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Chitosan is a biopolymer obtained from chitin, one of the most abundant and renewable materials on Earth. Chitin is a primary component of cell walls in fungi, the exoskeletons of arthropods such as crustaceans, e.g., crabs, lobsters and shrimps, and insects, the radulae of molluscs, cephalopod beaks, and the scales of fish and lissamphibians. The discovery of chitin in 1811 is attributed to Henri Braconnot while the history of chitosan dates back to 1859 with the work of Charles Rouget. The name of chitosan was, however, introduced in 1894 by Felix Hoppe-Seyler. Chitosan has attracted major scientific and industrial interests from the late 1970s due to its particular macromolecular structure, biocompatibility, biodegradability and other intrinsic functional properties. Chitosan and derivatives have practical applications in the food industry, agriculture, pharmacy, medicine, cosmetology, textile and paper industries, and in chemistry. In recent years, chitosan has also received much attention in dentistry, ophthalmology, biomedicine and bioimaging, hygiene and personal care, veterinary medicine, packaging industry, agrochemistry, aquaculture, functional textiles and cosmetotextiles, catalysis, chromatography, beverage industry, photography, wastewater treatment and sludge dewatering, and biotechnology. Nutraceuticals and cosmeceuticals are actually growing markets, and therapeutic and biomedical products should be the next markets in the development of chitosan. Chitosan is also the object of numerous fundamental studies. In this review, we highlight a selection of works on chitosan applications published over the past two decades. [ABSTRACT FROM AUTHOR]

This comprehensive review explores recent advancements in the manufacturing of cellulose nanofiber (CNF)-based cellulose nanopaper (CNP). The analysis delves into customizing CNPs through nanofiber manufacturing, mechanical refining, and chemical treatments. The report underscores the growing interest in CNPs derived from CNF due to their exceptional properties and eco-friendly attributes. CNP strength significantly enhanced through mechanical refining encompassing cellulose nanofibrillation were breaking down of cellulose into nanofibers takes place. Conversely, dense CNF network formed through filtration and casting method. Chemical treatments such as dispersion, functionalization, and coating methods followed by drying and consolidation introduce custom functionalities for diverse applications. These applications span packaging, electronics, energy harvesting, EMI shielding, optoelectronics, nanogenerators, transparent conducting films, water treatment, bioelectronics, and neuromorphic computing. The study conducts an in-depth investigation to assess CNP's effects on promoting sustainability and minimizing environmental waste, making a significant contribution to the circular economy. This investigation underscores the pursuit of innovation and aligns with the principles of progressing toward a more environmentally sustainable future. [Display omitted] • Explores CNF production, refining and chemical treatments for CNP customization. • Remarkable properties of CNP draw academic and industrial interest. • CNP applied in packaging, electronics, energy, and environmental science. • Investigates role of CNP in circular economy. • Emphasizes CNPs as eco-friendly, fostering innovation and sustainability. [ABSTRACT FROM AUTHOR]

In recent decades, there has been significant progress in non-invasive sampling techniques, which serve as effective tools in treating and managing various chronic diseases. Among these techniques, dried saliva spot (DSS) sampling of human saliva has emerged as a prominent alternative to serum for detecting targeted molecules. The diagnostic potential of saliva has been extensively studied, highlighting its applicability across a spectrum of diseases. In addition to DSS, other sampling methods, such as dried plasma spots, dried blood spots, and dried matrix spots, have been explored. Various types of filter papers have been employed in DSS sampling procedures, with notable examples including the utilization of Whatman™ 903 Protein Saver cards for identifying Streptococcus pneumoniae DNA through polymerase chain reaction (PCR) or LC-mass spectrometry analysis. Following sample collection onto the respective filter paper, specialized tools are employed to facilitate subsequent processes such as solvent extraction, evaluation of extraction, and drying times. DSS has found diverse applications, including the analysis of lidocaine in human saliva, serving as a diagnostic tool for diabetes mellitus, detecting antiepileptic, antipsychotic, and antidepressant drugs in oral fluid, identifying spinal muscle atrophy, determining uric acid levels in saliva, analyzing severe acute respiratory syndrome coronavirus 2 antibody levels, and detecting carriage of S. pneumoniae using (PCR). The utilization of DSS sampling represents a novel approach in the management and treatment of various chronic diseases. [ABSTRACT FROM AUTHOR]

