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.

With the rapid development of earth observation, satellite navigation, mobile communication and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. Under this circumstance, a new form of spatial data organization emerged-the global discrete grid. This form of data management can be used for the efficient storage and application of large-scale global spatial data, which is a digital multi-resolution the geo-reference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing and application of current spatial data. There are different types of grid system according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, and establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves that the availability hexagonal grid-based remote sensing data of remote sensing images. And among the three sampling methods, the image obtained by the nearest interpolation sampling method has the highest correlation with the original image.

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.

In 2010, Parties to the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011–2020 to address the loss and degradation of nature. Subsequently, most biodiversity indicators continued to decline. Nevertheless, conservation actions can make a positive difference for biodiversity. The emerging Post-2020 Global Biodiversity Framework has potential to catalyze efforts to ‘bend the curve’ of biodiversity loss. Thus, the inclusion of a goal on species, articulated as Goal B in the Zero Draft of the Post-2020 Framework, is essential. However, as currently formulated, this goal is inadequate for preventing extinctions, and reversing population declines; both of which are required to achieve the CBD’s 2030 mission. We contend it is unacceptable that Goal B could be met while most threatened species deteriorated in status and many avoidable species extinctions occurred. We examine the limitations of the current wording and propose an articulation with robust scientific basis. A goal for species that strives to end extinctions and recover populations of all species that have experienced population declines, and especially those at risk of extinction, would help to align actors towards the transformative actions and interventions needed for humans to live in harmony with nature.

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.

This article explores the cross-cultural significance of three iconic fairy tales: Cinderella, Snow White, and Sleeping Beauty. Using a comparative analysis approach, the study investigates recurring themes, motifs, and symbolism found in these tales across different cultures and time periods. The research draws on primary and secondary sources such as literary works and scholarly articles to uncover the underlying messages that resonate with audiences worldwide. The historical and cultural contexts of the tales are also examined to provide a deeper understanding of their significance in shaping cultural identity and values. The findings of the research demonstrate the enduring legacy of these tales and their continued relevance in contemporary society. The study highlights how the tales have evolved and adapted over time to reflect changing cultural values and beliefs. The interpretation of the findings offers insights into the role of storytelling in shaping cultural identity and values, and the ways in which these stories continue to inspire and captivate audiences worldwide. Overall, this research provides a comprehensive and nuanced understanding of the significance of these three fairy tales across cultures and time. By illuminating the similarities and differences in these tales, the study offers a fresh perspective on the power of storytelling and its ability to transcend cultural boundaries. The research contributes to the fields of folklore, cultural studies, and cross-cultural communication, inspiring further exploration into the captivating world of fairy tales.

Precipitation gauges are critical for measuring precipitation rates at regional and global scales and are often used to calibrate precipitation rates estimated from other instruments such as satellites. However, precipitation measured at the gauges is affected by gauge-undercatch that is often larger for solid precipitation. In the present work, two popular gauge-undercatch correction factors are assessed: one utilizes a dynamic correction model and is used in the Global Precipitation Climatology Centre (GPCC) Monitoring product and the other one employs a fixed climatology and is used in the Global Precipitation Climatology Project (GPCP) product. How much the choice of correction factors can impact the total estimate of precipitation was quantified over land at seasonal, annual, regional, and global scales. The correction factors are also compared as a function of the environmental variables used in their development, among those are near-surface air temperature, relative humidity, wind speed, elevation, and precipitation intensity. Results show that correction factors can increase the annual precipitation rate based on the gauges by ~9.5 % over the global land (excluding Antarctica), although this amount can vary from ~6.3% (in boreal summer) to more than 10% (in boreal winter), depending on the season and the method used for gauge-undercatch correction. Annual variations of correction factors can also be large, so the use of the fixed climatology correction factors requires caution. Given their magnitudes and differences, selection of appropriate correction factors can have important implications in refining the water and energy budget calculations.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

Immunology and microbiology research in the West Indies has witnessed remarkable growth and innovation, playing a pivotal role in advancing our understanding of immune mechanisms, disease pathogenesis, and therapeutic interventions. This manuscript presents a comprehensive exploration of key areas in West Indian immunology research, spanning from the utilization of bacterial proteins as antibody reagents to the intricate realms of clinical immunology and disease management. The utilization of bacterial immunoglobulin-binding proteins (IBPs), including protein A (SpA), protein G (SpG), and protein L (SpL), has revolutionised serological diagnostics in the region. promise in early disease detection and precision medicine. Microbiological studies in the Caribbean region have shed light on antimicrobial resistance patterns, particularly the emergence of extended-spectrum beta-lactamases (ESBLs), guiding antimicrobial stewardship programs and informing therapeutic strategies. Clinical immunology research has elucidated the molecular pathways underlying immune-mediated disorders, leading to tailored management strategies for conditions such as severe combined immunodeficiency (SCID), neuropsychiatric lupus erythematosus (NPLE), and others. In summary, West Indian immunology and microbiology research has made significant contributions to global healthcare, fostering collaboration, innovation, and improved patient outcomes.

Artificial intelligence methods and application have recently shown great contribution in modeling and prediction of the hydrological processes, climate change, and earth systems. Among them, deep learning and machine learning methods mainly have reported being essential for achieving higher accuracy, robustness, efficiency, computation cost, and overall model performance. This paper presents the state of the art of machine learning and deep learning methods and applications in this realm and the current state, and future trends are discussed. The survey of the advances in machine learning and deep learning are presented through a novel classification of methods. The paper concludes that deep learning is still in the first stages of development, and the research is still progressing. On the other hand, machine learning methods are already established in the fields, and novel methods with higher performance are emerging through ensemble techniques and hybridization.

Global emerge of zoonotic novel corona virus (COVID-19) became a pandemic and its effect to mankind is talk of the town now a days. This tiny, invisible enemy has affected every country in the world and almost every living directly or indirectly and nationwide complete lockdown has triggered a short-term environmental impact. Since 2003, corona virus came into existence in the form of Severe Acute Respiratory Syndrome (SARS) and more evolved Middle East Respiratory Syndrome (MERS) in 2012. This time, at the end of December 2019, outbreak of novel corona virus COVID-19 (also known as SARS-CoV₂, nCoV-2019) draw attention as global health emergency. World Health Organization (WHO) report says that the outbreak of this virus is so immense, it has already affected 35,57,235 people and caused death to 2,45,150 people worldwide and 46,433 Indians got affected with 1568 death as on 5^th May 2020 (2:00 am) and these numbers are increasing exponentially day by day. Virologist, micro-biologist and science community are hammering their head very hard to find out cure and vaccine against this powerful virus and to prevent mass demise of mankind. In order to curb the spread of COVID-19, Janta curfew on 22.03.2020 and nationwide complete lockdown was implemented in India for 21 days (phase-I, from 25.03.2020 to 14.04.2020) to stop community transmission of third stage, for 19 days (phase-II, 15.04.2020 to 03.05.2020) and 14 days (phase-III, 04.05.2020 to 17.05.2020) complete lockdown to minimize the community transmission effect. During complete lockdown and quarantine period a drastic change in Earth’s atmosphere, including reduction in emission of greenhouse gases, air pollution (~50% fall in air quality index), noise pollution, water pollution and solid waste pollution, have been recorded by government agencies as well as private agencies. In this paper we considered data of Janta curfew, phase-I and phase-II lockdown to link between geological and environmental aspect related to environmental impact due to emerge of COVID-19 and massive reduction in pollution level during complete lockdown in India. We propose future lockdown strategies to minimize the emission of greenhouse gas by ~100 Mt to ~200Mt (3.33% to 6.66%) of GHG_total per year by 2-4 days per month nationwide lockdown or ~70 Mt to ~140 Mt (2.33% to 4.66%) of GHG_total per year by 2-4 days per month complete lockdown of energy sectors only.

Atrial fibrillation (AF), a complex cardiac arrhythmia, necessitates a shift in management paradigms, emphasizing an integrative approach that incorporates lifestyle modifications. Investigations into the role of interleukins and inflammatory mediators are underway, exploring their potential as diagnostic markers and predictors of cardiovascular events in AF. Despite the identification of biomarkers related to cardiac remodeling, their predictive ability for post-cardioversion outcomes remains controversial. Computational models are being developed to understand proarrhythmic contributions and identify anti-AF targets. Addressing the rising global incidence of AF, linked to stroke and heart failure, presents a critical health challenge. As risk factors like obesity prevail, AF becomes a pervasive public health concern, expected to double in prevalence over the next 50 years. The impact on mortality and morbidity, especially through hospitalizations, underscores the need for early detection and effective clinical management. Identifying individuals at increased AF risk becomes crucial for screening and prevention strategies. Lifestyle modifications, including weight management and physical activity, emerge as influential factors in AF management, offering the potential to alleviate symptoms and modify disease progression. The paper concludes by emphasizing the need for safer antiarrhythmic therapies based on AF mechanisms, promising improvement in global AF management. The multifaceted nature of AF etiology requires a broader perspective beyond traditional medical interventions, acknowledging the importance of integrated care to address this significant public health challenge.

