difficult to be determined. Because PSO has many parameters and variants, I propose a general framework of PSO called GPSO which aggregates important parameters and generalizes important variants so that researchers can customize PSO easily. Moreover, two main properties of PSO are exploration and exploitation. The exploration property aims to avoid premature converging so as to reach global optimal solution whereas the exploitation property aims to motivate PSO to converge as fast as possible. These two aspects are equally important. Therefore, GPSO also aims to balance the exploration and the exploitation. It is expected that GPSO supports users to tune parameters for not only solving premature problem but also fast convergence.

Sequence analysis program is outlined that analyzes and investigates homology between various nucleic acid or protein sequence. The dot matrix technique compares the sequences and the consensus sequence is obtained by superimposing on each other all the dot matrices. Local Alignment and Global Alignment both sequence from start to end is the best possible alignment over the entire duration between the two sequences. This method is more important to align with two closely related sequences roughly the same length. This method may not able to generate optimal results for divergent sequences and variable length sequence because between the two sequences it does not recognize very similar local region.

The pandemic caused by SARS-CoV-2 virus obstructed the Chinese economy and has expanded to the rest of the world at a rapid pace affecting at least 215 countries, areas and territories. The advancement of the disease and its economic repercussions is profoundly ambiguous, making it challenging for policymakers to formulate suitable microeconomic and macroeconomic policy responses. The scenarios in this paper illustrate how an outbreak could significantly affect the global economy in the short run. It has been estimated that each additional month of crisis would cost from about 2.5-3% of the global GDP and that the GDP growth would take a blow, reaching about 3-6%, depending on the country. Scenarios also suggest that GDP can drop by more than 10% and even exceed 15% in some countries. Via addressing the economic consequence of COVID-19 in different industries and countries, the paper presents assessments of the likely global economic costs of COVID-19 and the GDP growth of different countries. Economies will be negatively affected because of the high number of jobs at risk. Countries highly dependent on foreign trade are more negatively affected. Given that disease and its economic influence are highly unpredictable in numerous aspects, the global economy at the moment is the most critically threatened in history.

Bio-economy is a major area of the strategy that can afford the European Union to achieve growth: (i) smart, through the development of knowledge and innovation; and (ii) sustainable, based on a greener, more efficient economy in resource management. We believe that the progress of bio-economy cannot be achieved without the harnessing of intellectual capital. Our research aimed to emphasize the benefits of the dynamics of the intellectual capital growth on the evolution of the bio-economy. Thus, the information published by Eurostat (European Statistic Institute) during a period spanning seven years (2011-2018) was used to assess the influence exerted by the conduct of the harness of intellectual capital related to sustainability as well as for the reporting of indicators relevant to appreciating an economic progress and sustainability (renewable waste material, share of renewable energy and energy intensity of the economy). The ultimate goal was represented by the generation of a regression model to see what factor influences mostly the progress of the bio-economy at European and Romanian level. Significant dependency relationships were identified. The results remain robust even after the introduction of certain control variables, such as gross domestic product rate, food production, population growth, urbanization growth and inflation. Our paper sets out to contribute to expanding the specialty literature by highlighting the involvement of intellectual capital as a factor in optimizing sustainability growth and, at a methodological level, by using a multiple regression.

The main ideas of F-transform came from representing expert rules. It would be therefore re reasonable to expect that the more accurately the membership functions describe human reasoning, the more efficient will be the corresponding F-transform formulas. We know that an adequate description of our reasoning corresponds to complicated membership functions -- however, somewhat surprisingly, most efficient applications of F-transform use the simplest possible triangular membership functions. There exist some explanations for this phenomenon which are based on local behavior of the signal. In this paper, we supplement this local explanation by a global one: namely, we prove that triangular membership functions are the only one that provide the accurate description of appropriate global characteristics of the signal.

We give a topological condition for a generic sliced space to be globally hyperbolic, without any hypothesis on the lapse function, shift function and spatial metric.

Human violence recognition is an area of great interest in the scientific community, given its broad spectrum of applications, especially in video surveillance systems, since detecting violence in real-time could prevent criminal acts and save lives. Despite the number of existing proposals and research, most focus on the precision of results, leaving aside efficiency and its practical implementation. Thus, this work proposes a model that is effective and efficient in recognizing human violence in real-time. The proposed model consists of three modules: a first module called Spatial Motion Extractor (SME), in charge of extracting regions of interest from a frame; a second module called Short Temporal Extractor (STC), whose function is to extract temporal characteristics of rapid movements, finally the Global Temporal Extractor (GET) module, responsible for identifying long-lasting temporal features and fine-tuning the model. The proposal was evaluated regarding efficiency, effectiveness, and ability to operate in real-time. The results obtained on Hockey, Movies, and RWF-2000 datasets demonstrated that this approach is highly efficient compared to other alternatives. A VioPeru dataset was created to validate real-time applicability with violent and non-violent videos captured by real video surveillance cameras in Peru. The effectiveness results in this dataset outperformed the best existing proposal. Therefore, our proposal has contributions in efficiency, effectiveness, and real-time.

Economic risks for livestock production are caused by volatile commodities and market conditions, but also by environmental drivers like increasing uncertainties due to weather anomalies and global warming. These risks impact the gross margin of farmers and can stimulated investment decisions. For confined pig and poultry production, farmers can reduce the environmental impact by implementing specific adaptation measures to reduce heat stress. A simulation model driven by meteorological data was used to calculate heat stress impact as a projection for 2030. For a business-as-usual livestock building, the indoor climate for several adaptation measures was calculated. The weather-related value-at risk quantified the economic risks caused by global warming and the stochastic component of the weather. The results show that only energy-saving adaptation measures to reduce the inlet air temperature are appropriate to reduce the economic risk to the level of the year 1980. The efficiency of other adaptation measures to reduce heat stress is distinctly lower. The results in this study can support the decision making of farmers concerning adaptation management and investments. It can inform agricultural policy design as well as technological development.

The emerging concept of planetary health needs to be discussed in a more organized and sustainable way within the global public health and healthcare disciplines. Therefore, planetary health should be considered a cardinal component of the global academic framework for healthcare professionals. The availability of related curricula and courses is crucial to equip health professionals in this relatively new discipline of planetary health. In this review article, we aimed to explore published articles and online databases of courses to summarize the available planetary health education opportunities and discussions for health professionals, to identify the gaps in resource allocation and to suggest future recommendations. We observed a visible re-source inequity in global south with the lack of a universal planetary health module for healthcare professionals. Additionally, there is minimal inclusion of allied health disciplines in this learning process. We, therefore, recommend a dedicated network of motivated healthcare professionals and regional hubs with an agenda to ensure a comprehensive, uniform, and inclusive planetary health education curriculum and practice.

Facing unprecedented global declines in the extent and integrity of ecosystems, the 15^th UN Biodiversity Conference (COP-15) in Kunming, China, presents an opportunity for transformative change. However, a lack of consensus on two key issues – resource mobilization and Access and Benefit Sharing (ABS) associated with Digital Sequence Information (DSI) – risks stalling negotiations for an ambitious ‘Post-2020 Global Biodiversity Framework’ as the next 10-year strategic plan under the Convention on Biological Diversity. We highlight systemic misconceptions concerning the financing of biodiversity and the burden this places on the ABS system. In the context of DSI, we caution that conflating ABS with resource mobilization risks disrupting modern science policy built on open access, with potentially severe ramifications for scientific research and innovation. To resolve these tensions, we call for a recalibration of discussions on ABS in order to maximize the value delivered by biodiversity for all of society, including indigenous peoples and local communities.

Metabolic pathways provide key information to achieve a better understanding of life and all its processes; this is useful information for the improvement of medicine, agronomy, pharmacy, and other similar areas. The main analysis tool used to study these pathways is based on the idea of pathway comparison, using graph data structures. Metabolic pathway comparison has been defined as a computationally complex task \cite{ay2011submap,abaka2013campways}. In previous work from 2017, two different approaches that simplify the problem of comparing pathways represented as graphs were introduced. The first algorithm consists of the transformation of a two-dimensional graph structure, representing a metabolic pathway, to a one-dimensional structure and thus aligning the corresponding data using a reduced 1 dimension string. The second algorithm consists of performing a paired analysis between reactions in pathways and thus eliminating all similarities, finally, showing these differences to the user. The suggestion is to use the information provided by these algorithms as a previous analysis to a deeper, more expensive, comparison tool use. Here we provide an extension of this work with more data and deeper analysis. These methods have shown to be an effective way to treat the problem of metabolic pathway comparison as listed in the discussion and results section. Our results show evidence of a quick, simple and effective way to resolve the described problem.

Hand gestures may play an important role in medical applications for health care of elderly people, where providing a natural interaction for different requests can be executed by making specific gestures. In this study we explored three different scenarios using a Microsoft Kinect V2 depth sensor then evaluated the effectiveness of the outcomes. The first scenario utilized the default system embedded in the Kinect V2 sensor, which depth metadata gives 11 parameters related to the tracked body with five gestures for each hand. The second scenario used joint tracking provided by Kinect depth metadata and depth threshold together to enhance hand segmentation and efficiently recognize the number of fingers extended. The third scenario used a simple convolutional neural network with joint tracking by depth metadata to recognize five categories of gestures. In this study, deaf-mute elderly people execute five different hand gestures to indicate a specific request, such as needing water, meal, toilet, help and medicine. Then, the requests were sent to the care provider’s smartphone because elderly people could not execute any activity independently. The system transferred these requests as a message through the global system for mobile communication (GSM) using a microcontroller.

