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

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

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.

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.

There are now a wide variety of global metrics. To find the degree of overlap between these different measures, we employ a principal components analysis (PCA) to 15 indices across 145 countries. Our results demonstrate that the most important underlying dimension highlights that economic development and social progress go hand in hand with state stability. The results are used to produce categorical divisions of the world. The threefold division identifies a world composed of what we describe and map as Rich, Poor and Middle countries. A five-group classification provided a more nuanced categorization described as; The Very Rich, Free and Stable, Affluent and Free, Upper Middle, Lower Middle, and Poor and Not Free.

Cardiac surgery is a modern science in the history of medicine. The impact in cardiac disease, in term of treatment and prognosis, has made this discipline indispensable in the global health. In recent decades, the greatest investment has been dispensed in technological and material improvement, for increase the life expectancy. This surgery must address different epidemiological aspects dictated by the geography and economic-social conditions of the global populations. For this reason, it is progressively important to address the cardiac surgery accessibility disparity. Many scientific paper and international meetings have studied how cardiac surgery can increase accessibility in various countries around the world. In this review we analyze all the challenges, solutions and suggestions to make this surgery accessible to the entire global population, with the purpose to reducing the disparity across the all seven continents. For a long time, high-income countries have invested in technological capabilities and experimental advancement, not caring about unequal access in the rest of the world. We believe that it is time to reverse the growth trajectory, placing – as a priority – the accessibility and distribution of a surgical science, too significant for the right to health of all the people of the world. This is the real new challenge in cardiosurgery.

A global approach towards quality management highlights the need for constructing a new body of knowledge that views the field of global quality from a systems perspective. Based on the results of field experiments, and in light of the need to develop new global quality management terminology, the current article presents several key concepts in this field, with emphasis on a systems-oriented rationale and perspective. As such, the article is an important stage in building this body of knowledge, and towards the conceptualization of key variables used in global quality management, from a systems approach that interacts with the fields of international management and strategic management.

Nested structure is a structural feature that is conducive to system stability formed by the co-evolution of species in mutualistic ecosystems, and reflects the ability of ecosystem stability to be restored to a stable state again after being destroyed. The co-opetition relationship and value flow between industrial sectors in the global value chain are similar to the mutualistic ecosystem, and the pattern of the global economic system is always changing in dynamic equilibrium. Nestedness theory is used in this article to define the generalist and specialist sectors in the global value chain to analyze the changes in the global supply pattern. Then we study the mechanism of the global economic system to reach a stable equilibrium and the role of different sectors in the steady of the economic system, so as to provide countermeasures for enhancing the stability of the global economic system. At the end of the article, the domestic trade network, export trade network and import trade network of each country are extracted, and an econometric model is designed to analyze how the microstructure of the production system affects a country’s macroeconomic performance, thereby deriving the conclusion that the stability of the international trade network is crucial to a country's economic development.

The 2019 novel coronavirus (previously 2019-nCoV) or coronavirus infectious disease 2019 (COVID-19) outbreak has been summarized as on March 29, 2020. COVID-19 is a highly transmittable and pathogenic viral infection caused by severe acute respiratory syndrome coronavirus 2 (SERS-CoV-2). The disease was first seen during an outbreak in Wuhan, China and continuous spreading from human to human around the sphere. The disease is uncontrolled and increasing the death toll through. The world is facing a global challenge to protect human lives caused by coronavirus outbreak. The number of infected patients is increasing day by day due to COVID-19 as a pandemic. The world health organization (WHO) has declared global public health emergency on January 30, 2020. The disease has been spread around 201 countries with total confirmed cases 634835 and death cases 29891 as on March 29, 2020. The goal of this review to summaries and update the clinical/medical features and suggestions for diagnosis of the COVID-19 as a pandemic. The discussion of the various therapeutic algorithms, risk, prevention and control based on the latest reports has been provided.

Complaint of transient impairment or loss of memory as an attendant feature in some migraine attacks has long been recognised. In some cases, migraine may be a trigger or precipitating factor for the syndrome of transient global amnesia (TGA). However, the exact frequency of this concurrence is unknown, perhaps related to the absence from the International Classification of Headache Disorders (ICHD3) of amnesia or memory loss symptoms in association with migraine, unlike the situation with epileptic seizure (migralepsy) or stroke (migrainous infarction). Similarly, headache has generally been regarded as an incidental feature of TGA, reported in about 10% of cases. We present further examples of TGA in the context of migraine headache; consider possible reasons why this concurrence might be under-recognised, such as the retrograde amnesia characteristic of TGA; review possible shared pathogenetic mechanisms; and suggest a new terminology, “migramnesia”, which may encourage clinicians to address the possible significance of migraine in the context of an episode of TGA.

Global health is significantly impacted by antimicrobial resistance. Antibiotic misuse and overuse have resulted in the emergence of drug-resistant bacteria, viruses, parasites and fungi, which makes ordinary infections more difficult to cure and accelerates the spread of disease. The World Health Organisation has declared that antimicrobial resistance could result in up to 10 million deaths yearly by 2050, making it a worldwide health emergency. One of the greatest challenges to global health, food security, and development today, according to the World Health Organisation is the emergence of antibiotic resistance. Even though antibiotic resistance can arise naturally, improper usage of these medications and many other factors are accelerating its global spread. Antimicrobial resistance is frequently referred to as the "Silent Pandemic" and is a problem that requires current action and should be managed more effectively rather than considered as a future situation. This paper address a number of antimicrobial classes, global health, Onehealth and how drug resistance affects human health, and related risk factors. This review will also provide background information on the causes and processes of antimicrobial resistance in brief by identifying these characteristics, targeted interventions can be developed to lower the risk of illnesses that are resistant to antibiotics. It will also offer insights into new and emerging solutions that are being studied and may be created in the future to address the advancement of antimicrobial resistance.

This paper aims to introduce an overview of several aspects of the so-called Artificial Intelligence, their potential impacts on economic and social dimen- sions, and suggestions for possible approaches of investiment based upon effective and mature techniques. In this fashion, it is important to address from educational and academic issues to industrial densities and profiles, rel- atively to a given region, country or continent. Even etymological adequacy and psychological consequences of the denomination ”Artificial Intelligence” need some reflection, and suggestions for a lucid replacement are presented. In addition, suggestions about how can specific firms choose the right type of technique in order to improve profit and organizational efficiency. After all, what are the main transformations needed to amplify gains and structural improvements from the use of higher level technological mecha- nisms? Which connections can be established between the pillars of evolu- tionary economics and this field of knowledge? Which institutional contexts are able to benefit from AI tools, inducing constructive externalities to firms in terms of education, technical and scientific skills upgrading, so as to reach higher levels of employment in the long term and limit unemployment in the short one? Which branches of the so-called Artificial Intelligence are best suited to which types of activities? This work aims to contribute in the search for answers to these questions.

Since the turn of the millennium, many individuals and groups, including Diane Moore (2007), Stephen Prothero (2007), the American Academy of Religion (2010), and The National Council for the Social Studies (2014, 2017, 2021), have advocated for better religious literacy education (RLE) in K-12 curriculum and public schools. Despite these calls, RLE has yet to make significant inroads in K-12 curriculum and public schools. This paper aims to define religious literacy and RLE, provide current rationales for its inclusion in K-12 curriculum and public schools, identify barriers to RLE, and explore the potential of global competence in promoting RLE.

DNA methylation is an epigenetic mechanism for gene expression modulation and can be used as a predictor of future disease risks. A prospective birth cohort study was performed to clarify the effects of neurotoxicants on child development, namely, the Tohoku Study of Child Development, in Japan. This study aimed to evaluate the association of prenatal exposure to five toxic metals—arsenic, cadmium, mercury, lead (Pb), antimony (Sb), and polychlorinated biphenyls (PCBs, N = 166)—with global DNA methylation in umbilical cord blood DNA. DNA methylation markers, 5-methyl-2’-deoxycytidine (mC) and 5-hydroxymethyl-2’-deoxycytidine (hmC), were determined using liquid chromatography-tandem mass spectrometry. The mC content in cord blood DNA was positively correlated with Pb and Sb levels (r = 0.442 and 0.288, respectively) but not with cord blood PCBs. We also observed significant positive correlations among Pb levels, maternal age, and hmC content (r = 0.159 and 0.243, respectively). The multiple regression analysis among the potential predictors demonstrated consistent positive associations between Pb and Sb levels and mC and hmC content. Our results suggest that global DNA methylation is a promising biomarker for prenatal exposure to Pb and Sb.

