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This study introduces a new approach to the development of generalized 1-parameter, 2-variable Hermite–Frobenius–Euler polynomials, which are characterized by their generating functions, series definitions and summation formulae. Additionally, the research utilizes a factorization method to establish recurrence relations, shift operators and various differential equations, including differential, integro-differential and partial differential equations. The framework elucidates the fundamental properties of these polynomials by utilizing generating functions, series definitions and summation formulae. The results of the study contribute to the understanding of the properties of these polynomials and their potential applications.

In the development of hybrid special polynomials, it is essential to incorporate the monomiality principle, operational rules, and other related properties. This research study adopts this approach and introduces a novel polynomial type called the two-iterated degenerate Appell polynomials, utilizing the monomiality principle. This study yields new findings that align with previous research efforts. The study presents explicit formulas and key properties of these polynomials, while also establishing connections with other polynomial types such as the Bernoulli, Euler, and Genocchi polynomials. These connections facilitate the derivation of additional results. By employing the monomiality principle and considering the aforementioned polynomials as initial members of the Appell family, this study contributes to the expansion of knowledge in the field of special polynomials.

Abstract Dinanath grass (Pennisetum pedicellatum Trin.) is an extensively grown forage grass known for its significant drought resilience. In order to comprehensively grasp the adaptive mechanism of Dinanath grass in response to water deficient conditions, transcriptomic and metabolomics were applied in the leaves of Dinanath grass exposed to two distinct drought intensities (48-hour and 96-hour). Transcriptomic analysis of Dinanath grass leaves revealed that a total of 218 and 704 genes were differentially expressed under 48- and 96-hour drought conditions, respectively. The genes that were expressed differently (DEGs) and the metabolites that accumulated in response to 48-hour drought stress mainly showed enrichment in the biosynthesis of secondary metabolites, particularly phenolics and flavonoids. Conversely, under 96-hour drought conditions, the enriched pathways predominantly involved lipid metabolism, specifically sterol lipids. In particular, phenylpropanoid pathway and brassinosteroid signaling played a crucial role in drought response to 48- and 96-hour water deficit conditions, respectively. This variation in drought response indicates that the adaptation mechanism in Dinanath grass is highly dependent on the intensity of drought stress. In addition, different genes associated with phenylpropanoid and fatty acid biosynthesis, as well as signal transduction pathways namely phenylalanine ammonia-lyase, putrescine hydroxycinnamoyl transferase, abscisic acid 8’-hydroxylase 2, syntaxin-61, lipoxygenase 5, calcium-dependent protein kinase and phospholipase D alpha one, positively regulated with drought tolerance. Combined transcriptomic and metabolomic analyses highlights the outstanding involvement of regulatory pathways related to secondary cell wall thickening and lignin biosynthesis in imparting drought tolerance to Dinanath grass leaves. These findings collectively contribute to an enhanced understanding of candidate genes and key metabolites relevant to drought response in Dinanath grass. Furthermore, they establish a groundwork for the creation of a transcriptome database aimed at developing abiotic stress-tolerant grasses and major crop varieties through both transgenic and genome editing approaches.

In this research, we leverage various $ q $-calculus identities to introduce the notion of $ q $-Hermite-Appell polynomials involving three variables, elucidating their formalism. We delve into numerous properties and unveil novel findings regarding these $ q $-Hermite-Appell polynomials, encompassing their generating function, series representation, summation equations, recurrence relations, $ q $-differential formula, and operational principles. Our investigation sheds light on the intricate nature of these polynomials, elucidating their behavior and facilitating deeper understanding within the realm of $ q $-calculus.

We present a novel framework for introducing generalized 3-variable 1-parameter Hermite-based Appell polynomials. These polynomials are characterized by generating function, series definition, and determinant definition, elucidating their fundamental properties. Moreover, utilizing a factorization method, we established recurrence relations, shift operators, and various differential equations, including differential, integrodifferential, and partial differential equations. Special attention is given to exploring the specific cases of 3-variable 1-parameter generalized Hermite-based Bernoulli, Euler, and Genocchi polynomials, offering insights into their unique features and applications.

The microwave-assisted fluidized bed two-stage novel, energy-efficient drying method was used for Agaricus bisporus drying which can be further utilised for mushroom protein powder, and soup. The effect of microwave heating time (MHT), fluidized bed drying temperature (FBDT), and slice thickness (ST) on rehydration ratio, total colour difference (TCD), and overall acceptability of white button mushroom (WBM) powder was investigated. The optimized values, i.e., 1 min (MHT), 60 °C (FBDT), and 2 mm (ST), were obtained during optimization using design expert software (ver. 13.0.1). The result revealed that MHT, FBDT, and ST affect the responses significantly. TCD was found to be increased while overall acceptability decreased as MHT and FBDT increased. Rehydration is an important criterion for using dry products in curry or soup since they may absorb water. The optimized WBM (O-WBM) powder was used to prepare the soup mix. Out of three formulations (F1, F2, and F3), F3 had a 9 % O-WBM powder score with a maximum mean value for colour, taste, flavor, consistency, and overall acceptability, followed by F2 with a 7 % O-WBM powder. The soup’s composition includes functional ingredients such as garlic, shallots, and milk powder, making it healthier.

OBJECTIVE: To study the frequency and antifungal susceptibility of the Candida albicans and non-albican species in diabetic foot infections from samples collected in a tertiary care hospital of district Peshawar. METHODOLOGY: This cross-sectional study was conducted from March 2020 to February 2021 in Khyber Teaching Hospital and Hayatabad Medical Complex, Peshawar. Specimen for culture swabs or tissue from diabetic foot ulcers was taken using aseptic methods. If pus was absent in the wound, ulcer scraping was collected. One tissue sample was soaked in 10% KOH for microscopy, while the second sample was used for fungal culture and sensitivity using Sabouraud dextrose agar. RESULTS: Of the 600 samples, 200 patients had diabetic foot ulcers with positive fungal culture from Males 102(51%) and Females 98(49%). The age range was 40-78 years. The frequency of C. albicans, C. dubliniensis, C. famata, C. glabrata, C. parapsilosis, and C. lusitaniae was 23(11.5%), 27(13.5%), 19(9.5%), 19(9.5%), 88(44%) and 24(12%). C. albicans was the most common fungal species. Antifungal susceptibility testing was done, and resistance to drugs like Amphotericin, Caspofungin, Fluconazole, Flucytosine, Itraconazole, Micafungin, Voriconazole which was 6.5%, 16%, 25.5%, 5.5%, 3%, 22.5%, 21% respectively. Resistance to Fluconazole, Micafungin and Voriconazole was the highest among all commonly used antifungal drugs. CONCLUSION: Fungal infection in diabetic foot ulcers usually does not respond to antibiotics. Candia albicans and non-albicans spp are also associated with diabetic foot ulcer infection and inflammation, and these fungi have the highest resistance to commonly used antifungal agents.