Malaria is a critical fevered illness caused by Plasmodium parasites transmitted among people through the bites of infected female Anopheles mosquitoes. Public awareness about the disease is important for the control of disease. This article proposes a mathematical model to study the dynamics of malaria disease transmission with the influence of awareness-based control interventions. We found two equilibria of the model, namely the disease-free and endemic equilibrium. Disease-free equilibrium is stable globally if basic reproduction number (R0) is less than unity (R0<1). Some basic mathematical properties of the proposed model, such as nonnegativity and boundedness of solutions, the feasibility of the equilibrium points and their stability properties, have been studied. Finally, we adopted optimal control to minimize the cost of disease control and solve the problem by formulating Hamiltonian functional. The optimal use of insecticides for controlling the mosquito population is determined. Numerical simulations have been provided for the confirmation of the analytical results. We conclude that media awareness with optimal control approach is best for cost-effective malaria disease management.

In the first part of this talk we review some prerequisites for and essential arguments involved in the construction of the thermal-ground-state estimate for the deconfining phase in the thermodynamics of SU(2) Quantum Yang-Mills theory and how this structure supports its distinct excitations. The second part applies deconfining SU(2) Yang-Mills thermodynamics to the Cosmic Microwave Background in view of (i) a modified temperature-redshift relation with an interesting link to correlation-length criticality in the 3D Ising model, (ii) the implied minimal changes in the dark sector of the cosmological model, and (iii) best-fit parameter values of this model when confronted with the spectra of the angular two-point functions TT, TE, and EE, excluding the low-$l$ physics. The latter, which is treated in an incomplete way because of the omission of radiative effects, is addressed in passing towards future work.

Over the past thirty years, the red gorgonian Paramuricea clavata in the Mediterranean Sea has faced increasing threats, including heat waves and human activities such as fishing and diving. Epibiosis on damaged gorgonian colonies is generally used as an indirect indication of stressed conditions. The density and height of P. clavata and the percentage of colonies affected by epibiosis and entangled in lost fishing gear were studied to investigate the phenomenon and its trend over time in the Ligurian Sea. Analyses were based on transects collected during ROV campaigns between 2015 and 2022 at depths of 33-90 meters. A strong correlation was observed between fishing effort in the study area and the level of epibiosis. Maximal percentages of colonies affected by epibiosis and entanglement were recorded at depths of 50-70 meters. Temporally, marine heat waves before 2019 were identified as the primary cause of damage to P. clavata. The decrease in epibiosis percentages after 2019, despite the 2022 heat wave, may be due to a quick recovery ability of the populations and a reduction in fishing activities during the COVID-19 lockdown in 2020. Long-term monitoring programs are essential to understand the changes in marine benthic communities exposed to different stressors.

Climate change is likely to have a complex effect on the growth of plants, their phenology, plant-pollinator interactions, and reproductive success. Therefore, we tested the impact of three key factors (temperature, water, and nitrogen supply) on traits, pollination, and seed production in Sinapis alba (Brassicaceae). We grew the plants in different combinations of temperature, water, and nitrogen supplementation, measured multiple vegetative and floral traits, and assessed the response of pollinators in the field. We also evaluated the effect of growing conditions on seed set in plants exposed to pollinators and hand-pollinated plants. Our results show that water stress impaired vegetative growth, decreased flower production, reduced visitation by pollinators and seed set, while nitrogen availability played an important role in nectar production. Temperature modulated the effect of water and nitrogen availability on vegetative and floral traits and strongly affected flowering phenology and flower production. We demonstrated that changes in temperature, water, and nitrogen availability induce changes in plant vegetative and floral traits which impact flower visitation and consequently plant reproduction. Climate change, particularly increasing temperature combined with reduced precipitation, thus may impact plant-pollinator interactions with negative consequences for the reproduction of wild plants and insect-pollinated crops.

Can investing in women’s agriculture increase productivity? This paper argues that it can. We assess climate impacts and gender bias on women’s production in the global South and North and challenge the male model of agricultural development to argue further that women’s farming approaches can be more sustainable. Level-based analysis (global, regional, local) draws on literature review, including authors’ published longitudinal field research in Ghana and the United States. Women farmers are shown to be undervalued and to work harder, with fewer resources, for less compensation; gender bias challenges are shared globally while economic disparities differentiate; breaches of distributive, gender, and intergenerational justices as well as compromise of food sovereignty affect women everywhere. We conclude that investing in women’s agriculture needs more than standard approaches of capital and technology investment. Effective ‘investment’ would include systemic interventions into agricultural policy, governance, education, and industry; be directed at men as well as women; and use gender metrics, e.g. quotas, budgets, vulnerability and impacts assessments, to generate assessment reports and track gender parity in agriculture. Increasing women’s access, capacity, and productivity cannot succeed without men’s awareness and proactivity. Systemic change can increase productivity and sustainability.

Global climate change, dominated by climate warming, is seriously affecting the balance of global ecosystems, but the risk of species extinction is particularly high in low-altitude mountain areas. To clarify the response of the endemic and critically endangered species Ilex nanchuanensis to climate change, this study used the MaxEnt model to simulate and predict the potential habitat of I. nanchuanensis during the Last Interglacial, Last Glacial Maximum, the current period, and two future periods (the 2050s and 2070s). The results showed that the hottest monthly minimum temperature is the most important climatic factor affecting the geographical distribution of I. nanchuanensis. Furthermore, I. nanchuanensis will be at risk of population shrinkage and extinction in the future, with the center of mass moving further northwest as concentrations of greenhouse gases increase, especially in the 2070s, when its geographical distribution shrinks the most under the RCP6 scenario. Global warming is causing habitat degradation for many species and will continue to migrate to higher altitudes and latitudes in the future, seriously affecting the global ecosystem balance. Therefore, to actively respond to the impacts of climate change, protected areas should be established around the geographical distribution centers of species, and core, buffer, and experimental areas should be scientifically and rationally delineated for the conservation and cultivation of germplasm resources.

In this paper, we consider the Cauchy problem of a time fractional nonlinear diffusion equation. According to the Kaplan’s first eigenvalue method, we first prove the blow-up of the solutions in finite time for some sufficient conditions. We next give sufficient conditions for the existence of global solutions by using the result of Zhang and Sun. In conclusions, we find the second critical exponent for the existence of global and non-global solutions via the decay rates of the initial data at spatial infinity.

Lifecycle assessment (LCA) quantified changes in environmental impact categories (global warming, eutrophication, etc.) from 2021 to 2030 due to genetic trends in (re)production traits in pig lines of breeding company Genus-PIC. The 2030 levels were projected with se-lection index theory based on weightings of traits in the breeding goals and genetic covari-ances among them. Projected improvement was 0.9% annually for most impact categories. Another LCA compared impacts of 2021 North American pig production based on PIC ge-netics versus the industry average. Software openLCA converted material and energy flows to impact categories of frameworks ReCiPe-2016, PEF-3.1 and IPCC-2021. Flows came from data recorded by customers (1.1/4.7 million sows/finishing pigs) and by subscribers to a third-party data-aggregator (1.3/9.1 million). PIC genetics have a 7-8% better impact than industry average for 13/18 categories of ReCiPe-2016, 19/25 of PEF-3.1, and all categories of IPCC-2001. Pig breeding delivers positive environmental outcomes as correlated respons-es to selection for profitability-oriented breeding goals. This trend is additive; technology development will increase it. Different investment levels in breeding population structure and technology, and different operational efficiencies of breeding companies, cause substan-tial differences in the environmental impact of pig production.

The construction industry plays a crucial role in shaping the built environment and contributes to the global economy. However, the construction process is associated with negative impacts on the environment and communities. This paper examines the environmental impacts of construction and presents strategies for mitigating them, focusing on sustainable construction practices. The research draws on a comprehensive literature review, case studies, and expert interviews to fully understand the construction industry and its environmental effects. The findings indicate that the implementation of greater supervision of every construction project phase, using alternative design practices, and the use of sustainable construction practices can reduce the negative impacts of construction on the environment and society. The study concludes that sustainable construction practices can contribute to a better environment for a better quality of life and should be embraced by the construction industry. The recommendations for future work include the adoption of green building standards, the use of renewable energy sources, the reduction of waste, and the promotion of stakeholder engagement. Future research should focus on the evaluation of the effectiveness of these strategies and their scalability.

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.

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.

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 < 0.001). PT was also decreased significantly from 28.71° ± 10.22° to 23.84° ± 9.96° (P < 0.001). Transforaminal Epidural Steroid Injection (TFESI) significantly improves VAS, ODI, and global sagittal parameters in lumbar spinal stenosis patients.

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<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.

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.

This paper extends the concept of weighted graphs to matrix weighted graphs. The consensus algorithms dictate that all agents reach consensus when the weighted graph is connected. However, it is not always the case for matrix weighted graphs. The conditions leading to different types of consensus have been extensively analysed based on the properties of matrix-weighted Laplacians and graph theoretic methods. However, in practice, there is concern on how to pick matrix-weights to achieve some desired consensus, or how the change of elements in matrix weights affects the consensus algorithm. By selecting the elements in the matrix weights, different clusters may be possible. In this paper, we map the roles of the elements of the matrix weights in the systems consensus algorithm. We explore the choice of matrix weights to achieve different types of consensus and clustering. Our results are demonstrated on a network of three agents where each agent has three states.