One of today’s most critical challenges is ensuring a sufficient food production and supply for the ever-expanding global population. Recently, many countries around the world, particularly those in Africa, grapple with severe hunger and food insecurity, frequently exacerbated by escalating global prices, persistent insecurity, and the repercussion of the COVID-19 pandemic. However, this study undertook an extensive review of the prevalence and severity of hunger and food insecurity across diverse countries and regions. The review utilised several metrics, including Global Hunger Index (GHI) scores, Global Food Security index (GFSI) scores, 2023 data (related to two Sustainable Development Goal 2 (SDG2) target) from the Food and Agriculture Organization (FAO), and other pertinent sources to assess the current status of the countries included in this study. The 20 countries with 2023 GHI scores below 5 were collectively ranked from 1 to 20, signifying low hunger levels. However, Central African Republic (CAR) received the lowest ranking at 125 out of 125, with a score of 42.3, indicating an alarming level of hunger. Finland achieved the highest GFSI score of 83.7, with Oman showing the most notable GFSI improvement at +13.8, while Syria experienced a significant decline in GFSI score by -10.5. Over time, many countries, particularly the developed ones, witnessed significant improvement in their GHI and GFSI scores. Meanwhile, most countries in sub-Saharan Africa experienced the most deterioration in their GFSI scores and notable increases in their GHI scores. The review documented the significant progress made by countries and regions in reducing levels of hunger and food insecurity, while highlighting the substantial burden borne by sub-Saharan Africa (SSA) in combating global hunger and food insecurity.

The term sustainable energy is very familiar to all of us yet its exact definition or meaning has so far been vague. To date the widely adopted definition of sustainable energy has been inspired by the definition of sustainable development formulated more than 30 years ago in the Our Common Future - the UN’s Report of the World Commission on Environment and Development. The current definition conceals the true spirit of the Report and this has some ramifications. It raises the question as to whether we have put too much emphasis on attaining the future dimension of sustainability in the middle of the situation where the energy survivability is in fact the real issue in many parts of the world. In this paper the role of energy in sustaining livelihoods of low income communities is discussed. Existing definition of sustainable energy that the whole world seems to have embraced is looked at critically and its downsides exposed. The identified pillars of sustainable energy and the associated issues is discussed and the need for an additional pillar, i.e. affordability is discussed and called for. This paper will argue that global definition of sustainable energy seems inappropriate and should be jettisoned and a more realistic definition should be formulated, adopted and embraced at local (i.e. national or regional) level taking into account local attributes and factors. The current push for a transition from the reliance on conventional energy sources to ‘cleaner’ energy sources (generally associated with renewable energy) has further exacerbated the issue of energy affordability that has made the conditions even more dire for so many groups of the world population. In the midst of this situation, those who push for a rushed energy transition seem to be those who also produce unsustainably high carbon footprint but who can easily offset their carbon foot-print through the ‘net-zero’ concept.

There are potentially promising mitigation activities for epidemic and pandemic scenarios that are not currently the subject of significant research effort. Large epidemics and pandemics pose risks that are important to mitigate, even if the likelihood of the events is low and uncertain. While some efforts are the subject of extensive funding and consideration, other approaches are neglected. Here, we consider such neglected interventions which could significantly reduce the impact of such an epidemic or large-scale pandemic. These are identified via a narrative literature review of extant literature reviews and overviews of mitigations in epidemic and pandemic situations, followed by consideration of the economic value of information of further study of heretofore neglected interventions and approaches.Based on that analysis, we considered several classes of mitigations, and conducted more exploratory reviews of each. Those discussed include mitigations for (1) reducing transmission, such as personal protective equipment and encouraging improved hygiene, (2) reducing exposure by changing norms and targeted changes for high-risk or critical professions and activities, (3) reducing impact for those infected, and (4) increasing large scale resilience using disaster and infrastructure continuity planning.Some proposed mitigations are found to be of low marginal value. Other mitigations are likely to be valuable, but the concepts or applications are underdeveloped. In those cases, further research, resources, or preparation are valuable for mitigating both routine and extreme disease outbreak events. Still more areas of research are identified as having uncertain value based on specific but resolvable uncertainties. In both of the latter cases, there is no guarantee that mitigations identified as worthy of further consideration will be valuable, but the argument for further research is clear.

Climate change presents an urgent and impending threat to virtually all global biological systems. In recent years, there has been a surge in research endeavors aimed at investigating the potential relationship between changes in climate patterns and the spread of infectious diseases. This scoping review included studies on global warming and infectious diseases from 2019 to 2023, The studies included in this research were obtained from reputable academic databases such as Web of Science and google scholar. A systematic keyword search was conducted to identify relevant studies, and a predefined set of inclusion criteria was applied to review and select the appropriate studies for analysis. This review found that climate change has a remarkable impact on the dissemination and incidence of many infectious diseases, it increases microbial resistance and may increase the prevalence the arthropods-borne diseases with mild effect on fungal infections, also, the low to middle income countries may be affected more than other countries from these virulent pathogens, this study concluded that a future research in the field of climate change and infectious diseases should involve a thorough examination of the transmission of diseases, considering both direct and indirect modes of transmission

In the transition towards sustainable energy sources, hydrogen has emerged as the predominant alternative after fossil fuels. This comprehensive literature review delves into the evolving landscape of hydrogen launching strategies within the energy market. Numerous countries have strategically initiated efforts to introduce products based on hydrogen, underscoring the global acknowledgment of the potential inherent in hydrogen. Despite witnessing significant growth in the adoption of hydrogen energy worldwide, impediments to its widespread commercialization persist. This review identifies key barriers, including cost structures, technical complexities, and marketing challenges, hindering the establishment of a robust hydrogen energy market. The article critically examines the actions already undertaken to harness hydrogen energy for commercial purposes, leveraging scientific insights and statistical data. By carefully examining the current state of hydrogen energy initiatives, the review highlights gaps in existing strategies that require thoughtful consideration. Insights derived from scientific and statistical analyses inform the identification of barriers and contribute to a nuanced understanding of the challenges faced in the journey towards hydrogen energy commercialization. Ultimately, the article presents a strategic proposal outlining marketing actions geared towards expediting the commercialization and widespread adoption of hydrogen energy. Grounded in a thorough review of existing literature and supported by scientific and statistical evidence, this comprehensive analysis offers valuable insights for stakeholders seeking to navigate the intricate landscape of hydrogen energy in the global energy market.

Myocardial involvement among critical patients with coronavirus disease 2019 (COVID-19) has a worse outcome. The occurrence of an imbalance in oxygen supply results in the release of pro-inflammatory cytokines which leads to increased ventilation support requirement and increase risk of mortality. Our aim was to evaluate the association between hs-Troponin I level and global longitudinal strain as evidence of myocardial involvement among critical COVID-19 patients. Methods. We performed prospective cohort study from February 1st – July 31st, 2021 at Dr. Soetomo General Hospital, Surabaya as referral center for COVID-19 care. Of the 65 critical COVID-19 included, 41 (63.1%) were men, with a median (interquartile range) age of 51.0 years (20.0-75.0).Subjects were recruited according to WHO criteria for severe COVID-19 and CDC criteria for myocarditis. All subjects recruited were examined using echocardiography to measure global longitudinal strain (GLS) and blood samples were taken to measure hs-Troponin. Subjects were then followed to assess their needs for mechanical ventilation and in-hospital mortality. Severe COVID-19 subjects with cardiac injury were associated with an increased need for intubation (78.5%) and an increased incidence of myocarditis (50.8%). There was an association between the use of intubation and the risk of mortality in patients (66.7% vs. 33.3%, p-value <0.001). Both reduced GLS and increased hs-troponin are associated with increased myocarditis (p-value <0.001 and 0.004 respectively). Reduced GLS is associated with higher mechanical ventilation needs (12.17 + 4.79 vs.15.65 + 4.90, p-value 0.02) and a higher mortality rate (11.36 + 4.64 vs. 14.74 + 4.82; p-value 0.005). Increased hs-troponin is associated with higher mechanical ventilation needs (25.33% vs. 3.56%, p-value 0.002) and a higher mortality rate (34.57% vs. 5.76%, p-value 0.002). Compared with contemporary controls, critical COVID-19 patients with myocardial involvement and elevated cardiac troponin level are associated with higher mechanical ventilation needs and a higher mortality rate.

This chapter explores the pivotal role of maize (Zea mays L.) in global nutrition, emphasizing its status as a staple food worldwide. It discusses maize's complex nutritional profile, including macronutrients, micronutrients, and dietary fiber. The chapter also covers biofortification efforts to enhance maize with essential nutrients, addresses nutritional concerns related to maize-centric diets, and explores genetic modification and agronomic strategies to boost nutrient-rich maize yields. Additionally, it delves into maize processing traditions, nutrient retention techniques, and the importance of promoting nutrient-rich maize varieties. The chapter outlines post-harvest strategies to combat nutrient loss and prevent contamination while emphasizing the significance of consumer education and diverse diets. Case studies illustrate the impact of improved maize nutrition and provide replicable strategies. The chapter concludes by considering emerging research and technology, identifying challenges, and proposing solutions to enhance maize's nutritional value in the future.

Syphilis continues to be a significant global health concern, and understanding the latest advancements in immunology and pharmacological treatment is crucial for effective disease management. This review article provides an in-depth exploration of these advancements, aiming to contribute to the growing body of knowledge on syphilis research. The epidemiology of syphilis sets the stage for this review, highlighting the persistent burden of the disease worldwide. Current trends and challenges in disease control are discussed, shedding light on the need for comprehensive prevention strategies and improved surveillance systems. The immunological aspects of syphilis are the focus of this review. The intricate interplay between the host immune response and the evasive strategies employed by Treponema pallidum, the causative agent of syphilis, are explored. These include the mechanisms of immune evasion, the role of adaptive and innate immunity, and the development of immune-mediated tissue damage. The article also highlights advancements in diagnostic methods, with emphasis on the importance of accurate and timely detection. From traditional serological tests to the emergence of novel molecular and point-of-care assays, these developments have significantly improved the efficiency and accuracy of syphilis diagnosis. In terms of pharmacological treatment, the review covers the current recommendations and emerging strategies for managing syphilis infections. The challenges posed by antimicrobial resistance are addressed, emphasizing the importance of appropriate treatment regimens and close monitoring of therapeutic efficacy. Looking to the future, this review highlights the potential of vaccine development as a preventive measure against syphilis. Promising vaccine candidates and ongoing research efforts are discussed, offering hope for an effective means of disease prevention. In conclusion, this comprehensive review explores the advancements in syphilis research, from the understanding of immunological complexities to the development of innovative treatment strategies. By collectively advancing our knowledge, we can strive towards better disease management and minimize the impact of syphilis on global public health.