Background: Agitation is frequently encountered in patients recovering from traumatic brain injury (TBI) in the intensive care unit (ICU). The etiopathology for agitation is multifactorial. Melatonin has been widely used to study the effects of delirium in ICU, however, its effect on agitation is not well studied. Aims and Objectives: The aim of this study was to assess the effect of melatonin administration on the prevalence of agitation and length of stay in patients with severe TBI, managed conservatively, or undergoing decompressive craniectomy. Materials and Methods: A retrospective observational study with 70 patients undergoing various decompressive craniotomy or managed conservatively, and admitted to neurosurgical ICU was included in the study. Thirty-six patients were recruited from the control group and 34 patients received melatonin during their stay in the ICU. In this study, records of 70 patients who had suffered isolated TBI with no associated injuries were analyzed. The patients had a Glasgow coma score of 3–14 on admission to ICU. The patients were managed as per the standard protocols, as per the existing guidelines, and based on TBI guidelines. Results: A non-significant decreasing trend of agitation and reduced duration of ICU stay was noted in patients who received melatonin compared with the control group. The prevalence of agitation observed on modified Ramsay scale (Mean±SD) in patients who received melatonin on Day 3, Day 4, Day 5, Day 6, Day 7, Day 8, and Day 9 were −1.67±3.01; −1.61±2.82; −1.2±2.55; −1.23±2.51; −1.23±2.11; −1.05±2.09; and 0.76±2.03, respectively. These scores were slightly lower than observed in the control group on Day 3, Day 4, Day 5, Day 6, Day 7, Day 8, and Day 9 as −1.58±3.16; −1.33±2.72; −1.08±2.46; −1.13±2.25; −0.94±1.87; −0.52±1.7; and 0.52±1.36, respectively. The mean±SD duration of stay in ICU of patients receiving melatonin (13.14±3.37) and not receiving melatonin (14.52±3.73) was comparable (P=0.1). Conclusion: Although there was a decreased prevalence of agitation and a decrease in the mean duration of the ICU stay in patients who received oral melatonin, these beneficial effects did not show any statistical significance once compared with the control group.

This study explores the evolution and application of integral transformations, initially rooted in mathematical physics but now widely employed across diverse mathematical disciplines. Integral transformations offer a comprehensive framework comprising recurrence relations, generating expressions, operational formalism, and special functions, enabling the construction and analysis of specialized polynomials. Specifically, the research investigates a novel extended family of Frobenius-Genocchi polynomials of the Hermite-Apostol-type, incorporating multivariable variables defined through fractional operators. It introduces an operational rule for this generalized family, establishes a generating connection, and derives recurring relations. Moreover, the study highlights the practical applications of this generalized family, demonstrating its potential to provide solutions for specific scenarios.

Originally developed within the realm of mathematical physics, integral transformations have transcended their origins and now find wide application across various mathematical domains. Among these applications, the construction and analysis of special polynomials benefit significantly from the elucidation of generating expressions, operational principles, and other distinctive properties. This study delves into a pioneering exploration of an extended lineage of Frobenius-Euler polynomials belonging to the Hermite-Apostol type, incorporating multivariable variables through fractional operators. Motivated by the exigencies of contemporary engineering challenges, the research endeavors to uncover the operational rules and establishing connections inherent within these extended polynomials. In doing so, it seeks to chart a course towards harnessing these mathematical constructs within diverse engineering contexts, where their unique attributes hold the potential for yielding profound insights. The study deduces operational rules for this generalized family, facilitating the establishment of generating connections and the identification of recurrence relations. Furthermore, it showcases compelling applications, demonstrating how these derived polynomials may offer meaningful solutions within specific engineering scenarios.

Background: Ultrasound has become the standard of care for the insertion of central venous catheters (CVCs) in the intensive care unit. With the introduction of ultrasonography in CVC insertion, there has been an improvement in the success rate and a dramatic decrease in the rate of complications. Aims and Objectives: The aim of this study was to compare the safety and ease of insertion of ultrasonically guided cannulation of the internal jugular vein (IJV) with that of the supraclavicular subclavian vein (SCV) in adult patients undergoing various surgical procedures. Materials and Methods: All the patients in whom central venous cannulation was planned were assigned to two groups. Group I underwent ultrasound-guided IJV while as Group II underwent cannulation ultrasound-guided SCV cannulation. A comparison was made between the two groups, of the success rates, durations of procedure, number of attempts at needle redirections, difficulties if any during insertion of guidewires, and the complications encountered. Results: The IJV group had a higher proportion of first-attempt success (93.2% versus 62.7%). The IJV group had a lesser incidence (3.2%) of complications such as guidewire progression and needle redirections compared with SCV (15.2%). The frequency of adverse events did not differ between the two study groups with an incidence in 3.2% in IJV group and 9.6% in the subclavian group. Higher first-attempt success rates and fewer procedural complications were seen with ultrasound-guided IJV. Conclusion: IJV central venous catheterization is an easier and less invasive and less risky procedure for patients.

Background: The occurrence of delirium in patients who undergo elective surgeries is a common occurrence. Multiple studies have assessed the effect of different drugs in various elective procedures to decrease the prevalence of postoperative delirium. The effect of melatonin to decrease the prevalence of delirium and duration of neurosurgical intensive care unit (NSICU) stay in patients undergoing neurosurgery has not been studied previously. The current study aimed to assess the same. Aims and Objectives: To assess the effect of preoperative and postoperative melatonin administration on the prevalence of delirium in patients undergoing elective ventilation in NSICU and to assess the effect of preoperative and postoperative melatonin administration on the duration of stay in NSICU. Methods and Methods: In this prospective observational study, 60 patients undergoing various neurosurgical procedures and admitted to NSICU were included. The patients were divided into two groups: one group received a placebo (Group P- tablet Sugarfree containing Aspartame) and another group received a tablet of melatonin 3 mg (Group M) in the preoperative and postoperative period. The effect of melatonin on the prevalence of delirium and duration of NSICU stay in these two groups was observed. Results: A decreasing trend of delirium was noted in both groups (Group M and Group P) with no statistical significance. A decreased prevalence of delirium was observed in patients of group M (33.3%) at the end of 12 h post-extubation compared to Group P (43.3%). The mean duration of stay for the patients in NSICU in Groups M and P were 2.7 and 3.2 days, with the range (1–14 Days) in Group M and Group P (1–20 days), respectively. Conclusion: Although there was a decreased prevalence of delirium and a decrease in the mean duration of the intensive care unit stay in patients who received oral melatonin, these beneficial effects did not show any statistical significance once compared with the control group.