Monitoring of the surface operations using movement and surveying radar (MSR) can prevent loss of life, equipment, production and loss of the mine. Slope monitoring using MSR is an important aspect of open-pit mining as it provides real-time movement of deformation data for the slope. It is therefore important that the radar is accurately geo-referenced in order to provide accurate real-time movement data. Geo-referencing is defined as the process of determining an instrument’s position (in the form of Easting, Northing, Height) as well as the orientation with respect to the mine’s local coordinate system. This helps in getting geo-referenced data points from the radar that are identified by a unique set of coordinates in relation to the mine’s coordinate system which allows the radar to track movement for a specific set of coordinates. In this research, we assess the performance of geo-referencing a radar using the total station method and compare it with the integration of Advance Navigation – Spatial Dual GPS system connected via RS422 on the MSR. This includes usage of the Spatial Dual navigation coordinates output to calculate the radar’s position relative to the mine local coordinates and mapping the radar’s azimuth, elevation and Range (Az, El and Rl) values to the measured pit-slope data points. Furthermore, a comparison of key attributes of both methods of geo-referencing is performed using a matrix system and giving an overall performance appraisal of both systems. Integrating a navigation system allows the radar to have an auto geo-referencing functionality that will reduce the time spent in completing this process. The findings reveal that the GPS obtained a higher score than the total station with prism method on the weighted matrix system. The total station was found to be more accurate than the GPS however, the deployment time for the GPS is quicker than that of the total station. This is important for different operation such as strip and open-pit mining to choose the preferred method of geo-referencing depending on the level of accuracy required.

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.

In this paper we investigate the global asymptotic stability of following system ofhigher order difference equations with quadratic terms:xn+1=A+Byn/yn−m^2, yn+1=A+Bxn/xn−m^2, where A and B are positive numbers and the initial values are positive numbers.We also study the boundedness, rate of convergence and oscillation behaviour of thesolutions of related system.

This paper aims to investigate the global asymptotic stability of following system of higher order difference equations with quadratic terms: x_{n+1}=A+B((y_{n})/(y_{n-m}²)),y_{n+1}=A+B((x_{n})/(x_{n-m}²)) where A and B are positive numbers and the initial values are positive numbers. We also study the rate of convergence and oscillation behaviour of the solutions of related system.

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.

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.

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 investigates a proposed new mathematical model that considers the infected individuals using various rate coefficients such as transmission, progression, recovery and vaccination. The fact that the dynamic analysis is completely determined by the basic reproduction number is established. More specifically, local and global stabilities of the disease-free equilibrium and the endemic equilibrium are proved under certain parameter conditions when the basic reproduction number is below or above unity. A realistic computer simulation is performed for better understanding of the variations in trends of different compartments after the outbreak of the disease.

COVID-19 severity is heterogeneously distributed over age strata, but current mitigation strategies are homogeneously applied to all population. Social-distancing and stay-home are effective conservative approaches but lack economic sustainability on long term. Conversely, herd-immunity is a nonrestrictive strategy which can cost remarkable number of human lives and can melt the healthcare system down. Here I propose an Age Adaptive Social Distancing (AASD) engineering strategy to mitigate COVID-19 outbreak. AASD is based on the scientific evidence that the fatality rate grows nonlinearly with age, hence also the containing strategy should adapt nonlinearly. Essentially, AASD suggests that ‘silent spreaders’ (age 0-39) should avoid/minimize direct and indirect contacts with individuals in ‘dangerous zone’ (age 40+). The rationale is: 0-19 should follow parents strategy, healthy 20-39 (low fatality rate) might conduct screened life under active surveillance, to sustain economy and acquire rational immunity; 40-59 should respect social distancing (waiting a therapy); 60+ should stay at home (waiting a vaccine). This might save human lives, reduce healthcare demand and improve economic sustainability. The final take-home message is that future studies should design precision and personalized strategies for specific contagious diseases that integrate different social constrains, active surveillance and contact tracing.

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.

Health innovations are generally oriented on a techno-economic vision. In this perspective, technologies are seen as an end in themselves, and there is no arrangement between the technical and the social values of innovation. This vision prevails in sanitary crises, in which management is carried out based on the search for punctual, reactive, and technical solutions to remedy a specific problem without a systemic/holistic, sustainable, or proactive approach. This paper attempts to contribute to the literature on the epistemological orientation of innovations in the field of public health. Taking the Covid-19 and Ebola crises as examples, the primary objective is to show how innovation in health is oriented towards a techno-economic paradigm. Second, we propose a repositioning of public health innovation towards a social paradigm that will put more emphasis on the interaction between social and health dimensions in the perspective of social change.

We propose a silviculture with a purely biological logic that takes soil into account. The article is divided into three parts: 1) presentation of the issue in the context of biodiversity and forest pro-tection; 2) impact of the soil functioning on forestry; 3) possible implementation of soil functioning in forestry practice, to support and protect a non-or minimally anthropized evolution of the forest. The first chapter illustrates the importance of the forest for the future of the planet and our human species, referring to recently published works on the topic of climate warming and biodiversity. The second illustrates the aspects that link soil dynamics to the silvogenetic cycle, focusing on the humipedon (organic and organo-mineral surface horizons, approximately the first 30 cm of forest soil), and more significant carbon storage in old forests since up to 2/3 is found in the soil. In the third chapter we consider the possibility of lengthening the forestry cycle, to allow the return of nutrients to the soil. Theoretical graphs and distribution models of the number of trees as a func-tion of diameter and age are reported, with examples of logging in uneven Alpine forests, with reference to Swiss fir-beech forests published on the Pro-Silva website.

Best practices in global health training prioritize leadership and engagement from investigators from low- and middle-income countries (LMICs), along with more conscientious community consultation and research that benefits local participants and autochthonous communities. However, well into the 20th century, international research and clinical care were rife with paternalism, extractive practices, and racist ideation, with race presumed to explain both vulnerability or protection from various diseases despite scientific evidence for more precise mechanisms for infectious disease. We highlight experiences in global research on health and illness among indigenous populations in LMICs, seeking to clarify what is both scientifically essential and ethically desirable in research with human subjects; we apply a critical view towards race and racism as historically distorting elements that must be acknowledged and overcome.

The Arctic freshwater budget is critical for understanding the climate in the northern regions. However, the hydrology of the Arctic circumpolar tundra region (ACTR) and the largest pan-Arctic rivers are still not well understood. In the present paper, we analyze the spatiotemporal variations in terrestrial water storage (TWS) of the ACTR, including three of its largest pan-Arctic river basins (Lena, Mackenzie, Yukon), using monthly Gravity Recovery and Climate Experiment (GRACE) data from 2002 to 2016. Together with global land reanalysis, river runoff, and inundation extent area (IEA) data, we identify declining TWS trends throughout the ACTR that we attribute largely to increasing evapotranspiration driven by increasing summer air temperatures. In terms of regional changes, large and significant negative trends in TWS are observed mainly over the North American continent. At basin scale, we show that, in the Lena River basin, the autumnal TWS signal persists until the winter of the following year, while in the Mackenzie River basin, the TWS levels in the autumn and winter has no significant impact on the following year. As global warming is expected to be particularly significant in the northern regions, our results are important for understanding future TWS trends, with possible further decline.

Temporal changes of population densities and species richness of three main pollinator groups: moths and butterflies (Lepidoptera), bees, wasps and sawflies (Hymenoptera) and hoverflies, horse-flies, tachninids and bee flies (Diptera) were investigated in the Carpathian Basin. Maintaining pollinator divesrity is a crucial factor for preserving our biodiversity and ecosystems, furthermore several pollinator species has strong economic role in maintaning crop and fruit cultures. Our conclusions are based on our three or four decades of faunistic surveys in various regions of the Carpathian Basin. Analysing and comparing our data with the historical data of the last 50 years, we concluded, densities of some pollinators were declined during the past decade and the half (Symphyta, hoverflies), although populations of several species of Mediterranean-origin were grown (Aculeata) and even new species were migrated from the warmer regions. In numerous cases, this decrease was dramatic: more than 90% decrease of certain butterfly species were detected. On the other hand, the composition of pollinator fauna significantly changed due to the disappearance of some montaneous or mesophyle species. The main reason of decrease of pollinator communities is partly the climatic change and partly anthropogenic factors. Our conclusion: in our region, the pollinator crisis is present, but moderate; however, there is clear sign of the gradual transition of our pollinator fauna towards the Mediterranean type.

The COVID-19 pandemic has struck educational experience systems around the globe. This paper investigates and evaluates the student participants’ perceptions who joined the international exchange seminar on global citizenship and peace held at a University in Hiroshima, Japan. Approximately seventy students and faculty members from nine to ten different universities from around the globe joined this summer program in August 2021 (online) and 2022 (face-to-face). This study is a mixed-method study. The first part consists of a quantitative analysis of BEVI data obtained from the students in the seminar before COVID-19 and after. The research concludes that there are no changes in the way students learn. The second part consists of qualitative data. This data shows the perceptions of students of online teaching versus hybrid teaching. It compares the differences in participants’ perceptions reported in students’ feedback on the programs during and post-COVID-19. Our results confirm prominent differences exist in the students’ perceptions of their learning experience during the pre-pandemic and post-pandemic periods. The findings of this study suggest that universities need to strive and define a meaning and purpose of international seminars, which enables students to experience a high level of intercultural social interaction face-to-face.

This work presents significant results obtained by the application of global optimization techniques to the design of finite, normal form games with mixed strategies. To that end, the Fuzzy ASA global optimization method is applied to several design examples of strategic games, demonstrating its effectiveness in obtaining payoff functions whose corresponding games present a previously established Nash equilibrium. In other words, the game designer becomes able to choose a convenient Nash equilibrium for a generic finite state strategic game and the proposed method computes payoff functions that will realize the desired equilibrium, making it possible for the players to reach the favorable conditions represented by the chosen equilibrium. Considering that game theory is a very significant approach for modeling interactions between competing agents, and Nash equilibrium represents a powerful solution concept, portraying situations in which joint strategies are optimal in the sense that players cannot benefit from individually modifying their current strategies provided that other players do not change their strategies as well, it is natural to infer that the proposed method may be very useful for strategists in general. In summary, it is a genuine instance of artificial inference of payoff functions after a process of global machine learning, applied to their numerical components.

