Panax ginseng C. A. Meyer (P. ginseng), has been widely used in traditional Chinese medicine (TCM). It contains a number of chemical components and possesses a variety of pharmacological activities. Alzheimer's disease (AD) is neurodegenerative disease that creates a huge burden on the lives and health of individuals. In recent years, studies have indicated that the chemical components of P. ginseng, especially ginsenosides, play a pronounced positive role in the prevention and treatment of neurological diseases. This review aimed to summarize currently studies on chemical components and the mechanisms action in AD intervention treatment of P. ginseng, especially ginsenosides. In this review, the components of P. ginseng and their respective active effects were first introduced. Then the key molecular mechanisms and signaling pathways of P. ginseng were introduced, and its different active ingredients in the prevention and treatment of Alzheimer's disease-related pathogenesis were also summarized from the pathogenesis of AD Aβ generation and aggregation, hyperphosphorylation of tau protein，oxidant stress，neuroinflammation，mitochondrial damage，disorder of neurotransmitter and gut microbiota. Signaling pathway networks related to the action of ginseng active ingredients was constructed, which could serve as a therapeutic target for Alzheimer's disease. In addition to a detailed report on P. ginseng in improving Alzheimer's disease-related pathogenesis, the application of the current technology, spatial metabonomics in AD therapeutics and diagnostics were later discussed. Spatial metabonomics could be applied to investigate the multi-target intervention of P. ginseng on Alzheimer's disease. Research perspectives for the study of P. ginseng in the treatment of Alzheimer's disease were provided for further studies.

The research is a deep study of the CBOE Volatility Index (VIX), which represent the market sentiments of the S & P 500 Index (SPX) over a period of 33 years. It evaluates how the two indexes perform in the stock market crash and how reliable VIX is in predicting market sentiments. The research distributes the market rally in two forms, and one is a trust rally, when investors are happy to see the market in a stable form, and investors' sentiments are positive towards the stock market. Second is a fear rally, where investors' sentiments are negative, and their outlook is bearish for various reasons. It observes the pattern of rallies, like the longest trust or fear rally, in which year and its duration. The research analyzes data to reach a meaningful conclusion and various inferences that can be drawn from the study of historical data.

When 2−1/Q<p≤2, we establish the C^{0,1} and C^{1,α}-regularities of weak solutions to quasi-linear p-Laplacian type non-homogeneous equations in the Heisenberg group.

Paenibacilli are efficient producers of potent agents against bacterial and fungal pathogens, which are of great interest both for therapeutic applications in medicine as well as in agrobiotechnol-ogy. Lipopeptides produced by such organisms play a major role in their inactivation potential. In this work we investigated two lipopeptide complexes, the fusaricidins and the polymyxins, produced by Paenibacillus polymyxa strains DSM 32871 and M1 by MALDI-TOF mass spectrometry. The fusaricidins show potent antifungal activities and are distinguished by an unusual variabil-ity. For strain DSM 32871 we identified numerous yet unknown variants mass spectrometrically. DSM 32871 produces polymyxins of type E (colistins), while M1 forms polymyxins P. For both strains novel, but not yet completely characterized polymyxin species were detected, which pos-sibly are glycosylated. These compounds may be of interest therapeutically, because polymyxins attain increasing attention as last-resort antibiotics against multiresistant pathogenic Gram-negative bacteria. In addition, the volatilomes of DSM 32781 and M1 were investigated with a GC-MS approach using different cultivation media. Production of volatile organic com-pounds (VOCs) was strain and medium dependent. In particular, strain M1 manifested as an effi-cient VOC-producer that exhibited formation of 25 volatiles in total. A characteristic feature of Paenibacilli is the formation of volatile pyrazine derivatives.

The trace element selenium (Se) is taken up from the diet and becomes metabolized mainly by hepatocytes. Selenoprotein P (SELENOP) constitutes the liver-derived Se transporter. Biosynthesis of extracellular glutathione peroxidase (GPx3) in kidney depends on SELENOP-mediated Se supply. We hypothesized that Se status may serve as a useful prognostic marker for outcome in patients undergoing liver transplantation. Serum samples from patients were routinely collected before and after transplantation. Concentration of serum SELENOP and total Se as well as GPx3 activity were determined by standardized tests and related to survival, aetiology and pre-operative Child-Pugh and Model for End-Stage Liver Disease Scores. A total of 314 serum samples from 78 transplanted patients were available for analysis. The Se and SELENOP concentrations were on average below the reference ranges of healthy subjects. Patients with ethanol toxicity-dependent aetiology showed particularly low SELENOP and Se concentrations and GPx3 activity. Longitudinal analysis indicated declining Se concentrations in non-survivors. We conclude that severe liver disease necessitating organ replacement is characterized by a pronounced Se deficit before, during and after transplantation. A recovering Se status after surgery is associated with positive prognosis, and an adjuvant Se supplementation may thus support convalescence.

In developed countries, especially the big-sized ones like Australia and the USA, a car is almost an inevitable necessity to carry out daily activities. Due to this, used cars have become a great alternative to brand new cars because of their cost effectiveness. In this work, estimation of prices of used cars based on numerous factors is studied statistically. Data is based on prices of used cars sold across Australia. Statistical methods like correlation and permutation tests using linear regression model, exact tests and non-parametric bootstrapping is implemented to study the relationship of price with mileage and year of manufacture of the car using p-values and null hypothesis. Predictions are also made on the price by calculating a 95% confidence interval (CI) of median prices in small portions of the dataset. The study presents potential ideas for understanding correlation between variables and parameters in business studies.

Epigallocatechin-3-gallate (EGCG) is the most abundant polyphenol in green tea. In this study, the effects of dietary EGCG on oxidative stress and the metabolism and toxicity of acetaminophen in liver were investigated. Rats were fed the diets with (0.54 %) or without EGCG supplementation for four weeks and were then intraperitoneally injected with acetaminophen (1g/kg). Results showed EGCG lowered hepatic oxidative stress and cytochrome P450 (CYP) 1A2, 2E1, and 3A, and UDP-glucurosyltransferase activities prior to acetaminophen injection. After acetaminophen challenge, the elevations in plasma alanine aminotransferase activity and histological changes in liver were ameliorated by EGCG treatment. EGCG reduced acetaminophen-induced apoptosis by increasing the Bax/Bcl2 ratio in liver. EGCG mildly increased autophagy by increasing the LC3B II/I ratio. Lower hepatic acetaminophen-glutathione and acetaminophen-protein adducts contents were observed after EGCG treatment. EGCG increased glutathione peroxidase and NAD(P)H quinone 1 oxidoreductase activities and reduced organic anion-transporting polypeptides 1a1 expression in liver after acetaminophen treatment. Our results indicate that EGCG may lower oxidative stress and reduce the metabolism and toxicity of acetaminophen. The reductions in CYP-mediated acetaminophen bioactivation and uptake transporter, as well as enhanced antioxidant enzyme activity, may limit the accumulation of toxic products in liver and thus lower hepatotoxicity

Copulas are useful tools for modeling the dependence structure between two or more variables. Copulas are becoming a quite flexible tool in modeling dependence among the components of a multivariate vector, in particular to predict losses in insurance and finance. In this article, we study the dependence structure of some well-known real life insurance data (with two components mainly) and subsequently identify the best bivariate copula to model such a scenario via VineCopula package in R. Associated structural properties of these bivariate copulas are also discussed.