Biodiversity loss is a pressing global issue, with protected areas and Other Effective Area-Based Conservation Measures (OECMs) identified as crucial strategies for conservation. This study investigates the contribution of wilderness networks beyond existing protected areas to biodiversity conservation in Central Asia, proposing a comprehensive framework for wilderness network assessment and identifying potential OECM areas. Using Boolean overlay and weighted linear combination approach, the research delineated core wilderness patches and assessed their spatial relationship with existing protected area. The study employed multi-scenario assessment framework to reconstruct twelve landscape ecological networks, results exposed the potential of wilderness networks as supplementary areas to existing protected area networks. The study also identified 241 critical pinch points essential for maintaining regional wildlife habitat connectivity and species migration. The research advocates for the integration of wilderness networks with OECMs to achieve the 30×30 conservation goal. The study's findings underscore need for additional conservation measures beyond existing protected areas and importance of considering human activity disturbances, maintaining landscape connectivity, as well as evaluating cost-effective conservation strategies. It also highlights the necessity for cross-border collaboration in regional-scale wilderness research. This study contributes to the planning and development of policies for wilderness conservation and provides a replicable framework for similar global assessments.

Introduction A patient safety culture primarily refers to the values, beliefs, attitudes, and behaviors within a healthcare setup in a community that assists in prioritizing patient safety and encouraging the reporting of errors and near-misses in that facility. There is a direct impact of patient safety culture on how well patient safety and quality improvement programs work. The aim of this cross-sectional descriptive study was to investigate the practices to improve patient safety culture and adverse event reporting practices among healthcare professionals in a tertiary care hospital located in Mirpur Azad Jammu and Kashmir. Methods In the non-probability convenience sampling of this cross-sectional study, Divisional Headquarters Teaching Hospital in Mirpur, Azad Kashmir used the Agency for Healthcare Research and Quality Surveys on Patient Safety Culture Hospital Survey to collect data about the perceptions of healthcare professionals regarding patient safety culture within their hospital to assess the trends of patient safety culture by obtaining longitudinal data. A pre-validated questionnaire that has undergone a rigorous trial of testing to maximize the reliability and accuracy of the outcomes was distributed among clinical staff (healthcare professionals who interact with patients on a daily basis, such as nurses, doctors, pharmacists, and laboratory technicians) and administrative staff (medical superintendent, deputy medical superintendent, assistant medical superintendent, heads of departments). Results A total of 312 questionnaires were returned (response rate, 76%). The study found that the dimension “supervisor/manager expectation and action promoting safety” had the highest positive response rate (65.16%), and “nonpunitive response” had the lowest (27.4%). Higher scores in “nonpunitive response to error” were associated with lower rates of medication errors, pressure ulcers, and surgical site infections, and higher scores in “frequency of event reporting” were associated with lower rates of medication errors, pressure ulcers, falls, hospital-acquired infections, and urinary tract infections. Conclusion We suggest that in order for hospital staff to continue providing excellent, clinically safe treatment, a well-structured hospital culture promoting patient safety is necessary. Moreover, further study is needed to determine strategies to improve patient safety expertise and awareness, and lower the frequency of adverse occurrences.

The construction of green infrastructure networks is an effective measure to guide orderly city expansion and ensure ecological security. However, limited research has been conducted to explore practical strategies for enhancing ecosystem services threatened by urban development, particularly in plateau cities with constrained natural resources. Xining, the largest and most densely urbanized city on the Tibetan Plateau in China, faces a significant conflict between urban expansion and ecosystem service conservation that is limited by an uninhabitable climate and mountainous topography. It is the only central city on the Tibetan Plateau, with a population of 2.47 million (2020). From 2000 to 2020, the urban area expanded by 37.42%; thus, reconciling the escalating demand for natural resources driven by urban development and promoting synergistic development between ecosystem services and urbanization remains a challenge. Here, we propose a modeling framework to reconstruct ecosystem service values using improved temporal (pi) and spatial (di) difference indices, highlighting the temporal sensibility and spatial aggregation of multiple ecosystem services. The material quantities (di) and monetary values (pi) of seven ecosystem services were estimated using experimentally verified local parameters as a case study in Xining from 2000 to 2020. The green infrastructure network and its interactions were identified based on the reconstructed ecosystem service value using the gravity modeling toolbox proposed in our previous study. The results illustrated that the identified green infrastructure network comprised 48 ecological sources and 96 corridors, covering an area of 162318.3 hm2; while this includes approximately one-fifth of the total study area, but it contributes to one-third of the overall ecosystem service value. The conservation priority and planning construction areas in the Xining City Master Planning (2021–2035) outlines were then optimized based on the identified green infrastructure network. Overall, these optimized urban planning scenarios would reserve 59.3 million CNY of the reconstructed ecosystem service value encroached on by urban sprawl. The opportunity cost is transferring 14.7% of the planned construction area overlapping with the green infrastructure network. This study provides a distinctive example for establishing a green infrastructure network based on the spatiotemporal dynamic sensitivity of ecosystem services and provides a strong reference for sustainable development and ecosystem service conservation, particularly in plateau cities.

This study presents the dynamic analysis for the fractional order economic and financial supply chain dynamical system using the supervised neural network performances aided with scale conjugate gradient. The investigations based on the fractional derivatives have been implemented to achieve the realistic and accurate performances of the fractional order economic and financial supply chain dynamical system. The mathematical form of the fractional order economic and financial supply chain dynamical system is categorized into three dynamics: rate of interest, investment cost, and price index. Three different variations based on the fractional order form of the economic and financial supply chain dynamical system have been numerically presented using the supervised neural network performances based on the scale conjugate gradient scheme. The selection of the data for solving the economic and financial supply chain dynamical system is taken as 80% for training, and 12% for testing, and 8% for endorsement. The accuracy of the proposed stochastic scheme is presented using the obtained and referenced Adam results. Rationality, capability and perfection are performed through the supervised neural network with scale conjugate gradient scheme performances-based together with the performances of correlation/regression, mean square error, state transition measures, and error histograms. Finally, a comparison of numerical results is examined and observed that the range of absolute error is between $10^{-05}$ to $10^{-07}$ which indicates that the proposed stochastic computing model can effectively analyze the economic and financial supply chain dynamical system.