This scholarly article provides an overview of the present and future issues and trends in social work on a global scale. Drawing upon recent bibliographic references and a review of the literature, this article explores the challenges faced by social workers in various regions and highlights emerging trends that are reshaping the field. The analysis incorporates insights from renowned authors and researchers to provide a comprehensive understanding of the current state and anticipated future of social work practice, education, and research worldwide.

Space syntax can be potentially applied for the evaluation of quality of user flows particularly in solving problems of sustainable projects in spaces intended for users to move around. This study aims to analyze the concepts of pedestrian flows (open and closed) by space syntax based bibli-ographical approach on a global scale, demonstrating the capability of improvements in Sus-tainable Development Goals (SDGs) as applied to the architecture of sustainable flows. Scopus theoretical reference bases were used, which are directly related to the theme of space syntax in open and closed spaces. Frequency analyzes were carried out, applying the content analysis, to identify words with a degree of similarity, related to “space syntax: flow in urban environ-ments” and “space syntax in closed built systems”, in relations to the SDGs. The results show that pedestrian flows identified in the literature aid to understand the global production on space syntax in open and closed spaces, directed to user flows in the built environment, where many environments of flows in the built space analyzed become unsustainable because they do not present full flow efficiency. In our study on space syntax, the following central terms were identified: pedestrian movements (open urban systems) and space (closed built systems), which allows a better understanding of the flows, highlighting the importance of the urbanist architect on the functionality of user flows in sustainable architectural projects on a global scale. The most frequent categories for open environments were the terms space and form and for closed envi-ronments were space and flow.

The work proposes a new approach for evolutionary global optimization which, in simple terms, may be described as a fusion of quantum and simulated annealing. This becomes possible by using basic concepts from Homotopy Theory, conjugated to the already existing Fuzzy Adaptive Simulated Annealing paradigm and other components. In this fashion, it occurs a temporal and nonlinear superposition of the two types of annealing, provoking interesting effects in runtime, including the so-called quantum tunneling, when there is a sudden transition between attraction basins of different minima without "climbing" potential barriers. In addition, the proposal includes a generalization of the "deformation" of Hamiltonians used in quantum annealing by suggesting the use of general homotopies between the surface corresponding to the cost function under processing and another specific landscape, being this possible because of the ability of Fuzzy ASA of handling time-varying objective functions. The proposed paradigm shows that it is possible and beneficial to superpose the two types of annealing, displaying amazing numerical results and suggesting a kind of interlacing or synergic behavior - perhaps we could call it an "annealing entanglement". Finally, given the fast advances in commercial quantum annealing processors, it seems sensible to expect that an implementation of the proposed approach using such devices may occur very soon. In order to demonstrate the efficacy of the proposed algorithm, some significant and detailed examples are included in the text, so as to illustrate and clarify the presented ideas.

Trends focused on the Global Innovation Index (GII) as a measure for progress of nanochemistry. This paper provides projections of recent developments in the word in nanochemistry based on the Global Innovation Index as a predictor for certain Arab countries. The GII is an annual ranking of countries by its ability and performance in innovation and is calculated on a basic average from five and two pillars in two sub-indexes, the Innovation Input Index and the Innovation Output Index. Each pillar represents a trait of creativity and consists of up to five measures, with a weighted average formula for measuring their ranking. In 2008, the GII rose to 36.3 in 2016 from 0.5. The GII is smaller than the GII in Arabic countries worldwide. During the years 2013-2016, the worldwide GII was increasing while for the same period, for Arabic countries, this decline could be explained by economic and industrial wars in the Arab region.

Although total nett CO₂ atmospheric flow can be estimated with reasonable accuracy, the contributing gross fluxes between the atmosphere and the earth's surface are poorly understood. This paper presents a method, driven by the objective of simplicity, by which the global outflow and inflow of CO₂ between atmosphere and a globally equivalent "mixing reservoir" can be estimated, using the isotopes ¹⁴C and ¹³C as tracers. It has been asserted that the isotopic carbon in CO₂ cannot be directly used as a tracer in flow studies because it is not subject to the Revelle factor. Evidence is provided showing that this view is mistaken. The model contains 7 key parameters which are used to create synthetic records of Δ¹⁴C and d¹³C spanning 200 years or more, including during the period of atmospheric weapons testing and its decay known as the "bomb pulse". By optimising the fit between these computed values and the historical records of d¹³C and Δ¹⁴C, all seven key parameters are determined. The effective "mixing reservoir" is thereby determined to have a size around six times that of the atmosphere, with global outflux rising from 39.7 GTC yr-1 in 1750 to 58.9 GTC/yr in 2020, this figure probably not including annually cycled carbon.

Tropical corals construct the three-dimensional framework for one of the most diverse ecosystems on the planet, providing habitat to a plethora of species across taxa. However, these ecosystem engineers are facing unprecedented challenges, such as increasing disease prevalence and marine heatwaves associated with anthropogenic global change. As a result, major declines in coral cover and health are being observed across the world's oceans, often due to the breakdown of coral-associated symbioses. Here, we review the interactions between the major symbiotic partners of the coral holobiont – the cnidarian host, algae in the family Symbiodiniaceae, and the microbiome – that influence trait variation, including the molecular mechanisms that underlie symbiosis and the resulting physiological benefits of different microbial partnerships. In doing so, we highlight the current framework for the formation and maintenance of cnidarian-Symbiodiniaceae symbiosis, and the role that immunity pathways play in this relationship. We emphasize that understanding these complex interactions is challenging when you consider the vast genetic variation of the cnidarian host and algal symbiont, as well as their highly diverse microbiome, which is also an important player in coral holobiont health. Given the complex interactions between and among symbiotic partners, we propose several research directions and approaches focused on symbiosis model systems and emerging technologies that will broaden our understanding of how these partner interactions may facilitate the prediction of coral holobiont phenotype, especially under rapid environmental change.

The varved sediments of the Pyrenean Lake Montcortès (Pallars Sobirà, Lleida) embody a unique continuous high-resolution (annual) paleoarchive of the last 3000 years for the circum-Mediterranean region. A variety of paleoclimatic and paleoecological records have been retrieved from these uncommon sediments that have turned the lake into a regional reference. Present-day geographical, geological, ecological and limnological features of the lake and its surroundings are reasonably well known but the lack of a local weather station has prevented characterization of current climate, which is important to develop modern-analog studies for paleoclimatic reconstruction and to forecast the potential impacts of future global warming. Here, the local climate of the Montcortès area for the period 1955-2020 is characterized using a network of nearby stations situated along an elevational transect in the same river basin of the lake. The finding of statistically significant elevational gradients for annual and monthly average temperature and precipitation has enabled to estimate these parameters and their seasonal regime for the lake site. A representative climograph has been shaped with these data that can serve as a synthetic descriptive and comparative climatic tool. The same analysis has provided climatic data for modern-analog studies useful to improve the interpretation of sedimentary records in climatic and ecological terms. In addition, the seasonal slope shifting of the climatic elevational gradients has been useful to gain insights about possible future climatic trends under a warming scenario.

New setting is introduced to study the global powerful alliance. Global powerful alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global powerful alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs excluding empty, path, star, and wheel and containing complete, cycle and r-regular-strong are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is used in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-powerful-alliance number and minimal-global-powerful-alliance-neutrosophic number. Two different types of sets namely global-powerful alliance and minimal-global-powerful alliance are defined. Global-powerful alliance identifies the sets in general vision but minimal-global-powerful alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-powerful-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-powerful alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs has an open avenue, in the way that, the family only contains same classes of neutrosophic graphs. The results are about minimal-global-powerful alliance, minimal-global-powerful-alliance number and its corresponded sets, minimal-global-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-powerful alliances, minimal-t-powerful alliance, minimal-t-powerful-alliance number and its corresponded sets, minimal-t-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-t-powerful alliances. The connections amid t-powerful-alliances are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications and closing remarks. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global powerful alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set and reversely for non-members of set with less members in the way that the set is simultaneously t-offensive and(t-2)-defensive. A set is global if t=0. It leads us to the notion of global powerful alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

New setting is introduced to study the global offensive alliance. Global offensive alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global offensive alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs containing complete, empty, path, cycle, star, and wheel are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is defined in new way. It’s first time to define this type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-offensive-alliance number and minimal-global-offensive-alliance-neutrosophic number. Two different types of sets namely global-offensive alliance and minimal-global-offensive alliance are defined. Global-offensive alliance identifies the sets in general vision but minimal-global-offensive alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-offensive-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-offensive alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs is studied in the way that, the family only contains same classes of neutrosophic graphs. Three types of family of neutrosophic graphs including m-family of neutrosophic stars with common neutrosophic vertex set, m-family of odd complete graphs with common neutrosophic vertex set, and m-family of odd complete graphs with common neutrosophic vertex set are studied. The results are about minimal-global-offensive alliance, minimal-global-offensive-alliance number and its corresponded sets, minimal-global-offensive-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-offensive alliances. The connection of global-offensive-alliances with dominating set and chromatic number are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, path, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global offensive alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set. It leads us to the notion of global offensive alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

Increased severity of droughts, due to anthropogenic activities and global warming has imposed a severe threat on agricultural productivity ever before. This has further advanced the need for some eco-friendly approaches to ensure global food security. In this regard, application of plant growth-promoting rhizobacteria (PGPR) can be beneficial. PGPR through various mechanisms viz. osmotic adjustments, increased antioxidant, phytohormone production, regulating stomatal conductivity, increased nutrient uptake, releasing Volatile organic compounds (VOCs), and Exo-polysaccharide (EPS) production, etc not only ensures the plant’s survival during drought but also augment its growth. This review, extensively discusses the various mechanisms of PGPR in drought stress tolerance. We have also summarized the recent molecular and omics-based approaches for elucidating the role of drought responsive genes. The manuscript presents an in-depth mechanistic approach to combat the drought stress and also deals with designing PGPR based bioinoculants. Lastly, we present a possible sequence of steps for increasing the success rate of bioinoculants.