In this paper, we introduced many new notions and new contraction named as S-weakly contraction after that we obtained the p-common best proximity point theorems for different types of contractions in the setting of complete metric spaces by using weak P_p-property and proved the uniqueness of these points. Also we presented some examples to prove the validity of our results.

Metal oxide p-n heterojunction nanofibers (NFs) are among the most promising approaches to enhancing the efficiency of gas sensors. In this paper, we report the preparation of a series of p-NiO-loaded n-ZnO NFs, namely (1 − x) ZnO-xNiO (x = 0.03, 0.05, and 0.1 wt%), for hydrogen gas sensing experiments. Samples were prepared through the electrospinning technique followed by a calcination process. The sensing experiments showed that the sample with 0.05 wt% NiO loading resulted in the highest sensing performance at an optimal sensing temperature of 200 °C. The sensing mechanism is discussed in detail and contributions of the p-n heterojunctions, metallization of ZnO and catalytic effect of NiO on the sensing enhancements of an optimized gas sensor are analyzed. This study demonstrates the possibility of fabricating high-performance H₂ sensors through the optimization of p-type metal oxide loading on the surfaces of n-type metal oxides.

Kummerowia striata is a traditional medicine used for the therapy of inflammation-related diseases. Herein, we investigated the anti-melanogenic and antioxidant activities of an ethanolic extract of K. striata (EKS) using a number of in vitro and cell culture model systems. The anti-melanogenic effect was assessed in B16F10 melanoma cells based on melanin synthesis and in vitro tyrosinase inhibitory activity and the anti-oxidant activity assays were performed using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2ʹ-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS); EKS exhibited strong anti-oxidant activities in both the assays. The expression of tyrosinase, tyrosinase-related protein 1, tyrosinase-related protein 2, and microphthalmia-associated transcription factor was decreased in a dose-dependent manner at mRNA and protein levels upon treatment with EKS. Notably, EKS did not affect the cell viability at all the EKS concentrations used in this study, indicating that EKS-mediated inhibition of melanin synthesis is not accompanied with cytotoxicity. Collectively, our findings demonstrate, for the first time, that EKS possesses anti-melanogenic and anti-oxidant activities, and suggest that further evaluation and development of EKS as a functional supplement or cosmetic might be useful for skin whitening and for reduction wrinkles.

Graph coloring is a manifestation of graph partitioning, wherein, a graph is partitioned based on the adjacency of its elements. Partitioning serves potentially as a compartmentalization for any structural problem. Vertex coloring is the heart of the problem which is to find the chromatic number of a graph. The fact that there is no general efficient solution to this problem that may work unequivocally for all graphs opens up the realistic scope for combinatorial optimization algorithms to be invoked. The algorithmic complexity of graph coloring is non-deterministic in polynomial time (NP) and hard. To the best of our knowledge, there is no algorithm as yet that procures an exact solution of the chromatic number comprehensively for any and all graphs within the polynomial (P) time domain. However, several heuristics as well as some approximation algorithms have been attempted to obtain an approximate solution for the same. Here, we present a novel heuristic, namely, the 'trailing path', which returns an approximate solution of the chromatic number within polynomial time, and, with a better accuracy than most existing algorithms. The ‘trailing path’ algorithm is effectively a subtle combination of the search patterns of two existing heuristics (DSATUR and Largest First), and, operates along a trailing path of consecutively connected nodes (and thereby effectively maps to the problem of finding spanning tree(s) of the graph) during the entire course of coloring, where essentially lies both the novelty and the apt of the current approach. The study also suggests that the judicious implementation of randomness is one of the keys towards rendering an improved accuracy in such combinatorial optimization algorithms. Apart from the algorithmic attributes, essential properties of graph partitioning in random and different structured networks have also been surveyed, followed by a comparative study. The study reveals the remarkable stability and absorptive property of chromatic number across a wide array of graphs. Finally, a case study is presented to demonstrate the potential use of graph coloring in protein design – yet another hard problem in structural and evolutionary biology.

This paper includes some new investigations and results for post quantum calculus, denoted by (p,q)-calculus. A chain rule for (p,q)-derivative is developed. Also, a new (p,q)-analogue of the exponential function is introduced and some its properties including the addition property for (p,q)-exponential functions are investigated. Several useful results involving (p,q)-binomial coefficients and (p,q)-antiderivative are discovered. At the final part of this paper, (p,q)-analogue of some elementary functions including trigonometric functions and hyperbolic functions are considered and some properties and relations among them are analyzed extensively.

In this paper we establish several Hermite-Hadamard type integral inequalities for hyperbolic p-convex functions. Applications for special means are provided as well.

In this paper, we introduce a new generalization of the Hermite polynomials via (p, q)-exponential generating function and investigate several properties and relations for mentioned polynomials including derivative property, explicit formula, recurrence relation, integral representation. We also de…ne a (p, q)-analogue of the Bernstein polynomials and acquire their some formulas. We then provide some (p, q)-hyperbolic representations of the (p, q)-Bernstein polynomials. In addition, we obtain a correlation between (p, q)-Hermite polynomials and (p, q)-Bernstein polynomials.

In this study, a graphene-doped porous silicon (G-doped/p-Si) substrate for low ppm H₂ gas detection by an inexpensive synthesis route was proposed as a potential noble graphene-based gas sensor material and to understand the sensing mechanism. The G-doped/p-Si gas sensor was synthesized by a simple capillary force-assisted solution dropping method on p-Si substrates, whose porosity was generated through an electrochemical etching process. G-doped/p-Si was fabricated with various graphene concentrations and exploited as a H₂ sensor operated at room temperature. The sensing mechanism of the sensor with/without graphene decoration on p-Si was proposed to elucidate the synergetic gas sensing effect generated from the interface between the graphene and p-type silicon.

The current generation of nuclear reactors are evolutionary in design, mostly based on the technology originally designed to power submarines, and dominated by Light Water Reactors. The aims of the GenIV consortium are driven by sustainability, safety and reliability, economics, and proliferation resistance. The aims are extended here to encompass the ultimate and universal vision for strategic development of energy production, the ‘perpetuum mobile’ – at least as close as possible. We propose to rethink nuclear reactor design with the mission to develop a system which uses no fresh resources and produces no fresh waste during operation as well as generates power safe and reliably in economic way. The results of the innovative simulations presented here demonstrate that, from a theoretical perspective, it is feasible to fulfil the mission through the reuse of spent nuclear fuel from currently operating reactors as the fuel for a new reactor. The produced waste is less burdensome than current spent nuclear fuel which is used as feed to the system. However, safety, reliability and operational economics will need to be demonstrated to create the basis for the long term success of nuclear reactors as a major carbon free, sustainable, and applied highly reliable energy source.