With the development of energy technology, hydrogen is gradually becoming widely used. China is also rapidly developing its own hydrogen energy industry in an effort to accomplish the "dual carbon target'. Hydrogen from methane is one of the mainstream sources, of which hydrogen from methane cracking is the decomposition of methane into hydrogen and solid carbon, with the solid carbon also having a high economic value. In particular, this technology does not emit carbon dioxide, which is very friendly to the environment, but it cannot avoid larger energy consumption. In contrast, hydrogen production from methane cracking driven by solar energy not only combines the characteristics of no CO 2 emission, but also greatly reduces the consumption of primary energy, which is the future development trend of hydrogen production from methane. This paper provides a brief overview of the various technological pathways for methane to hydrogen production in the context of China's actual development, focusing on the current status of the development and application of solar methane cracking to hydrogen production technologies at home and abroad. Among them, this paper mainly discusses the characteristics of solar reactors of different sizes and structures, and summarizes the results of related optimization studies. Meanwhile, the application of catalysts in solar reactors and the problem of carbon deposition are analyzed, and the practical application of solar methane cracking hydrogen production system is outlined. Finally, the future development of solar methane cracking hydrogen production technology is prospected from the national situation of China. [Display omitted] • Solar methane cracking for hydrogen can reduce emissions and energy consumption. • The current state of research on solar reactors is summarized. • Solar methane cracking requires higher performing catalysts. • Providing insights into the future development of solar methane cracking in China. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are a significant source of environmental pollution, posing threats to human safety. With growing concerns about environmental degradation, catalytic oxidation technology emerges as a paramount and widely adopted approach for VOC elimination, renowned for its operational simplicity, energy efficiency, and environmental friendliness. As a representative transition metal catalyst, cobalt‐based catalysts have garnered widespread use in VOC catalytic oxidation due to their cost‐effectiveness, versatility, and distinctive physicochemical properties. This paper provides a detailed exposition of the construction strategies and structure‐activity relationship of Co3O4‐based catalysts in VOCs oxidation reaction, encompassing both monometallic Co3O4 and multimetallic cobalt‐based catalysts. Furthermore, it offers a comprehensive summary and discussion of the latest research progress concerning Co3O4‐based catalysts in practical applications. Concluding with a meticulous analysis, the paper addresses the technical challenges inherent in developing Co3O4‐based catalysts for VOCs degradation. Additionally, it proposes research directions aimed at overcoming these challenges, contributing to the ongoing discourse on environmental sustainability. [ABSTRACT FROM AUTHOR]

In this paper, we consider and study in detail the generalized Fox–Wright function Ψ ˜ q p introduced in our recent work as an extension of the Fox–Wright function Ψ q p . This special function can be seen as an important case of the so-called I-functions of Rathie and H ¯ -functions of Inayat-Hussain, that in turn extend the Fox H-functions and appear to include some Feynman integrals in statistical physics, in polylogarithms, in Riemann Zeta-type functions and in other important mathematical functions. Depending on the parameters, Ψ ˜ q p is an entire function or is analytic in an open disc with a final radius. We derive its basic properties, such as its order and type, and its images under the Laplace transform and under classical fractional-order integrals. Particular cases of Ψ ˜ q p are specified, including the Mittag-Leffler and Le Roy-type functions and their multi-index analogues and many other special functions of Fractional Calculus. The corresponding results are illustrated. Finally, we emphasize the role of these new generalized hypergeometric functions as eigenfunctions of operators of new Fractional Calculus with specific I-functions as singular kernels. This paper can be considered as a natural supplement to our previous surveys "Going Next after 'A Guide to Special Functions in Fractional Calculus': A Discussion Survey", and "A Guide to Special Functions of Fractional Calculus", published recently in this journal. [ABSTRACT FROM AUTHOR]

Text matching, as a core technology of natural language processing, plays a key role in tasks such as question-and-answer systems and information retrieval. In recent years, the development of neural networks, attention mechanisms, and large-scale language models has significantly contributed to the advancement of text-matching technology. However, the rapid development of the field also poses challenges in fully understanding the overall impact of these technological improvements. This paper aims to provide a concise, yet in-depth, overview of the field of text matching, sorting out the main ideas, problems, and solutions for text-matching methods based on statistical methods and neural networks, as well as delving into matching methods based on large-scale language models, and discussing the related configurations, API applications, datasets, and evaluation methods. In addition, this paper outlines the applications and classifications of text matching in specific domains and discusses the current open problems that are being faced and future research directions, to provide useful references for further developments in the field. [ABSTRACT FROM AUTHOR]