School closures (SC) were adopted globally as a COVID-19 disease pandemic containment strategy. This extreme measure provoked a disruption of the educational system involving hundreds of million children worldwide. The return of children to school has been variable and is still an unresolved and contentious issue. Importantly the process has not been directly correlated to the severity of the pandemic s impact and has fueled the widening of disparities, disproportionately affecting the most vulnerable populations. Available evidence shows SC added little benefit to COVID-19 control whereas the harms related to SC severely affected children and adolescents. This unresolved issue has put children and young people at high risk of social, economic and health-related harm for years to come, triggering severe consequences during their lifespan. In this article we describe the process of SC and the reopening timetable across the globe. We highlight the data regarding the international state of educational systems around the world, putting emphasis on the rights of children to come back to school.

In this paper, we investigate the dynamics of following higher order difference equation x_{n+1}=A+B((x_{n})/(x_{n-m}²)) with A,B and initial conditions are positive numbers, and m∈{2,3,⋯}. Especially we study the boundedness, periodicity, semi-cycles, global asymptotically stability and rate of convergence of solutions of related higher order difference equations.

This theoretical paper continues a spectrum of research on sign character of narrative discourse on the background of modern post-classical theory of narrativity. It aims to uncover the relationships between the meaning of the narrative text and a sign signitication, assuming an intentional character of the narrative discourse governed by telic aspects (global semiotics). Global semiotic approach (Thomas Sebeok, 2001) views a narrative discourse as a self-organizing entity with purposeful (telic) character of all its constituent parts which turn a static text into a dynamic whole in the process of reading/perception/interpretation. The key notion for analysis of emergency is the term Umwelt (Jakob von Uexküll) to denote the perceptional world in which an organism (and a human) exists and acts as a subject. Therefore, Umwelt represents human’s perceptual boundary, which modifies the surrounding in accordance with the human’s subjective perspective. As Umwelt can be attributed to both biological and abiotic texts, meaning creation in the narrative discourse is compared to a semiotic study of comparative Umwelten (Cobley, 2014) where narrative is defined as a modeling device for the world creation through embodied subjectivity. It has been confirmed, that stressing on the subjective sphere of information eхchange and processing from the position of global semiotics necessitates introduction of basic principles of biosemiotics (i.e. semiotic scaffolding etc.) and teleology (i.e. cause, purpose, result) to analysis of narrative discourse and it constitutes the perspectives for further research in this domain.

The ongoing COVID-19 pandemic is shaking the foundations of public health governance all over the world. Researchers are challenged by informing and supporting authorities on acquired knowledge and practical implications. This commentary applies established theories of risk perception research to COVID-19 and reflects on the role of risk perceptions in these unprecedented times. Moreover, it calls for utilizing the knowledge on risk perception to improve health risk communication, build trust and contribute to a collaborating governance.

We used the Bootstrap ARDL method to test the relationship between the export trades, FDI and CO₂ emissions of the BRICS countries. We found that China's foreign direct investment and the lag one period of CO₂ emissions have a cointegration on exports. South Africa's foreign direct investment and CO₂ emissions have a cointegration relationship with the lag one period of exports, and South Africa's the lag one period of exports and foreign direct investment have a cointegration relationship with the lag one period of CO₂ emissions. But whether it is China or South Africa, these three variables have no causal relationship in the long-term. Among the variables of other BRICS countries, Russia is the only country showed degenerate case #1 in McNown et al. mentioned in their paper. When we examined short-term causality, we found that CO₂ emissions and export trade showed a reverse causal relationship, while FDI and carbon emissions were not so obvious. Export trade has a positive causal relationship with FDI. Those variables are different from different situations and different countries.

Earth atmosphere is almost opaque in the infrared: about 374 W/m² is absorbed by the atmosphere out of 396 W/m² surface upward longwave radiation, and only about 22 W/m² leaves the system unabsorbed in the atmospheric window. This makes rise to the idea to approximate the annual global mean energy flow system from a simple idealized greenhouse model, where the surface is surrounded by a single-layer shortwave (SW) transparent, longwave (LW) opaque, non-turbulent atmosphere. The energy flows in this geometry can be described by elementary arithmetic relationships. Starting from this model, the realistic Earth’s atmosphere can be achieved by introducing partial atmospheric SW opacity, partial atmospheric LW transparency and turbulent fluxes during the course of the deduction. The resulted global mean energy flow system is then compared to several data sets such as satellite observations from the CERES mission; estimates using direct surface observations and climate models; global energy and water cycle assessments; and independent detailed clear-sky radiative transfer computations. We find that the deduction from this idealized model approximates the real values in Earth energy budget with reasonable accuracy: the deduced fluxes and the observed ones are consistent within the acknowledged error of observations; while fundamental features of the initial geometry like special ratios and definite relationships between the fluxes are preserved.

Climate change is predicted to alter the geographic distribution of a wide variety of taxa, including butterfly species. Research has focused primarily on high latitude species in North America, with no known studies examining responses of taxa in the southeastern US. The Diana fritillary (Speyeria diana) has experienced a recent range retraction in that region, disappearing from lowland sites and now persisting in two, phylogenetically disjunct mountainous regions. These findings are consistent with the predicted effects of a warming climate on numerous taxa, including other butterfly species in North America and Europe. We used ecological niche modeling to predict future changes to the distribution of S. diana under several climate models. To evaluate how climate change might influence the geographic distribution of this butterfly, we developed ecological niche models using Maxent. We used two global circulation models, CCSM and MIROC, under low and high emissions scenarios to predict the future distribution of S. diana. Models were evaluated using the Receiver Operating Characteristics Area Under Curve test and the True Skill Statistics (mean AUC = 0.91± 0.0028 SE, TSS = 0.87 ± 0.0032 SE for RCP = 4.5, and mean AUC = 0.87± 0.0031SE, TSS = 0.84 ± 0.0032 SE for RCP = 8.5), which both indicate that the models we produced were significantly better than random (0.5). The four modeled climate scenarios resulted in an average loss of 91% of suitable habitat for S. diana by 2050. Populations in the Southern Appalachian Mountains were predicted to suffer the most severe fragmentation and reduction in suitable habitat, threatening an important source of genetic diversity for the species. The geographic and genetic isolation of populations in the west suggest that those populations are equally as vulnerable to decline in the future, warranting ongoing conservation of those populations as well. Our results suggest that the Diana fritillary is under threat of decline by 2050 across its entire distribution from climate change, and is likely to be negatively affected by other human-induced factors as well.

Environmental lead exposure is a population health concern in many low- and middle-income countries. Lead is found throughout Myanmar and prior to the 1940s, the country was the largest producer of lead worldwide. The aim of this study was to examine any potential association between lead mining and adult literacy rates at the level of the 330 townships in Myanmar. Townships were identified as lead or non-lead mining areas and 2015 census data were examined with association being identified using descriptive, analytical and spatial statistical methods. Overall, there does appear to be a significant relationship between lead mining activity and adult literacy levels (P<0.05) among townships with both low access [OR= 2.701 (1.136-6.421)] as well as townships with high access to safe sanitation [OR=18.40 (1.794-188.745)]. LISA cluster maps confirm these findings. This exploratory analysis is a first step in the examination of potential environmental lead exposure and its implications in Myanmar.

In Ghana, about 73% of households rely on solid fuels for cooking. Over 13,000 annual deaths are attributed to exposure to indoor air pollution from inefficient combustion. In this study, assessment of thermal efficiency, emissions and total global warming impact of three cookstoves commonly used in Ghana was completed using IWA water boiling test (WBT) protocol. Statistical averages of three replicate tests for each cookstove were computed. Thermal efficiency results were: wood-burning cookstove 12.2% (Tier 0), traditional charcoal cookstove 23.3% (Tier 1-2) and improved charcoal cookstove 30% (Tier 2-3). The wood-burning cookstove emitted more CO, CO2 and PM2.5 than charcoal cookstove (coalpot) and improved cookstove. Emission factor for PM2.5 and emission rate for the wood-burning cookstove (Tier 0) were over four times higher than the traditional charcoal cookstove (Tier 3) and improved cookstove (Tier 2). On the basis of WBT, annual global warming impact potential for emissions are estimated at 4 tonnes of CO2e for the wood-burning cookstove, 1.5 tonnes of CO2e for charcoal cookstove (coalpot) and 1 tonne of CO2e for improved cookstove. We conclude that there is the need for awareness, policy and incentives to enable end-users switch to improved cookstoves for increased efficiency, reduced emissions/global warming impact.

Post-training quantization is pivotal in deploying convolutional neural networks for mobile applications. Block-wise reconstruction with adaptive rounding, as employed in prior works like BrecQ and Qdrop, facilitates acceptable 4-bit quantization accuracy. However, adaptive rounding is time-intensive, and its constraint on weight optimization space curtails the potential for quantization performance. The optimality of block-wise reconstruction hinges on the quantization status of subsequent network blocks. In this investigation, we delve into the theoretical underpinnings of the limitations inherent in adaptive rounding and block-wise reconstruction. Our exploration leads to the development of a post-training quantization methodology, designated as AE-Qdrop. This algorithm operates in two distinct phases: block-wise reconstruction and global fine-tuning. The block-wise reconstruction phase introduces a progressive optimization strategy, superseding adaptive rounding, which not only augments quantization precision but also significantly improves quantization efficiency. To mitigate the risk of overfitting, we introduce a random weighted quantized activation mechanism. During the global fine-tuning phase, we account for interdependencies among quantized network blocks. The weight of each network block will be corrected with logit matching and feature matching. Extensive experiments validate that AE-Qdrop achieves high-precision and efficient quantization. For instance, in the case of 2-bit MobileNetV2, AE-Qdrop outperforms Qdrop by achieving a 6.26% enhancement in quantization accuracy and quintupling the quantization efficiency.