A well-prepared public health workforce is essential for reducing disease burdens and improving population health, requiring an education that addresses global and complex challenges. This paper examines the integration of the relational employability framework in public health education to cultivate critical global citizenship among students and graduates. Our research, conducted at Edith Cowan University in Perth, Western Australia, involved two case studies using qualitative interviews. Case Study 1, drawn from Cook’s doctoral research, explored student experiences with the relational employability framework within an undergraduate capstone unit. Case Study 2, a school-funded project, gathered graduate perspectives to inform ongoing curriculum development. The findings indicate that the relational employability framework enhances global competencies among students and graduates, through research skills development and critical reflective practice. Students reported improved awareness of their learning needs, self-confidence, and an increased ability to engage with diverse perspectives and societal challenges. Graduates highlighted the framework’s role in understanding ethical standards, conducting rigorous research and applying evidence-based practices in professional settings. Additionally, the framework supported the development of a reflective mindset, enabling graduates to make informed, value-based career decisions and advance their professional growth. The study suggests that adopting a relational employability approach can effectively prepare globally competent and reflective public health professionals. We advocate for the broader implementation of this framework in health education and higher education, offering practical recommendations for curriculum transformation. Such an approach will equip future professionals to contribute meaningfully to public health debates and embody the principles of global citizenship in their practice.

In 2023, the World Economic Forum reported the existence of high-severity global risks in both the short and long term, including climate change, natural disasters and biodiversity loss. In response, Clive L. Spash, a scholar specializing in ecosocial issues, has proposed a paradigm shift that considers the interconnection between ecological, economic, and social challenges, advocating for approaches that go beyond the positivistic approach of orthodox economics. He refers to this approach as Social Ecological Economics (SEE), a school of thought that has received limited attention, evident from the scarcity of publications on the subject. In light of this, the objective of this paper is to provide an overview of the key elements that define Social Ecological Economics as an alternative field within ecological thought. To achieve this, a literature review was conducted, employing open and in vivo coding using Atlas.ti 9 software. The findings identify the core components of Social Ecological Economics, organized into categories such as background, characteristics, dimensions, problems, criticisms, foundations, and proposals. These categories highlight the distinctive identity of this school. As this study is exploratory in nature, a future research agenda is proposed to further examine the relevance of this approach in tackling pressing global issues.

This paper addresses the historically biased selection of problems in technoscience, which has been predominantly shaped by Western male perspectives. We propose a novel framework with objective criteria for identifying and prioritizing human problems worthy of scientific and technological attention. Our approach aims to transcend traditional biases, incorporating a more inclusive, global perspective. We outline metrics considering factors such as scale, urgency, potential impact, and relevance across diverse populations. Using these criteria, we identify key global challenges including climate change, pandemic preparedness, food and water security, education access, sustainable energy transition, AI governance, biodiversity conservation, and mental health. We present a network analysis of their interconnections, revealing complex interdependencies and potential cascading effects of interventions. Our mathematical framework, based on graph theory and network analysis, provides a rigorous foundation for understanding and quantifying these relationships. This research contributes to decolonizing and degendering technoscience, offering a more equitable framework for addressing pressing human problems \cite{roy2018}. Our findings have significant implications for research prioritization, policy-making, and resource allocation in scientific and technological endeavors, potentially reshaping how we approach and address the most critical issues facing humanity.

This article underscores the immense potential for substantial economic growth and development that can be harnessed through effective participation in global value chains (GVCs). It emphasises the role of policymakers in adeptly navigating GVCs, prioritising tasks, exploring different forms of GVC governance, and fostering a conducive environment for foreign investments. By effectively managing power dynamics and supply chain risks, countries can attract valuable foreign investors, enhance market connectivity, and improve infrastructure and services, leading to significant economic growth. The potential benefits of GVC participation are vast, and policymakers can shape the situation by understanding and addressing strategic inquiries, laying the foundation for a prosperous future. Furthermore, the article explores the potential for a country to enhance its involvement in GVCs and progress to more lucrative activities by strengthening existing connections between GVCs and the local economy. By enhancing the capacity of local stakeholders to acquire knowledge, policymakers can play a crucial role in maximising the benefits from GVC spillovers, positively impacting a country's economic development.

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

The relationship between nations is largely seen as a peripheral issue in the recent history of political philosophy and in the majority of discussions of political philosophy issues today. The idea of a universal natural state were countries are seen as essentially self-sufficient, functional units, and have been proposed to represent the relative lack of moral standards guiding relationships between nations. At one extreme of the tradition, international thought has substituted raison d'état being the highest norm for any universal laws governing relations between states, a view embodied by Machiavelli, Rodin, and others and Hobbes , The lack of supranational political powers has led to the conclusion that, even in cases where the possibility of international moral relationships has been acknowledged, such as in post-Grotian publications on international law, these ties are significantly weaker than in-tranational social bonds. The justification and aversion to war—the primary mode of social in-teraction in the natural condition of the world—is the only issue in the field of global relations to have received substantial theoretical study. Even though this disregard was justified in the past, a number of recent events force us to re-consider the "recalcitrance of international affairs to being theorized about."2. The growing gap between both prosperous and impoverished nations; the emergence of centers of economic in-fluence beyond the reach of effective state regulation; the emergence of severe food and energy shortages brought on, at least in part, by national governments' pursuit of disorganized and uncontrolled growth policies; the growing sensitivity of domestic Countries to the outside eco-nomic, political, and cultural events are some of these developments , requests from third-world nations for greater equal access to international politics and economy. To put it in terms more familiar to conversations about this topic, the rise of "low politics" in negotiation and "welfare questions" within global forums corresponds with the growing influence of transnational con-nections and international agreements on human well-being. Not because "high politics"—that is, the threat and prevention of war—has lost significance; rather, it is just one issue among many for which international cooperation is now required in order to find answers.

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

Strategic intelligence covers the examination of what impacts and influences the business and the related SWOT analysis, (strengths, weaknesses, opportunities, and threats mapping). Through this research, leaders will be able to properly allocate and re-route resources, identify areas of improvement, and ensure that strategic initiatives are aligned with the organization's mission. Strategic intelligence is, therefore, effective through the use of critical thought and data-driven decisions and seeing the outcomes of different positioned alternatives. It must also form and support a culture of cooperation and open communication within the organizations, stimulating employees' inputs and learning curves. The article's subject is the necessity for strategic intelligence, a crucial competence for leaders, managers, and companies striving to remain competitive, to be utilized and best leveraged in today's volatile and dynamic business contexts. It helps the leadership turn proactive, foresee trends, and make correct, agile decisions that enforce companies' long-term growth and success. This study follows a research design that includes a thorough literature review and bibliometric research, executed via VoSViewer, illustrating the concept of strategic intelligence from a leadership point of view as a driver of competitive advantage. Further, the article points out that the limitations are acknowledged because the literature on the matter is limited, as strategic intelligence is relatively new to the business sector; moreover, more research is required to fully understand and use the potential of strategic intelligence in business growth. By overcoming these limitations and continuing to study this concept, businesses can gain a competitive edge and make informed decisions that fuel their success in an ever-evolving market. As a result, this study contributes to developing strategic intelligence in leadership and business and paves the road for further research and applications of strategic intelligence theories in organizational contexts.