Locating veins accurately is a common challenge in clinical settings, particularly with patients where veins are difficult to discern. The development of effective vein visualization technology is crucial for improving patient outcomes and minimizing procedural complications. This study aimed to design, develop, and evaluate a low-cost, high-resolution portable vein finder device. It was developed using affordable components and integrated imaging technology. The device captured images of veins in challenging patient scenarios. Four conventional image enhancement techniques were initially applied to these images. Subsequently, a novel image enhancement technique is proposed. The performance of each technique was qualitatively accessed using visual representation and histogram distribution and quantitatively assessed using the peak signal-to-noise ratio and structural similarity index measure. The proposed technique significantly outperformed the conventional methods. This indicates a superior enhancement of vein visibility, confirming the effectiveness of the proposed method. Thus, the newly developed vein finder, enhanced with the proposed image enhancement technique demonstrates significant potential for clinical use. It offers a reliable solution for vein detection in patients, potentially improving treatment accuracy.

In the ever-changing world of decision-making, when game theory and reinforcement learning(RL) come together, they create a fascinating combination that shows a new way to solve complex problems in many fields. The combination of game theory and RL is a powerful convergence that opens up a hopeful new frontier for dealing with complex decision-making problems in many different fields. Research on the convergence of game theory and RL has shown to be beneficial, providing essential insights into challenging decision-making issues in various disciplines. This study investigates the recent developments of game theory and RL approaches through a systematic review and highlights the significance of game theory in boosting reinforcement algorithms and increasing the interaction of autonomous vehicles, safeguarding edge caching, and more. It offers a thorough account of the developments at the confluence of game theory and RL. The reviewed papers mainly focus on broad themes and address three important research questions: the impact of game theory on multi-agent reinforcement learning (MARL), the significant contributions of game theory to RL, and the significant impact areas. Following the methodology, search outcomes, and study areas is a discussion on game theory-related terminology, followed by study findings. The review’s conclusions offer ideas for further study and open research questions. The importance of game theory in advancing MARL, the potential of game theory in promoting RL strategies, and the opportunities for combining game theory and RL in cutting-edge fields like mobile edge caching and cyber-physical systems(CPS) are all emphasized in the conclusion. This review article advances our knowledge of the theoretical underpinnings and real-world applications of game theory and RL, laying the groundwork for future improvements in decision-making techniques and algorithms.

This paper offers a thorough examination of a unified class of Humbert’s polynomials in two variables, extending beyond well-known polynomial families such as Gegenbauer, Humbert, Legendre, Chebyshev, Pincherle, Horadam, Kinnsy, Horadam–Pethe, Djordjević, Gould, Milovanović, Djordjević, Pathan, and Khan polynomials. This study’s motivation stems from exploring polynomials that lack traditional nomenclature. This work presents various expansions for Humbert–Hermite polynomials, including those involving Hermite–Gegenbauer (or ultraspherical) polynomials and Hermite–Chebyshev polynomials. The proofs enhanced our understanding of the properties and interrelationships within this extended class of polynomials, offering valuable insights into their mathematical structure. This research consolidates existing knowledge while expanding the scope of Humbert’s polynomials, laying the groundwork for further investigation and applications in diverse mathematical fields.

The primary objective of this research is to introduce and investigate novel polynomial variants termed Δh Laguerre polynomials. This unique polynomial type integrates the monomiality principle alongside operational rules. Through this innovative approach, the study delves into uncharted territory, unveiling fresh insights that build upon prior research endeavours. Notably, the Δh Laguerre polynomials exhibit significant utility in the realm of quantum mechanics, particularly in the modelling of entropy within quantum systems. The research meticulously unveils explicit formulas and elucidates the fundamental properties of these polynomials, thereby forging connections with established polynomial categories. By shedding light on the distinct characteristics and functionalities of the Δh Laguerre polynomials, this study contributes significantly to their comprehension and application across diverse mathematical and scientific domains.

The main purpose of this article is to construct a new class of multivariate Legendre-Hermite-Apostol type Frobenius-Euler polynomials. A number of significant analytical characterizations of these polynomials using various generating function techniques are provided in a methodical manner. These enactments involve explicit relations comprising Hurwitz-Lerch zeta functions and λ-Stirling numbers of the second kind, recurrence relations, and summation formulae. The symmetry identities for these polynomials are established by connecting generalized integer power sums, double power sums and Hurwitz-Lerch zeta functions. In the end, these polynomials are also characterized Svia an algebraic matrix based approach.

This paper presents a novel framework for introducing generalized 1-parameter 3-variable Hermite polynomials. These polynomials are characterized through generating functions and series definitions, elucidating their fundamental properties. Moreover, utilising a factorisation method, this study establishes recurrence relations, shift operators, and various differential equations, including differential, integro-differential, and partial differential equations.

Various authors have put their sincere efforts into proposing ratio estimators for estimating the population's mean and variance under different situations and sampling methods. But the problem arises when data is unstable, imprecise, ambiguous, incomplete and vague. In such situations, classical methods of estimation do not yield precise results, as these methods are not meant for such problems. Given this difficulty, Neutrosophic statistics are the only alternative as it deals with indeterminacy. So in this study, we have proposed a generalized Neutrosophic robust ratio type estimator which can be used to provide good results in such situations, as well as in the case of the presence of outliers. For the evaluation point of view, we have made use of real data set and simulation study to check the efficacy of our suggested estimators over the mentioned existed estimators.

This paper introduces the operational rule for 2-iterated 2D Appell polynomials and derives its generalized form using fractional operators. It also presents the generating relation and explicit forms that characterize the generalized 2-iterated 2D Appell polynomials. Additionally, it establishes the monomiality principle for these polynomials and obtains their recurrence relations. The paper also establishes corresponding results for the generalized 2-iterated 2D Bernoulli, 2-iterated 2D Euler, and 2-iterated 2D Genocchi polynomials.