Global public health systems have continuously faced challenges from the advent of novel infectious illnesses, necessitating quick and efficient actions to stop their spread.First discovered in Saudi Arabia in 2012, Middle East respiratory syndrome (MERS) is a viral respiratory disorder caused by the Middle East respiratory syndrome coronavirus (MERS-CoV). Since then, the nation has reported most cases and fatalities related to this sickness, with occasional outbreaks happening in other nations and regions. Severe sickness and high mortality are caused by MERS-CoV, especially in older persons and those with underlying chronic conditions. Through intimate contact, the virus can spread from people to dromedary camels and vice versa. It has sparked multiple epidemics both domestically and abroad in the Middle East, raising the possibility of fatalities and widespread transmission, especially in susceptible groups. The Riyadh region was the main target of the most current MERS-CoV outbreak in Saudi Arabia, which began in 2023 and ended on September 1, 2023, with 312 confirmed cases and ninety-seven fatalities. With the use of published studies and their contributions to the field, we hope to present a thorough overview of the MERS-CoV outbreak in Saudi Arabia in this review of the literature, including its epidemiological investigation, public health response, impact, and lessons learned. In addition to highlighting the importance and continued relevance of this problem, our work suggests ways to lower the risk of MERS-CoV transmission and avert further outbreaks.

Artificial Intelligence (AI) emerges as a powerful catalyst poised to reshape the global sustaina-bility landscape by facilitating the attainment of Sustainable Development Goals (SDGs). This comprehensive Delphi study meticulously probes the insights of domain experts, shedding light on the strategic utilization of AI to advance these critical sustainability objectives. Employing rigorous statistical techniques, encompassing measures of central tendency and interquartile de-viation, this research scrutinizes consensus dynamics among experts and elucidates potential variations in their viewpoints. The findings resoundingly convey experts' collective positive perspective regarding AI's pivotal role in propelling the SDGs forward. Through two iterative rounds of extensive discussions, a compelling consensus crystallizes—AI indeed exerts an overall positive impact, exemplified by a robust mean score of 78.8%. Intriguingly, distinct SDGs manifest varied propensities toward AI intervention, with Goals 6, 7, 8, 9, 11, 13, 14 and 15 basking in the radiance of highly positive impacts. Goals 1, 2, 3, 4, 5, 10 and 12 exhibit positive impact scores, indicating a juncture ripe for positive advancements. Meanwhile, Goal 16 and Goal 17 languish with neutral scores, signifying a juncture demanding nuanced deliberations about AI's impact on peace, justice, and strong institutions as well as on partnerships for the goals respectively. This paper underscores AI as a formidable instrument poised to address humanity's most pressing challenges while harmonizing seamlessly with the overarching SDG objectives. It gracefully dovetails into established practices across pivotal domains such as health, education, and resilient infrastructures, amplifying the collective global endeavor to navigate the path toward a more sustainable future.

In recent years, there has been significant growth in the ubiquity and popularity of three dimensional(3D) point clouds, with an increasing focus on the classification of 3D point clouds. To extract richer features from point clouds, many researchers have turned their attention to various point set regions and channels within irregular point clouds. However, this approach has limited capability in attending to crucial regions of interest in 3D point clouds and may overlook valuable information from neighboring features during feature aggregation. Therefore, this paper proposes a novel 3D point cloud classification method based on global attention and adaptive graph convolution. The method consists of two main branches: the first branch com-putes attention masks for each point, while the second branch employs adaptive graph convolu-tion to extract global features from the point set. It dynamically learns features based on point interactions, generating adaptive kernels to effectively and precisely capture diverse relationships among points from different semantic parts. Experimental results demonstrate that the proposed model achieves 93.8% in overall accuracy and 90.8% in average accuracy on the ModeNet40 dataset.

Dietary guidance to recommend food patterns to deliver nutrients has been well accepted for the past century. Foods to deliver essential nutrients and energy are needed across the life cycle and are dependent upon local industries and accepted cultural practices to deliver essential nutrients to prevent nutrient deficiency diseases. Since the 1980s, dietary guidelines to prevent chronic diseases have relied on epidemiological research to predict what dietary patterns are linked to reduced risk of chronic disease or links to health outcomes. Dietary guidelines have been broad, typically recommending avoiding “too much sugar”, “too much saturated fat”, and “too much sodium”. Efforts to fine tune these recommendations have met with limited scientific data to support more specific recommendations across the life cycle. Consumers have become skeptical of dietary guidelines as media coverage of new studies is often in conflict with accepted nutrition dogma. We discuss whether we really have a science-based databank to support dietary guidelines, based on a scientific session at the 10th International Conference on Nutrition and Growth.

This paper describes the optimal design of a miniature fiber-optic linear displacement sensor. It is characterized by its ability to measure displacements along a millimetric range with sub-micrometric resolution. The sensor consists of a triangular reflective grating and two fiber-optic probes. The measurement principle of the sensor is presented. The design of the sensor's triangular grating has been geometrically optimized by considering the step angle of the grating to enhance the sensor's resolution. The optimization method revealed a global optimum at which the highest resolution is obtained

Efficient energy extraction in photovoltaic (PV) systems relies on the effective implementation of Maximum Power Point Tracking (MPPT) methods. Conventional MPPT techniques often suffer from slow convergence speeds and suboptimal tracking performance, particularly under dynamic variation of environmental conditions. Smart optimization algorithms (SOA) using metaheuristic optimization algorithms can avoid this limitation inherent in the conventional MPPT methods. The problem of slow convergence of the SOA is avoided in this paper using a novel strategy called Swarm Size Reduction (SSR) utilized with Particle Swarm Optimization (PSO) algorithm, specifically designed to achieve short convergence time (CT) while maintaining exceptional tracking accuracy. The novelty of the proposed MPPT method introduced in this paper is the dynamic reduction of the swarm size of the PSO for improved performance of the MPPT of the PV systems. This adaptive reduction approach allows the algorithm to efficiently explore the solution space of PV systems and rapidly exploit to identify the global maximum power point (GMPP) even under fast fluctuation of uneven solar irradiance and temperature. This pioneering ultra-fast MPPT method represents a significant advancement in PV system efficiency and promotes the wider adoption of solar energy as a reliable and sustainable power source. The novel adaptive PSO algorithm also opens new possibilities for further innovations in optimization-driven applications, extending its potential impact on a diverse range of real-world challenges. The results obtained from this proposed strategy are compared with several optimization algorithms to validate its superiority.

Daniel Yergin’s “The New Map: Energy, Climate, and the Clash of Nations” is a remarkable and groundbreaking work that addresses the ever-changing global energy landscape and its profound geopolitical implications. In this modest book review, we aim to offer a fresh perspective by re-examining the core issues from the standpoint of political geography. The aim of this article is twofold: to enrich the existing literature on political geography and to provide valuable insights to students of geography to broaden their knowledge in this field.

In an increasingly interconnected world, the internationalization of languages plays a pivotal role in shaping global linguistic landscapes. This qualitative study delves into the intriguing realm of Cebuano, a language with a rich cultural heritage and a vibrant community of speakers. Through a meticulous exploration of language variation, adaptation, and policy dynamics, the researcher unravels the complex interplay between Cebuano and the global linguistic tapestry. Drawing upon a comprehensive literature review and qualitative research, including in-depth interviews and focus group discussions, this paper illuminates the nuanced manifestations of Cebuano beyond its traditional borders and sheds light on its presence in diverse international settings. The findings reveal the intricate dance of language and identity, offering insights into the processes of language maintenance, shift, and revitalization. As the researcher navigates the multifaceted dimensions of Cebuano's internationalization, not only is its global significance unraveled, but also the intricate connections between language, culture, and human experience are investigated. This study not only contributes to the scholarly discourse on language dynamics but also raises compelling questions about the preservation of linguistic diversity, the power of language in shaping identities, and the role of language in fostering intercultural understanding. By embracing the kaleidoscope of Cebuano's global journey, this paper invites readers to contemplate the broader implications for language diversity, communication, and cultural preservation in an increasingly interconnected world.

Mass mortality events and anthropogenic impacts were increasingly documented affecting Paramuricea clavata (Risso, 1826) during the last decades. These impacts enhance the settling of epibiontic organisms on the injured colonies. The epibiosis was studied by photographic sampling carried out on the granitic outcrops of the Tavolara Channel within the Tavolara-Punta Coda Cavallo Marine Protected Area (NE Sardinia) between 2017-2023 at 35-55 m. The number of colonies and percent surface involved in epibiosis, the specific richness of the epibiontic community and the temporal evolution of the phenomenon were investigated. Almost all the investigated gorgonians (93%) showed parts involved in epibiosis, with a high percentage of covering (one-third of the surface). Out of the 37 epibiontic species recorded, the most recurrent described an ecological succession dominated by hydrozoans, sponges, bryozoans, serpulids and the parasitic soft coral Alcyomiun coralloides. Nevertheless, single colonies studied through time revealed the unpredictability of the colonization process. The peculiar habitat of a high naturalistic value of the granitic outcrops hosting the P. clavata forests demonstrates a widespread suffering condition, supported both by environmental and anthropogenic sources of stress. Such considerations make it necessary to review the current zonation of the area, where the actual vulnerability and usability evaluations are based on obsolete information.

The global warming our generation is experiencing is just one of the great environmental crises of the Anthropocene, a geological period that began with the use of fossil fuels and that, in merely one century and a few decades of industrial activity, has altered ecosystemic processes that sustain human health and well-being. Beyond the loss of the “intrinsic value of nature”, changes in the magnitude and direction of biogeochemical cycles and increases in temperature are phenomena that not only accompany the loss of habitats and species but impair resilience by ultimately generating greater and more complex numbers and types of exposures that constitute a danger to human health. In this study, we attempted to offer some notes about the margin, understood as that space with the greatest inequity and therefore the fastest growth of risk: the collision area where deprivation marks the social determinants of health and where the greatest interaction with causes of disease occur.

Patients' functional adaptation to pain can affect global sagittal alignment. This study evaluated the short-term spinal sagittal alignment change after Transforaminal Epidural Steroid Injection (TFESI) in lumbar spinal stenosis patients. Patients with lumbar spinal stenosis who underwent TFESI were retrospectively examined. Clinical outcomes were Visual Analog Scale (VAS) and Oswestry Disability Index (ODI). Before and two weeks after the intervention, whole spine lateral standing view radiographs were taken. Radiographic parameters, e.g., Sagittal Vertical Axis (SVA), C2C7 Cobb, Thoracic Kyphosis (TK), Lumbar Lordosis (LL), Pelvic Incidence (PI), Pelvic Tilt (PT), Sacral Slope (SS), and Lumbopelvic Mismatch (PI-LL), were measured. Ninety-nine patients (mean age 64.3 ± 9.2 years) were included in this study. Both VAS and ODI outcomes were statistically improved after two weeks of intervention. Radiographic parameters showed that SVA, PT, and PI-LL mismatch were significantly decreased, while C2C7 Cobb, TK, SS, and LL were significantly increased after the intervention. SVA was improved by 29.81% (52.76 ± 52.22 mm to 37.03 ± 41.07 mm, P &lt; 0.001). PT was also decreased significantly from 28.71° ± 10.22° to 23.84° ± 9.96° (P &lt; 0.001). Transforaminal Epidural Steroid Injection (TFESI) significantly improves VAS, ODI, and global sagittal parameters in lumbar spinal stenosis patients.