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

Walnut trees are grown worldwide for their edible fruits of high nutritional value. To address climate change, researchers have studied walnut phenology to create cultivars adapted to warmer climates. The standardisation of walnut phenological observations is needed and the Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie (BBCH) scale is the most accurate and internationally accepted for this purpose. Here, the principal growth stages (PGS) of Persian walnut (Juglans regia L.) are described using stages from a previously available alphanumerical scale. This standardised phenological scale describes Persian walnut growth from the dormant vegetative state through reproductive budding to senescence. This phenological scale is expected to increase the efficiency of walnut phenological monitoring. Fifty-seven stages were used to describe the life cycle of Persian walnut in this BBCH scale. Of these 57 stages, 3 stages are dedicated to seed germination (PGS-0), 4 stages to bud development (PGS-0), 7 stages to leaf development (PGS-1), 4 stages to stem elongation (PGS-3), 8 stages to inflorescence emergence (PGS-5), 5 stages to male flowering (PGS-6), 5 stages to female flowering (PGS-6), 5 stages to fruit development (PGS-7), 12 stages to fruit ripening (PGS-8) and 4 stages to leaf senescence (PGS-9).

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

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

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

We know that the classical Mittag-Leffler function play an important role as solution of fractional order differential and integral equations. We introduce the j-generalized p - k Mittag-Leffler function. We evaluate the second order differential recurrence relation and four different integral representations and introduce a homogeneous linear differential equation whose one of the solution is the j-generalized p-k Mittag-Leffler function. Also we evaluate the certain relations that exist between j-generalized p - k Mittag-Leffler function and Riemann-Liouville fractional integrals and derivatives. We evaluate Mellin-Barnes integral representation of j-generalized p-k Mittag-Le er Function. The relationship of j-generalized p-k Mittag-Leffler Function with Fox H-Function and Wright hypergeometric function is also establish. we obtained its Euler transform, Laplace Transform and Mellin transform. Finally we derive some particular cases.

In this paper, we derive multifarious relationships among the two types of higher order q-Daehee polynomials and p-adic gamma function via Mahler theorem. Also, we compute some weighted p-adic q-integrals of the derivative of p-adic gamma function related to the Stirling numbers of the both kinds and the q-Bernoulli polynomials of order k.

The use of natural health products (NHP) is constantly increasing worldwide. Among the most NHP consumed are the resins of Commiphora myrrha (C. myrrha) tree. Consumption of C. myrrha may result in herb-drug interactions that can lead to serious health consequences. This study aims to determine the herb-drug interactions based on the induction of drug-metabolizing enzyme cytochrome P-450 (CYP) 2C9 by a non-toxic boiled aqueous extract of C. myrrha and to unveil the potential involvement of xenobiotic-sensing nuclear receptors such as Pregnane X Receptor (PXR), a well-known CYP 2C9 transcription factor. Tested at low concentrations (0.01-10 g/mL) devoid of anti-proliferative effects, boiled C. myrrha resin aqueous extract upregulated CYP 2C9 gene and protein expressions in a dose-dependent manner, reaching a mean expression level exceeding 3.0-fold change in Hep G2 cells, compared with the basal level expressed in untreated cells. Furthermore, chemical analysis using mass spectrometry and computational molecular docking using in silico studies revealed that few C. myrrha resin-derived metabolites are strongly bound to PXR. In particular, the identified metabolite named diayangambin exhibited a predicted molecular docking score close to that of a native PXR ligand. The use of the nuclear receptor binding assays confirmed the binding between C. myrrha metabolite(s) and PXR, while no binding to the other xenobiotic-sensing nuclear receptor, the constitutive androstane receptor (CAR), was observed, suggesting that C. myrrha metabolite(s) are potential PXR agonists. In conclusion, although in vivo studies are needed, this study cautions patients, healthcare providers, and governmental regulators against the consumption of C. myrrha and diayangambin-rich preparations with a high potential for herb-drug interactions through drug-metabolizing CYP 2C9 enzyme induction, which could affect drug efficacy.

Different materials prepared by appropriate synthesis methods and applying different post syn-thesis processes could be used as hole transport layer in perovskite solar cells. In the present work annealing was employed to enhance physical properties of copper oxide (CuO) thin films fabricated via spin coating technique and the effects of annealing on their optical, morphological, electrical and structural properties were investigated. The XRD findings revealed the polycrystalline structure with large crystallite size. Optical spectra showed larger transmission beyond the visible region, reduced absorption, and a decrease in bandgap energy from 1.93 eV to 1.81 eV. The Ag phonon modes at 299.22 and 304 cm-1 shown by the Raman shift confirmed the development of the CuO pure phase. FTIR spectra showed the Cu-O stretching band at 759, 764 and 446 cm−1. SEM revealed the agglomeration of nano crystallites with large grains on the surface. The carrier type conductivity of annealed CuO thin films was determined via two-point hot probe technique. Low resistivity values were determined via four-point probe method. These findings indicate that CuO thin films may be successfully used as a companion with an n-type layer in p-n junction solar cells, and a hole transport layer in perovskite solar cells.

Ab initio density functional theory molecular dynamics extensive calculations were used for the first time to evaluate stability conditions for relevant phases of InN. In particular, thermal decomposition of InN with formation of N2 molecules and pressure induced wurtzite – rocksalt solid-solid phase transition were established. The results consistent with available experimental data allowed a critical evaluation of potential and limitations of the proposed simulation method. The ab initio molecular dynamics as an efficient tool for simulations of phase transformations of InN including solid-solid structural transition and thermal decomposition with formation of N2 molecules has been demonstrated. It is of high interest because InN being important component of epitaxial quantum structures has still not been obtained as a bulk single crystal making difficult a determination of its basic physical properties and designing new applications.

This study was designed to examine the relationships among the impulsivity construct as a personality trait, the dehydroepiandrosterone sulfate (DHEA-S), and testosterone in a sample of 120 healthy middle-aged males. (Mage = 44.39; SD = 12.88). The sum of the three BIS-11 scales, the SR and the five UPPS-P scales correlated with DHEA-S .23 (p < .006) and testosterone .19 (p < .04), controlling for age. Partial correlations showed that DHEA-S is significantly related to Motor impulsivity (.24; p < .008), Sensitivity to Reward (.29; p < .002) and Lack of premeditation (.26; p < .05) and, to a lesser extent, Sensation Seeking (.19; p < .04) and Positive Urgency (.19; p < .04). Testosterone correlated with Attention impulsivity (.18; p < .04), Sensation Seeking (.18; p < .04), and Positive Urgency (.22; p < .01). Sensitivity to Reward, Negative Urgency and Positive Urgency were significant predictors of DHEA-S (R2 = .28), and Positive Urgency for testosterone (R2 = .09). Non-parametric LOESS graphical analysis for local regression allowed us to visualize the non-linear relationships between the impulsivity scales with the two androgens, including non-significant trends. We discuss the implications of these results for biological impulsive personality traits, the limitations of our analyses, and the possible development of future research.