Despite several attempts by governments and non-governmental organizations to eliminate female genital mutilation or cutting, it is puzzling that this traditional procedure is widely practiced today in many parts of sub-Saharan Africa (SSA). Scholarly arguments on the influence of female genital mutilation on sexual behavior up until now remain inconclusive. The current study sought to examine the association between female genital mutilation and early sexual initiation among girls and young women (AGYW) in SSA. Data from Demographic and Health Surveys (DHS) of 12 SSA countries were combined. A total of 30,089 AGYW (15-24 years) who had ever had sex and had complete information on all the variables of interest were considered. The outcome variable for the study was early sexual initiation. The study employed multilevel logistic regression for the data analysis, with reported odds ratio and associated 95% confidence intervals (CIs). The overall prevalence of female genital mutilation among AGYW was 49.9%, with the highest and lowest prevalence in Guinea (95.8%) and Togo (3.3%) respectively. The prevalence of early sexual initiation was 42.4%, with the highest and lowest prevalence in Niger (59.9%) and Burkina Faso (30.6%) respectively. AGYW who had not experienced female genital mutilation were less likely to have early sexual initiation [OR= 0.74, CI= 0.70-0.78], compared to those who had experienced female genital mutilation, after controlling for significant covariates. The likelihood of early sexual initiation was high among AGYW aged 15-19 [OR=2.38, CI=2.26-2.51] but low among AGYW with secondary education [AOR=0.58, CI=0.54-0.63], those who had never married [OR=0.68, CI=0.60-0.78], those in households with richest wealth quintile [OR=0.64, CI=0.57-0.72], those who were exposed to mass media [OR=0.88, CI=0.83-0.93], and those working [OR=0.91, CI=0.87-0.96]. Not undergoing female genital mutilation in the midst of socio-economic factors (e.g., education level, household wealth) could limit AGYW from early sexual debut. These findings underscore the need for effective campaign and programs (e.g., educational programs, entrepreneurial training, micro-finance schemes) against the practice of female genital mutilation. Policy interventions (e.g., “schooling for the girl-child” initiatives) that might delay early sexual initiation among adolescent girls and young women in the midst of identified socio-economic factors should be developed.

There is a long trail of research studies testing the in vitro and in vivo efficacy of chloroquine and its derivatives in treating and preventing infection by various coronavirus species. More recent findings have highlighted the possibility of treating patients infected with the 2019 novel coronavirus, SARS-CoV-2. This review describes the mechanism of coronavirus infection, the mechanism of action of chloroquine, and summarizes the available literature highlighting the efficacy of chloroquine as an anti-coronavirus agent. These findings should encourage the wider scientific community to conduct thorough research on the possible efficacy of chloroquine and its derivatives in treating and preventing SARS-CoV-2 infection.

In this paper, the forecast horizon and solar variability influences on MHFM model based on multiscale decomposition, AR and NN models, are studied. This article follows the works published in [1] showing the performance of the MHFM using 3 multiscale decomposition methods and a forecast horizon equal to 1 hour. Several forecast horizon strategies and his influence on the MHFM performances are investigated. We show that the best strategy for a rRMSE variying from $4.43\%$ to $10.24\%$ is obtained for forecast horizons from $5$ minutes to $6$ hours. In a second part, the solar variability influence on the MHFM is studied. A classification based on a shows that the best performance of MHFM is obtained for clear sky days with a rRMSE of $2.91\%$ and worst for cloudy sky days with a rRMSE of $6.73\%$.

Methane and carbon dioxide are the main contributors to global warming, being the methane effect twenty-five times more powerful than carbon dioxide. Although the sources of methane are diverse, it is a very volatile and explosive gas. One way to store the energy content of methane is its conversion to methanol. Methanol is liquid under ambient conditions, easy to transport and, apart from its use as an energy source, it is a chemical platform that can serve as a starting material for the production of various higher value-added products. Accordingly, the transformation of methane to methanol has been extensively treated in the literature, using traditional catalysts as different types of zeolites. However, in the last years, a new generation of catalysts have emerged to carry out this transformation with higher conversion and selectivity, and more importantly, under mild temperature and pressure conditions. These new catalysts typically involve the use of a highly porous supporting material such as zeolite, or more recently, metal-organic frameworks (MOFs) and graphene, and metallic nanoparticles or a combination of different types of nanoparticles that are the core of the catalytic process. In this review, the characteristics, the catalytic mechanisms, reactors, and the main results of these catalysts are presented as a way to overcome the challenges found in traditional catalysts.

This article develops duality principles, a related convex dual formulation and primal dual formulations suitable for the local and global optimization of non-convex primal formulations for a large class of models in physics and engineering. The results are based on standard tools of functional analysis, calculus of variations and duality theory. In particular, we develop applications to a Ginzburg-Landau type equation. Other applications include primal dual variational formulations for a Burger's type equation and a Navier-Stokes system. We emphasize the novelty here is that the first dual variational formulation developed is convex for a primal formulation which is originally non-convex. Finally, we also highlight the primal dual variational formulations presented have a large region of convexity around any of their critical points.

The important topic of climate change is discussed in this article, with a focus on the historical background and present effects. It draws attention to the differences between climate change and global warming and attributes the faster pace of climate change to human activity, specifically the release of greenhouse gases into the atmosphere. Agricultural practices, deforestation, and the combustion of fossil fuels are examined in conjunction with natural contributors like volcanic emissions. There is discussion of the far-reaching effects of climate change, such as increased temperatures, rising sea levels, harsh weather, and effects on water supplies. The article emphasizes how crucial it is to mitigate and adapt to the effects of climate change by putting in place climate-resilient infrastructure, switching to renewable energy sources, and lowering greenhouse gas emissions. While recognizing the difficulties involved, it examines several approaches, including nuclear energy, wind power, carbon capture and storage, and green building techniques. To successfully address the global challenge of climate change, the conclusion emphasizes the urgent need for joint efforts by scientists, environmentalists, communities, and governments.

The research develops and validates new decomposition models for DNI estimations from Southern African data. The results demonstrated improved DNI estimation accuracy compared to the baseline models across all testing and validation datasets. These outcomes suggest that utilising a localised model can significantly enhance DNI estimations for Southern Africa and potentially for developing similar models in diverse geographic regions worldwide. Furthermore, clustered models highlighted the potential advantages of grouping data based on shared geographical and climatic attributes. This clustering approach could enhance decomposition model performance, particularly when local data is limited or data is available from multiple nearby stations. The Southern African decomposition model, which encompasses a wide spectrum of climatic regions and geographic locations, exhibited notable improvements over the baseline models despite occasional overestimation or underestimation. The overall metrics affirm the substantial advancement achieved with the Southern African model. This study focused on validating the model for hourly DNI in Southern Africa within a range of clearness index-intervals from 0.175 to 0.875. Implementing accurate decomposition models in developing countries can accelerate the adoption of renewable energy sources, diminishing reliance on coal and fossil fuels.

In our increasingly urbanized world, precise and up-to-date maps of human settlements are essential for sustainable urban development policies. The availability of open-access Sentinel-2 data from the Copernicus program presents an opportunity to create a comprehensive global map of human settlements, offering a detailed view of built areas on a large scale. This study estimates large-scale built-up fractions using encoder-decoder deep learning architectures like U-net, Res-U-net, and Attention-U-net in the large and complex urban area of Delhi, India. Openly available datasets like Open Street Map (OSM) and Microsoft building footprint datasets are used to derive built-up fractions at 10×10m resolution cells for over 34,000 km2. Our results show that Attention-U-net with the Huber loss function performs the best in different built-up densities (i.e., urban, semi-urban or rural) with an R2 score of 0.631, while Res-U-net and U-net obtained an R2 score of 0.623 and 0.612, respectively. The investigated networks significantly improve the accuracy over the latest Global Human Settlement Layer product (GHSL-S2), which uses a deep-CNN and reaches an R2 of 0.387 in our case study area. The result of this study yields a valuable spatial layer for examining the spatial distribution of human settlements across the entire spectrum from rural to urban areas.

We propose Context-aware Feature Transformer Network (CaFTNet), a novel network for human pose estimation. To address the issue of limited modeling of global dependencies in convolutional neural networks, we design Transformerneck to strengthen the expressive power of features. Transformerneck directly substitutes the 3×3 convolution in bottleneck of HRNet with Contextual Transformer (CoT) block, while reducing the complexity of the network. Specifically, CoT first produces keys with static contextual information through 3×3 convolution. Then, relying on the query and contextualization keys, the dynamic contexts are generated through two concatenated 1×1 convolutions. Static and dynamic contexts are eventually fused as an output. Additionally, for the multi-scale networks, in order to further refine the features of the fusion output, we propose an Attention Feature Aggregation Module(AFAM). Technically, given an intermediate input, AFAM successively deduces attention maps along channel and spatial dimensions. Then, Adaptive refinement module(ARM) is exploited to activate the obtained attention maps. Finally, the input undergoes adaptive feature refinement through multiplication with the activated attention maps. Through the above studies, our lightweight network provides a powerful clue for detection of keypoints. Experiments are implemented on the COCO and MPII datasets. The model achieves 76.2 AP on the COCO val2017. Compared to other methods with the CNN as the backbone, CaFTNet reduces the number of parameters by 72.9 %. On the MPII, our method uses only 60.7% of the number of parameters, acquiring semblable results to other methods with the CNN as the backbone.