The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables it to process massive volumes of data and produce text that is both cohesive and illuminating. Service is a crucial component everywhere as it provides the basis for establishing client rapport and offering aid and support. In healthcare, the application of ChatGPT for patient service support has been one of the most significant advances in recent years. ChatGPT can help overcome language obstacles and improve patient satisfaction by facilitating communication with healthcare personnel and understanding of care. It can assist in enhancing the entire patient experience by offering personalised information and support to patients and making it more straightforward for them to communicate with healthcare professionals. Its goal can be to expedite and streamline service by promptly and accurately responding to customers. Businesses of all sizes increasingly use ChatGPT since it allows them to provide 24/7 customer support without requiring human contact. This paper briefly discusses ChatGPT and the need for better services. Various perspectives on improving customer and patient services through ChatGPT are discussed. The article also discussed the major key enablers of ChatGPT for refining customer and patient assistance. Further, the paper identifies and discusses the critical application areas of ChatGPT for customer and patient service. With its ability to handle several requests simultaneously, respond quickly and accurately to client questions, and gain knowledge from every interaction, ChatGPT is revolutionising customer and patient service. Its accessibility and compatibility with various communication channels make it a desirable solution for businesses looking to improve support. As technology advances, ChatGPT is positioned to become an essential tool for businesses wishing to provide speedy and customised service. Although ChatGPT may give convincing solutions, the chance of providing accurate and updated information poses a problem for its usage in service jobs that need accurate and up-to-date information. In future, various services will become better and more efficient due to ChatGPT and AI. [ABSTRACT FROM AUTHOR]

Personalisation, which tailors to individual preferences, is considered a possible route for improving engagement with digital mental health (DMH) products. Despite claims about the presence and importance of personalised features, evidence about their extent and impact is limited. The study objective was to review evidence from published research to investigate and characterise the contribution of personalisation to engagement and effectiveness.Research papers were retrieved using keywords, with 139 papers being fully examined and 61 meeting our eligibility criteria. Most of the eligible articles reviewing DMH systems have weak to intermediate forms of personalisation (45). Only nine were coded as having strong, adaptive personalisation. Of the 40 articles which evaluated the personalisation effectiveness, 28 were qualitative indicating user preference for personalised features. The 16 controlled, quantitative designs lacked a non-personalised intervention, making it difficult to determine the added value. Effect sizes calculated from available data showed minimal differences in effectiveness compared to non-personalised apps.Our review indicates mixed evidence of personalisation’s performance in DMH interventions. Generally, there is a lack of good quality evidence to isolate specific contributions of personalisation. Opportunities were identified for improved evaluation, however caution is required when implementing more sophisticated methods of DMH personalisation. [ABSTRACT FROM AUTHOR]

A novel class of nanomaterials known as carbon quantum dots (CQDs) has drawn significant attention because of numerous benefits, particularly its small size (between 1 and 10 nm) and great water solubility, fluorescence, ease of synthesis, and low toxicity among others. There are still many crucial questions that need to be answered, such as how to prepare high-quality CQDs with an appropriate yield using a simpler and easier approach. Most of the articles reviewed have discussed the production of CQDs intended for applications in imaging and sensing. Nevertheless, there is a scarcity of research focusing on producing undecorated and doped CQDs. In this review paper, the various methods for synthesizing CQDs by using various carbon sources have been summarized. Additionally, In this paper, we discuss the primary characterization techniques and the applications of CQDs in various fields. The fundamental objective of this paper is to analyze various synthesis methods used over different periods to address the challenges that one might encounter during the synthesis of CQDs. [ABSTRACT FROM AUTHOR]

Over recent years, thermoplastic polyurethane (TPU) has been widely used as a substrate material for flexible strain sensors due to its remarkable mechanical flexibility and the ease of combining various conductive materials by electrospinning. Many research advances have been made in the preparation of flexible strain sensors with better ductility, higher sensitivity, and wider sensing range by using TPU in combination with various conductive materials through electrospinning. However, there is a lack of reviews that provide a systematic and comprehensive summary and outlook of recent research advances in this area. In this review paper, the working principles of strain sensors and electrospinning technology are initially described. Subsequently, recent advances in strain sensors based on electrospun TPU are tracked and discussed, with a focus on the incorporation of various conductive fillers such as carbonaceous materials, MXene, metallic materials, and conductive polymers. Moreover, the wide range of applications of electrospun TPU flexible strain sensors is thoroughly discussed. Finally, the future prospects and challenges of electrospun TPU flexible strain sensors in various fields are pointed out. [ABSTRACT FROM AUTHOR]