Background: To inform global health policies and resources planning, this paper analyzes evolving trends in physical rehabilitation needs, using data on Years Lived with Disability (YLDs) from the Global Burden of Disease Study (GBD) 2017. Methods: Secondary analysis of how YLDs from conditions amenable to physical rehabilitation have evolved from 1990 to 2017, for the world and across countries of varying income levels. Linear regression analyses were used. Results: A 66.2% growth was found in estimated YLD Counts amenable to physical rehabilitation: a significant and linear growth of more than 5.1 billion YLDs per year (99%CI: 4.8–5.4; r² = 0.99). Low-income countries more than doubled (111.5% growth) their YLD Counts amenable to physical rehabilitation since 1990. YLD Rates per 100,000 people and the percentage of YLDs amenable to physical rehabilitation also grew significantly over time, across locations (all p > 0.05). Finally, only in high-income countries Age-standardized YLD Rates significantly decreased (p < 0.01; r² = 0.86). Conclusions: Physical rehabilitation needs have been growing significantly in absolute, per-capita and in percentage of total YLDs, globally and across countries of varying income level. In absolute terms, growths were higher in lower income countries, wherein rehabilitation is under-resourced.

The purpose of this disquisition is to analyze bullfighting, its advances and setbacks at a global and local level in terms of animal law. It was developed as a descriptive documentary research with a non-experimental design, using the observation and interpretation of documents related to the subject, from the global level, to the local, the national, specific to the regions and communities, being interpreted through the hermeneutic method. In the analysis, results were reached such as: every day more countries are willing to assume that bulls, because they are living beings that feel, are being attended to from the legal and the ethical, propitiating changes in the way of thinking of people in terms of wanting to consider bullfighting, a sport, art and hobby considered cultural heritage of many countries. For this reason, different actions have been generated from surveys, to define the acceptance or not of these events. It is concluded that there are important advances in this regard, as bullfighting is being prohibited in different parts of the world, taking into account the protection that protects animals, but the laws do not establish specific prohibition in this regard worldwide.

This paper explores the imminent threat posed by climate change to the unique platypus species. It delves into the ecological repercussions of global temperature rise and altered climate patterns on platypus habitats. The study emphasises the multifaceted impacts, including changes in aquatic habitat quality, food sources, and breeding rituals. Climate-induced shifts in phytoplankton spring blooms and anthropogenic pressures further endanger the platypus's habitat. The article stresses the importance of understanding these effects for both species conservation and anticipating broader ecological and socio-economic consequences. Mitigating climate change impacts requires a multidimensional approach, involving habitat manipulation and restoration strategies.

The decay of the low-mode internal tide due to the superharmonic energy cascade is investigated in a realistically forced global Hybrid Coordinate Ocean Model (HYCOM) simulation with 1/25 degrees (4 km) horizontal grid spacing. Time-mean and depth-integrated supertidal kinetic energy is found to be largest near low-latitude internal tide generation sites, such as the Bay of Bengal, Amazon Shelf, and Mascarene Ridge. The supertidal kinetic energy can make up to 50% of the total internal tide kinetic energy several hundred kilometers from the generation sites. As opposed to the tidal flux divergence, the supertidal flux divergence does not correlate with the barotropic to baroclinic energy conversion. Instead, the time-mean and depth-integrated supertidal flux divergence correlates with the nonlinear kinetic energy transfers from (sub)tidal to supertidal frequency bands as estimated with a novel coarse-graining approach. The regular spaced banding patterns of the surface-intensified nonlinear energy transfers are attributed to semidiurnal mode 1 and mode 2 internal waves that interfere constructively at the surface. This causes patches where both surface tidal KE and nonlinear energy transfers are elevated. The simulated internal tide off the Amazon shelf steepens significantly near these patches, generating solitary-like waves in good agreement with Synthetic Aperture Radar (SAR) imagery. Globally, we find that regions of high supertidal energy flux also show a high correlation with observed instances of solitary nonlinear internal waves.

Coronavirus (COVID-19) pandemic caused sicknesses ranging from mild to deadly, which disrupted lives and healthcare systems across the globe. Despite the availability of vaccines that are effective in significantly reducing the risks of death and severe dis-ease, misperceptions of COVID-19 vaccine safety, efficacy, risks, and mistrust in insti-tutions responsible for vaccination campaigns have been reported as factors contrib-uting to vaccine hesitancy, making vaccination rate not satisfactory, which resulted in some countries implementing mandatory covid-19 vaccination to increase vaccine up-take. This scoping review aimed at mapping global countries that have adopted the mandatory covid-19 vaccination and the reaction of citizens. PRISMA Extension for Scoping Reviews was used. Google Scholar was used to identify papers published in English from December 2019 to February 2022, irrespective of their methodology. One hundred forty studies were identified. After screening for duplication, access, and rel-evance, 24 were eligible for review. About eleven countries implemented mandatory vaccination, mostly among health workers. Citizens’ reactions towards the policy var-ied, with some in support of the policy but with a preference for the healthcare workers, and some in support but with the condition that it will only apply to travel, schools, and shopping areas, while others rejected the policy. Studies that may be relevant but were excluded due to eligibility criteria may be a limiting factor to this study. Several ethical considerations should be explicitly addressed when evaluating whether man-datory COVID-19 vaccination is an ethically justifiable policy option as recommended by the WHO policy brief.

Global warming is one of the problems of human civilization and decarbonization policy is the main solution to this problem. In this work, we propose an alternative method of using the gravity-assist by the asteroids to increase the orbital distance of the Earth from the Sun. We can manipulate the orbit of asteroids in the asteroid belt by solar sailing and propulsion engines to guide them towards the Mars orbit and a gravitational scattering can put asteroids in a favorable direction to provide an energy loss scattering from the Earth. The result would be increasing the orbital distance of the earth and consequently cooling down the Earth’s temperature. We calculate the increase in the orbital distance of the earth for each scattering and investigate the feasibility of performing this project.

This study aims to summarize the literature on sustainable global supply chain management so that researchers and practitioners can see the trends in the area in a single place. Systematic literature review (SLR) or Content analysis is used as a methodology of this literature review, studies that are published within the time frame of 2010 to 2020 are included in this literature. Dimensions to analyze each article includes; year of publications, methodology of research, data collection type, unit of analysis, industry, a country in which data is being collected, respondents’ types, the theory that is used in the study, dimensions of the sustainability and finally the purpose of study either it is to test the already existing theory or building up a new theory. I found that sustainable global supply chain management is an emerging field and there is potential in the area for researchers to explore the area.

A sufficient condition for the almost global sta-bility of nonlinear switched systems under average dwell timerestriction is obtained. This condition is derived leaning uponthe existence of multiple Lyapunov densities, which are associ-ated to subsystems and satisfy some compatibility conditions.An upper bound for the average dwell time that ensures almostglobal stability is obtained.

Background. Asbestos has been used for thousands of years but in a large industrial scale for about 100–150 years. The first identified disease was asbestosis, a type of incurable pneumoconiosis caused by asbestos dust and fibres. The latest estimate of global number of asbestosis deaths from the Global Burden of Disease estimate 2016 is 3495. Asbestos caused cancer was identified in the late 1930’s but despite of today’s overwhelming evidence of the strong carcinogenicity of all asbestos types including chrysotile it is still widely used globally. Various estimates have been made over time including those of WHO and ILO 107,000–112,000 deaths. Present estimates are radically higher. This special edition of the Journal summarizes key aspects of the past and present of the asbestos problem globally. Methods. Documentation on milestones of asbestos related diseases, ARDs, their recognition, reporting, compensation and prevention efforts were examined, in particular from the regulatory and prevention point of view. Estimated global numbers of incidence and mortality of ARDs were looked at. Results. Asbestos causes an estimated 257,000 deaths (243,223–270,635) annually according to latest knowledge. Work-related exposures are responsible for 235,000 deaths (222,322–247,363) of those. In the European Union, USA and in other High income economies (WHO regional classification) the direct costs for sickness, early retirement and death, including production losses, have been estimated to be very high, in the Western European countries and EU equivalent of 0.70% of the GDP or 114.9*109 USD. Intangible costs could be much higher. When applying the Value of Statistical Life (VSL) of 4 million EUR per cancer death used by the European Commission we arrived 5at 410*109 USD while the human suffering and loss of life is impossible to quantify. The numbers and costs are increasing practically in every country and region in the world. Asbestos has been banned in 55 countries but used widely today, some 2,030,000 tons consumed annually according to latest available consumption data. Every 20 tons of asbestos produced and consumed kills a person somewhere in the world. Buying 1 kg asbestos powder format e.g. in Asia costs some 0.38 USD and 20 tons would cost in such retail market 7600 USD. Conclusions. Present efforts to eliminate this man-made problem, in fact an epidemiological disaster, and preventing exposures leading to it are insufficient in most countries in the world. Applying programmes and policies, such as those on the elimination of all kind of asbestos use—that is banning of new asbestos use and tight control and management of existing structures containing asbestos—need revision and resources. The ILO/WHO Joint Programme for the Elimination of Asbestos-related Diseases need to be revitalized. Exposure limits do not protect properly against cancer but for asbestos removal and equivalent exposure elimination work we propose a limit value of 1000 fibres/m³.