Amidst worsening climate change, drought stress imperils global agriculture, jeopardizing crop yields and food security, necessitating urgent exploration of sustainable methods like biopriming, harnessing beneficial microorganisms to bolster plant resilience. Recent research has revealed diverse biological compounds with versatile applications produced by Schizophyllum commune, rendering this fungus as a promising contender for biopriming applications. For the first time this study aimed to investigate,the potential of S. commune exo- (EPSH) and intra-PSH (IPSH), isolated from two strains: Italian (ITA) and Serbian (SRB) under submerged cultivation, in enhancing the resilience of Pisum sativum L. seeds through biopriming technique. Testing of seed quality of bioprimed, hydroprimed, and unprimed seeds was done using a germination test, under optimal and drought conditions. In optimal conditions, the IPSH SRB increased germination energy by 5.50% compared to the control, while the highest percentage of germination (94.70%) was shown after biopriming with PSH isolated from the ITA strain. Additionally, all assessed treatments resulted in a boost in seedling growth and biomass accumulation, where the ITA strain demonstrated greater effectiveness in optimal conditions, whereas the SRB strain showed superiority in drought conditions. The drought tolerance indices increased significantly in response to all examined treatments during the drought, with EPSH ITA (23.00%) and EPSH SRB (24.00%) demonstrating the greatest effects. Results demonstrate a significant positive influence of fungal PSH, indicating their potential as biopriming agents and offers insights into novel strategies for agricultural resilience in the face of changing environmental conditions.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

The cycling of soil phosphorus (P) is inherently linked with soil organic carbon-iron (C-Fe) cycling, yet empirical integration of these processes within paddy soils remains scarce. In this study, we conducted a microcosm experiment using paddy soils subjected to six distinct fertilization regimes involving varying P inputs for five years. In addition to evaluating P activation under reflooding conditions, we assessed the Fe reduction process and characterized the properties of dissolved organic matter (DOM) at the molecular level using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), alongside profiling the composition of soil microbial communities with high-throughput sequencing. Our findings revealed that after 25 days of reflooding, soil Olsen-P content increased by an average of 73% compared to its initial state, showing a strong correlation with the Fe reduction process. Specifically, treatments involving pig manure application exhibited higher Fe reduction rates and enhanced P activation, highlighting the role of organic matter in facilitating Fe reduction. Investigations on the relative abundance of typical iron-reducing microbes further supported their importance in P activation, but the rate of iron reduction is limited by soil organic matter content. Delving deeper into DOM properties, soil DOM composition profiling and network analysis suggested that high-molecular-weight DOM, particularly lignins, served as the primary resources driving Fe reduction by iron-reducing microbes, consequently promoting Fe reduction and P release. Taken together, our study assembled the C-Fe-P cycling dynamics in paddy soils, emphasizing the pivotal role of microbial-driven Fe reduction facilitated by soil DOM in P availability and subsequently sustainable agricultural practices.

In this work, a modeling technique utilizing the P-Graph framework was used for a case 1 study involving biomass-based local energy production. In recent years, distributed energy systems 2 gained attention. These systems aim at satisfying energy supply demands, supporting the local 3 economy, decreasing transportation needs and dependence on imports, and in general obtaining a 4 more sustainable energy production process. Designing such systems is a challenge, for which novel 5 optimization approaches were developed to help decision-making. Previous work used the P-Graph 6 framework to optimize energy production in a small rural area, involving manure, intercrops, grass, 7 and corn silage as inputs, and fermenters. Biogas is produced in fermenters, and Combined Heat 8 and Power (CHP) plants provide heat and electricity. A more recent result introduced the concept of 9 operations with flexible inputs in the P-Graph framework. In this work, the concept of flexible inputs 10 was applied to model fermenters in the original case study. A new implementation of the original 11 decision problem was made both as a Mixed-Integer Linear Programming (MILP) model and as a 12 purely P-Graph model by using the flexible input technique. Both approaches provided the same 13 optimal solution, with a 31% larger profit than originally reported.

(1) Background: P-cadherin (CDH3) is a transmembrane protein that plays a crucial role in maintaining the structural integrity of epithelial tissue and homeostasis. Its role in carcinogenesis remains a subject of debate, as its behavior can vary depending on the molecular context and the specific tumor cell model under study. In this study, we explored the role of P-cadherin in head and neck squamous cell carcinoma (HNSCC) and the mechanism underlying its function. (2) Methods: We analyzed P-cadherin expression in HNSCC patients using The Cancer Genome Atlas (TCGA) database. For in vitro functional analysis, we conducted proliferation, migration, invasion, and western blot assays after either suppressing or overexpressing P-cadherin. For in vivo functional analysis, we utilized mouse xenograft models. (3) Results: P-cadherin was significantly overex-pressed in tumor samples compared to normal samples in the TCGA-HNSCC cohort. P-cadherin knockdown resulted in decreased proliferation, migration, and invasion compared to control cells, while P-cadherin overexpression increased cell proliferation and migration in HNSCC cells. We discovered that c-Met functioned as an upstream regulator of P-cadherin. Surprisingly, we found that P-cadherin knockdown increased the phosphorylation of c-Met and STAT3. Combining P-cadherin siRNA with the c-Met inhibitor SU11274 resulted in a more effective reduction in HNSCC cell growth, both in vitro and in vivo, compared to either treatment alone. (4) Conclusions: Our study uncovered a previously unknown aspect of P-cadherin-mediated c-Met regulation. The enhanced activation of c-Met/STAT3 following P-cadherin inhibition could be responsible for the survival of resistant tumor cells. Therefore, dual inhibition of P-cadherin and c-Met may be a potentially effective approach for treating HNSCC.

We suggest a new solution to the strong CP problem. The solution is based on the proper use of the boundary conditions for the QCD generating functional integral. It obeys the principle of renormalizability of Quantum Field Theory and does not involve new particles like axions.

LiFePO4 (LFP) has undergone extensive research and is a promising cathode material for Li-ion batteries. The high interest is due to its low raw material cost, good electrochemical stability, and high-capacity retention. However, poor electronic conductivity and a low Li+ diffusion rate decrease its electrochemical reactivity, especially at fast charge/discharge rates. In this work, the volumetric energy density of lithium-ion batteries is successfully increased by using different amounts of conductive carbon (Super P) in the active material content. The particle size and morphology of the electrode material samples are studied using field emission scanning electron microscopy and dynamic light scattering. Two-point-probe DC measurements and adhesive force tests are used to determine the conductivity and evaluate adhesion for the positive electrode. Cyclic voltammetry, electrochemical impedance spectroscopy (EIS), and charge/discharge tests are used to analyze the electrochemical properties of the battery. The samples containing 88% LFP, 5.5% Super P and 6.5% PVDF perform best, with discharge capacities reaching 169.8 mAhg-1 at 0.1C, and they can also manage charging/discharging of 5C. EIS indicates that this combination produces the lowest charge-transfer impedance (67 Ω) and the highest Li+ ion diffusion coefficient (5.76 x 10-14 cm2s-1).