With higher standards in terms of diet and leisure enjoyment, spices and essential oils of aromatic plants (APEOs) are no longer confined to the food industry. The essential oils (EOs) produced from them are the active ingredients that contribute to different flavors. The multiple odor sensory properties and their taste characteristics of APEOs are responsible for their widespread use. The research on the flavor of APEOs is an evolving process attracting the attention among scientists in the past decades. For APEOs, which are used for a long time in the catering and leisure industries, it is necessary to analyze the components associated with the aromas and the tastes. It is important to identify the volatile components and assure quality of APEOs in order to expand their application. It is worth celebrating the different means by which the loss of flavor of APEOs can be retarded in practice. Unfortunately, relatively little research has been done on the structure and flavor mechanisms of APEOs. This also points the way to future research on APEOs.Therefore, this paper reviews the principles of flavor, identification of components and sensory pathways in humans for APEOs. Moreover, the article outlines the means of increasing the efficiency of using of APEOs. Finally, with respect to the sensory applications of APEOs, the review focuses on the practical application of APEOs in food sector and in aromatherapy. [ABSTRACT FROM AUTHOR]

Diamond materials at different nanoscales provide them various characteristics such as elastic mechanical properties in needle‐like nanotips, flexibility of 2D films having atomic thicknesses and constant hardness under high pressures, superior field electron emission properties of vertically wall‐like composites, unprecedented hardness and improved toughness of nanotwin diamond (nt‐diamond), while the inherent excellent properties of bulk diamond (e.g., high Young's modulus, robustness, biocompatibility) can be maintained. In this paper, the newly born 1D diamond nanothreads, 2D diamanes, as well as 3D nt‐diamond are briefly reviewed. The innovations, progresses and achievements of different dimensional diamond nanostructures, covering lines, planes and volumes are overviewed. The topical problems and future outlooks of diamond nanostructures are outlined and discussed. [ABSTRACT FROM AUTHOR]

Yttrium aluminum garnet (YAG)-based optical fiber is one of the research hotspots in the field of fiber lasers due to its combined advantages of a wide doping range of rare earth ions and the high mechanical strength of YAG material, as well as the flexibility and small size of the fiber structure. YAG-based optical fibers and related laser devices can be used in communication, sensing, medicine, etc. A comprehensive review of YAG-based optical fibers is provided in this paper. Firstly, the fabrication processes of YAG-based optical fibers are summarized and the structure and properties of fibers are classified and compared. Secondly, according to the optical wavelength regions, rare earth-doped YAG-based optical fibers for the applications of single-frequency and mode-locked fiber lasers are summarized. Lastly, the development challenges in both the fabrication and applications of YAG-based optical fibers are discussed. [ABSTRACT FROM AUTHOR]

AbstractOvotransferrin(OVT)is a protein found in many types of egg white and has a wide range of functional properties. It has 50% homology with human/bovine lactoferrin, and is expected to be one of the most important alternative proteins for use in food and nutritional applications. This paper mainly reviews the structural characteristics and chemical properties of OVT, as well as its extraction and purification methods. It also systematically describes the various biological activities of OVT and its applications in food and medical industries. The challenges and limitations in the research of OVT were suggested. This review recommends some possible methods such as nanoparticle carriers and microencapsulation to improve the bioavailability and stability of OVT. In addition, this review highlights several strategies to overcome the limitations of OVT in terms of preparation and purification. This review systematically summarizes the recent advances in OVT and will provide guidance for the its development for food and nutritional applications. [ABSTRACT FROM AUTHOR]

Collagen extracted from leather waste was modified with maleic anhydride. Then, using ammonium persulfate as an initiator, by premodifying collagen reacted with styrene and ethyl acrylate monomers, a vinyl-grafted collagen sizing agent (VGCSA) for paper was prepared. Before the experiment, the performance of VGCSA was tested and VGCSA emulsion was applied to the surface sizing of the corrugated paper. Effects of the amount of VGCSA, the compound proportion of VGCSA, and starch and styrene-acrylic emulsion were studied relative to paper properties. The morphological changes of the paper before and after sizing were characterized by SEM. It was found that the collagen reacted with styrene and ethyl acrylate monomers. Through the grafting of vinyl and collagen, the crystallinity and thermal stability of VGCSA increased. The structure of VGCSA was spherical with a uniform size, and the average particle size was approximately 350 to 400 nm. After being sized, the surface fibers of paper became smooth and orderly. The optimal sizing of VGCSA was 8 g/m². The optimal proportion of VGCSA with starch was 4:6, and the optimal proportion of VGCSA with SAE was 2:8. The research indicates that collagen extracted from leather waste could be used as a biomaterial, and environmental and economic benefits could be created as well. [ABSTRACT FROM AUTHOR]