The rapid growth of Earth's global geospatial data necessitates an efficient system for organizing the data, facilitating data fusion from diverse sources, and promoting interoperability. Mapping the spheroidal surface of the planet presents significant challenges, as it involves balancing distortion and splitting the surface into multiple partitions. The distortion decreases as the number of partitions increases, but at the same time the complexity of data processing increases, since each partition represents a separate data set and is defined in its own local coordinate system. In this paper, we propose the dual orthogonal equidistant cylindrical projection method to mitigate distortion and reduce the number of partitions. Additionally, we use the rotation of projection cylinders to effectively minimize average angular and areal distortions of the Earth’s landmass and reduce the interruption of continental plates caused by partition edges. By incorporating auxiliary latitudes and proposing an approximate authalic latitude, we further enhance the mapping of the ellipsoid onto the sphere, simplifying calculations. Experimental results demonstrate a substantial reduction in distortion and interruption of continental plates. With only two partitions, an average landmass angular distortion of less than 3.56 degrees and an average normalized surface distortion of less than 1.07 were achieved.

This study examines the Health Silk Road (HSR) as a critical component of China's Belt and Road Initiative (BRI) and its implications for global health and international relations. The HSR aims to enhance public health and foster international cooperation in the healthcare sector, with objectives including strengthening healthcare infrastructure, expanding China's global health leadership, and enhancing international health cooperation. Through an in-depth analysis of the China-Pakistan collaboration on healthcare under the China-Pakistan Economic Corridor (CPEC) as a case study, this research explores the motives, implications, and potential concerns associated with the HSR. This research posits that the HSR has a mix of positive and negative implications, making it challenging to categorize the initiative as simply good or bad. While the HSR contributes to improved healthcare services, infrastructure, and capacity-building in participating countries, it also raises concerns about debt sustainability, transparency, and China's geopolitical influence. This research contributes to a nuanced understanding of the HSR's multifaceted impacts and underscores the importance of open dialogue, cooperation, and the sharing of best practices among stakeholders in order to maximize the initiative's benefits and minimize potential negative consequences. By assessing the motives, implications, and concerns of the HSR, this study offers valuable insights for policymakers, global health practitioners, and scholars, highlighting the significance of international collaboration in addressing shared health challenges and promoting sustainable development.

Water resource management and flood forecasting are crucial societal and financial stakes requiring reliable predictions of flow parameters (depth, velocity), the accuracy of which is often limited by uncertainties in hydrodynamic numerical models. In this study, we assess the effect of two uncertainty sources, namely breach characteristics induced by overtopping and the roughness coefficient, on water elevations and inundation extent. A two-dimensional (2D) hydraulic solver was applied in a Monte Carlo integration framework to a reach of the Loire river (France) including about 300 physical parameters. Inundation hazard maps for different flood scenarios allowed highlighting the impact of the breach development chronology. A special attention was paid to proposing a relevant sensitivity analysis to exam the factors influencing the depth and extent of flooding. The spatial analysis of vulnerability area induced by a levee breach width exhibits that, with increasing the flood discharge, the rise of the parameter influence is accompanied by a more localized spatial effect. This argues for a local analysis to allow a clear understanding of the flood hazard. The physical interpretation, highlighted by a global sensitivity analysis, showed precisely the dependence of the flood simulation on the main factors studied, i.e. the roughness coefficients and the characteristics of the breaches.

Background: Chronic kidney disease, one of the most common diseases in the world, is characterized by irreversible impairment of the kidney’s metabolic, excretory, and endocrine functions. During end-stage renal disease, patients require renal replacement therapy, such as hemodialysis (HD). Protein-energy wasting is a common health problem among HD patients. However, this study aims to assess the nutritional status of HD patients at two HD centers in Jeddah, Saudi Arabia, and to determine its associated factors. Methods: A cross-sectional study was conducted at two different Dialysis Centers in Jeddah, Saudi Arabia; 211 female and male HD patients. Malnutrition was recognized using the Modified-SGA (M-SGA) comprising two parts: medical history and physical examination. Sociodemographic and health status for all patients were also determined. Patients were classified based on their M-SGA score into two groups: normal and malnourished. Results: Overall, 54.5% of the participants showed malnutrition. Unemployment, low muscle strength and mass, high level of medication use, and high dialysis vintage were positively (P&lt;0.05) associated with malnutrition. Conclusion: The M-SGA score indicates a high prevalence of malnutrition among HD patients. These results show the importance of regular assessment and follow-ups for HD patients ensuring better health and nutritional status.

In dry season paddy farming, the alternate wetting and drying (AWD) irrigation improves water productivity, paddy production, and has the potential to decrease greenhouse gas (GHG) such as methane (CH4) and nitrous oxide (N2O) emissions when compared to continuous flooding (CF). However, there is a lack of research in Bangladesh on the effects of water management on CH4 and N2O emissions. During November 2017–April 2018, participatory on-farm trials were conducted at Feni and Chattogram districts of Bangladesh. Total 105 farmers comprising 20-hectare of land (62 farmers at Feni and 43 farmers at Chattogram district, each location having 10 hectare of land). We compared irrigation water and cost reductions, paddy yield, and CH4 and N2O emissions from paddy fields irrigated using AWD and CF irrigation methods. The CH4 and N2O emissions were determined using the Cool Farm Beta-3 methodology, and the global warming potential (GWP) was estimated using the Intergovernmental Panel on Climate Change-2014 standard approach. The mean results of randomly selected 30 farmers from two locations (15 of each) showed that AWD remarkably decreased irrigation water consumption by about 24% and increased water productivity by 224%. We estimated 23% savings for irrigation costs in AWD. By this time, AWD improved paddy production by 3% over CF. The AWD irrigation resulted in a 47% reduction in cumulative CH4 emissions having a lower CH4 emission factor (0.74 kg ha-1 day-1) than CF (1.39 kg ha-1 day-1). There was no obvious difference in N2O emission between AWD and CF. When compared to CF, AWD decreased the overall GWP by 27% and lowered the GHG intensity by 42%. The CH4 and N2O emissions did not differ substantially between Feni and Chattogram.

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants. However, the lack of global surface concentration of HCHO monitoring is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or data- demanding for a global scale of research. To alleviate this issue, we adopted neural networks to estimate surface HCHO concentration with confidence intervals in 2019, where HCHO vertical column density data from TROPOMI, in-situ data from HAPs (harmful air pollutants) monitoring network and ATom mission are utilized. Our result shows that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentration in Amazon Basin, Northern China, South-east Asia, Bay of Bengal, Central and Western Africa are among the highest. The results from our study provides a first dataset of the global surface HCHO concentration. In addition, the derived confidence interval of surface HCHO concentration adds an extra layer for the confidence to our results. As a pioneer work in adopting confidence interval estimation into AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper will pave the way for the rigorous study on global ambient HCHO health risk and economic loss, thus providing a basis for pollutant controlling policies worldwide.

Background: global longitudinal strain (GLS) measures myocardial deformation and is a sensitive modality for detecting subclinical myocardial dysfunction and predicting cardiac outcomes. The accuracy of speckle-tracking echocardiography (STE) is dependent on temporal resolution. A novel software enables relatively high frame rate (Hi-FR) (~200 fps) echocardiographic images acquisition which empowers us to investigate the impact of Hi-FR imaging on GLS analysis. The goal of this pilot study was to demonstrate the feasibility of Hi-FR for STE. Methods: In this prospective study, we acquired echocardiographic images using clinical scanners on patients with normal left ventricular systolic function using Hi-FR and conventional frame rate (Reg-FR) (~50 FPS). GLS values were evaluated on apical 4-, 2- and 3-chamber images acquired in both Hi-FR and Reg-FR. Inter-observer and intra-observer variabilities were assessed in Hi-FR and Reg-FR. Results: There were 143 resting echocardiograms with normal LVEF included in this study. The frame rate of Hi-FR was 190 ± 25 and Reg-FR was 50 ± 3, and the heart rate was 71 ± 13. Strain values measured in Hi-FR were significantly higher than those measured in Reg-FR (all p < 0.001). Inter-observer and intra-observer correlations were strong in both Hi-FR and Reg-FR. Conclusions: We demonstrated that strain values were significantly higher using Hi-FR when compared with Reg-FR in patients with normal LVEF. It is plausible that higher temporal resolution enabled the measurement of myocardial strain at desired time point. The result of this study may inform clinical adoption of the novel technology. Further investigations are necessary to evaluate the value of Hi-FR to assess myocardial strain in stress echocardiography in the setting of tachycardia.

This study investigates the impact of global financial crisis and the present COVID-19 pandemic on daily and weekly Crude oil futures using four variants of ARMA-GARCH models: ARMA-sGARCH, ARMA-eGARCH, ARMA-TGARCH and ARMA- aPARCH with dummy variables We also investigated the persistence, half-life and backtesting of the models. This study therefore seeks to contribute to the body of literature on the impact of global financial crisis and the present COVID-19 pandemic on crude oil futures market. This investigation of the impact of global financial crisis and the COVID-19 on crude oil futures has not been much studied at present. We obtained and analyzed the daily and weekly crude oil futures from secondary sources. Daily crude oil futures used in this study covers the period from the 4th January 2000 to 27th April 2020 while the weekly crude oil futures covered from 2ndJanuary 2000 to 26th April 2020 . The global financial crisis period covered from 2nd July 2007 to 31st March 2009 and the current COVID-19 pandemic covered from 1st January 2020 to 27th April, 2020. The study used both student t and skewed student t innovations with AIC, goodness-of-test fit and backtesting to select the best model. Most of the estimated ARMA-GARCH models are supported by skewed student t distribution while most of the ARMA-GARCH models exhibited high persistence values in the presence of global financial crisis and the COVID-19 pandemic. In the overall, the estimated ARMA(1,0)-eGARCH(2,1) and ARMA(1,0)-eGARCH(2,2) model for daily crude oil futures and weekly crude oil futures respectively have been significantly impacted by the global financial crisis and the Present COVID-19 pandemic while the preferred estimated models also passed the goodness-of-test fit and backtesting.This study recommends shareholders and investors should think outside the box as crude oil futures tend to be affected by global financial crisis and COVID-19 pandemic while countries also that depend mostly on crude oil are encouraged to diversify their economy in other to survive and be sustained during financial and health crisis.