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.

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.

Background: With new challenges to the health system, many new competencies within the scope of teaching public health need to be addressed in medical schools’ curricula such as disaster risk management and health system science. The aims of this study were to identify the needs of public health competencies for medical doctors in Thailand and to assess the level of integration for technical collaboration in teaching public health. Method: A total of 17 out of 21 Thai medical schools participated in the national survey. Qualitative inquiries applied focus group interviews of community representatives from ten sample villages and in-depth interviews of representatives from stakeholder organizations particularly employers. The list of public health competencies framework recommended by WHO-SEARO was applied. Quantitative analysis applied descriptive analysis using STATA 15 and qualitative findings were validated by interrelating the meaning of themes from Word Clouds created in NVivo12. Data integration applied a mixed-method Quan-qual approach. Results: 17 medical schools returned the questionnaires (80.95 % yield). The most common regionally-defined public health competencies (in over 70% of schools) were shown to be: Biostatistics, Community Medicine, Epidemiology, Family Medicine, Medical Ethics and Professional Laws, Preventive Medicine, Health Promotion, Holistic Care, and Research. The curriculum in only one medical school lacked Health Economics, whilst Disaster Management was lacking in two other schools. Discipline-based subjects were found to be more prevalent than interdisciplinary competencies. A variety of methods were being applied for teaching public health. The majority of the schools applied lecture as the main teaching method and multiple-choice questions as the main assessment method. Thai communities expect the doctors to get in touch with the community more often, lead the primary health care team through training the health professionals and community health volunteers, and educate the community for better health. Conclusion: Human resource is the main challenge in addressing interdisciplinary competencies. It is necessary to establish a collaborating mechanism among the big and small medical schools and the faculties of public health to improve the teaching of public health to undergraduate students in medical schools. There is also a need to strengthen the health system science and leadership so that future MDs can lead health service delivery according to the needs of their employers such as the Ministry of Public Health and the Rural Doctors Association. The findings of this study may help to identify a national framework of public health core competencies for medical schools and create a common platform for interdisciplinary collaborations.

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.

We studies the initial value problem for the fractional Navier-Stokes-Coriolis equations, which obtained by replacing the Laplacian operator in the Navier-Stokes-Coriolis equation by the more general operator $(-\Delta)^\alpha$ with $\alpha>0$. We introduce function spaces of the Besove type characterized by the time evolution semigroup associated with the general linear Stokes-Coriolis operator. Next, we establish the unique existence of global in time mild solutions for small initial data belonging to our function spaces characterized by semigroups in both the scaling subcritical and critical settings.

Over recent years globalisation has occasioned a dramatic rise in cross-cultural interactions – until this was disrupted by the COVID-19 pandemic (OECD 2018, Nelson &amp; Luetz 2021). The ability to competently engage in a multicultural world is often considered the “literacy of the future” (UNESCO 2013, OECD 2018). Global interconnectedness has brought studies into intercultural competence to centre stage (UNDP 2004, Bissessar 2018, Nelson et al. 2019). This has increased the demand for cross-cultural education experiences that facilitate such learning. However, there is a dearth of empirical research into the issues and effects surrounding short-term cross-cultural educational experiences for adolescents. This mixed methods study extends previous research by looking specifically into what impact short-term cross-cultural experiences may have on the formation of intercultural competence and emotional intelligence of Australian high school students. This study used two instruments for measuring intercultural competence and emotional intelligence in a pre- and posttest quasi-experimental design (n=14), the GENE Scale and TEQ. Moreover, it conducted in-depth post experience qualitative interviews (n=7) that broadly followed a phenomenological paradigm of inquiry. The findings suggest that fully embodied cross-cultural immersive experiences offer benefits in areas of intercultural competence and emotional intelligence and can offer meaningful application in areas of current affairs. A greater understanding of the linkages between immersive cross-cultural experiences and intercultural competence offers prospects for policy makers, educators, pastoral carers, and other relevant stakeholders who might employ such experiential learning to foster more interculturally and interracially harmonious human relations.

The use of different primary energy sources in human society has led to two major polluting emissions in the environment: energy (mostly heat), and chemical substances (mostly carbon dioxide). In this paper, the total global anthropogenic emissions of heat to the atmosphere during the industrial era (years 1850-2018) were determined and their effect on the change of global atmospheric temperature was calculated. The concept of a theoretical three-phase Earth reactor was introduced to estimate global atmospheric temperature increase caused by anthro-pogenic heat emissions. The resulting calculations closely approximated the actual atmospheric temperature change recorded during the last 170-year period. These results suggest that the temperature change of the atmosphere (global warming) is entirely due to anthropogenic heat emissions.

In Secondary Education, the focus of History teaching must be on the development of global citizenship. The present research was a study contextualized in the Fiesta de la Historia Youth Congress in Seville (Spain). A documentary analysis with a descriptive and interpretive design was made of 63 projects of inquiry that pupils carried out. The main objectives were to assess the incidence of the proposal in terms of participation, and to determine whether the pupils' projects followed a logic of inquiry about socially relevant problems which favours the construction of global citizenship. The results point to a low incidence of schools participating in this initiative. The projects of inquiry analysed present for the most part themes related to the historical and social heritage of the locality. The proposals are approached as problems of a specific discipline, and are worked on through a method based on a pseudoscientific research process. The findings indicate the need to continue implementing initiatives based on school inquiry that allow the teaching of History to be articulated around relevant social problems, with the objective being to develop citizenship skills.

In this paper, we study the global asymptotically stability of following system of difference equations with quadratic terms: x_{n+1}=A+B((y_{n})/(y_{n-1}²)),y_{n+1}=A+B((x_{n})/(x_{n-1}²)) where A and B are positive numbers and the initial values are positive numbers. We also investigate the rate of convergence and oscillation behaviour of the solutions of related system.

Many corporations aspire to become Net Zero Carbon Dioxide by 2030-2050. This paper examines what it will take. It requires understanding where energy is produced and consumed, the magnitude of CO2 generation, and the Carbon Cycle. Reviews are provided for prior technologies for reducing CO2 emissions from fossil to focus on their limitations and to show that none offer a complete solution. Both biofuels and CO2 sequestration reduce future CO2 emissions from fossil fuels. They will not remove CO2 already in the atmosphere. Planting trees has been proposed as one solution. Trees are a temporary solution. When they die, they decompose and release their carbon as CO2 to the atmosphere. The only way to permanently remove CO2 already in the atmosphere is to break the Carbon Cycle by growing biomass from atmospheric CO2 and sequestering biomass carbon. Permanent sequestration of leaves is proposed as a solution. Leaves have a short Carbon Cycle time constant. They renew and decompose every year. Theoretically, sequestrating a fraction of the world’s tree leaves can get the world to Net Zero without disturbing the underlying forests. This would be CO2 capture in its simplest and most natural form. Permanent sequestration may be achieved by redesigning landfills to discourage decomposition. In traditional landfills, waste undergoes several stages of decomposition, including rapid initial aerobic decomposition to CO2, followed by slow anaerobic decomposition to methane and CO2. The latter can take hundreds to thousands of years. Understanding landfill chemistry provides clues to disrupting decomposition at each phase.

Skin and soft-tissue infections (SSTI) are common cases of hospital-acquired infections with aetiologic agents exhibiting antimicrobial resistance (AMR). We determined the prevalence, proportion of laboratory-investigated cases, AMR-profiles, and factors associated with SSTI and multi-drug resistance (MDR). This study was based on archived data of patients suspected of SSTI from 2019-2021 at Jinja Regional Referral Hospital. The analysis involved 268 randomly selected patient reports. Prevalence of SSTI was 66.4%. Laboratory-investigated cases were 14.11%. Staphylococcus aureus (n=51) was the most isolated organism. MDR pathogens explained 47% of infections. Methicillin-resistant S. aureus was up to 44%. In addition, 61% of Gram-negatives had the potential to produce extended-spectrum beta-lactamases, while 27% were non-susceptible to carbapenems. Ward of admission was significantly associated with infection (aPR=1.78, 95% CI: 1.003-3.18, p-value=0.04). Age category (19-35) was an independent predictor for MDR infections (aPR=2.30, 95%CI:1.02-5.23, p-value=0.04). The prevalence is relatively high with MDR pathogens responsible for almost half of the infections. Routine use of culture and sensitivity testing should be done for proper infection management. Gentamicin and ciprofloxacin can be considered for empirical management of emergency SSTI suspected of S. aureus. Recognizing SSTI under the Global Antimicrobial resistance Surveillance System would lead to improved preparedness and response to AMR.