This paper reviews several theoretical works on the computation of the Rate of Occurrence of Failure (ROCOF) for general multi-state random systems, focusing on recent generalizations. The discussion begins by defining the ROCOF for a Markov process and discussing the main results achieved in the literature, then moves towards the richer framework represented by semi-Markov systems. The paper discusses complications that arise when extending the ROCOF to higher orders so that a measure of the association of failures in time can be obtained. The work then analyzes possible modifications in terms of a conditional version of the ROCOF, which is of special interest in applications. The findings are illustrated by a numerical example from reliability, and the broad applicability is demonstrated by a discussion of different applications in other domains. [ABSTRACT FROM AUTHOR]

One of the most widely referenced Swarm Intelligence (SI) algorithms is the Grey Wolf Optimizer (GWO), which is based on the pack hunting and natural leadership organization of grey wolves. The GWO algorithm offers several significant benefits, including simple implementation, rapid convergence, and superior convergence outcomes, leading to its effective application in diverse fields for solving optimization issues. Consequently, the GWO has rapidly garnered substantial research interest and a broad audience across numerous areas. To better understand the literature on this algorithm, this review paper aims to consolidate and summarize research publications that utilized the GWO. The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. Subsequently, the primary applications of the GWO are thoroughly explored, spanning various fields such as computer science, engineering, energy, physics and astronomy, materials science, environmental science, and chemical engineering, among others. This review paper concludes by summarizing the key arguments in favour of GWO and outlining potential lines of inquiry in the future research. [ABSTRACT FROM AUTHOR]

Edible insects are accepted as food and feed ingredients in many parts of the world. Insects account for more than 80% of animal kingdom providing rich biodiversity of protein and lipid profiles compared to conventional livestock. Insect biomasses contain an average of 35-62% protein, 3-57% lipid, and 3-12% chitin, and their nutritional values are widely recognized due to their presence, including minerals, and vitamins. While whole insects are consumed as eggs, larvae, pupae, or adults, there has been a recent uptick in interest to use fractions, e.g., protein, lipid, and chitin, as food and feed ingredients. To utilize these fractions in various food and feed preparations, a deeper understanding of the physicochemical as well as functional properties of the ingredients is required, which are generally impacted by extraction and preparation processes. Thus, the methods of extraction/purification are important to preserve the quality and functional properties of these ingredients. This paper discusses the extraction methods for insect protein, lipid, and chitin, their functional properties, and potential applications in food and feed applications. [ABSTRACT FROM AUTHOR]

Growing concerns about the harmful impact of synthetic polymers on the environment and living organisms have shifted the attention towards biopolymers which are environment‐friendly and biocompatible. Biopolymers represent attractive sustainable and biodegradable alternatives for replacing commercial synthetic polymers. Chitosan is one of the most prevalent biopolymers available on Earth. Chitosan is an alkaline cationic polymer, the deacetylated form of chitin. Chitosan possesses excellent physicochemical properties such as biocompatibility, biodegradability, nontoxic, nonallergenic, and biologically active molecules. During recent years, there has been a surge in the demand for chitosan in various fields, however, due to poor water solubility and mechanical properties, chitosan applications are limited to some extent. Strong inter and intramolecular hydrogen bonds in the chitosan matrix make it highly crystalline, reducing its water solubility. Chemical modification of the chitosan matrix by various technologies is reported to improve its solubility and other physicochemical characteristics, expanding the application areas. Details on various chemical reactions involved in chemical modification and other available technologies have been focused in this paper. The role of chitin deacetylase enzyme in chitosan modification has been discussed. This review aims to provide insight into recent developments in chitosan functionalization, and the development of chitosan derivatives for various applications. [ABSTRACT FROM AUTHOR]

A great deal of study has been done recently on support vector machines (SVMs) and how they are used in various scientific domains. The statistical learning theory's mathematical foundation allows SVM to offer logical solutions to issues. A portion of the training input serves as the SVM's solution. SVM is frequently employed in applications involving feature reduction. regression. and novelty detection. Additionally, studies conducted in certain fields where SVM performs badly have prompted the creation of alternative SVM applications. including big data sets, multiclassification SVM. and imbalanced data sets SVM. Furthermore, SVM is used with other more sophisticated techniques. such as evolve algorithms. to enhance classification performance and optimize parameters. SVM algorithms are now widely used in research and applications across a number of scientific and engineering domains. The SVM might be one of the primary options for big data compatibility and big data classification because of its advantages. Data preparation methods must be created in order to mask data into the appropriate format for learning in order to do this. This paper provides a quick overview of SVM. list several applications, draw attention to current issues and patterns, and point out sonic of SVM's drawbacks in this essay. This document can be used to categorize vast volumes of data and recommend research areas for further investigation. [ABSTRACT FROM AUTHOR]