Considering the sustained increase of dengue outbreaks in Latin America in recent years, this study proposes the use of machine learning (ML) tools with epidemiological data, meteorological climate parameters considering El Niño and La Niña (Niño 3.4 Index), and socioeconomic and demographic phenomena as a basis for the construction of an early warning system for dengue outbreaks in Zulia State, Venezuela. The study area covers 21 municipalities. Two ML models, support vector regression machine (SVM-R) and Gaussian process regression (GPR), were used. The data were used raw, standardised, and normalized for each model to be trained. The predictions of dengue outbreaks from the GPR and SVR algorithms show agreement with the dates of the real data; it was determined that there is a range of 2 to 3 weeks depending on the municipality. These coincide with previous studies showing that the algorithms do not work properly for some municipalities.

Introduction: Left ventricular dysfunction in an independent predictor of mortality in Chagas disease. Global longitudinal strain (GLS) is an emerging echocardiographic modality with possible incremental value in early detection of cardiac involvement. Objective: Compare left ventricular function with multiple echocardiographic parameters between patients with the indeterminate and chronic forms of Chagas and perform a literature review. Methods: In this observational study, 11 patients with a confirmed diagnosis of Chagas disease were evaluated. Individuals were distributed as follows: 5 with the indeterminate and 6 with the chronic forms. Conventional echocardiographic evaluation was followed by GLS measurement. Results: The mean left ventricle ejection fraction LVEF was 33 ± 2.88 and the mean GLS of the left ventricle was - 10.76 ± 2.20 in the chronic form as compared to 57.80 ± 6.49 and - 17.34 ± 3.82, respectively in the indeterminate group. Contractility was reduced in segments of the inferior, inferoseptal and anteroseptal walls in both groups. Conclusion: Analysis of longitudinal strain in the indeterminate form has potential incremental value to the conventional analysis of ejection fraction when compared to patients with chronic Chagas cardiomyopathy, especially with individual segmental analysis but the impact and clinical significance of these techniques is still unknown.

Introduction: The disease caused by Coronavirus-2019 (COVID-19) was initially described in December 2019. Severe acute respiratory syndrome type 2 (Sars-Cov-2) is responsible for an important multisystem inflammatory spectrum. Cardiovascular conditions have been reported with an estimated frequency of 8-28%. In this context, transthoracic echocardiography associated with the analysis of the two-dimensional Global Longitudinal Strain (GLS) of the left ventricle derived from Speckle Tracking emerges as a promising modality. Objective: This study aims to evaluate the applicability of GLS and segmental deformity assessment in detecting subclinical myocardial dysfunction in patients that recovered from COVID-19 infection. Methods: The observational study involved 18 patients (mean age 52 years) with recent evidence of COVID-19 infection that underwent detailed echocardiographic evaluation with GLS, and cardiac magnetic resonance (CMR) according to segmental assessment results. The degree of correlation between the methods was analyzed and a systematic literature review was also conducted. Results: The mean left ventricular ejection fraction (LVEF) was 57.50 ± 9.98%. Only 16.6% of patients had reduced LVEF. The average GLS was – 18.70 ± 3.54% and in 44% of cases only one myocardial segment was affected, particularly the inferolateral basal. CMR revealed inflammatory cardiomyopathy. Discussion: Subclinical myocardial involvement is associated with major adverse cardiac events. Literature review supports the use of GLS for detecting early cardiac involvement. Conclusion: Speckle-tracking echocardiography has been shown to have clinical utility in a variety of settings and to offer superior prognostic value with a potential to enhance subclinical detection of myocardial changes in patients after COVID-19 infection.

Global optimization is widely adopted nowadays in a variety of practical and scientific problems. In this context, a group of techniques that is widely used is that of evolutionary techniques. A relatively new evolutionary technique in this direction is that of Giant Armadillo Optimization, which is based on the hunting strategy of giant armadillos. In this paper, a number of modifications to this technique are proposed, such as the periodic application of a local minimization method as well as the use of modern termination techniques based on statistical observations. The proposed modifications have been tested on a wide - series test functions, available from the relevant literature and it was compared against other evolutionary methods.

A method of geoengineering/solar radiation management is proposed as global warming countermeasure. The idea is to decrease surface temperature by increasing stratospheric ozone. One-dimensional (vertical) radiative-convective equilibrium temperature calculations show that surface temperature can be lowered by increasing the amount of ozone in the stratosphere. It was the increase in altitude above about 25 km that reduced surface temperatures. The method of increasing the amount of ozone (O3 injection), the rate of decrease of surface temperature after the ozone increase, and the rate of decrease of ozone concentration by photochemical reaction and diffusion/transport after the ozone increase are discussed.

Natural montane peatlands generally are not a significant source of nitrous oxide (N₂O) due to environment limitation including phosphorus (P) scarcity and temperature lowness. Phosphorus enrichment and warming caused by global change are altering this limitation, likely to increase the source function of N₂O. However, the combined effects of P addition and warming on N₂O fluxes and biotic/abiotic factor in peatlands are still uncertain. To address this, we investigated the long-term (12 yrs) effects of P addition (5 and 10 kg ha^-1 yr^-1) and its interaction with warming on N₂O fluxes in a peatland. The results showed that although long-term P addition did not significantly affect the source/sink function of N₂O in the peatland, it stimulated enzyme activities, promoted peat decomposition. However, warming amplified the effect of P addition to increase N₂O emissions by stimulating enzyme activities and changing soil stoichiometry, even turned the peatland into a significant source of N₂O with an emission of approximate 100 g m^-2 during the growing season. Our study suggests that P enrichment under the current background of global warming will enhance the possibility of strong N₂O emissions in montane peatlands, which may increase the risk to further aggravate global warming.

Monkeypox is a rare disease which is rising nowadays in different countries since the first case in the UK was diagnosed on May 6, 2022, by the United Kingdom (UK) Health Security Agency. Then more than 12,500 cases were identified in over 68 countries up to July 18, 2022. In endemic areas, the monkeypox virus (MPXV) is commonly transmitted through zoonosis, while in non-endemic regions, it is spread through human-to-human transmission. Symptoms can include flu-like symptoms, rash, or sores in hands, feet, genitalia, or anus. In addition, people who did not take the smallpox vaccine were more liable to be affected than others. The exact pathogenesis and mechanisms are still unclear; however, most identified cases are reported in men who have sex with other men (MSM). According to the CDC, transmission can happen with any sexual or non-sexual contact with the infected person. However, a recent pooled meta-analysis reported that sexual contact is involved in more than 91% of the cases. Also, it is the first time that semen analysis for many patients has shown positive monkeypox virus DNA. Therefore, in this review, we will describe transmission methods for MPXV while focusing mainly on potential sexual transmission and associated sexually transmitted infections. We will also highlight the preventive measures that can limit the spread of the diseases in this regard.

Disaggregated population counts are needed to calculate health, economic, and development indicators in Low- and Middle-Income Countries (LMICs), especially in settings of rapid urbanisation. Censuses are often outdated and inaccurate in LMIC settings, and rarely disaggregated at fine geographic scale. Modelled gridded population datasets derived from census data have become widely used by development researchers and practitioners. These datasets are evaluated for accuracy at the spatial scale of the input data which is often much courser (e.g. administrative units) than the neighbourhood or cell-level scale of many applications. We simulate a realistic "true" 2016 population in Khomas, Namibia, a majority urban region, and introduce realistic levels of outdatedness (over 15 years) and inaccuracy in slum, non-slum, and rural areas. We aggregate these simulated realistic populations by census and administrative boundaries (to mimic census data), and generate 32 gridded population datasets that are typical of a LMIC setting using WorldPop-Global-Unconstrained gridded population approach. We evaluate the cell-level accuracy of these simulated datasets using the original "true" population as a reference. In our simulation, we found large cell-level errors, particularly in slum cells, driven by the use of average population densities in large areal units to determine cell-level population densities. Age, accuracy, and aggregation of the input data also played a role in these errors. We suggest incorporating finer-scale training data into gridded population models generally, and WorldPop-Global-Unconstrained in particular (e.g., from routine household surveys or slum community population counts), and use of new building footprint datasets as a covariate to improve cell-level accuracy. It is important to measure accuracy of gridded population datasets at spatial scales more consistent with how the data are being applied, especially if they are to be used for monitoring key development indicators at neighbourhood scales with relevance to small dense deprived areas within larger administrative units.