This study explores several global and country cluster sustainable development (herein SD) models. It jointly examines constructs from the “Neoliberal-turn” ((e.g., Institutional Enhancers (e.g., business freedom, property rights, government integrity, and judicial effectiveness), Financial Enhancers (e.g., government spending and monetary, trade, investment, and financial freedoms), Foreign Direct Investment, Global Competitiveness-institutions, and Global Competitiveness-innovation-sophistication)), and the “Social-turn” (five SD pillars (e.g., Planet, People, Peace, Prosperity, and Resources), which synthesize the 17 United Nations SD goals); and Happiness and Life Satisfaction (herein H&amp;LS). The study examines a large and diverse set of relationships encompassing 11 years of data of 108 social, economic, and environmental indicators from 129 countries at the global, country cluster, and country levels. We analyze data using structural equation modeling. Remarkably, Planet, an SD pillar constituted by biophysical variables, is the least of the five SD pillars positively related to the "neoliberal-turn" constructs and H&amp;LS. Results show model configurations and scale effects. Furthermore, findings reveal both synergies between neoliberal and the five SD pillars as well as both negative and non-significant relationships among them. The diversity of results calls for further model integration and specificity. Diverse findings entail caution and difficulties in generalizing knowledge. Similarly, results suggest that it is not advisable, since there may be many different and partly legitimate alternatives, to rely on just one perspective (e.g., giving primacy to economic-based analyses) and or in analyses at only one scale. The perspective effects and the stakes involved in SD urgently call for more collaborative efforts at all levels.

The present paper proposes a fractal analysis of the Covid-19 dynamics in 45 European countries. We introduce a new idea of using the box-counting dimension of the epidemiologic curves as a means of classifying the Covid-19 pandemic in the countries taken into consideration. The classification can be a useful tool in deciding upon the quality and accuracy of the data available. We also investigated the reproduction rate, which proves to have significant fractal features, thus enabling another perspective on this epidemic characteristic. Moreover, we studied the correlation between two meteorological parameters: global radiation and daily mean temperature and two Covid-19 indicators: daily new cases and reproduction rate. The fractal dimension differences between the analysed time series graphs could represent a preliminary analysis criterion, increasing research efficiency. Daily global radiation was found to be stronger linked with Covid-19 new cases than air temperature (with a greater correlation coefficient -0.386, as compared with -0.318), and consequently it is recommended as the first-choice meteorological variable for prediction models.

Detecting the trends of species and populations is fundamental to identify taxa with high conservation priority. Unfortunately, long-term monitoring programs are challenging and often lacking. The Italian agile frog Rana latastei is endemic to Northern Italy and adjacent countries, is considered vulnerable by the IUCN, and is protected at the European level. However, quantitative estimates of its decline are extremely scarce. In this study, we document the trends in abundance and distribution of Rana latastei within the Monza Park, which currently represents the area closer to the type locality of the species. Wetlands within the park were monitored from 2000 to 2023; counts of egg clutches were taken as a measure of reproductive output and of the abundance of breeding females. In 2000, the species occurred over a significant proportion of the park. Total abundance showed strong yearly variation but remained rather constant from 2000 to 2019. However, Rana latastei disappeared from the park around 2021 and was never detected in 2022-23. The decline is probably related to the joint effect of multiple factors, including the conversion of breeding sites for farming, inappropriate water management, invasive alien species, and severe drought. The local extinction of Rana latastei occurred despite legal protection, highlighting the need for more effective and stringent tools for the conservation of European biodiversity.

Sustainable energy development (SED) is a crucial component of the Sustainable Development Goals (SDG), aiming to maintain economic and social progress while protecting the environment and mitigating climate change’s effects. SED serves as a transition paradigm for sustainable development, providing a blueprint for energy peace and prosperity for people and all uses. This article presents the history of SED and then uses a critical discourse approach to summarize existing review studies in SED. Ten interlinked themes of SED are identified, with two of them considered to be among the least studied in existing SED reviews and in the current global discussion around climate change. This study explores these two themes, which include energy financing and the need for 100% renewable energy (RE), a sub-theme of decarbonization strategy working towards the 1.5–2.0 °C scenario. The study suggests that the current G20 countries’ contributions, if maintained continuously per annum, in addition to 80% more funding from private investment compared to the amount in the 1.5 °C scenario financial requirements for clean energy, are sufficient to limit global warming. In addition to the present drive for 100% RE, the article also discusses emerging issues, such as energy storage options with an indication of hydrogen as the most promising, other energy-related development agendas, and the need for regional security stability to prevent energy wars. Selected SED decarbonization strategies are presented across the power, transport, building, and industrial sectors. The study concludes with progress and directions for future research, mainly the need for re-defining nationally determined contribution (NDC) through an emissions budgeting and centralized global or regional emissions stock-taking strategy working towards the 1.5 °C scenario.

Myiasis is a medical condition in humans caused by the larvae and worms of certain types of flies, specifically the Sarcophagidea species. If this parasitic infection occurs in the external part of the eye, it is known as external ophthalmomyiasis. This condition is more commonly found in the Mediterranean and the Near East and is rare in North America. Objective: This report and review aim to describe and compare the risk factors, clinical course, and parasitologic features of external ophthalmomyiasis. We also discuss the different preventive measures in a large case series reported from January 2000 to December 2022. Methods: We report the first case of external ophthalmomyiasis in Mexico caused by Lucilia sericata in an adolescent with no clinical risk factors. Additionally, we perform a literature review of reported cases of external ophthalmomyiasis to determine the clinical characteristics, therapeutic management, and information on the organisms that most commonly cause external ophthalmomyiasis. Results: A total of 312 cases of external ophthalmomyiasis were recorded, with 208 cases in males (66.7%) and 102 cases in females (32.7%). In two cases, the gender and species responsible for the ophthalmomyiasis were not reported (0.6%). The mean age of those affected was 32.1 ± 18.5 years, ranging from newborns to 91 years old. The male-to-female ratio was 2:1. The most common causative organism was Oestrus ovis, accounting for 72.1% of cases, followed by Dermatobia hominis at 5.4%, Lucilia sericata at 0.96%, and Chrysomyia bezziana at 0.96%. Before experiencing symptoms, 43.6% of cases reported having direct contact with flies or being hit in the eye, 33% reported no associated risk factors, 9.3% reported living with sheep and goats, and 7.7% reported a history of foreign objects entering the eye. The most common symptoms for those affected by Oestrus ovis were sudden onset, including a foreign body sensation and movement, redness, tearing, itching, swelling, irritation, photophobia, burning, and ocular secretion. In cases caused by Dermatobia hominis, symptoms included eyelid edema, pain, redness, itching, movement within the lesion, ocular irritation, and discharge. Regarding occupational or recreational activity, agriculture and livestock had the highest incidence, followed by trades and technical activities, being a student, and having traveled to an endemic region for work or recreation. Conclusion: Patients with red eyes may suffer from external ophthalmomyiasis, which requires a thorough examination to diagnose and treat it early. Moreover, as the temperature increases due to climate change, it is essential to consider how this will affect the spread of different pathogens. Specifically, the life cycle of Oestrus ovis is greatly influenced by temperature, which suggests that the incidence of ophthalmomyiasis will rise with warmer temperatures.

Following the adoption of the Kunming-Montreal Global Biodiversity Framework (KM-GBF), with the Convention on Biological Diversity serving as its guiding treaty, the European Union (EU) has just reached an agreement on an EU Nature Restoration Regulation. This study carries out a systematic cross-walk between the restoration regulation and the KM-GBF, focusing on their implications for forest ecosystems. This paper identifies areas of alignment, divergence, and potential gaps related to habitat restoration, species protection, climate resilience, and the sustainable use of natural resources. The methodology adopts a grounded approach, starting with the 23 targets outlined in the KM-GBF and proceeding to the 28 articles set out in the restoration regulation. The results highlight the need for better alignment between the KM-GBF, the restoration regulation, and other forest-relevant EU policy instruments. The study stresses the need for a coherent and integrated EU policy approach that can address the diverse challenges and policy objectives facing forests. It concludes that amendments to the restoration regulation have significantly diluted its potential impact, limiting the EU Members States accountability and ability to meet KM-GBF goals and targets. It further stresses the need for strategies that can reconcile divergent EU policy pathways, support forest management and restoration efforts, while aligning with global biodiversity objectives.

Whereas many carbon cycle models track CO₂ perturbations relative to a pre-industrial equilibrium, this paper uses absolute quantities to describe atmospheric CO₂ sinks, source and flow rates. This method, when combined with the notion of source and sink resistance, and a finite biospheric reservoir, accurately describes ¹⁴C levels between 1820 and 2020 using only five external parameters. The inputs are:- global records of fossil-fuel emissions, records of CO₂ mixing-ratio and listings of atmospheric atomic weapons tests. Over the same period ¹³C flows are also accurately described given a ð¹³C value for fossil fuel and a ð¹³C value for the initial background. This top-down approach differs from complex climate models since it circumvents the necessity to catalogue individual processes. The paper proceeds to use the method to examine the anthropogenic fossil-fuel emissions contributions during the period 1750 to 2020, deducing that around 24% remains in the atmosphere, while 76% has been absorbed in the land, terrestrial biosphere and surface ocean. During the same period 13% of the total CO₂ atmospheric concentration is due to fossil fuels. However, regarding the increase, fossil fuels contributed to 38% of the rise during this period.