With the reduction in fossil fuels and growing concerns about global warming, energy has become one of the most important issues facing humanity. It is crucial to improve energy utilization efficiency and promote a low-carbon transition. In comparison with traditional heat exchangers, heat pipe heat exchangers indicate high compactness, a flexible arrangement, complete separation of hot and cold fluids, good isothermal operations, etc. As a result, heat pipe heat exchangers have attracted wide attention and application in various fields in recent years. This paper provides an overview of the application of heat pipe heat exchangers, with a focus on the application in waste heat recovery, and analyzes the opportunities and challenges of heat pipe heat exchanger applications based on existing publications. [ABSTRACT FROM AUTHOR]

World is presently facing major challenges in energy industry to reduce or replace greenhouse gases (CO 2 , CH 4 , NO x etc.) emissions to net zero in the coming decades while decreasing the reliance on traditional fossil fuels. In the current scenario, hydrogen (H 2) appears to be an excellent alternative energy source to meet the criteria. Storage of H 2 over a long period of time in large quantities poses a significant challenge for its widespread uses. In order to overcome this issue, the idea of using large-scale depleted underground hydrocarbon reservoirs, salt caverns, underground aquifers, etc. is considered to be a suitable option for underground hydrogen storage. However, underground storage of H 2 for a longer time period comes up with a potentially high microbial activity where H 2 can be utilized in the microbial metabolism and converted into undesirable gases like CH 4 and H 2 S which in turn, damage the porous medium due to clogging, acid formation, and corrosion activity. This review paper explores the various scientific challenges during large-scale H 2 storage in porous medium to facilitate the global H 2 economy. Moreover, a detailed description of the effect of subsurface environment conditions such as pressure, temperature, pH, and salinity on microbes is included in this study. In addition to this, steps to counter microbial activity in stored H 2 monitoring and mitigation approaches are also discussed in this article. • Underground hydrogen storage and its mechanism are discussed. • Effect of microorganisms on stored hydrogen and porous media properties comprehensively reviewed. • The impact of microbial activity on subsurface storage environment conditions. • Monitoring and mitigation strategies to counter microbial activities comprehensively reviewed. • Latest treatment proposition of microbial activities and role of biocides in underground hydrogen storage discussed. [ABSTRACT FROM AUTHOR]

Introduction: Understanding the complex link between our gut health and general well-being has drawn more attention in recent years. Prebiotics can promote mineral absorption, influence metabolism, improve immune system regulation, and fight infections. Aim: This article focuses into the evolving paradigms in prebiotics research, highlighting their regulation, diverse applications, impact on diseases, and their growth on the global market. Discussion: Prebiotics are Generally Recognized as Safe (GRAS), novel foods and food additives by the Food and Drug Administration (FDA), EU and Japan, respectively. The multifaceted applications of prebiotics go across various sectors, ranging from functional foods and dietary supplements to cosmetics. A comprehensive review of prebiotics' effects on human health and illness prevention is a significant strength of the paper. Prebiotics support a healthy microbiome by feeding helpful gut flora, which may reduce the risk of a variety of illnesses and improve general health. In parallel, it covers an overview of the prebiotics industry in the world, considering aspects including consumer knowledge of gut health and growing prebiotic demand. Conclusion: Prebiotics are anticipated to have a significant role in determining the direction of nutrition and preventive healthcare as research advances and consumer demand for natural health solutions rises. [ABSTRACT FROM AUTHOR]

In recent years, an increasing number of viruses have triggered outbreaks that pose a severe threat to both human and animal life, as well as caused substantial economic losses. It is crucial to understand the genomic structure and epidemiology of these viruses to guide effective clinical prevention and treatment strategies. Nanopore sequencing, a third-generation sequencing technology, has been widely used in genomic research since 2014. This technology offers several advantages over traditional methods and next-generation sequencing (NGS), such as the ability to generate ultra-long reads, high efficiency, real-time monitoring and analysis, portability, and the ability to directly sequence RNA or DNA molecules. As a result, it exhibits excellent applicability and flexibility in virus research, including viral detection and surveillance, genome assembly, the discovery of new variants and novel viruses, and the identification of chemical modifications. In this paper, we provide a comprehensive review of the development, principles, advantages, and applications of nanopore sequencing technology in animal and human virus research, aiming to offer fresh perspectives for future studies in this field. [ABSTRACT FROM AUTHOR]