The purpose of this paper is to bring to light a method through which the global in time existence for arbitrary large in H¹ initial data of a strong solution to 3D periodic Navier-Stokes equations follows. The method consists of subdividing the time interval of existence into smaller sub-intervals carefully chosen. These sub-intervals are chosen based on the hypothesis that for any wavenumber m, one can find an interval of time on which the energy quantized in low-frequency components (up to m) of the solution u is lesser than the energy quantized in high-frequency components (down to m) or otherwise the opposite. We associate then a suitable number m to each one of the intervals and we prove that the norm ||u(t)||_H1 is bounded in both mentioned cases. The process can be continued until reaching the maximal time of existence T_max which yields the global in time existence of strong solution.

This paper introduces new improvements to the modified version of the BIRECT (BI secting RECTangles) algorithm referred to as BIRECTv. We explore various approaches, by first including a grouping strategy for hyper-rectangles having almost the same sizes by categorizing them into different classes. Therefore constraining them not to exceed a certain pre-defined threshold (a small positive value to define the tolerance level). This approach allows for more efficient computation and can be particularly useful when dealing with a large number of hyper-rectangles with varying sizes. To avoid over-sampling, and preventing redundant or excessive sampling, at some shared vertices in descendant subregions, a particular vertex database is used to limit the number of samples taken within each subregion to two. The experimental investigation shows that these improvements have a positive impact on the performance of the BIRECTv(imp.) algorithm and the proposal is a promising global optimization algorithm compared to the original BIRECTv algorithm and its variants. Additionally, the BIRECTv(imp.) algorithm showed particular efficacy in solving high-dimensional problems.

Despite continued efforts by educators, UN declarations and numerous international agreements, progress is still limited in handling major global challenges such as ecosystem collapse, accelerating climate change, poverty and inequity. The capacity to collaborate globally on addressing these issues remains weak. This systematic review of research on global learning for sustainable development (GLSD) aims to clarify the diverse directions research on GLSD has taken, to present the historical development of the research area, and highlight emerging research issues. The review summarises key findings of the English language literature in the period 1994-2020 identified with the search terms “global learning” and “sustainable development”, sustainability or GLSD, respectively. The review documented a gradually growing knowledge base, mostly authored by scholars located in the global North. Conclusions point to what we might achieve if we could learn from one another in new ways, moving beyond Northern-centric paradigms. It is also time to re-evaluate core assumptions that underlie education for sustainable development more generally, such as a narrow focus on formal learning institutions. The review provides a benchmark for future reviews of research on GLSD, reveals the emerging transformative structure of this transdisciplinary field, and offers reference points for further research

Amethod for the certification of local and almost global stability of invariant sets of ordinary differential equations on torus is proposed. The method is based on using trigonometric polynomials as candidates of local Lyapunov functions or (global) Lyapunov densities (so-called dual Lyapunov functions) and converting the required local Lyapunov or dual Lyapunov conditions into semidefinite programming. We provide several examples with three and four oscillators to showcase the adaptability of our results, which can be used to certify partial or complete phase-locking/phase-cohesion and to validate the presence of an attracting/repelling set in various scenarios.

Cerebral ischemic stroke poses a significant global cause of death, with ischemia-reperfusion injury contributing to neuronal cell death and tissue damage. However, significant therapeutic approaches with meaningful treatment effects for patients with ischemic stroke in actual clinical practice are lacking. This study investigated the potential neuroprotective effects of sildenafil, a phosphodiesterase-5 inhibitor, in a global cerebral ischemia model. We explored the impact of sildenafil on GFAP and AQP-4 expression, which are markers associated with astrocyte activation and water homeostasis, respectively. The immunofluorescence analysis revealed that the number of cells co-expressing the markers, which increased in the ischemia-induced group, was significantly reduced in sildenafil-treated groups, suggesting a potential mitigating effect on ischemia-induced astrocyte activation. Additionally, we conducted diverse behavioral tests, including the open-field test, novel object recognition, Barnes maze, Y-maze, and passive avoidance tests, to assess the effect of sildenafil on the cognitive function impaired by ischemia. Cognitive improvements were observed following sildenafil administration (20mg/kg) compared to the untreated group. Taken together, the results presented here suggest sildenafil's potential as a neuroprotective agent for alleviating delayed neuronal cell death and cognitive function impaired by ischemia.

Background: Evaluation of left ventricular(LV) functions in patients with idiopathic premature ventricular contraction(PVC) with preserved LV Ejection Fraction(LVEF), especially in the subclinical stage, may be of great importance in terms of directing early treatment. Methods: A total of 122 patients, retrospectively recruited, were divided into three groups according to PVC burden: Group 1; 5%PVC<10%, Group 2; 10%PVC<15%, and Group 3; 15% PVC. Transthoracic echocardiography(TTE) was performed to evaluate LV parameters. Results: LV-GLS was found to be significantly lower in groups 2 and 3 with high PVC burden (18.89 ± 1.4, 17.55 ± 2.1, 16.26 ± 1.3; p<0.001 respectively). Correlation analysis revealed a positive and significant correlation between PVC burden with deterioration in LV-GLS (r:0.536; p<0.001). In addition, PVC burden was found to be an independent predictor of LV-GLS deterioration in multiple linear regression analysis(:0.525, p<0.001). The ROC curve analysis demonstrated that a PVC burden cut-off value of 8.4% was associated with a LV-GLS deterioration greater than -18, with a specificity of 75.4% and a sensitivity of 75.4% (AUC: 0.81 [0.73-0.88] 95% CI; p<0.001). Conclusions: PVC burden was an independent predictor of deterioration in LV-GLS. In the presence of subclinical LV injury associated with PVC burden, early catheter ablation strategies may be therapeutically beneficial.

Previous studies have suggested that digitization of finance leads to growth in the economy in several middle- and high-income countries, but research in low- and lower-middle-income countries (LLMICs) remains limited. This research aimed to examine the trends, barriers, relationships, and prospects of finance digitization in LLMICs. This study used analytical and descriptive cross-sectional study designs. Sixty-six countries were purposively selected based on the available data on the Global Findex and the World Development Indicators databases. Descriptive analysis was used to identify the trends in the finance digitization indicators, correlation analysis was used to assess the nature of the association between finance digitization and the economy, and exponential smoothing was used to predict future outcomes in digital finance. The results indicated that the adoption and utilization of finance digitization increased in these countries, but the growth rates varied by region and income group. Low-income countries reported the highest rates of subscriptions to digital finance accounts and storing money in digital accounts, while lower-middle-income countries (LMICs) reported higher rates of inbound/outbound digital transactions, borrowings, and savings using digital channels. Sub-Saharan Africa reported the highest rates of digital finance account subscriptions, digital savings, and digital borrowings, while Europe and Central Asia reported the highest rates of in/out digital transactions. Barriers to digitization in these countries included poor access to the internet, high cost of digital finance products, and lack of a mobile phone, with low-income countries facing more challenges. The analysis revealed a negative significant relationship between finance digitization and Gross National Income growth and a positive significant correlation between finance digitization and other economic growth indicators (gross savings and Gross Domestic Product). Finance digitization was predicted to continue to rise in these countries for the next decade. The study recommended that policymakers should promote the adoption of digital finance and address the barriers and risks of finance digitization in LLMICs, as it had positive effects on economic growth.

Nowadays, higher education students play an active role in the realization of sustainable development goals (SDGs) for global citizenship. However, some important issues such as how much students know about these goals can play a role in achieving these goals are not yet clear. The aim of this study is to establish a fundamental study for determining the level of knowledge on the higher education students about SDGs. An open-ended questionnaire was conducted with the qualitative research methods on 54 higher education students after pandemic of COVID-19. As a result of the research, the goals of quality education, gender equality, health and quality of life, reduction of inequalities and peace, justice and strong institutions are the most frequently mentioned by the students. In addition, the opinions of the students on the subject of “sustainable cities and communities” are sequentially; the themes include ensuring socio-economic development, preserving cultural heritage identity, safe environment and durable buildings, as well as modern irrigation and waste methods, and reducing air pollution. On the other hand, they agreed on the need for global citizenship to have universal qualifications. In conclusion, global citizenship contributes directly to the SDGs and human-oriented production should be given more importance.