The threats of climate change and the sustainable supply of clean energy are global challenges that require an international approach to the energy supply. Utilizing the wind and solar energy potential of regions where these renewable sources are especially viable to produce hydrogen by means of water electrolysis represents an attractive option to counter the above-mentioned challenges. Within the scope of this techno economic analysis of a worldwide hydrogen supply infrastructure based on renewable energy, selected regions are assessed on the basis of their wind or solar energy potential. In contrast to established analyses of hydrogen infrastructures, this paper introduces a worldwide allocation approach to the supply hydrogen from strong wind and solar regions to different demand regions on the premise of a global supply cost minimum. The allocation results show a significant dependence of hydrogen export volumes and the oversea transport distances of potential trading partners. Hence, the transnational trading flows of hydrogen derived from wind and solar energy are concentrated in continental regions.

Recently, both global and domestic environmental events have been occurring more frequently, bringing catastrophic consequences to humans and the environment. These adverse events have caused widespread concern among the general public. In positive terms, these devastating events could potentially enhance people’s environmental awareness, which, in turn, could instill a greater sense of environmental responsibility. This study aims to investigate how university students concern themselves with global and domestic catastrophic environmental events and to examine how global and domestic environmental concerns mediate the effect of environmental knowledge and attitudes on university students’ environmental responsibility. Students of King Mongkut’s University of Technology Thonburi in Bangkok, Thailand were selected as the participants. A simple random technique was applied to select the research participants. Questionnaire surveys with 863 students were carried out during September–October 2019. A path analysis was performed to test how global and local environmental concerns mediate the effect of environmental knowledge and attitudes on university students’ environmental responsibility. The results demonstrated that domestic environmental concerns, taken alone, contributed less to the students’ sense of environmental responsibility. Domestic environmental concerns had a stronger effect on environmental responsibility when taken together with global environmental concerns. In addition, both domestic and global environmental concerns could help transform environmental knowledge and attitudes into environmental responsibility. Only environmental attitudes had no direct effect on responsibility. These results show that domestic and global catastrophic environmental events could raise students’ levels of concern for the environment, and, ultimately, enhance their sense of responsibility to protect the environment.

Taking capital, manpower, and natural resources as inputs, regional GDP as expected output, and industrial pollution as undesired output, this study measures the ecological efficiency of various regions in China through the Global-Malmquist model. The results show a trend of an initial sharp decline in ecological efficiency followed by a gradual increase in the time dimension, but there is no significant correlation in the spatial dimension. Using the gravity model to quantify the attractiveness of the regions’ capital and human resources for collaborative innovation, it estimates the impact of collaborative innovation on eco-efficiency through the system-Generalized Method of Moments (GMM) model. The results show that technological innovation capital in other regions has a negative “U” relationship with local ecological efficiency, while scientific and technological innovation human resources have a positive “U” relationship. In addition, government financial support in science and technology and the ecological efficiency of the previous period serve as promoting factors of the current local ecological efficiency, while the introduction of foreign technological innovation is likely to inhibit improvements in ecological efficiency. Based on these findings, this study puts forward corresponding policy recommendations for local governments to advance their development agendas alongside their environmental priorities in line with their specific circumstances.

In this study, we investigate the form of solutions, stability character and asymptotic behavior of the following four rational difference equations x_{n+1} = (1/(x_{n}(x_{n-1}±1)±1)), x_{n+1} = ((-1)/(x_{n}(x_{n-1}±1)∓1)), such that their solutions are associated with Tribonacci numbers.

The active debate about the processes governing the organic-rich sediment deposition generally involves the relative roles of elevated primary productivity and enhanced preservation related to anoxia. However, other less spotlighted factors could have a strong impact on such deposits: e.g. residence time into the water column (bathymetry), sedimentation rate, transport behavior of organo-mineral floccules on the sea floor. They are all strongly interrelated and may be obscured in the current conceptual models inspired from most representative modern analogues (i.e. upwelling zones and stratified basins). To improve our comprehension of organic matter distribution and heterogeneities, we conducted a sensitivity analysis on the processes involved in organic matter production and preservation which have been simulated within a 3D stratigraphic forward model. The Lower-Middle Toarcian of the Paris Basin was chosen as a case study as it represents one of the best documented example of marine organic matter accumulation. The relative influence of the critical parameters (bathymetry, diffusive transport, oxygen mixing rate and primary production) on the output parameters (Total Organic Carbon, and oxygen level), determined performing a Global Sensitivity Analysis, shows that, in the context of a shallow epicontinental basin, a moderate primary productivity (> 175 gC.m^-².yr^-1) can led to local anoxia and organic matter accumulation. We argue that, regarding all the processes involved, the presence and distribution of organic-rich intervals is linked as a first-order parameter to the morphology of the basin (e.g. ramp slope, bottom topography). These interpretations are supported by very specific ranges of critical parameters which allowed to obtain output parameter values in accordance with the data. This quantitative approach and its conclusions open new perspectives about the understanding of global distribution and preservation of organic-rich sediments.

Reliable and robust control of power converters is a key issue in the performance of numerous technological devices. In this paper we show a design technique for the control of a DC-DC buck converter with a switching technique that guarantees not only good performance but also global stability. We show that making use of the contraction theorem in the Jordan canonical form of the buck converter, it is possible to find a switching surface that guarantees stability but it is incapable of rejecting load perturbations. To overcome this, we expand the system to include the dynamics of the voltage error and we demonstrate that the same design procedure is not only able to stabilize the system to the desired operation point but also to reject load, input voltage and reference voltage perturbations.

This article draws on empirical research seeking to develop more nuanced understandings of child prostitution, previously theorised on the basis of children’s rights, feminist, and structure/agency debates, largely ignoring children’s own understandings of their involvement in prostitution. Conducted in Malawi, one of the economically poorest countries in the world, the study goes to the heart of questions of inequality and child protection. With careful attention to ethical considerations, a participatory approach was used to enable 19 girls and young women, whose involvement in prostitution began in childhood, to convey their own experiences and understandings of involvement. Data were collected using a range of methods, chosen by participants to match their abilities and interests. Data analysis and interpretation were aided by reference to the capability approach focussing on questions of human rights and social justice for women and girls. Generating rare insights into participants’ worlds, the research demonstrates how the persistence of deeply embedded cultural values in contexts of extreme poverty serves to sustain gender inequalities, constraining choices for girls and denying them opportunities to lead valued lives. The article ends by considering the theoretical and methodological implications of the study, policy and practice recommendations and opportunities for further research.

A temperate deep lake, Lake Kuttara, Hokkaido, Japan (148 m deep at maximum) was completely frozen every winter in the 20th century. However, unfrozen conditions of the lake over winter occurred four times in the 21st century, which is probably due to global warming. In order to understand how thermal regime of the lake responds to climate change, its heat storage change was calculated by estimating heat budget of the lake and monitoring water temperature at the deepest point for September 2012–June 2016. As a result, temporal change of the heat storage from the heat budget was very consistent with that from the direct temperature measurement (determination coefficient R² = 0.827). The 1978–2017 data at a meteorological station near Kuttara indicated that there are significant (less than 5% level) long-term trends for air temperature (0.024 °C/yr) and wind speed (−0.010 m/s/yr). A sensitivity analysis for the heat storage from the heat budget estimate and an estimate of return periods for mean air temperature in mid-winter allow us to conclude that the lake could be unfrozen once per about two year in a decade.

The features of a class of cubic curves with a shape factor are analyzed by means of the theory of envelope and topological mapping. The effects of the shape factor on the cubic curves are made clear. Necessary and sufficient conditions are derived for the curve to have one or two inflection points, a loop or a cusp, or to be locally or globally convex. Those conditions are completely characterized by the relative position of the edge vectors of the control polygon and the shape factor. The results are summarized in a shape diagram, which is useful when the cubic parametric curves are used for geometric modeling. Furthermore we discussed the influences of the shape factor on the shape diagram and the ability for adjusting the shape of the curve.

Abstract: Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urban interface. Herein, we propose a framework that jointly uses remote sensing derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach for two U.S. study sites against historical settlement extents derived from the Historical Settlement Data Compilation for the US, HISDAC-US, achieving Area-under-the-Curve values >0.9. Our results are largely in agreement with model-based urban areas from the HYDE database, and demonstrate that the integration of remote sensing derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization, and long-term land cover change in countries where historical maps are available.

Growing food autonomously on Mars is challenging due to the Martian soil's low nutrient content and high salinity. Understanding how plants adapt and evaluating their nutritional attributes are pivotal for sustained Mars missions. This research delved into the regeneration, stress tolerance, and dietary metrics of sweet potato (Ipomoea batatas) across different Mars Global Simulant (MGS-1) concentrations (0, 25, 50, and 75%). In our greenhouse experiment, 75% MGS-1 concentration most significantly inhibited sweet potato growth, storage root biomass, and chlorophyll content. This concentration also elevated plant tissues' H2O2, proline, and ascorbic acid levels. Higher MGS-1 exposures (50 and 75%) notably boosted vital amino acids and sugar groups in the plant's storage roots. Yet, increased MGS-1 concentrations notably diminished the total C: N ratio and elemental composition in both vines and storage roots. In summary, sweet potato exhibited optimal growth, antioxidant properties, yield, and nutrient profiles at 25% MGS-1 exposure, compared to higher concentrations. This study underscores the need for future interventions, like nutrient enhancement and controlled metal accessibility, to render it a suitable plant for space-based studies.