Background: Transcranial magnetic stimulation (TMS) equipment has advanced dramatically over the years thanks to considerable advancements in signal motors, coils, placement devices, and modeling, optimization, and treatment scheduling programs. In this review, a primary assessment of the impact of transcranial magnetic stimulation (TMS) on seizure course in people with and without epilepsy has been done through search in the Embase, PubMed, Scopus, and Web of Science databases. Other proposed roles of TMS in various studies has been reported. The features of TMS protocols for several potential disorders was assessed and the key TMS findings has been documented starting from 1985 until 2023. Results: More than 500 papers were found that describe various research populations, TMS techniques, and TMS functions in 16 various medical conditions. Conclusion: After reviewing recent updates in TMS, further researches are needed to improve the technical part of the used TMS protocols and to have definitive results not experimental one with regard to TMS usage in various psychiatric and neurological disorders. [ABSTRACT FROM AUTHOR]

In this paper we study the computational complexity issues of the problem of secondary domination (known also as (1, 2)-domination) in several graph classes. We also study the computational complexity of the problem of determining whether the domination and secondary domination numbers are equal. In particular, we study the influence of triangles and vertices of degree 1 on these numbers. Also, an optimal algorithm for finding a minimum secondary dominating set in trees is presented. [ABSTRACT FROM AUTHOR]

This paper analyzes the impact of college athletic reclassification for educational institutions in the United States. Most of America's colleges and universities offer athletic opportunities for their students under NCAA governance. The level of competition and associated resource requirements range from relatively low (Division 3) to high (Division 1). In recent years, there has been an increase in the number of institutions that have either reclassified to a higher division, or publicly considered such a move. The resource obligations of reclassification are significant, and administrators must carefully weigh expected benefits and costs with respect to the institution's mission and vision. While several studies (Bell, 2017; Schwarzber, 2014; Frieder & Fulks, 2007; Tomasini, 2005) have focused on reclassification from Division 1-FCS to FBS—the highest level of competition—less attention has been paid to colleges in Division 2 and 3—which comprise two-thirds of NCAA membership. Our study addresses a gap in the literature by analyzing athletic reclassification among schools moving up from Division 2 to Division 1 (FCS and no-football) during the period of 2001–2018. Drawing upon multiple data sources, we construct a panel of 33 schools (14 treatments and 19 controls) to evaluate the impact of reclassification on applications and athletic department budgets. Results from quasi-experimental methods (difference in differences, event study, and synthetic control models) suggest that reclassification significantly increased basketball program revenues and athletic department expenses among the treatment schools. However, we do not find evidence that reclassification raises student applications in the short term. [ABSTRACT FROM AUTHOR]

This review article examines the utility of artificial intelligence (AI) in anesthesia, with a focus on recent developments and future directions in the field. A total of 19,300 articles were available on the given topic after searching in the above mentioned databases, and after choosing the custom range of years from 2015 to 2023 as an inclusion component, only 12,100 remained. 5,720 articles remained after eliminating non-full text. Eighteen papers were identified to meet the inclusion criteria for the review after applying the inclusion and exclusion criteria. The applications of AI in anesthesia after studying the articles were in favor of the use of AI as it enhanced or equaled human judgment in drug dose decision and reduced mortality by early detection. Two studies tried to formulate prediction models, current techniques, and limitations of AI; ten studies are mainly focused on pain and complications such as hypotension, with a P value of <0.05; three studies tried to formulate patient outcomes with the help of AI; and three studies are mainly focusing on how drug dose delivery is calculated (median: 1.1% ± 0.5) safely and given to the patients with applications of AI. In conclusion, the use of AI in anesthesia has the potential to revolutionize the field and improve patient outcomes. AI algorithms can accurately predict patient outcomes and anesthesia dosing, as well as monitor patients during surgery in real time. These technologies can help anesthesiologists make more informed decisions, increase efficiency, and reduce costs. However, the implementation of AI in anesthesia also presents challenges, such as the need to address issues of bias and privacy. As the field continues to evolve, it will be important to carefully consider the ethical implications of AI in anesthesia and ensure that these technologies are used in a responsible and transparent manner. [ABSTRACT FROM AUTHOR]