Semantic segmentation of remote sensing urban scene imagery is a pixel-wise prediction, which is applied to identify the land-cover or land-use category. However, semantic segmentation demands huge computation cost. In order to reduce the huge computation cost, a common method is to introduce transformer and CNN hybrid method to have a good trade-off between accuracy and computation cost. However, recent CNN-transformer hybrid methods often capture local-global context and cross-window interaction information simultaneously. Then they introduce the local-global context to fuse the local feature, which repeat fuse the local and global feature and result in the additional computation cost. And previous methods often ignore to filter the local and global feature. To fix the problem, we design a lightweight decoder-EDDformer, which is Efficient Global Value Transformer with Dynamic Gatefusion module. Efficient global value transformer only response for extracting global feature. Dynamic Gatefusion module filter the local and global semantic feature and fuse them to capture the local-global context in one time. Extensive experiments reveal that our method not only runs faster but also achieves higher accuracy compared with other state-of-the-art lightweight models.

The oncogenicity of the human cytomegalovirus (CMV) is debated to this day. In recent years, mounting evidence addresses an anti-cancer effect via T cell-mediated CMV-targeted tumor de-struction. However, the data mostly comes from single-center studies and in vitro experiments. Broad geographic coverage is required to offer a global perspective. This study examined the correlation between country-specific CMV seroprevalence (n=73) and age-standardized inci-dence rates for 34 tumors using data obtained from the International Agency for Research on Cancer of the World Health Organization. The association between CMV and cancer incidences in 10-year age increments was also analyzed. The study revealed a worldwide inverse correlation between CMV seroprevalence and incidences of 88.2% tumors. Notably, this inverse link persists for all cancers combined (Spearman’s ρ= -0.732, p= 0.001). An antithetical and significant correlation is also observed in particular age groups for the vast majority of tumors. Our results corroborate the conclusions of previous studies and indicate that this phenomenon holds true on a global scale. It applies to a wide spectrum of cancer histologies, suggesting a common under-lying mechanism – CMV-stimulated T cell tumor targeting. Although these results further advance the notion of CMV-based therapies, further in-depth investigation of host-virus interactions is warranted.

This book review addresses the contribution of Tim Marshall’s “The Power of Geography”. The purpose of this essay is to highlight the significant role of geography in shaping political landscapes, alliances, and global affairs through the book review. What is new about this essay is its accessible presentation of complex geopolitical concepts, making it a valuable resource for students of geography and readers interested in global politics. Through the analysis of case studies and historical background, the book illuminates the interplay between physical landscapes, territoriality, and power dynamics. The findings highlight the continuing influence of geography on nations, regional identities, and the evolving global order.

Contamination with Arsenic, a toxic metalloid, is increasing in the marine environment. Additionally, global warming can alter metalloids toxicity. Polychaetes are key species in marine environments. By mobilizing sediments, they play vital roles in nutrient and element (including contaminants) cycles. Most studies with marine invertebrates focused on the effects of metalloids on either adults or larvae. Here we bring information on the effects of temperature increase and arsenic contamination on the polychaete Hediste diversicolor in different growth stages and water temperatures. Feeding activity and biochemical responses – neurotransmission, indicators of cell damage, antioxidant and biotransformation enzymes and metabolic capacity - were evaluated. Temperature rise combined with As imposed alterations on feeding activity and biochemical endpoints at different growth stages. Small organisms have their antioxidant enzymes increased, avoiding lipid damage. However, larger organisms are the most affected class due to inhibition of superoxide dismutase, which resulted in protein damage. Oxidative damage was observed on smaller and larger organisms exposed to As and 21 °C, demonstrating higher sensibility to the combination of temperature rise and As. The observed alterations may have ecological consequences, affecting the cycle of nutrients, sediment oxygenation and the food chain that depend on the bioturbation of this polychaete.

This short report contains a result that characterizes almost global pullback attractor of discrete-time non-autonomous systems. Analogously to the multiple Lyapunov functions approach for switched systems, we show here that existence of multiple Lyapunov densities implies pullback convergence of almost all initial states to the origin for a discrete-time non-autonomous system.

Transient global amnesia (TGA) is an uncommon clinical syndrome characterized by a loss of short-term memory and disorientation that resolves in twenty-four hours. The etiology is unknown and the diagnosis is made by exclusion of other possible etiologies that may cause similar patterns and the reversibility of the condition in less than 24 hours. Here we report a 60-year-old male presented with sudden onset of disorientation and short-term memory loss early in the morning while at home and started to ask his whereabouts and what happened. He had no history of significant medical or psychiatric disease. There was no history of previous similar episodes. He had no recent history of sleep problems, head trauma, substance abuse, or loss of consciousness. He had no history of seizure disorder, or migraine. A neurologic examination revealed a normal wakefulness state with mild disorientation, and short-term memory impairment. He had score of 18/30 on mini-mental state examination (which later returned to normal baseline in 24 hours). Extensive lab investigations did not show any abnormal findings. Brain MRI did not show any acute cerebral pathology. The EEG was negative for any abnormal cerebral activity. His memory improved and returned to normal baseline over the course of a 20-hour from the onset. After exclusion of potential causes and the patient returned to normal state of memory, the diagnosis of transient global amnesia was made. At the follow-up visit, the patient was in a state of normal function without a recurrence of memory impairment. Here we presented this interesting case of transient global amnesia. TGA is diagnosis of exclusion and important to keep in mind when evaluating a patient with acute onset of short-term memory impairment, especially when etiological investigation revealed no potential cause.

Heat stress during the grain-filling period is the main abiotic stress factor limiting grain yield and quality in wheat (Triticum aestivum L.). In this study, 64 wheat genotypes were exposed to heat stress during reproduction caused by delayed sowing in two growing seasons. Grain yield, 1000 grain weight (GW), grain hardness (GH), and grain-quality related traits were investigated using wholemeal flour. Heat stress caused a significant decrease in GW through reducing starch content (SC) and a non-compensating rise in protein content (PC), and thereby resulted in lower yield. In addition, significant increases in flour water absorption (WA), Zeleny sedimentation volume (ZT), ash content (AC), lipid content (LC), loaf volume (LV), wet gluten content (WG), dry gluten content (DG), gluten index (GI), and amylopectin content (APC) were found following heat stress. In contrast, decreases in grain moisture content (MC) and amylose content (AMC) induced by heat stress were observed. The heat-tolerant genotypes were superior in grain yield, GW, SC, AMC, and MC. While the sensitive genotypes contained higher PC, LV, GI and AMP. A group of wheat genotypes characterized with a higher yield, AMC, GW, and SC as well as lower PC, WA, GH, ZT, and LV; and was found to be the most heat tolerant by principal component analysis. Decreases in the ratio of carbohydrates to proteins induced by heat stress, and lower protein content of normal grown wheat genotypes were observed. Therefore, lighter weight and smaller grains produce a smaller starchy endosperm with lower quality (less amylose) and higher grain protein content in heat stress compared to normal conditions. Heat stress caused by delayed sowing improves some of the baking-quality related traits. Whether this improvement in grain quality attributes will translate into better human health outcomes requires further investigation.

Serendipity favors the prepared mind, but how does the brain make that lucky find? Analyzing the cerebral mechanisms behind an exceptional (albeit trivial) discovery, the author suggests that a combination of ‘concept cells’ and the Global Neuronal Workspace Hypothesis could explain how we make great discoveries.

The usual equation for both motions of a single planet around the sun and electrons in the deterministic Rutherford-Bohr atomic model is conservative with a singular potential at the origin. When a dissipation is added, new phenomena appear which were investigated thoroughly by R. Ortega and his co-authors between 2014 and 2017, in particular all solutions are bounded and tend to $0$ for $t$ large, some of them with asymptotically spiraling exponentially fast convergence to the center. We provide explicit estimates for the bounds in the general case that we refine under specific restrictions on the initial state, and we give a formal calculation which could be used to determine practically some special asymptotically spiraling orbits. Besides, a related model with exponentially damped central charge or mass gives some explicit exponentially decaying solutions which might help future investigations. An atomic contraction hypothesis related to the asymptotic dying off of solutions proven for the dissipative model might give a solution to some intriguing phenomena observed in paleontology, familiar electrical devices and high scale cosmology

The usual equation for both motions of a single planet around the sun and electrons in the deterministic Rutherford-Bohr atomic model is conservative with a singular potential at the origin. When a dissipation is added, new phenomena appear. It is shown that whenever the momentum is not zero, the moving particle does not reach the center in finite time and its displacement does not blow-up either, even in the classical context where arbitrarily large velocities are allowed. Moreover we prove that all bounded solutions tend to $0$ for $t$ large, and some formal calculations suggest the existence of special orbits with an asymptotically spiraling exponentially fast convergence to the center.