Snow leopards (Panthera uncia) are elusive predators inhabiting high-altitude and mountainous rugged habitats. The current study was conducted in the Yanchiwan National Nature Reserve, Gansu Province, China, to assess the habitat suitability of snow leopards and identify key environmental factors inducing their distribution. Field data collected between 2019 and 2022 through scat sampling and camera trapping techniques provided insights into snow leopard habitat preferences. Spatial distribution and cluster analyses show distinct hotspots of high habitat suitability, mostly concentrated near mountainous landscapes. While altitude remains a critical determinant, with places above 3300 m showing increased habitat suitability, other factors such as soil type, human footprint, forest cover, prey availability, and human disturbance also play important roles. These variables influence ecological dynamics and are required to assess and manage snow leopard habitats. The MaxEnt model has helped us to better grasp these issues, particularly the enormous impact of human activities on habitat suitability. The current study highlights the importance of altitude in determining snow leopard habitat preferences and distribution patterns in the reserve. Furthermore, the study underscores the significance of considering elevation in conservation planning and management strategies for snow leopards, particularly in mountainous regions. By combining complete environmental data with innovative modeling tools, this study not only improves local conservation efforts but also serves as a model for similar wildlife conservation initiatives around the world. By understanding the environmental factors driving snow leopard distribution, conservation efforts can be more efficiently directed to ensure the long-term survival of this endangered species. This study provides valuable insights for evidence-based conservation efforts to safeguard the habitats of snow leopards amidst emerging anthropogenic pressure and environmental fluctuations.

This research aims to introduce and examine a new type of polynomial called the Δh Legendre–Appell polynomials. We use the monomiality principle and operational rules to define the Δh Legendre–Appell polynomials and explore their properties. We derive the generating function and recurrence relations for these polynomials and their explicit formulas, recurrence relations, and summation formulas. We also verify the monomiality principle for these polynomials and express them in determinant form. Additionally, we establish similar results for the Δh Legendre–Bernoulli, Euler, and Genocchi polynomials.

The inevitable impacts of climate change have reverberated across ecosystems and caused substantial global biodiversity loss. Climate-induced habitat loss has contributed to range shifts at both species and community levels. Given the importance of identifying suitable habitats for at-risk species, it is imperative to assess potential current and future distributions, and to understand influential environmental factors. Like many species, the Demoiselle crane is not immune to climatic pressures. Khyber Pakhtunkhwa and Balochistan provinces in Pakistan are known wintering grounds for this species. Given that Pakistan is among the top five countries facing devastating effects of climate change, this study sought to conduct species distribution modeling under climate change using data collected during 4 years of field surveys. We developed a Maximum Entropy distribution model to predict the current and projected future distribution of the species across the study area. Future habitat projections for 2050 and 2070 were carried out using two representative concentration pathways (RCP 4.5 and RCP 8.5) under three global circulation models, including HADGEM2-AO, BCC-CSM1-1, and CCSM4. The most influential factors shaping Demoiselle Crane habitat suitability included the temperature seasonality, annual mean temperature, terrain ruggedness index, and human population density, all of which contributed significantly to the suitability (81.3%). The model identified 35% of the study area as moderately suitable (134,068 km2) and highly suitable (27,911 km2) habitat for the species under current climatic conditions. Under changing climate scenarios, our model predicted a major loss of the species’ current suitable habitat, with shrinkage and shift towards western–central areas along the Pakistan–Afghanistan boarder. The RCP 8.5, which is the extreme climate change scenario, portrays particularly severe consequences, with habitat losses reaching 65% in 2050 and 85% in 2070. This comprehensive study provides useful insights into the Demoiselle Crane habitat’s current and future dynamics in Pakistan.

The development of certain aspects of hybrid special polynomials after incorporating monomiality principle, operational rules, and other properties and their aspects is obvious and indisputable. The study presented in this paper follows this line of research. By using the monomiality principle, new outcomes are produced, thus in line with prior facts, our aim is to introduce the degenerate 2D bivariate Appell polynomials $ \mathbb {R}^{m}_j(u,v;h) $ . Further, we obtain some well-known main properties and explicit forms satisfied by these polynomials. Also, generating relations corresponding to the degenerate 2D bivariate Bernoulli, Euler, and Genocchi polynomials are established, they will further be helpful in establishing the corresponding results for these polynomials.

Human expansion and anthropogenic activities are causing the conversion of forests to other land uses in the Himalayas, which is threatening species with extinction. To address this issue, we used an ensemble model to simulate the future landscape and assess its impact on the Kashmir Musk Deer (KMD) distribution in the context of land use change. Our simulation suggests a decline in croplands and shrublands and increase of mixed forests in the future scenario. Evergreen broad-leaf and needle-leaf forests are likely to convert to mixed forests, while croplands and barren areas transform into savannas. Precipitation, elevation, and mixed forests were found to be the most significant factors influencing KMD distribution. Only 20,690 km2 out of the total area of 324,666 km2 is currently suitable for KMD, but this is projected to increase to 22,701.47 km2 in the future. We predict a habitat gain of about 2,722 km2 in new areas and a loss of 711 km2 in existing habitats for KMD by 2030, with Uttarakhand state losing much of the suitable habitat. However, new habitats in future will become available for the species in Jammu and Kashmir. Our landscape configuration investigation indicates a decline in the number of patches and aggregation index in the future scenario. Most of the suitable KMD habitats are outside the current protected areas (PA), making the current PA network insufficient for long-term conservation. Therefore, we suggest forest managers to rationalize the boundary of the PAs to include suitable habitats that are currently not protected for the long-term survival of the KMD.

The COVID-19 pandemic has had an immense economic, social, and environmental impact on Supply Chains (SCs) worldwide. Despite the importance of the impact of the pandemic on SCs, very little research has been conducted on a comprehensive systematic literature review on the COVID-19 pandemic and SCs. This study presents this comprehensive analysis and includes a summary and classification of 393 papers published between 2019 and 2022. We show four broad themes in the literature: (1) the impacts of the COVID-19 pandemic on SCs, (2) SC resilience strategies for managing impacts, (3) SC sustainability issues, and (4) SC disruptions and mitigation techniques. We analyzed each theme based on the research aim, findings, methodology, specific methods, context, and study scale. We also present the open research questions and suggestions for further investigation. These suggestions can provide extensive insights for scholars and practitioners in designing and conducting impactful and insightful research.

Abstract Global forest area has declined over the past few years, forest quality has declined, and ecological and environmental events have increased with climate change and human activity. In the context of ecological civilization, forest health issues have received unprecedented attention. By improving forest health, forests can better perform their ecosystem service functions and promote green development. This study was carried out in the WuZhi Shan area of Hainan Tropical Rainforest National Park. We employed a decision tree algorithm, a machine learning technique, for our modeling due to its high accuracy and interpretability. The objective weighted method using criteria of importance through intercriteria correlation (CRITIC) was used to determine forest health classes based on survey and experimental data from 132 forest samples. The results showed that species diversity is the most important metric to measure forest health. An interpretable decision tree machine learning model was proposed to incorporate forest health indicators, providing up to 90% accuracy in the classification of forest health conditions. The model demonstrated a high degree of effectiveness, achieving an average precision of 90%, a recall of 67%, and an F1 score of 70.2% in predicting forest health. The interpretable decision tree classification results showed that breast height diameter is the most important variable in classifying the health status of both primary and secondary forests. This study highlights the importance of using interpretable machine learning methods for the decision‐making process. Our work contributes to the scientific underpinnings of sustainable forest development and effective conservation planning.