In this paper we study a special kind of finite mixture model. The sample drawn from the model consisits of three parts. The first two parts are drawn from specified distributions f1 and f2, while the third one is drawn from the mixture. A problem of interest is whether the two distributions f1 and f2 are the same. To test this hypothesis, we first define the regular location and scale family of distributions and assume that f1 and f2 are regular denisty functions. Then the hypothesis transforms to the equalities of the location and scale parameters, respectively. To utilize the information in the sample, we use Bayes’ theorem to obtain the posterior distribution and give the sampling method. Then we propose the posterior p-value to test the hypothesis. The simulation studies show that our posterior p-value largely improves the power in both normal and logistic cases while nicely controls the Type-I error. A real halibut dataset is used to illustrate the validity of our method.

Limited availability of expensive alloying elements elevates low-alloyed steels to a unique position in the field of lightweight construction and mass production. Quenching and partitioning (Q&P) heat treatments of low-alloyed steels with exceptional property combinations are particularly promising. In this study, we characterize for the first time a new low-alloyed steel to be processed by Q&P heat treatments. In combined experimental and numerical studies, we design a novel approach that effectively combines the short cycle times of press hardening with the excellent property profiles of Q&P-treated steels. We identify appropriate transformation parameters for Q&P heat treatments by dilatometric studies and we adjust a number of reference conditions with different isothermal holding times. By means of SEM analysis and XRD measurements, we show that different fractions of retained austenite result in different mechanical properties. Initial numerical designs of the process can identify varying temperature profiles and cooling rates depending on the position in the die. The results show that the geometry of the part plays a minor role, but the die temperature is the dominant factor for successful partitioning directly in the press hardening process.

Bimetallic Ni/Cu core-shell and Cu-Ni heterostructural micro- and nanoparticles were prepared using two simple successive reduction procedures. Monometallic Ni and Cu particles were synthesized for comparison. The phase constitutions and morphological features of the particles were studied by means of X-ray diffraction, energy-dispersive X-ray spectroscopy and scanning electron microscopy methods. All the obtained mono- and bimetallic particles were applied as electrocatalysts in the electrohydrogenation of p-nitrophenol (p-NPh). An additional electrochemical reduction of copper cations during the hydrogen saturation of Cu-containing particles was established. Some of the prepared particles exhibited high catalytic activity with an increase in the hydrogenation rate of p-NPh by more than 3 times compared to its electrochemical reduction on the non-activated cathode, and p-NPh conversion yielded the maximum values. The main product of p-NPh electrocatalytic hydrogenation over Ni-Cu particles is p-aminophenol, which is an intermediate in the synthesis of many drugs. p-Aminophenol formation is confirmed by UV-Vis spectra.

In this note we, first, recall that the sets of all representatives of some special ordinary residue classes become $\left( m,n\right) $-rings. Second, we introduce a possible $p$-adic analog of the residue class modulo a $p$-adic integer. Then, we find the relations which determine, when the representatives form a $\left( m,n\right) $-ring. At the very short spacetime scales such rings could lead to new symmetries of modern particle models.

Knowledge of the interaction between inorganic and organic phosphates with soil minerals is vital for improving the soil P fertility. To achieve an in-depth understanding we combined adsorption experiments and hybrid ab initio molecular dynamics simulations to analyze the adsorption of common phosphates, i.e. orthophosphate (OP), glycerolphosphate (GP) and inositolhexaphosphate (IHP), onto the 100 surface plane of goethite. Experimental adsorption data per mol P-molecule basis fitted to the Freundlich model show the adsorption strength increases in the order GP &lt; OP &lt; IHP, and IHP adsorption being saturated faster followed by GP and OP. Modeling results show that OP and GP form stable monodentate (M) and binuclear bidentate (B) motifs with B being more stable than M, whereas IHP forms stable M and 3M motifs. Interfacial water plays an important role through hydrogen bonds and proton transfers with OP/GP/IHP and goethite. It also controls the binding motifs of phosphates with goethite. Combining both experimental and modeling results, we propose that the B motif dominates for OP, whereas GP forms M and IHP forms a combination of M and 3M motifs. The joint approach plausibly explains why IHP is the predominant organically bound P form in soil. This study could be considered as a preliminary step for further studies for understanding the mechanisms of how microbes and plants overcome the strong IHP–mineral binding to implement the phosphate groups into their metabolism.

Financial system is essentially chaotic and unstable if there is not any external inputs. By means of Lyapunov function method, design of switching law, novel fuzzy assumption, $L^p$ estimation technique and Laplace semigroup theory, the author presents the boundedness and LMI-based (globally) asymptotical input-to-state stability criteria of financial systems. Particularly, the globally asymptotical stability in the meaning of switching implies that when the time $t$ is big enough, the dynamic of any subsystem must approach its unique equilibrium point. Besides, the global financial crisis often erupts periodically, which illuminates that the global stability in the classical sense is actually meaningless. So the stability in the meaning of switching proposed in this paper is suitable and appropriate. Numerical examples illuminate the effectiveness of the obtained results.

Novel severe acute respiratory syndrome coronavirus 2 infection (SARS-Cov-2) is an acute respiratory and infectious disease. This perspective aims to provide the basic understanding of the inflammation caused by SARS-Cov-2 and relation to trigeminal ganglion (TG). Virus enters through the mucous membranes of orofacial region and reach the TG where it resides and take control of its peptides including Substance P (SP).SP is the main neuropeptide, neuromodulator and neuro-hormone of TG, associated with nociception and inflammation under noxious stimulus. SP release is triggered and consequently, it affects the immune cells, blood vessels to release the mediators for inflammation. Cytokine storming is initiated and cause respiratory distress, bronchoconstriction and death in complicated cases. Neurokinin-1 Receptor (NK-1R) antagonist and glucocorticoids may be used to alleviate the symptoms and treat this infection. SP is the main culprit seem to be involved in the triggering of inflammatory pathways in SARS-Cov-2 infection. It has direct association with cardiorespiratory rhythm, sleep-wake cycle, nociception, ventilator responses and regulates many important physiological and pathological roles. Its over-secretion should be blocked by NK-1R antagonist. However, experimental work leading to clinical trials are mandatory for further confirmation.

Acute myeloid leukemia (AML) is an incurable hematological malignancy. To treat the disease successfully, new therapeutic strategies are urgently needed. One of these strategies can be the use of neurokinin-1 receptor (NK-1R) antagonists (e.g., aprepitant), because the substance P (SP)/NK-1R system is involved in cancer progression, including AML. AML patients show an up-regulation of the NK-1R mRNA expression; human AML cell lines show immunoreactivity for both SP and the NK-1R (it is overexpressed: the truncated isoform is more expressed than the full-length form) and, via this receptor, SP and NK-1R antagonists (aprepitant, in a concentration-dependent manner) respectively exert a proliferative action or an antileukemic effect (apoptotic mechanisms are triggered by promoting oxidative stress via mitochondrial Ca++ overload). Aprepitant inhibits the formation of AML cell colonies and, in combination with chemotherapeutic drugs, is more effective in inducing cytotoxic effects and AML cell growth blockade. NK-1R antagonists also exert an antinociceptive effect in myeloid leukemia-induced bone pain. The antitumor effect of aprepitant is diminished when the NF-κB pathway is overactivated and the damage induced by aprepitant in cancer cells is higher than that exerted in non-cancer cells. Thus, the SP/NK-1R system is involved in AML and aprepitant is a promising antitumor strategy against this hematological malignancy. In this review, the involvement of this system in solid and non-solid tumors (in particular in AML) is up-dated and the use of aprepitant as an anti-leukemic strategy for the treatment of AML is also mentioned (a dose of aprepitant (> 20 mg/kg/day) for a period of time according to the response to treatment is suggested).