The COVID-19 crisis has brought unprecedented strain on healthcare systems around the world. It has perhaps taught us some key lessons that are worth considering and addressing to help build more sustainable health systems as well as improve our ability to combat future epidemics.

Frailty is an important age-associated risk-state. Despite this, many countries lack population estimates and large heterogeneity exists amongst studies. The Global Burden of Disease (GBD) study, provides comparable high-quality population-level data for 195 countries and territories. Frailty has never been measured in the GBD studies. This analysis applies the deficit accumulation model to construct a novel frailty index (FI) using the GBD 2017 dataset. Standard FI criteria were applied to all GBD categories such that selected items were health-related, age-correlated, sufficiently prevalent, did not saturate at an early age, had little redundancy/duplication, covered a range of systems, were plausible and were available serially for the same population. From all 554 GBD items, 36 were selected including 26 non-communicable diseases, 3 metabolic risks, 3 biological impairments, infectious diarrheal diseases, protein-energy malnutrition, injurious falls, and low physical activity. Variable face validity was displayed against a selection of established FIs. The mean GBD-FI score for the global population aged ≥70 years in 2017 was 0.16; scores were higher in females than males (0.16 vs 0.15, respectively). Deficits accumulated with age at an estimated rate of 0.026 per year. Adding the mean GBD-FI scores to a regression model including country-level variables for demographics (proportion ≥85 years, proportion female), healthcare quality (HAQ index), and development (SDI) increased the adjusted r2 value from 27.0% to 39.6% (p<0.001) for predicting country-level death rates from non-communicable diseases, suggesting that the GBD-FI is a useful predictor of mortality. Further analysis is required to compare the reliability and predictive validity of the GBD-FI with existing frailty tools

This article aims to discuss, the stability and boundedness character of the solutions of the rational equation of the form \begin{equation}\label{eql21.1} y_{t+1}=\frac{\nu\epsilon^{-y_t}+\delta\epsilon^{-y_{t-1}}}{\mu+\nu y_t+\delta y_{t-1}},\quad t\in N(0). \end{equation} Here, $\epsilon>1, \nu,\delta,\mu\in (0,\infty)$ and $y_0, y_1$ are taken as arbitrary non-negative reals and $N(a)=\{a,a+1,a+2,\cdots \}$. Relevant examples are provided to validate our results. The exactness is tested using MATLAB.

The article mounts an argument for public theology as an appropriate if not vital adjunct to contemporary education’s addressing of security issues in light of current world events with indisputable religious and arguably quasi-theological foundations. It will briefly expound on the history of thought that has marginalized theology as a public discipline and then move to justify the counter view that the discipline, at least in the form of public theology, has potential to address matters of such public concern in a unique and helpful way. The article will culminate with an exploration of Global Jihadism as a case study that illustrates the usefulness of public theology in understanding it better and so allowing for a response with potential to be more informed and security-assured than is commonly effected.

The article mounts an argument for public theology as an appropriate if not vital adjunct to contemporary education’s addressing of security issues in light of current world events with indisputable religious and arguably quasi-theological foundations. It will briefly expound on the history of thought that has marginalized theology as a public discipline and then move to justify the counter view that the discipline, at least in the form of public theology, has potential to address matters of such public concern in a unique and helpful way. The article will culminate with an exploration of Global Jihadism as a case study that illustrates the usefulness of public theology in understanding it better and so allowing for a response with potential to be more informed and security-assured than is commonly effected.

Mpox, formerly known as Monkeypox, is a rare viral disease initially discovered in Africa in 1958. Since its first identification, several outbreaks have occurred in various African nations. Recently, the global community has witnessed a resurgence in the number of Mpox cases reported worldwide, prompting the World Health Organization (WHO) to declare the ongoing multi-country outbreak a public health emergency in July 2022. This study reports on the first cases of Mpox detected in Khartoum State, Sudan, outlining the epidemiology, preparedness, and public health response to this new challenge. A total of 55 suspected cases were identified, with two confirmed cases. The clinical manifestations observed in these cases align with the classic skin rash typical of Mpox, presenting alongside symptoms like fever, headache, and joint pain. The findings underscore the need for heightened surveillance, early detection, and timely intervention to prevent the domestic spread of Mpox and its potential impact on public health. Continued global efforts are needed to support effective screening, diagnostic, and control measures, ultimately enhancing preparedness and response in the face of this emerging disease.

Based on recent interest and on the importance of the ongoing climate change catastrophe, this article provides the basics of global carbon cycle modelling as required for the assessment of the degree of carbon neutrality of biomass energy, and its underlying dynamics. It is aimed at clari-fying the question “Are biomass fuels carbon neutral?”. The "Combined Energy and Biosphere Model" (CEBM) computes annual carbon flows including growth and decay of plants on 2.52.5° grid elements of the continents’ surface and offers detailed results on the changes of after implementation of large-scale biomass energy strategies world-wide. The main (and possibly unexpected) effect is the long-term depletion of the soil organic compartment after extraction of biomass fuels. When comparing CEBM model runs using (i) biomass energy sources and (ii) carbon-free energy sources (such as solar or wind), it becomes quantitatively clear already on the theoretical level (i.e., even without taking into account effi-ciency losses) that biomass is only “half as carbon neutral” as ideally assumed, to express a rule of thumb – mainly because of soil carbon depletion. Still, biomass energy will play an important role when fighting global warming, even if efforts to lower energy demand are preferable as a fundamental strategy.

This study presents the first genome assembly of the freshwater saprobe fungus Neonectria lugdunensis and a comprehensive phylogenomics analysis of the Nectriaceae family, examining genomic traits according to fungal lifestyles. The Nectriaceae family, one of the largest in Hypocreales, includes fungi with significant ecological roles and economic importance as plant pathogens, endophytes, and saprobes. The phylogenomics analysis identified 2684 single-copy orthologs, providing a robust evolutionary framework for the Nectriaceae family. We analyzed the genomic characteristics of 17 Nectriaceae genomes, focusing on their carbohydrate-active enzymes (CAZymes), biosynthetic gene clusters (BGCs), and adaptations to environmental temperatures. Our results highlight the adaptation mechanisms of N. lugdunensis, emphasizing its capabilities for plant-litter degradation and enzyme activity in varying temperatures. Comparative genomics of different Nectriaceae lifestyles revealed significant differences in genome size, gene content, repetitive elements, and secondary metabolite production. Endophytes exhibited larger genomes, more effector proteins, and BGCs, while plant pathogens had higher thermo-adapted protein counts, suggesting greater resilience to global warming. In contrast, the freshwater saprobe shows less adaptation to warmer temperatures and is important for conservation goals. This study underscores the importance of understanding fungal genomic adaptations to predict ecosystem impacts and conservation targets in the face of climate change.

Ocean exploration is crucial for utilizing its extensive resources. Images captured by underwater robots suffer from issues such as color distortion and reduced contrast. To address the issue, we propose an innovative enhancement algorithm that integrates Transformer and Convolutional Neural Network (CNN) in a parallel fusion manner. Firstly, a novel transformer model is intro-duced to capture local features, employing peak-signal-to-noise ratio (PSNR) attention and linear operations. Subsequently, to extract global features, both temporal and frequency domain features are incorporated to construct convolutional neural network. Finally, the Fourier’s high and low-frequency information of the original image are utilized to fuse different features. To demon-strate the algorithm's effectiveness, underwater images with various levels of color distortion are selected for both qualitative and quantitative analyses. The experimental results demonstrate that our approach surpasses other mainstream methods, achieving superior PSNR and structural sim-ilarity index measure (SSIM) metrics and leading to a detection performance improvement of over ten percent.

In this study, we develop a stochastic partial differential equation (SPDE) model to assess the regional severity of temperature increases due to global warming. The model incorporates various stochastic processes to account for uncertainties such as solar explosions, economic upheavals, rising emissions, and irreversible changes in the climate system. Our base temperature model, influenced by latitude, is enhanced by these random factors to simulate realistic and diverse outcomes of climate change. Numerical simulations on a global grid provide a heatmap representing potential temperature increase severity across different regions. The results highlight the significant impact on tropical and polar regions, demonstrating the utility of SPDE models in understanding and predicting the complex dynamics of climate change. This approach offers valuable insights for policymakers and researchers aiming to develop adaptive strategies for mitigating the adverse effects of global warming.