The aim of such work is to design a Meyer wavelet neural network (WNN) for solving the mathematical form of the Leptospirosis disease model (LDM). The global and local search optimization schemes based on the genetic algorithm (GA) and active-set algorithm (ASA) are used in this study. Leptospirosis is an infection spread by rodents, which is found in the world and causes fatalities in humans. The mathematical LDM model form consists of susceptible-infected-recovered (SIR), which is based on the disease spread processes. A fitness function is designed by using the mathematical LMD and then optimized by the hybridization of the GAASA. For the correctness, and capability of the Meyer WNN along with the procedures of GAASA, the comparison of the obtained and reference results is provided. Moreover, the reducible absolute error provides the efficiency of the proposed Meyer WNN along with the procedures of GAASA. The statistical observations are also provided to authenticate the convergence of the stochastic Meyer WNN along with the procedures of GAASA.

The evolution of a physical system occurs through a set of variables, and the problems can be treated based on an approach employing multivariable Hermite polynomials. These polynomials possess beneficial properties exhibited in functional and differential equations, recurring and explicit relations as well as symmetric identities, and summation formulae, among other examples. In view of these points, comprehensive schemes have been developed to apply the principle of monomiality from mathematical physics to various mathematical concepts of special functions, the development of which has encompassed generalizations, extensions, and combinations of other functions. Accordingly, this paper presents research on a novel family of multivariable Hermite polynomials associated with Frobenius–Genocchi polynomials, deriving the generating expression, operational rule, differential equation, and other defining characteristics for these polynomials. Additionally, the monomiality principle for these polynomials is verified, as well as establishing the series representations, summation formulae, operational and symmetric identities, and recurrence relations satisfied by these polynomials. This proposed scheme aims to provide deeper insights into the behavior of these polynomials and to uncover new connections between these polynomials, to enhance understanding of their properties.

Abstract The less phytopathogen susceptibility in Himalayan Brassica rapa L. has made it an exceptional crop eluding synthetic pesticide inputs, thereby guarantying economically well-founded and ecologically sustainable agriculture. The relevance of niche microflora of this crop has not been deliberated in this context, as endosymbiosiome is more stable than their rhizosphere counterparts on account of their restricted acquaintance with altering environment; therefore, the present investigation was carried out to study the endophytic microfloral dynamics across the B. rapa germplasm in context to their ability to produce chitinase and to characterize the screened microflora for functional and biochemical comportments in relevance to plant growth stimulation. A total of 200 colonies of bacterial endophytes were isolated from the roots of B. rapa across the J&K UT, comprising 66 locations. After morphological, ARDRA, and sequence analysis, eighty-one isolates were selected for the study, among the isolated microflora Pseudomonas sp. Bacillus sp. dominated. Likewise, class γ-proteobacteria dominated, followed by Firmicutes. The diversity studies have exposed changing fallouts on all the critical diversity indices, and while screening the isolated microflora for chitinase production, twenty-two strains pertaining to different genera produced chitinase. After carbon source supplementation to the chitinase production media, the average chitinase activity was significantly highest in glycerol supplementation. These 22 strains were further studied, and upon screening them for their fungistatic behavior against six fungal species, wide diversity was observed in this context. The antibiotic sensitivity pattern of the isolated strains against chloramphenicol, rifampicin, amikacin, erythromycin, and polymyxin-B showed that the strains were primarily sensitive to chloramphenicol and erythromycin. Among all the strains, only eleven produced indole acetic acid, ten were able to solubilize tricalcium phosphate and eight produced siderophores. The hydrocyanic acid and ammonia production was observed in seven strains each. Thus, the present investigation revealed that these strains could be used as potential plant growth promoters in sustainable agriculture systems besides putative biocontrol agents.

Abstract With growing water scarcity, jeopardized by climate change, springs are likely to perform a vital role in meeting the domestic water demand in future. This paper examines the water quality status of Kashmir valley springs in relation to their geographical location, regional hydrogeological conditions, anthropogenic activities and climate change. We analyzed data for 258 springs from the whole Kashmir valley using water quality index (WQI) and geographic information system techniques. WQI ranged from 23 (excellent water) to 537 (water unsuitable for drinking). The WQI indicated that 39.5% of the springs had excellent waters, 47.7% had good water, 5% had poor water, 1.6% had very-poor water, and 6.2% of the springs had water unfit for drinking purposes. The Piper diagram identified Ca–Mg–HCO3, Ca–Mg–SO4, and Na–HCO3 as the most predominant hydro-chemical facies, whereas Gibbs diagram revealed that the water of springs in the study region is mainly controlled by rock weathering dominance. The results of the study offer inputs about the water quality to be used by the concerned departments and agencies at a bigger scale for drinking purposes. Our findings therefore suggest that springs which are in thousands in Kashmir landscape have the potential to offer viable solution to the rising drinking water demand and therefore merit an attention for their protection and management.

The mechanisms underlying latitudinal and longitudinal patterns in species diversity remain a central issue in ecology and are vital for effective biodiversity conservation. Few studies have been conducted to synthesize the latitudinal patterns and the underlying mechanisms of multi-dimensional biodiversity in Chinese Nature Reserves, and we will provide comprehensive patterns of species and phylogenetic diversity for plant species along the latitudinal patterns. In this study, we selected 10,458 angiosperm species from 157 China’s nature reserves along the latitudinal gradients to explore the geographical distribution patterns of species richness (SR), phylogenetic diversity (PD), phylogenetic endemism (PE), net relatedness index (NRI) and phylogenetic structure. The results indicated that the angiosperm’s SR, PD, PE and NRI increased along the latitudinal gradients in China. Species diversity was significantly correlated with phylogenetic diversity and phylogenetic endemism. Our findings suggested that the species in the higher latitude regions were significantly phylogenetically clustered, whereas the species in the lower latitude regions indicated phylogenetic overdispersion. Temperature strongly correlated with species diversity, phylogenetic diversity, phylogenetic endemism, and phylogenetic structure for all plants. Our results showed that the determinants of diversity patterns and phylogenetic structure were different among herbs and woody plants. For herbs, the reserve area had the highest explanatory power for phylogenetic endemism. For woody plants, temperatures determine their diversity patterns and phylogenetic structure. This study improves our understanding of the latitudinal and longitudinal gradients of species diversity, and phylogenetic structure and provides support for the improvement of biodiversity conservation in China.