Pyracantha angustifolia has been used in traditional medicine to treat a range of diseases of the stomach and improve digestion, blood circulation, diarrhea, dysentery, and hemostasis. This study evaluated bioactivity-guided fractionation as a means to identify therapeutic phytochemicals from P. angustifolia that can attenuate melanogenesis and oxidation. Seven compounds with inhibitory effects on melanin production and tyrosinase (TYR) activity, as well as ABTS and DPPH radical scavenging activities, and have not been reported as whitening materials, were isolated from the n-butanol fraction from P. angustifolia leaves (PAL). Among the seven compounds, p-hydroxybenzoic acid beta-d-glucosylester (HG), and cimidahurinine (CD) had strong inhibitory effects of melanin production, TYR activity, and ABTS and DPPH radical scavenging activities. Western blot analysis showed that HG and CD suppressed tyrosinase-related protein (TYRP)-1 and TYRP-2 expression. These results suggest that P. angustifolia containing active compounds, such as HG and CH, is a potent therapeutic candidate for the development of hypopigmenting agents.

In this paper we consider Changhee polynomials of type two, which are motivated from the recent work of Kim and Kim. We investigate some symmetry identities for the Changhee polynomials of type two which are derived from the properties of symmtery for the fermionic p-adic integral on Zp.

In this paper, we represent the generating function of w-torsion Fubini polynomials by fermionic p-adic integral on Z_p. Then we consider a quotient of such fermionic p-adic integrals on Z_p, representing generating functions of three w-torsion Fubini polynomials and derive some new symmetric identities for the w-torsion Fubini and two variable w-torsion Fubini polynomials.

Watermelon fusarium wilt caused by Fusarium oxysporum f.sp. niveum (FON) is a destructive soil-borne disease throughout the world leading to serious economic losses and limit watermelon production. Cuminic acid, extracted from the seed of Cuminum cyminum L., belongs to benzoic acid analogues. In this study, the median effective concentration (EC₅₀) values for cuminic acid in inhibiting mycelial growth of FON was 22.53μg/mL. After treatment with cuminic acid, mycelial morphology was seriously influenced; cell membrane permeability and glycerol content were increased markedly, but pigment and mycotoxin (mainly fusaric acid) were significantly decreased. Synthesis genes of bikaverin and fusaric acid both were down regulated compared with the control confirmed by quantitative RT-PCR. In greenhouse experiments, cuminic acid at all concentrations displayed significant bioactivities against FON. Importantly, significant enhancement of activities of SOD, POD, CAT and decrease of MDA content after cuminic acid treatment in watermelon leaves were observed in vivo. These indicated that cuminic acid not only showed high antifungal activity, but also could enhance the self-defense system of the host plant. Above all, cuminic acid showed the potential as a biofungicide to control FON.

In CNS drug discovery, estimation of brain exposure of lead compounds is critical for their optimization. Compounds need to cross the blood-brain barrier (BBB) to reach the pharmacological targets in the CNS. The BBB is a complex system involving passive and active mechanisms of transport and efflux transporters such as P-glycoproteins (P-gp) and breast cancer resistance protein (BCRP), which play an essential role in CNS penetration of small molecules. Several in vivo, in vitro and in silico methods are available to estimate human brain penetration. Preclinical species are used as in vivo models to understand the unbound brain exposure by deriving the Kp,uu parameter, the brain/plasma ratio of exposure corrected with the plasma and brain free fraction. MDCK-mdr1 (Madin Darby canine kidney cells transfected with the MDR1 gene encoding for the human P-gp) assay is the most commonly used in vitro assay to estimate compound permeability and human efflux. The in silico methods to predict brain exposure, such as CNS MPO, CNS BBB scores and various Machine Learning models, help save costs and speed up compound discovery and optimization at all stages. These methods enable the screening of virtual compounds and building of a CNS penetrable compounds library as well as optimization of lead molecules for CNS penetration. Therefore, it is crucial to understand these methods' reliability and ability to predict CNS penetration. We review the in silico, in vitro and in vivo data and their correlation with each other and assess published in silico approaches to predict the BBB penetrability of compounds.

The global burden of drug-resistant tuberculosis (DR-TB) continues to challenge healthcare systems worldwide. There is a critical need to tackle DR-TB by enhancing diagnostics and drug susceptibility testing (DST) capabilities, particularly for emerging DR-TB drugs. This endeavor is crucial to optimize the efficacy of new therapeutic regimens and prevent the resistance and overuse of these invaluable weapons. Despite this urgency, there remains a lack of comprehensive review on public health measures aimed at improving the diagnostics and DST capabilities. In this review, we outline strategies to enhance the capabilities especially tailored to address the challenges posed by resistance to new DR-TB drugs. We discuss the current landscape of DR-TB drugs, existing diagnostic and susceptibility testing methods, notable gaps and challenges in these methods, and explore strategies for ensuring fair access to DST while narrowing these disparities. The strategies include public health interventions aimed at strengthening laboratory infrastructure, workforce training, and quality assurance programs, technology transfer initiatives, involving drug developers in the DST development, establishing national or regional referral hubs, fostering collaboration and resources pooling with other infection control efforts, extending testing access in underserved areas through public-private partnerships, advocating for lowering costs or loans at low-interest, remote technical support, and implementing mandatory molecular surveillance monitoring. This review underscores the urgent need to enhance DST capacities for new DR-TB drugs and identifies opportunities for innovation and improvement. Assessing the extent of the global health impact of these measures is crucial to ensure their effectiveness in combating DR-TB.

This article describes a new application of the global optimization method HQF ASA to the investigation of the Riemann hypothesis, in the sense of searching for zeros of the Riemann zeta function ζ outside the critical line but inside the (open) subset of the critical strip ((0,1/2)∪(1/2,1))×(−∞,∞). The underlying idea is very simple: a complex root r of a given complex function f : C → C must satisfy the condition ||f(r)|| = 0, that is, f(r) must have 2-dimensional Eu- clidean norm equal to 0, considering r as a point of R2. In the opposite direction, for any r ∈ C, ||f(r)|| = 0 implies f(r) = 0 and r is a root of f. Focusing again on the Riemann zeta function ζ, the open and simply connected region Rc = (1/2,1)×(0,∞) is used along the text, taking into account the symmetries of zeros of ζ in the critical strip. In this fashion, finding a global optimizer for ||ζ|| is equivalent to finding a root of ζ. Therefore, and taking into account the well-known efficacy of HQF ASA, a good sign of the trueness of RH would be not finding global minima in several optimization sessions with expanding subsets of Rc. In practical terms, several optimization sessions are executed using QMF ASA with increasing subsets of Rc, searching for global minima of ||ζ||. After presenting numerical results and figures, the adequacy of the proposed approach as a tool for preliminary empirical analysis for this type of problem is discussed.