Using a sample of 103 surviving and non-surviving global bond funds over a long sample period of 1998 to 2022, we perform a comprehensive analysis of the funds under our modified Sharpe’s (1992) style analysis model. We find that dynamic style analysis is useful in explaining time-series and cross-sectional and in predicting future returns of global bond funds. The dynamic style analysis also allows us to examine asset allocation over time. The results show that, during 2001 to 2014, funds shift their allocations from intermediate-term bonds to world corporate bonds and from world corporate bonds to emerging market bonds in search of higher returns at the price of credit quality.

(1) Background: Multiple alterations of cellular metabolism have been documented in experimental studies of autosomal dominant polycystic kidney disease (ADPKD) and are thought to contribute to its pathogenesis. (2) Methods: To elucidate the molecular pathways and transcriptional regulators associated with the metabolic changes of renal cysts in ADPKD, we compared global gene expression data from human PKD1 renal cysts, minimally cystic tissues (MCT) from the same patients, and healthy human kidney cortical tissue samples. (3) Results: We found PKD1 renal cysts displayed the Warburg effect with gene pathway changes favoring increased cellular glucose uptake and lactate production, instead of pyruvate oxidation. Additionally, mitochondrial energy metabolism was globally depressed, associated with downregulation of gene pathways related to fatty acid oxidation (FAO), branched-chain amino acid (BCAA) degradation, the Krebs cycle, and oxidative phosphorylation (OXPHOS) in renal cysts. Activation of mTORC1 and its two target proto-oncogenes, HIF-1α and MYC, was predicted to drive the expression of multiple genes involved in the observed metabolic reprogramming (e.g., GLUT3, HK1/HK2, ALDOA, ENO2, PKM, LDHA/LDHB, MCT4, PDHA1, PDK1/3, MPC1/2, CPT2, BCAT1, NAMPT); indeed, their predicted expression patterns were confirmed by our data. Conversely, we found AMPK inhibition was predicted in renal cysts. AMPK inhibition was associated with decreased expression of PGC-1α, a transcriptional coactivator for transcription factors PPARα, ERRα, and ERRγ, all of which play a critical role in regulating oxidative metabolism and mitochondrial biogenesis. (4) Conclusions: These data provide a comprehensive map of metabolic pathway reprogramming in ADPKD and highlight nodes of regulation that may serve as targets for therapeutic intervention.

The conventional well placement was done manually by using a numerical reservoir simulator, and it required a lengthy trial-and-error process. It required great experience and expertise to manipulate the variables and uncertainties that lie on the reservoir to determine the best placement of the well. In addition, the traditional gradient-based methods such as Line-search and Trust-region were not viable in terms of maximum results obtained. Gradient-based methods were too dependent on the surface gradient of the solution and may only converge to local optima instead of global optima. Complex reservoirs have rough surfaces with high uncertainties, which hinders the traditional gradient-based method from converging to global optima. Thus, genetic algorithms were utilized to automate the manual trial-and-error process and to overcome the limitations of the traditional gradient-based method. The objectives of this study were to analyse the effect of different initial well placement distributions, the number of random solution sizes, and the crossover rate on cumulative oil production. A synthetic reservoir model built using CMG Builder was used as the testing platform for the optimization problems. Well-placement parameterization and optimization set-up were carried out using the CMG CMOST optimization tool. The integration of CMG IMEX and CMOST optimized cumulative oil production based on the objectives of the study. The results obtained showed that the higher number of random solutions used resulted in higher cumulative oil production, with more generations needed to reach the optimum solution. It can be concluded that the larger number of random solutions used increased the probability of reaching the optimum solution, but will take more generations.

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

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

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

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

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

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

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

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

This study aimed to investigate the diagnostic potential of circulating microRNAs (miRNAs) for detecting early myocardial fibrosis development in HFpEF patients. This observational study used a case-control research design. Peripheral blood samples were isolated from 25 HFpEF patients and 25 normal patients. They were measured for NTproBNP levels using ELISA, as well as MicroRNA-1, 21, and 29 levels using RT-PCR. All patients also underwent echocardiography for global longitudinal strain (GLS) to measure the myocardial fibrosis progression. Data were analyzed using SPSS 25.0. HFpEF patients had significantly higher GLS compared to the normal patients (-13±2.4% vs -19±3.2%; p &lt; 0.05), suggesting HFpEF patients tended to have myocardial fibrosis. HFpEF patients also had significantly higher microRNA-1 and microRNA-21 compared to the normal patients (p &lt; 0.05), but they had lower microRNA-1 (p &lt; 0.05). There was a positive correlation between microRNA-1 (r = 0.753; p &lt; 0.05) and microRNA-21 (r = 0.675; p &lt; 0.05) and an inverse correlation with microRNA-29 (r = -0.653; p &lt; 0.05) based on the GLS findings. By using a GLS cutoff of -15% for myocardial fibrosis, microRNA-1, microRNA-21, and microRNA-29 were found to be able to predict myocardial fibrosis based on GLS with a specificity of 78% and sensitivity of 75%. Increasing microRNA-1 and microRNA-21 followed by decreasing microRNA-29 in HFpEF patients suggest early myocardial fibrosis.

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

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

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

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

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

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

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

The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, statistics and data (e.g., local monitoring of Sustainable Development Goals - SDGs) are hindered by the unavailability of spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, which has been captured in existing literature with a strong focus on household-level deprivation while giving limited attention to area-level deprivation. Within this scoping review, we build on existing literature on household- as well as area-level deprivation frameworks to arrive at a combined understanding of how urban deprivation is defined with a focus on LMIC cities. The scoping review was enriched with local stakeholder workshops in LMIC cities to arrive at our framework of Domains of Deprivations, splitting deprivation into three different scales and nine domains. (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) city Governance (Area Connect scale). The Domains of Deprivation framework provides a clear guidance for collecting data on various aspects of deprivation, while providing the flexibility to decide at city level which indicators are most relevant to explain individual domains. The framework provides a conceptual and operational base for the Integrated Deprived Area Mapping System (IDEAMAPS) Project for the creation of a data ecosystem, which facilitates the production of routine, accurate maps of deprived “slum” areas at scale across cities in LMICs. The Domains of Deprivation Framework is designed to support diverse health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities.

Influenza epidemics in temperate regions display dynamics that are characterized by pronounced seasonal peaks during the winter. The general lack of influenza cases during the off-season may result from the virus physically disappearing at the end of the season, in which case it must be imported annually. Alternatively, it may result from persistent asymptomatic carriers or unnoticed local transmission chains that develop into local epidemics as conditions become conducive. Here I attempt to understand these differing explanations by analyzing the global distribution of the four major subtypes that comprise influenza over a period of 18 years based on FluNet data, the surveillance network and database compiled by the WHO, and the NCBI influenza data resource, a repository of relevant genetic information. Examining the annual proportion of each subtype, I find considerable variations in subtype annual proportions between the regions. Moreover, I find that seasonal influenza subtypes can remain confined to specific temperate regions, without showing measurable global presence. These results indicate that although largely undetected during the off-season, influenza is likely to persist locally, and imply a ‘local-global’ model where annual influenza epidemics are a mixture of local strains undergoing reactivation together with an influx of global variants.

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

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

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

Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path traced results, but with a greatly reduced computational complexity allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.

In this paper, we investigate the equilibrium points, stability of two equilibrium points, convergences of negative equilibrium point, periodic solutions, and existence of bounded or unbounded solutions of a system of nonlinear difference equations x_n+1 =x_n-1y_n - 1, y_n+1 = y_n-1x_n - 1 n = 0,1,..., where the initial values are real numbers. Additionally we present some numerical examples to verify our theoretical results.

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

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

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

Bio-economy is a major area of the strategy that must enable the European Union to achieve growth: smart, through the development of knowledge and innovation; and sustainable, based on a greener, more efficient economy in resource management. We believe that the progress of bio-economy cannot be achieved without the harnessing of intellectual capital. Our research aimed to emphasize the benefits of the dynamics of the intellectual capital growth on the evolution of the bio-economy. The aim of this analysis was to study the established link between the Energy Intensity of the Economy (EIE) and a number of factors that can measure the intellectual capital, such as: Market Capitalization of Bitcoin, Patent applications listed by European Patent Office and the Turnover from Innovation as a proportion of the total Turnover. The ultimate goal was represented by the generation of a regression model to see what factor influences mostly the progress of the bio-economy at European and Romanian level.