Seagrass meadows provide essential ecosystem services globally in the context of climate change. However, seagrass is being degraded at an accelerated rate globally due to ocean warming, ocean acidification, aquaculture, and human activities. The need for more information on seagrasses’ spatial distribution and health status is a serious impediment to their conservation and management. Therefore, we propose a new hybrid machine learning model (RF-SWOA) that integrates the sinusoidal chaos map whale optimization algorithm (SWOA) with a random forest (RF) model to accurately model the suitable habitat of potential seagrasses. This study combines in situ sampling data with multivariate remote sensing data to train and validate hybrid machine learning models. It shows that RF-SWOA can predict potential seagrass habitat suitability more accurately and efficiently than RF. It also shows that the two most important factors affecting the potential seagrass habitat suitability on Hainan Island in China are distance to land (38.2%) and depth to sea (25.9%). This paper not only demonstrates the effectiveness of a hybrid machine learning model but also provides a more accurate machine learning model approach for predicting the potential suitability distribution of seagrasses. This research can help identify seagrass suitability distribution areas and thus develop conservation strategies to restore healthy seagrass ecosystems.

Over the years, the vaste expansion of plastic manufacturing has dramatically increased the environmental impact of microplastics [MPs] and nanoplastics [NPs], making them a threat to marine and terrestrial biota because they contain endocrine disrupting chemicals [EDCs] and other harmful compounds. MPs and NPs have deleteriouse impacts on mammalian endocrine components such as hypothalamus, pituitary, thyroid, adrenal, testes, and ovaries. MPs and NPs absorb and act as a transport medium for harmful chemicals such as bisphenols, phthalates, polybrominated diphenyl ether, polychlorinated biphenyl ether, organotin, perfluorinated compounds, dioxins, polycyclic aromatic hydrocarbons, organic contaminants, and heavy metals, which are commonly used as additives in plastic production. As the EDCs are not covalently bonded to plastics, they can easily leach into milk, water, and other liquids affecting the endocrine system of mammals upon exposure. The toxicity induced by MPs and NPs is size-dependent, as smaller particles have better absorption capacity and larger surface area, releasing more EDC and toxic chemicals. Various EDCs contained or carried by MPs and NPs share structural similarities with specific hormone receptors; hence they interfere with normal hormone receptors, altering the hormonal action of the endocrine glands. This review demonstrates size-dependent MPs’ bioaccumulation, distribution, and translocation with potential hazards to the endocrine gland. We reviewed that MPs and NPs disrupt hypothalamic-pituitary axes, including the hypothalamic-pituitary-thyroid/adrenal/testicular/ovarian axis leading to oxidative stress, reproductive toxicity, neurotoxicity, cytotoxicity, developmental abnormalities, decreased sperm quality, and immunotoxicity. The direct consequences of MPs and NPs on the thyroid, testis, and ovaries are documented. Still, studies need to be carried out to identify the direct effects of MPs and NPs on the hypothalamus, pituitary, and adrenal glands.

Objective: To study electrocardiographic changes during haemodialysis and determine the relationship between electrolyte alterations and acid-base balance. Study Design: Cross-sectional analytical study. Place and Duration of Study: Haemodialysis Unit, Combined Military Hospital, Peshawar Pakistan, from Jun to Jul 2022. Methodology: Adult patients with end-stage renal disease on maintenance hemodialysis were selected by convenience sampling. Exclusion criteria included current hospitalization, chest pain during haemodialysis, intra-dialytic hypotension,atrial fibrillation, pericardial effusion, shortening of haemodialysis sessions and unwillingness to participate in the study.Twelve lead electrocardiograms were recorded immediately before the start and end of haemodialysis sessions. At the same time, serum urea, creatinine, potassium, calcium and phosphate were measured. Bicarbonate levels were assessed by venous blood gas analysis. In addition, measurements for heart rate and durations of the PR interval, QRS complex, QT interval andcorrected QT interval reported by ECG machine software were recorded. Results: There were 35 patients with a mean age of 48.69±11.39 years. Duration of QRS complex increased from 92.83±9.98 to 100.00± 17.94 seconds after haemodialysis (p=0.017). Changes in other parameters were insignificant. QT/QRS and QTc/QRS ratios reduced by 0.27±0.62 and 0.31±0.62 after haemodialysis (p=0.014 and 0.005, respectively). Changes in none of the biochemical parameters during haemodialysis could predict the reduction in QT/QRS or QTc/QRS ratios. Conclusion: The reduction in the index of cardiac electrophysiological balance during hemodialysis was not related to intradialytic changes in different electrolytes or base content.

Accurately delimiting phylogenetic relationships and taxonomic status is important for understanding species diversity and distributions and devising effective strategies for biodiversity conservation. However, species delimitation is controversial in Gymnocypris eckloni, a schizothoracine fish endemic to the Qinghai–Tibetan Plateau. The aim of this study is robustly identifying the phylogeny of G. eckloni in the Yellow River (YR) population and Qaidam basin (QB) population. The specific-locus amplified fragments sequencing (SLAF-seq) is employed with comprehensively sampling of schizothoracine fishes. In total, 350,181,802 clean reads and 5,114,096 SNPs are identified from SLAF-seq. Phylogenetic analysis recovers a non-monophyletic population of G. eckloni between YR and QB populations, representing an independent phylogenetic relationship between the two populations. Species delimitation analyses by SNAPPER and GMYC methods using the genome-wide SNP data confirm that their taxonomic statuses are separated. This study highlights the importance of further reconsidering clearer taxonomy, which would improve the genetic diversity conservation of Tibetan highland fishes.

This paper investigates the significance of generating expressions, operational principles, and defining characteristics in the study and development of special polynomials. The focus is on a novel generalized family of degenerate 2D Appell polynomials, which were defined using a fractional operator. Motivated by inquiries into degenerate 2D bivariate Appell polynomials, this research reveals that well-known 2D Appell polynomials and simple Appell polynomials can be regarded as specific instances within this new family for certain values. This paper presents the operational rule, generating relation, determinant form, and recurrence relations for this generalized family. Furthermore, it explores the practical applications of these degenerate 2D Appell polynomials and establishes their connections with equivalent results for the generalized family of degenerate 2D Bernoulli, Euler, and Genocchi polynomials.