The issue of climate change represents a significant global risk that demands immediate attention. However, higher education frequently fails to incorporate global perspectives and intricate transdisciplinary matters. In order to integrate global and transdisciplinary aspects into the curriculum of a technical university with a focus on computer science, a Master's programme has been developed. The programme's objective is to situate global risk at the core of the curriculum, thereby encouraging scientists to work beyond the boundaries of their respective disciplines. The paper considers the challenges that science and higher education must address to facilitate pathways towards a peaceful and sustainable future. It argues for a shift in focus from short-term and localised issues to a more holistic approach, emphasising the importance of considering universal problems. The curriculum, as developed, may be regarded as a guide for future university efforts in the fields of global risk and climate change.

More than 400 million tons of livestock waste are generated annually by approximately 25,000 concentrated animal feeding operations (CAFOs) located in the United States (US). These operations give rise to externalities, including adverse local and global health impacts from CAFO waste emissions, which can potentially outweigh their economic viability. However, a shortage of evidence synthesis research on US-based CAFO emissions may hinder effective policy development. This scoping review (ScR) study, conducted following guidance from the Joanna Briggs Institute, searched databases including Scopus, Web of Science, PubMed and Embase in May 2020, yielding ten publications meeting inclusion criteria. Results suggest possible CAFO worker exposures to multidrug-resistant Staphylococcus aureus (MDRSA), campylobacteriosis and cryptosporidiosis. Communities near CAFOs experienced higher rates of adverse health impacts compared to those in non-CAFO areas, with patterns suggesting proximity may correlate with increased odds of detrimental health effects. Implicit global health threats include Methicillin-resistant Staphylococcus aureus  (MRSA), MDRSA, campylobacteriosis, tuberculosis, and cryptosporidiosis. These studies provide foundational insights into CAFO proximity, density patterns, and adverse public health effects, indicating a need for evidence-informed environmental health policies to minimize local and global risks.

Energy poverty in the Global South generally focuses on the lack of basic access to modern fuels and energy carriers. Impoverished people rely primarily on traditional biomass as a source of energy. This situation of basic resource deprivation, in which almost one third of the world's population lives, masks other relevant features of the problem. Current assessments of energy poverty in impoverished areas and the mitigation strategies being implemented derive from the development agenda and, with variations in detail and scope, highlight electricity connections and access to clean cooking fuels as guarantors of progress. However, a comprehensive understanding of energy poverty requires going beyond basic access, building on the interactions between the supply of energy sources and carriers, the provision of energy services and its impact on decent living conditions. Several studies in the last decade have attempted to construct an assessment framework centered on energy services to deal with these interactions. This work discusses the relevant dimensions in the framework (supply, services and impact in wellbeing), reviews the multidisciplinary work available in each aspect, presents a range of proposed taxonomies, and discusses the different issues. A detailed framework is proposed for the integrated assessment of the supply of energy carriers and energy equipment, the provision of relevant energy services, and the improvements obtained in living conditions.

Vaccination is an important method of immunological preventive care required for health management of all animal including fish. More particularly, immunization is important in in-land fisheries for the management of diseases in fish brood stocks and healthy seed production. According to the latest statistics in 2020, 90.3 million tonnes of captured fish production was achieved from the aquaculture sector. Out of the above, 78.8 million tonnes from marine and 11.5 million tonnes from inland waters aquaculture sectors. About 4% decline in fish production was achieved in 2020 than 2018 from inland fisheries sectors. On the other hand, the digestive protein content, healthy fats and nutritional values of fish products are comparitively more affordable as compared to other meat sources. In 2014, about 10% aquatic cultured animals were lost (costing &gt; 10 billion $ global annual loss) due to infectious diseases. Therefore, vaccination in fish especially in brood stocks is one of the most important approaches to stop such losses in the fisheries sector. Fish vaccines consist of either whole killed pathogens, subunit of a protein, a recombinant protein, DNA vaccines or live attenuated vaccines. Challenges existing are adaption of vaccination in fisheries sector, route of administration, use of effective adjuvants and most importantly lack of effective results. Use of autogenous vaccines, vaccination via intramuscular, intraperitoneal or oral routes, and most importantly adding vaccines in feed using top dressing methods or as a constituent in fish feed are now in emerging. These method shall lower the risk of using antibiotics in cultured water which in turn will reduce the environmental contamination.

International law faces numerous challenges in the 21st century, ranging from the traditional issues of sovereignty to emerging threats like cyber warfare and climate change. This article explores the evolving landscape of international law, discussing both the challenges it faces and the prospects for its future. By examining the role of international organizations, the impact of technological advancements, and the growing influence of non-state actors, this article provides a comprehensive overview of the current state of international law and offers insights into how it can adapt to meet the demands of an increasingly interconnected world.

Background: Many clinical conditions are affected by meteorological factors and climate changes. Psychiatric disorders are large contributors to the global disease burden, but the literature on the impact of climate changes on mental health is limited. The aim of this study is to investigate the correlation between rising temperatures and admissions for acute exacerbations of psychiatric disorders. Methods: Data were collected for summer months of years 2013 to 2022. Mean monthly tempera-tures were obtained from the meteorological station of the Department of Physics of the Universi-ty of Turin. Data on patients admitted to the acute psychiatric unit of San Luigi Gonzaga Univer-sity Hospital (Turin, Italy) were extracted from the hospital registry. Linear regression analyses were used to investigate the correlation between temperature and number of admissions. Results: A total of 1600 admissions to our psychiatric ward were recorded. Mean monthly temper-ature and monthly number of admissions were directly correlated (P = 0.0020). The correlation between temperature and admissions was significant for the subgroup of admissions due to Bipo-lar Disorders (BD) (P=0.0011), but not for Schizophrenia (P=0.6070) (SCZ) or Major Depressive Disorder (MDD) (P=0.0588). Conclusions: These results confirm the impact of meteorological factors on mental disorders, and in particular on the course of BD. This provides new insights into etiopathological mechanisms and can contribute to improved follow up and relapse prevention.

Sarcopenia is associated with clinical complications, which increase mortality. Effective sarcopenia risk screening in the elderly should be grounded in a comprehensive assessment, encompassing both nutritional status and medication use. Current screening tools, while emphasizing muscular per-formance, exhibit limited sensitivity in identifying elderly individuals at risk of sarcopenia. This cross-sectional study aimed to develop a sarcopenia risk screening tool, named Sarc-Global, with enhanced sensitivity, incorporating factors pertinent to the overall health of the elderly. Utilizing the criteria established by EWGSOP2 for diagnosing sarcopenia, we evaluated 395 communi-ty-dwelling elderly individuals. This evaluation served as a reference for assessing the efficacy of two validated questionnaires, Sarc-F and Sarc-CalF, and our newly developed Sarc-Global. Con-structed through multiple logistic regression, Sarc-Global integrates variables such as sex, age, medication use, body mass index, arm circumference, and handgrip strength – all significantly associated with sarcopenia (p

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

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

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

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

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