Myocardial deformation imaging (strain imaging) is a technique to directly quantify the extent of myocardial contractility and overcomes several of the limitations of ejection fraction. The application of the most commonly used strain imaging method; speckle-tracking echocardiography to patients with sepsis cardiomyopathy heralds an exciting development to the field. However; the body of evidence and knowledge on the utility, feasibility and prognostic value of left ventricular global longitudinal strain in sepsis cardiomyopathy is still evolving. We conducted a review of literature on utility of left ventricular global longitudinal strain in sepsis cardiomyopathy. We discuss the role of left ventricular global longitudinal strain in mortality prediction, utility and limitations of the technique in the context of sepsis cardiomyopathy.

The present article provides a thorough examination of innovationology, a groundbreaking transdisciplinary field of study that is revolutionizing the concepts and methods associated with innovation, economic growth, and worldwide sustainable transformation. This work provides unparalleled insights into the transformative potential of innovationology, drawing on a comprehensive review of literature across diverse fields such as development economics, sustainability science, social entrepreneurship, transition studies, complexity theory, decolonial thought, and design thinking. In presenting innovationology as a force for systemic, multidimensional economic change, the paper explores the strong theoretical underpinnings, creative approaches, and elite case studies that highlight the groundbreaking science's extraordinary influence. Through a rigorous, evidence-based examination, the author provides policymakers, researchers, and practitioners with a comprehensive understanding of innovationology's capacity to redefine the principles and practices of wealth creation, inclusive growth, sustainable finance, and community-centric entrepreneurship. Anchored in real-world case studies from the Global North and South, the article demonstrates innovationology's potential to drive progress towards a more equitable, resilient, and prosperous global economy. By challenging dominant neoclassical paradigms and offering a decolonial, transdisciplinary framework for economic transformation, this work presents a groundbreaking pathway to a just, sustainable, and inclusive economic future.

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

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

Since the Industrial Revolution, nearly 700 GtC of carbon have been emitted into the atmosphere as CO2 derived from human activities, of which 292 GtC remain uncontrolled. Furthermore, the emission rate is increasing yearly, with the latest value (2022) of 11 GtC. By the end of this century, the atmospheric CO2 concentration is predicted to surpass 700 ppm. The effects of this sudden carbon release on the worldwide biogeochemical cycles and balances are not yet fully understood, but it is undeniable that global warming and climate change are already a fact, with this gas playing a starring role. Governmental policies and international agreements on emission reduction need to produce results quickly enough, and the deadline to act is running out. Besides the agreements to reduce emissions, alternative strategies to reverse this trend must be sufficiently promoted. Biological CO2 capture is a speedy flow of the carbon cycle capable of capturing over 115 GtC annually through photosynthesis. An increase of 6.5% in this capture and the subsequent stabilization of produced biomass could counteract the current CO2 emission rate. In this overview, the artificial culture of phytoplankton is considered a potential alternative to conducting this large-scale capture. A production system model is suggested and the main technological and political challenges for using large areas as partially-natural photobioreactors are discussed. The global implementation of these large CO2 sinks and the associated infrastructure would stabilize the carbon cycle while it is developed as a new source of richness.

The digital transformation of the global economy presents new challenges and opportunities for businesses and nations. With the growing role of digital technologies and the dynamic changes in the structure of the economy, there is a need for a better understanding of the processes shaping contemporary enterprises. This article analyzes the impact of digital transformation on businesses and the global economy, identifying key areas where these changes are most evident. As part of this discussion, a modification of the “9 Pillars of Industry 4.0” concept is proposed, incorporating solutions that have emerged since its inception. The resulting model, “11 Pillars of Industry 4.0,” enabled the analysis of the “born digital” and “born global” concepts, highlighting their numerous common features in the context of the digital transformation of economies. This became the basis for proposing a new concept: “born digibal” — enterprises that from the outset operate in multiple markets, with their main sphere of activity based on digital solutions.The conclusions of the article provide an assessment of the changes occurring in businesses and the global economy in the digital age. They suggest that the dynamics of globalization in the 21st century will be shaped by complex interactions between digital transformation and the actions of businesses and nations, requiring flexibility and innovation in adapting to new economic realities.

This paper presents a critical review of key issues related to the emergence of new networks for the spread of zoonotic diseases amid the mass extinction of species. Zoonotic and infectious diseases account for approximately 70% of new and existing diseases affecting humans and animals. The initial section argues that the term "zoonoses" should not be confined to single-cause events within veterinary medicine. Instead, zoonoses should be viewed as complex, systemic phenomena shaped by interrelated factors, including environmental, sociocultural, and economic elements, influenced by anthropogenic climate change. The second section presents bioethical principles and potential strategies for those engaged in zoonotic disease prevention. The third section uses the slaughter of animals in disaster settings as a case study to illustrate the need for further clarification of normative and interspecies justice conflicts in One Health ethics. This section concludes with an outlook on "zoonoethics." Section four develops the analysis of the interlinked elements that trigger zoonoses and examines antimicrobial resistance (AMR) from an ethical and political standpoint, concluding with policy recommendations for addressing AMR. Section five offers a critical reflection, integrating contributions from zoonoethics, human ecology, and the ecotheological turn. Finally, section six concludes with a call to action and policy recommendations for an inclusive, intercultural, and gender-sensitive One Health approach.

The aim of the present study was to predict the response of non-small cell lung cancer (NSCLC) patients to immune checkpoint inhibitors (ICIs) by leveraging computed tomography (CT) images using deep learning techniques. Retrospectively, 624 sequential CT images were gathered from 156 patients at Jiangsu Province Hospital, along with their clinical data. The dataset was subsequently partitioned into three groups: training (n=547), validation (n=64), and test (n=64). Moreover, an external validation cohort included 37 CT images from patients at Nanjing Pukou Peoples' Hospital, accompanied by comprehensive clinical data. An advanced Video Vision Transformer (ViViT) model incorporating global self-attention was utilized to analyse patients treated with ICIs and predict their response. The ViViT model's efficacy was evaluated using a confusion matrix and a receiver operating characteristic curve (ROC). Notably, the ViViT model demonstrated predictive prowess for ICIs response, yielding respective areas under the receiver operating characteristic curve (AUC) of 0.74 (95% CI: 0.69-0.78), 0.74 (95% CI: 0.61-0.86), 0.76 (95% CI: 0.62-0.88), and 0.69 (95% CI: 0.5-0.87) in the training, validation, test, and external validation cohorts. The present study illustrates how a deep learning model can provide a non-invasive means to predict clinical outcomes in NSCLC patients undergoing ICIs, potentially transforming personalized treatment approaches for individuals with NSCLC.

Ruminant animals naturally emit methane gas owing to anaerobic microbial fermentation in the rumen, and these gases are considered major contributors to global warming. Scientists worldwide are attempting to minimize methane emissions from ruminant animals. Some of these attempts include the manipulation of rumen microbes using antibiotics, synthetic chemicals, dietary interventions, probiotics, propionate enhancers, stimulation of acetogens, manipulation of rumination time, vaccination, and genetic selection of animals that produce low methane (CH4). The majority of synthetic additives are harmful to both beneficial rumen microbes and the host or only temporarily affect methanogenesis. Phytogenic feed additives (PFAs) have recently emerged as the best alternatives to antibiotics and synthetic chemicals because of growing public concerns regarding drug resistance and the negative impacts of antibiotics and synthetic chemicals on humans, livestock, and the environment. These additives reduce methane production and improve the volatile fatty acid profile. In this review, we provide an overview of PFA sources and how their bioactive components affect the rumen microbiome to reduce methane emissions. Additionally, we highlight the mechanisms of action of PFAs as a whole as well as some of their bioactive components.

The principal function of science education is to introduce students to core scientific concepts and practices; nevertheless, it is now impossible, in such a complex world, to neglect the ethical issues involved. Placing school science in a broader context motivates students and equips them with valuable critical skills. A meaningful example was from palm oil production and pervasive use worldwide: plantations result in major deforestation occurring in species-rich tropical regions, making the palm oil issue global in scope and highly critical for several aspects related to sustainability. This paper reports a sequence of didactic activities starting from palm oil chemistry, gradually extended initially by a multidisciplinary approach, then by interdisciplinary-systemic maps and, ultimately, through a holistic vision - involving anthropological and cultural considerations about indigenous people of deforested territories. This progressive broadening corresponds to an ever-greater penetration into the personal sphere, a condition for a real ethical consciousness. The increased students’ awareness was tested by qualitative considerations, supporting the teaching dimension more than the learning one. Contrary to disciplinary contents, the emergence of moral feelings cannot be measured but only perceived. Therefore, chemistry provides key concepts essential for global competences development in order to deal with sustainability issues with an increased ethical awareness.

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