In this paper, we consider a novel family of the mixed-type hypergeometric Bernoulli–Gegenbauer polynomials. This family represents a fascinating fusion between two distinct categories of special functions: hypergeometric Bernoulli polynomials and Gegenbauer polynomials. We focus our attention on some algebraic and differential properties of this class of polynomials, including its explicit expressions, derivative formulas, matrix representations, matrix-inversion formulas, and other relations connecting it with the hypergeometric Bernoulli polynomials. Furthermore, we show that unlike the hypergeometric Bernoulli polynomials and Gegenbauer polynomials, the mixed-type hypergeometric Bernoulli–Gegenbauer polynomials do not fulfill either Hanh or Appell conditions.

This paper introduces a new type of polynomials generated through the convolution of generalized multivariable Hermite polynomials and Appell polynomials. The paper explores several properties of these polynomials, including recurrence relations, explicit formulas using shift operators, and differential equations. Further, integrodifferential and partial differential equations for these polynomials are also derived. Additionally, the study showcases the practical applications of these findings by applying them to well-known polynomials, such as generalized multivariable Hermite-based Bernoulli and Euler polynomials. Thus, this research contributes to advancing the understanding and utilization of these hybrid polynomials in various mathematical contexts.

A comprehensive framework has been developed to apply the monomiality principle from mathematical physics to various mathematical concepts from special functions. This paper presents research on a novel family of multivariate Hermite polynomials associated with Apostol-type Frobenius–Euler polynomials. The study derives the generating expression, operational rule, differential equation, and other defining characteristics for these polynomials. Additionally, the monomiality principle for these polynomials is verified. Moreover, the research establishes series representations, summation formulae, and operational and symmetric identities, as well as recurrence relations satisfied by these polynomials.

In this article, we explore the construction of Jakimovski–Leviatan operators for Durrmeyer-type approximation using Sheffer polynomials. Constructing positive linear operators for Sheffer polynomials enables us to analyze their approximation properties, including weighted approximations and convergence rates. The application of approximation theory has earned significant attention from scholars globally, particularly in the fields of engineering and mathematics. The investigation of these approximation properties and their characteristics holds considerable importance in these disciplines.

Background and Objectives: This study was designed to determine the in vitro efficacy of mecillinam against extended spectrum beta lactamse producing Enterobacterales. Materials and Methods: After proper permission from Ethical Review Committee of the Institute, all samples yielding growth of ESBL producing Enterobacterales were part of the study and were processed according to routine microbiological procedures. Routine antibiotic sensitivity testing was done on Muller Hinton Agar by Modified Kirby Bauer Method. All Gram negative isolates were subjected to concomitant detection of ESBL production by double disc synergy method. All ESBL producers were then subjected to the mecillinam Minimum Inhibitory Concentration (MIC) determination by E test. The results were interpreted as per CLSI Guidelines. Results: A total of 120 ESBL producing Enterobacterales isolates were included in the study. The mean age of patients with ESBL infection was 45 ± 18.7 years. There were 44% male and 55% female patients. Majority of the ESBL producing Enterobacterales were isolated from urine samples (56%), followed by pus. Among the isolated organisms, Escherichia coli (45%) was the most frequently isolated organism followed by Klebsiella spp. (22%). Overall 83% of the isolates turned out to be sensitive to mecillinam. MIC50 of mecillinam against ESBL producing Gram negative rods (GNR) turned out to be 1 ug/ml and MIC90 turned out to be 2 ug/ml. Conclusion: Mecillinam shows good in vitro efficacy against ESBL producing Enterobacterales in our study. Further studies with more sample size and from diverse areas across the country should be done to evaluate its efficacy.

Trace elements are a major pollutant in the river water and these pollutants are present in all components of the ecological system. Since time immemorial, the River Veshaw has been one of the important sources of water and has shaped the cultural and social values in the Kashmir Valley. This study was conducted in rural parts of South Kashmir in the Western Himalaya from February to January 2020–2022. The river Veshaw provides various ecosystem services to the local communities as well as in the upper and lower stream regions in the form of many direct and indirect ecosystem services. The river is polluted by human waste from both rural and urban communities, as well as by agricultural runoff and effluent discharges from a variety of industrial activities due to its proximity. Effluent that makes it to the river contains a variety of pollutants, some of which are trace elements that accumulate in the local ecosystem, killing off plants and animals and reducing biodiversity. Trace element levels in water and sediment were found to follow the trend as: Sangam > Khudwani > Kulgam > Nihama > Aharbal > Kingwattan. The dominance pattern of heavy metals in water was Pb > As > Cd. The overall trend showed a downward trend of heavy metals, indicating the effect of land area drainage and anthropogenic activities on the stream water. The dominance pattern of heavy metals in water was Pb > As > Cd. Heavy metals were not detected in the middle and upstream sites. The average levels of heavy metals were highest at Downstream (Sangam), with values of Cd, Pd ad As 0.0054, 0.038 and 0.038 mgL-1. This shows that land drainage and human activities have an effect on the water in the stream.

River floods are globally the most damaging and costliest natural disasters. The functions of nonstructural flood mitigation measures (e.g., water retention by vegetation and soil) provide critical regulation ecosystem services to human beings. For example, the Sponge Cities are national watershed management projects in China to increase the nonstructural flood regulation services, aiming to enable the urban ecosystem to absorb, infiltrate, and retain storm water to mitigate pluvial flooding. Decision-makers need to acquire critical areas for the supply, demand, and flow of flood regulation ecosystem services, which would affect the delivery of services and the distribution of any benefits among stakeholders. However, relatively few empirical studies present this information. One reason is the lack of appropriate methods and tools for a rapid assessment of flood regulation ecosystem services that do not require substantial resources or rely heavily on hydrological process data. This article presents the Flood Regulation Ecosystem Service Flow (FRESF) model to address this gap. FRESF is an open-access and open-source ArcGIS script toolbox for an integrated evaluation of flood regulation ecosystem services' supply, demand, and flow. Based on a land surface process model and a generic framework quantifying ecosystem services flow, FRESF provides a rapid and serviceable assessment framework for the relevant ecosystem services at a relatively low cost and effort. The validation results suggest that the outputs are moderately consistent with the actual flood conditions, compared with the flood disaster of the Yangtze River in 2020. Its open codes and flexible inputs imply that ecologists, planners, decision-makers, and developers involved in ecosystem services would have the opportunity to test and apply the FRESF model in several contexts and even contribute further improvements.

Objective While greater body mass index (BMI) is associated with increased risk of developing atrial fibrillation (AF), the impact of BMI on outcomes in newly diagnosed AF is unclear. We examine the influence of BMI on outcomes and whether this is modified by sex and evaluate the effect of non-vitamin K oral anticoagulants (NOACs) in patients with high BMI.Methods GARFIELD-AF is a prospective registry of 52 057 newly diagnosed AF patients. The study population comprised 40 482 participants: 703 underweight (BMI