The Global Hunger Index (GHI) is a vital tool for assessing and understanding the state of hunger and food security across the world. In this review article, we examine the GHI scores of various countries in the years 2000, 2008, 2015, and 2023. We aim to explore the changes in GHI scores over this period, identify trends, and discuss the implications for global food security. The GHI provides a comprehensive snapshot of the world's progress in reducing hunger, and this analysis sheds light on the successes and challenges faced by different countries.

This scholarly investigation conducts a rigorous exploration of Bangladesh's textile sector spanning the years 2011 to 2022, centering its attention primarily on the development of an intricate econometric framework. The study unveils profound insights into the sector's growth trajectories, the intricate dynamics of global demand, the undulating fluctuations of interest rates, and other pivotal economic gauges. The core component of this research, the econometric model, adeptly prognosticates textile exports through the incorporation of multifarious variables, encompassing the count of garment establishments, the magnitude of the workforce, market penetration, worldwide demand patterns, currency exchange rates, and interest rate fluctuations. Notably, the model attains a lofty degree of explicative potency, with an R-squared coefficient approximating 0.756, thereby attesting to its remarkable capacity to elucidate variances in textile export values. These discoveries carry substantial consequences for policymakers and stakeholders within the industry, as they bestow upon them a potent instrument for judicious decision-making and strategic blueprinting within Bangladesh's textile domain. The model accentuates the paramount significance of global demand and market share, concurrently accentuating the latent repercussions posed by fluctuations in interest rates.This research provides valuable insights into promoting the industry's sustainable growth, diversification, and resilience in the face of economic challenges.

This research highlights the importance of error-correcting codes in ensuring secure and efficient data transmission over noisy channels. It discusses the application of Convolutional codes and the Viterbi algorithm for error detecting and correcting in applications where the data rate is high and the error probability is relatively low. This research extends beyond previous studies by conducting a comparative analysis of Convolutional codes, the Viterbi algorithm, and alternative coding methods utilized in satellite communication systems, by evaluating their effectiveness and efficiency relative to other coding approaches like BCH, LDPC, and turbo codes. The evaluation encompasses key performance metrics including error correction capabilities, computational complexity, and robustness against various error types. Additionally, practical implementation factors such as power consumption, computational requirements, and compatibility with existing hardware are considered. The analysis sheds light on the advantages and disadvantages of each coding method, offering insights into why convolutional codes and the Viterbi algorithm are particularly suitable for GPS systems.

(1) Background: The purpose of this study was to investigate the relationship between IMO and burnout while assessing the contribution of job demands and resources on increasing internal orientation and worker well-being and, consequently, the levels of perceived performance; (2) Methods: Data were collected between April and December 2021 by completing an online questionnaire, developed in the Google Forms platform. The following descriptive statistics were analyzed: measures of central tendency (mean), dispersion (standard deviation), minimum value and maximum value. Next, Pearson's correlation coefficient was calculated to analyze the relationship between the variables under study.; (3) Results: The results showed the mediating effect of IMO between performance feedback and perceived performance, while burnout mediates the relationship between emotional and technology demands and perceived performance. (4) Conclusions: These conclusions demonstrate that constructive feedback might help a more efficient performance through better internal communication and the positive effects of technology demands could be the result of the interaction between personal and organizational resources.

Coastal areas situated at lower elevations are becoming more vulnerable to flooding as a result of the accelerating global sea level rise. As the sea level rises, so does the groundwater. Barriers designed to shield against marine flooding do not provide protection against flooding caused by rising groundwater. Despite the increasing threat of groundwater flooding, there is limited knowledge about the relationship between sea level rise and groundwater fluctuations. This hinders the ability to adequately consider sea level rise induced groundwater flooding in adaptation initiatives. This study aims to investigate how local groundwater in Juelsminde, Denmark, responds to changes in sea level and to evaluate the predictability of these changes using a machine learning model. The influence of the sea on the shallow groundwater level has been investigated using six groundwater loggers located between 45 and 210 m from the coast. An initial manual analysis of the data revealed a systematic delay in the rise of water levels from the coast to inland areas, with a delay of approximately 15–17 hours per 50 m of distance. Subsequently, a support vector regression model was used to predict groundwater levels 24 hours into the future. This study shows how the groundwater level in Juelsminde is affected by sea level fluctuations. Results suggest a need for increased emphasis on this topic.

Measles is a highly contagious airborne disease that is endemic in many developing countries with low levels of vaccination coverage. In this paper, we propose a deterministic compartmental mathematical model for measles disease dynamics. We establish the global stability conditions for the disease-free and endemic equilibria using the Lyapunov function stability method. \textcolor{red}{Using arbitrary parameters it is obtained that the proposed model exhibits forward bifurcation}. Numerical integration using MATLAB software was used to simulate the model solution of the forward problem. We calibrate the proposed model to estimate the parameters with a 95\% confidence interval (CI) using real data from Ethiopia by formulating an inverse problem. We notice that the model fits well with the real data of Ethiopia. The estimated basic reproduction number ($R_0$) is found to be $R_0=1.3973$ which proves that the disease is endemic. It is also obtained from the local sensitivity analysis that reducing the transmission rate and increasing the vaccination rate could effectively minimize the $R_0$.

Patches of Diopatra species from Brazilian sandy beaches were followed for ca. 50 years. Data were accessed from papers, gray literature, images and collections to verify time changes in the South Brazilian Bight (SBB) from 1974-2021. We modeled maximum density over time at 15 beaches, observing very high densities (&gt; 100 ind.m-2) in 1974 followed by a decrease (~ 10 ind.m-2) of three species of Diopatra until 1995 and a strong decline (1996-2002) when populations were almost regionally extinct (0-1 ind. m-2). A slight recovery (3-4 ind.m-2) occurred after 2006 for a single species, D. marinae, associated with warmer northern waters, suggesting a range shift. This pattern was associated with a) heatwaves linked to an El-Niño event (1988) and gradual SST surface warming of ca. 1 oC since 1974. The usage of Diopatra spp. as fishing bait could also be associated with such a reduction. After 2016, D. neapolitana, a likely alien species, was established in the SBB in high densities. Projections based on Species Distribution Modeling (SDM) suggest a potential of invasion in the same range of the known species of D. cuprea complex along the Brazilian coast despite that there are no signs of competition between both species.

The increase in the production and entry of greenhouse gases into the earth's atmosphere has disturbed the balance of the environment. The signs of climate change (caused by global warming) are clearly visible and its effects are tangible. According to the United Nations, if the current trend continues, the global average temperature will increase by 3.2°C by the end of the century, which will have terrible consequences if it happens. This research aimed to investigate the effects of greenhouse gases and climate changes resulting from them on Hyrcanian forests. The Hyrcanian forests, as one of the oldest forest areas (remaining from the Paleogene era), were studied by telemetry from 2013 to 2021. The analysis of the images taken from the Landsat 8 satellite showed that during 9 years, the NDVI index decreased by 0.6 units and the average air temperature increased by 0.5°C. Although the average relative humidity has only increased by 2%, the average annual rainfall has recorded an increase of 25mm. The analysis of the statistics showed that the rains occur irregularly and are often torrential. Therefore, it is predicted that as the average temperature continues to increase, the NDVI index will further decrease, and as a result, the forest cover will become weaker and the soil will lose more water absorption power, and due to the increase in average rainfall. successive floods will occur. Therefore, soil erosion increases and the extinction and migration of plant and animal species increase significantly.

Indigenous trees have great economic potential and ecological benefits for enhancing environmental prosperity, mostly in forestry and the forest products sector in the developing countries of Sub-Sahara Africa. The baobab (Adansonia Digitata L.) is known as the African green jewel in both fruit production and medicinal benefits also remarkable for so many forest products exported across the world. Research conducted in the different Sub-Saharan African sub-regions has shown this iconic tree with a majestic outlook has a priority tree species for local and foreign use and conservation. However, data on the benefits and conservation of baobab trees in Africa, especially the Sub-Saharan countries is limited. This study aimed to assess the predominant geo-graphical distribution of the tree, the indigenous (cultural, socio-economic, ecological, and medical/health) benefits, and the conservation strategies of the baobab resources in Sub-Saharan Africa. The baobab tree's succulent roots, bulbs, branches, fruit, pods, foliage, and petals are all nourishing. Baobab parts have been used for diverse reasons in Africa, some countries of Asia, and Europe for the past two centuries due to their medicinal well-being properties. In addition, the medicinal applications of the plant parts are discussed. Many authors have highlighted the baobab tree as one of the most important trees to be saved and localized in Africa because of its high indigenous usage and commercial worth. Anthropogenic global warming may induce a drop in baobab species, which could inflict negative impacts on African economies. As a result, it's critical to research the species' likely future distribution and develop conservation policies. Literature was consulted for records and availability of this tree in the Western, Central, Eastern, and Southern African species records and it was also analyzed what percentage of the current environment would be appropriate in the future. Recent studies suggested that farmers and the locals be provided free seeds and seedlings to encourage biological rejuvenation to maximize the plant's potential, people should be informed about the additional uses of baobab that have been discovered. Individuals must also be educated on simple sustainable agroforestry activities that can be performed in plant and forest management.

Approximately one-third of mankind is chronically exposed to the carcinogenic aflatoxin M1 contained in milk and dairy products and there is no ready to use procedure for decontamination purposes applicable in milk technology. Since β-cyclodextrin is frequently used in food industry, its effect on aflatoxin M1 concentration was investigated during cholesterol removal. So, milk samples were spiked with aflatoxin M1 at the average level 0.89 µg/kg and cholesterol removal was carried out by 2.0% (w/w) β-cyclodextrin addition. As found, average cholesterol concentration decreased by 92.3% while aflatoxin M1 concentration decreased to 0.53 µg/kg, i. e. by 39.1% after the treatment. The procedure itself is easy, inexpensive, and ready to use in milk processing technology on current production lines without any investments, thus fully applicable with a high potential of full aflatoxin M1 milk decontamination efficiency and such way to strengthen considerably the food safety issues associated with milk and dairy products on global level.