To safeguard against meat supply shortages during pandemics or other catastrophes, this study analyzed the potential to provide the average household’s entire protein consumption using either soybean production or distributed meat production at the household level in the U.S. with: 1) pasture-fed rabbits, 2) pellet and hay-fed rabbits, or 3) pellet-fed chickens. Only using the average backyard resources, soybean cultivation can provide 80%-160% of household protein and 0%-50% of a household’s protein needs can be provided by pasture-fed rabbits using only the yard grass as feed. If external supplementation of feed is available, raising 52 chickens while also harvesting the concomitant eggs or alternately 107 grain-fed rabbits can meet 100% of an average household’s protein requirements. These results show that resilience to future pandemics and challenges associated with growing meat demands can be incrementally addressed through backyard distributed protein production. Backyard production of chicken meat, eggs, and rabbit meat reduces environmental costs of protein due to savings in production, transportation, and refrigeration of meat products and even more so with soybeans. Generally, distributed production of protein was found to be economically competitive with centralized production of meat if distributed labor costs were ignored.

Considering the landing gear's R/E hydraulic system is nonlinear in nature, identifying and isolating its defects is not straightforward. Using the power bond graph (BG), analytical redundancy relations (ARRs) are derived based on the fundamental principle of energy conservation. Boolean logic variables are then introduced to describe the operating state of the system, and finally, global analytic redundancy relations (GARRs) are produced. It is given the corresponding residuals from the GARRs and mapped to the fault signature matrix (FSM) for the purpose of assessing its detectability and isolation. Different progressive types of deficiencies have been studied, including filter blockage, actuator leaks, and landing gear selector valve reversing stuck. The residuals against threshold range results for the injected faults calculated in MATLAB/Simulink showed that this method can considerably detect the faults. In complex nonlinear systems, such as landing gear R/E hydraulic systems, the research methodology can be used to detect faults and monitoring of statuses.

This study examines the nexus between oil prices and inflation in G20 economies, addressing critical gaps by adopting a comparative approach across three pivotal oil price downturns in 2008, 2014, and 2020 (COVID-19). The study utilized monthly time series data from January 2000 to December 2023 and the Bayesian Structural Time Series (BSTS) approach for causal impact analysis. The study found that during the global financial crisis (December 2007 to June 2014), advanced economies like Australia and the UK displayed varying degrees of negative absolute causal impact, aligning with the deflationary impact of falling oil prices. In contrast, emerging economies faced significant negative causal impacts. From June 2014 to January 2020, diverse inflation impacts were observed across G20 economies after a significant oil price decline. Advanced economies like Australia and emerging economies like Brazil experienced negative impacts, while others showed negligible effects. In the subsequent period from January 2020 to December 2023, amid the COVID-19 pandemic and substantial oil price decline, G20 countries exhibited varied inflation outcomes. Positive absolute effects indicated a notable rise in inflation with China standing out with a substantial negative impact. The wavelet coherence analyses also showed an asymmetrical impact of oil prices on inflation. The findings suggest that policymakers should adopt proactive and adaptive policy frameworks, considering the asymmetric responses of G20 economies to oil price dynamics.

Climate change, recognized as a global crisis, is not only altering our environment but also significantly impacting human health. Particularly, its influence on non-communicable diseases (NCDs), a leading cause of global mortality, is becoming increasingly evident yet underexplored. This review aims to synthesize current research on the impact of climate change on NCDs, addressing a critical gap in our understanding of how environmental changes affect human health. We examine the complex interplay between climate change and NCDs, drawing insights from recent studies that highlight the adverse effects of climate variables on chronic diseases, such as cardiovascular and kidney diseases, and the role of food and nutrition security in this nexus. Furthermore, the review explores the disproportionate impact on vulnerable regions and populations, particularly in Pacific Island countries and territories, underscoring the urgent need for context-specific solutions and a cross-sectoral approach. By integrating findings from various disciplines, this review aims to inform policy and public health interventions, highlighting the necessity of collaborative efforts to mitigate the burgeoning burden of NCDs in a rapidly changing climate.

Background and Objectives Transpulmonary thermodilution has gained interest in recent years. It measures cardiac output (CO), stroke volume (SV), but also calculates global end diastolic indexed volume (GEDVI), and global ejection fraction (GEF). GEDVI is a static variable of cardiac preload. GEF provides information regarding cardiac function. GEF algorithm depends on SV and GEDVI. Therefore, in hypovolemic patients with decreased preload, SV or GEDVI could be decreased, and lead to altered GEF. The aim of our work was to evaluate whether impairment in GEDVI and SV may constitute a limitation for the interpretation of GEF in hypovolemic patients. A secondary objective was to determine factors independently associated with impaired GEF. Materials and Methods A retrospective study was conducted. Statistical analysis was performed by means of Mann Whitney and student t test. To determine correlation between GEF with SV, or GEF with GEDVI Pearson's coefficient was used. To determine factors independently associated with the presence of impaired GEF, binary logistic regression was performed. Results We included 113 patients with shock. Differences in mortality were detected in GEF (21[16-28] survivors versus 18 in non survivors[11-26]; p= 0.01). 38(34%) patients had hypovolemia. 44(39%) of them had depressed GEF values. Hypovolemic patients had lower GEF values than non-hypovolemic patients (16 [12-22] vs 20 [15-27]; p=0.01). Both SV and GEDVI had a statistically significant correlation with GEF (SV (Pearson's r 0.74; (p=0.00)) and GEDVI (Pearson's r -0.25; (p=0.00)). The only factors independently associated with low GEF were low SV and low GEDVI. Conclusion Hypovolemic patients frequently show low GEF values. We found correlation between SV and GEDVI with GEF. Low SV and low GEDVI were associated with low GEF. This could constitute a limitation in the interpretation of GEF and cardiac pump function. Hypovolemic patients could have low GEF without implying disorders in cardiac contractility.

Cultures in Mediterranean climate zones (MCZs) around the world have long been reliant on groundwater and springs as freshwater sources. While their ecology and cultural sustainability are recognized as critically important, inter-relationships between springs and culture in MCZs has received little attention. Here we augmented a global literature review with case studies in MCZ cultural landscapes to examine the intensity of cultural and socio-economic impacts on springs ecohydrogeology. MCZs are often oriented on the west and southern coasts in tectonically active landscapes, which control aquifer structure, the prevalence of westerly winds, and aridity, and generally expose associated habitats to harsh, afternoon sunlight. Cultural appreciation and appropriation of springs ranges widely, from their use as subsitence supplies to profound traditions, such as Greco-Roman nymphs, and Asian and Abrahamic spiritual cleansing and baptism. Commoditization of water resources for agriculture, industry (e.g., mining, water bottling, geothermal resorts), and urban needs is placing ever-increasing, non-sustainable demands on aquifers and springs. When economic values approach or exceed cultural values, these irreplaceable aquatic resources are degraded and lost. Sustainable stewardship of springs and the aquifers that support them are a little-recognized, but central conservation challenge for modern society facing global climate changes.

The aims of this paper are 1) to explore the type of industry of SMEs that can survive for more than 5 years in ASEAN, and 2) to analyze the success factors of SMEs in ASEAN to be able to survive for more than 5 years. This paper employs a qualitative method, with a literature review and meta-analysis. From 2007 to 2017, data was extracted from Google Scholar, Emerald Insight, Sage Pub, and EBSCO databases. There are 14 factors that influence the success of SMEs in the main sectors, 20 factors in the manufacturing sectors, and 14 factors in the service sectors, depending on the type of industry. For instance: eCommerce, technology, and social media, international oriented, good management system, government support, working condition /environment, skill and competency labour/owner, market penetration/selection, policy, organizational performance, and characteristics, networking with government /supplier / customer, networking with government /supplier /customer, planned /strategy (business /market /operational /organizational). The findings of this literature review reveal several important factors that are critical to the success of SMEs in competing with other industries and can be developed for a longer period.

Human disturbance, such as trampling, is an integral component of global change, yet we lack a comprehensive understanding of its effects on alpine ecosystems. Many alpine systems are seeing a rapid increase in recreation, and in understudied regions, such as the Coast Mountains of British Columbia, disturbance impacts on alpine plants remain unclear. We surveyed disturbed (trail-side) and undisturbed (off-trail) transects along elevational gradients of popular hiking trails in the T’aḵ’t’aḵ’múy̓in tl’a In̓inyáx̱a7n region (Garibaldi Provincial Park), Canada, focusing on dominant shrubs (Phyllodoce empetriformis, Cassiope mertensiana, Vaccinium ovalifolium) and graminoids (Carex spp). We used a hierarchical Bayesian framework to test for disturbance by elevation effects on total plant percent cover, maximum plant height and diameter (growth proxies), and buds, flowers, and fruits (reproduction proxies). We found that trampling reduces plant cover and impacts all species, but that effects vary by species and trait, and disturbance effects only vary with elevation for one species’ trait. Growth traits are more sensitive to trampling than reproductive traits, which may lead to differential impacts on population persistence and species level fitness outcomes. Our study highlights that disturbance responses are species-specific, and this knowledge can help land managers minimize disturbance impacts on sensitive vegetation types.

In the case of indigenous grapevine varieties, the aim of clonal selection is twofold: to improve their technological cultivation problem while preserving the varietal character. As the sensitivity of perennial crops to climate change becomes more pronounced, clonal selection, which is already very time-consuming for perennial woody crops, may take even longer. In Badacsony, clonal selection breeding of the ‘Kéknyelű’ and ‘Juhfark’ varieties was started in the early 2000s. The problem mentioned above in cultivation technology is the poor fertility of ‘Kéknyelű’ (functionally female-flowered variety), while in the case of ‘Juhfark’ the high susceptibility to grey rot (Botrytis). Based on 11 years of data significant difference in yield between clone B.2. and the base variety was found. In this comparison the year clusters also gave different values, as in years belonging to cluster 1 the ’Kéknyelű’ yielded more than in another year. Both clones of ‘Kéknyelű’ matured with significantly lower pH compared to the base variety. ‘Kéknyelű' is renowned for the distinctive variety character of its wine, which is said to be acidic. Given the acidic nature of ‘Kéknyelű’ wine and the expected increase in must degrees and pH due to climate change, these distinctions may be beneficial in the future. Daily meteorological parameters were also recorded in the years under study, and different indexes were calculated for both of varieties for different phenological periods. The years were classified into 3 clusters and the harvest data were analyzed within each cluster. In the case of 'Kéknyelű' our results revealed significant differences in yield between vintage clusters for clone B.2. However, clone B.1 demonstrated distinct KMW and pH values. Both 'Kéknyelű’ clones have produced a substantially higher incidence of Botrytis infection in cluster 2 years than in cluster 3 years. Botrytis infection only showed statistically significant differences between year clusters for ‘Juhfark’. It is intriguing that in most years, the rotting rate was lower in both clones, especially in year clusters 1 and 3 when the overall rate of Botrytis infection was quite low. Our results highlighted the year-round sensitivity of the two varieties studied and the difficulties of clonal selection.

Bread wheat (Triticum aestivum L.) is one of the world's most important staple food crop providing 20% global energy and dietary proteins. It is widely grown in sub-tropical and tropical areas and as such exposed to heat-stress especially at grain filling period (GFP). Global warming has further affected its production and productivity in these heat-stressed environments. We examined the effect of heat-stress on 18 morpho-physiological and yield-related traits in 96 bread wheat accessions. Heat susceptibility index (HSI <0.60) and yield stability (i <0.55) used as criteria for selecting the tolerant accessions. Heat-stress, imposed by delayed sowing, decreased crop growth and GFP, and as a result reduced morphological and yield-related traits, namely days to 50% anthesis, plant height, peduncle length, flag-leaf area, spike length, spikelets per spike, grain length and width, thousand grain weight (TGW), harvest index and yield. The reduction in the trait values was severe in susceptible accessions (48.2% yield reduction in IC277741) than the tolerant. Physiological traits like chlorophyll content, canopy temperature depression (CTD), normalized difference vegetation index (NDVI), plant waxiness and leaf rolling showed higher expression in the tolerant accessions under heat-stress. Scanning electron microscopy of matured wheat grains revealed ultrastructural changes in endosperm and aleurone cells caused due to heat-stress. The reduction of size and density of large starch granules is the major cause of yield and TGW decrease in the heat-stress susceptible lines. The most stable and high-yielding accessions namely IC566223, IC128454, IC335792, EC576707, IC535176, IC529207, IC446713 and IC416019 were identified as the climate-smart germplasm lines. Germplasm lines possessing desirable traits were selected as po-tential parents for the development of bi-parental and multi-parental populations.

In the paper, we explore the notion of global digital citizenship, particularly with respect to museums and cultural heritage organizations. In this perspectives study, we explore current examples of how museums can adapt to the tenets of global digital citizenship necessary to navigate and participate in increasingly interconnected digital worlds and culture, and to collectively address global challenges.

Sexually transmitted infections encompass considerable effects on human sexual and reproductive health. Its presence is ubiquitous despite decades of prevention and management. The present study has been conducted to provide an insightful bibliometric analysis of syphilis based on the Scopus repository. Therefore, given the dearth of a consolidated bibliometric analysis on Syphilis, this investigation aimed to compile the literature of the last century (1921-2021) to gain insight into the publications pertinent to the burden, diagnosis, treatment, and management of Syphilis. In this study, we have provided the year-wise, and subject-wise publications, type of articles, country, funding organizations, institutions, citations, and H-index. The data obtained from the Scopus database was exported to CSV file format and then converted to Microsoft Excel version for analysis to curtail the chances of error in the information. It has been evidenced that the USA possesses the highest track of proven publications. Therefore, this study considerably contributes to the future leaders, researchers & specialists/ clinicians of the domain

A large variety of fermentation products are used in food and feed production, but also in other industries, and many of these products are produced with genetically modified microorganisms (GMMs). In food and feed production, prominent examples are amino acids, vitamins, food and feed enzymes, colorants, non-caloric sweeteners and human milk oligosaccharides. From a regulatory perspective, fermentation products are typically produced under containment. This means that premises, equipment and work processes need to be designed to prevent or at least minimize release of GMMs into the environment. The fermentation products themselves should not contain any live cells of the GMM. Over the past years, there have been concerning developments, particularly in the European Union, stipulating that also absence of recombinant DNA might be interpreted as a regulatory requirement for fermentation products produced with GMMs. In this paper, we (i) attempt to place these developments into the historical context, (ii) sketch the potential negative repercussions for the food and feed industries, (iii) elaborate on the safety of recombinant DNA, and (iv) postulate that recombinant DNA should remain an integral part of the safety assessment of fermentation products but should not be misconstrued as a criterion for regulatory classification of products of biotechnology.

During the novel coronavirus disease (COVID-19) pandemic, several environmental factors have influenced the activities and the protection policy measures. This has had a major effect on climate change and global environmental catastrophe. In many countries, the strategy of closing various activities such as tourism, industrial production, stopped normal life, transportation, among others. This closure has a positive impact on the environment. However, the massive use of masks and personal protection could significantly increase pollution worldwide. The impact on the environment needs to be calculated to have information for public health actions. In this study, we present a first overview of the potential impacts of COVID-19 on some environmental matrices in Bogota, Colombia.

In this paper, impulsive control on a single-species Markovian jumping ecosystem leads to a stability criterion, and the newly-obtained theorems improve the related existing results. Numerical examples illuminate the effectiveness.

This paper concerns a new methodology for accuracy assessment of global positioning system verified experimentally with LiDAR (Light Detection and Ranging) data alignment at continent scale for autonomous driving safety analysis. Accuracy of GPS (Global Positioning System) positioning of an autonomous driving vehicle within a lane on the road is one of the key safety considerations. Safety is addressed as a geometry of the problem, where the aim is to maintain knowledge that the vehicle (its bounding box) is within its lane. Accuracy of GPS positioning is checked by comparing it with mobile mapping tracks in the recorded high definition source. The aim of the comparison is to see if the GPS positioning remains accurate up to the dimensions of the lane where the vehicle is driving. For this reason, a new methodology is proposed. Methodology is composed of six elements: 1) Mobile mapping system minimal setup, 2) Global positioning data processing, 3) LiDAR data processing, 4) Alignment algorithm, 5) Accuracy assessment confirmation and 6) Autonomous driving safety analysis. The research challenge is to assess positioning accuracy of moving cars taking into account the constraints of the coverage of limited access highways in the United States of America. The available coverage limits the possibility of repeatable measurements and introduces an important challenge being the lack the ground truth data. State-of-the-art methods are not applicable for this particular application, therefore a novel approach is proposed. The method is to align all the available LiDAR car trajectories to confirm the GNSS+INS (Global Navigation Satellite System + Inertial Navigation System) accuracy. For this reason, the use of LiDAR metric measurements for data alignment implemented using SLAM (Simultaneous Localization and Mapping) was investigated, assuring no systematic drift by applying GNSS+INS constraints. SLAM implementation used state-of-the-art observation equations and the Weighted Non-Linear Least Square optimization technique that enables integration of the required constraints. The methodology was verified experimentally using arbitrarily chosen measurement instruments (NovAtel GNSS+INS, LiDAR Velodyne HDL32) mounted onto mobile mapping systems. The accuracy was assessed and confirmed by the alignment of 32785 trajectories with total length of 1,159,956.9~km and of total $186.4*10^{9}$~optimized parameters (six degrees of freedom of poses) that cover the United States region in the 2016--2019 period. It is demonstrated that the alignment improves the trajectories, thus final map is consistent. The proposed methodology extends the existing methods of global positioning system accuracy assessment focusing on realistic environmental and driving conditions. The impact of global positioning system accuracy on autonomous car safety is discussed. It is shown that 99\% of the assessed data satisfies the safety requirements (driving within lanes of 3.6~m) for Mid-Size (width 1.85~m, length 4.87~m) vehicle and 95\% for 6-Wheel Pickup (width 2.03--2.43~m, length 5.32--6.76~m). The conclusion is that this methodology has great potential for global positioning accuracy assessment at global scale for autonomous driving applications. LiDAR data alignment is introduced as a novel approach to GNSS+INS accuracy confirmation. Further research is needed to solve the identified challenges.

In this paper, by considering Einstein-Hilbert-Bumblebee (EHB) gravity around global monopole field, we derive exactly a black hole spacetime metric. To test the effect of global monopole field and bumblebee field, which causes the spontaneous Lorentz symmetry breaking, we calculate the weak deflection angle using the Gauss-Bonnet theorem.

Indirect effects of global change via changing species interactions have been largely ignored in studies predicting global change impacts on ecosystems. Antagonistic biotic interactions, however, can strongly affect ecosystems and are likely to be affected by global change drivers themselves. We synthesize current knowledge on the impact of invertebrate herbivores and pathogens on plant productivity, diversity and community composition, and outline theory and expectations on how important global change drivers – nitrogen enrichment, climate change and elevated CO², and plant and insect diversity loss, may affect enemy impact on plant communities. We illustrate that our ability to predict global change impact requires a holistic perspective, taking into account direct as well as indirect effects via the biotic component of ecosystems.

This paper deals with the form, the stability character, the periodicity and the global behavior of solutions 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)).