Precision medicine is emerging as an integral component in delivering care in the health system leading to better diagnosis and optimizing the treatment of patients. This growth is due to the new technologies in the data science field that have led to the ability to model complex diseases. Precision medicine is based on genomics and omics facilities that provide information about molecular proteins and biomarkers that could lead to discoveries for the treatment of patients suffering from various diseases. However, the main problems related to precision medicine are the ability to analyze, interpret, and integrate data. Hence, there is a lack of smooth transition from conventional to precision medicine. Therefore, this work reviews the limitations and discusses the benefits of overcoming them if big data tools are utilized and merged with precision medicine. The results from this review indicate that most of the literature focuses on the challenges rather than providing flexible solutions to adapt big data to precision medicine. As a result, this paper adds to the literature by proposing potential technical, educational, and infrastructural solutions in big data for a better transition to precision medicine. [ABSTRACT FROM AUTHOR]

In the recent decade, there has been a significant increase in the number of maturity models offered in Building Information Modelling (BIM). However, several problems exist, such as no proper criteria for model choice for organisations and no adequate understanding of BIM maturity model (BIMMM) application areas. Thus, a systematic literature review (SLR) was undertaken using 32 papers published between 2010 and 2021, directed with a descriptive and content analysis, following the PRISMA standards. The results of this paper extend the knowledge on BIMMM development, application and validation. BIMMM development has always been initiated with a literature review on existing maturity models. National BIM Standard's Interactive Capability Maturity Model is the most dominant base for developing and applying BIMMMs. However, the literature lacks applications and validation of mainstream models. The application of BIMMMs is mainly focused on assessing BIM performance, while a few studies tried to explore new avenues such as applying BIMMMs to other contexts, finding the relationship between maturity level and other factors, and understanding the impact of BIM maturity level on factors like project performance. Despite interviews and case studies being popular methods of model validation, doubts on the validity of the models have been raised due to the dearth of information on how most of the models were validated. The results of the study lead future research in the BIMMMs and inform the development and application of valid BIMMMs in practice. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Plithogenic sets coined by Smarandache in the year 2018 has unveiled new research opportunities in the field of Multi criteria decision making (MCDM). The contributions and developments of new decision making approaches based on plithogeny is gaining high momentum presently. The theoretical conceptualization of different phenomenon with plithogenic sets are also applied in designing optimal solutions to the decision making problems. This review paper presents the applications of plithogenic MCDM from the year 2018 to till date in almost all the spheres of decision making scenario. The literature works of the researchers presented in this paper will certainly portray the compatibility and flexibility of plithogenic sets, operators and other decision making tools. Though the time span considered for counting on the plithogeny based works is short, the applications of plithogenic sets are growing many in number and also plithogeny based theories are amplifying in a speedy manner. This has motivated the authors to investigate on the proliferation of plithogeny applications in decision making. This review paper has focused on the dimensions of different fields to which plithogeny is applied, new plithogeny based theories, extension of plithogeny, plithogenic based operators and measures. In addition to it the data on the publications of plithogeny based articles and interests of researchers are also presented as a part of this review work. The overall impact of plithogeny in the arena of decision making science and on the researchers of the same field is well sketched in this paper with the intention and hope of inspiring plithogenic researchers. [ABSTRACT FROM AUTHOR]

Smart living, an increasingly prominent concept, entails incorporating sophisticated technologies in homes and urban environments to elevate the quality of life for citizens. A critical success factor for smart living services and applications, from energy management to healthcare and transportation, is the efficacy of human action recognition (HAR). HAR, rooted in computer vision, seeks to identify human actions and activities using visual data and various sensor modalities. This paper extensively reviews the literature on HAR in smart living services and applications, amalgamating key contributions and challenges while providing insights into future research directions. The review delves into the essential aspects of smart living, the state of the art in HAR, and the potential societal implications of this technology. Moreover, the paper meticulously examines the primary application sectors in smart living that stand to gain from HAR, such as smart homes, smart healthcare, and smart cities. By underscoring the significance of the four dimensions of context awareness, data availability, personalization, and privacy in HAR, this paper offers a comprehensive resource for researchers and practitioners striving to advance smart living services and applications. The methodology for this literature review involved conducting targeted Scopus queries to ensure a comprehensive coverage of relevant publications in the field. Efforts have been made to thoroughly evaluate the existing literature, identify research gaps, and propose future research directions. The comparative advantages of this review lie in its comprehensive coverage of the dimensions essential for smart living services and applications, addressing the limitations of previous reviews and offering valuable insights for researchers and practitioners in the field. [ABSTRACT FROM AUTHOR]

This special issue of the Journal Mathematical Methods in the Applied Sciences on the topic of Modelling, Analysis, and Applications is devoted to the development of mathematical modelling, analysis, and applications, from theoretical and numerical perspectives, involving different applied sciences and engineering. It collects invited contributions, from selected quality full papers submitted to the International Conference on Mathematical Analysis and Applications in Science and Engineering (ICMA2SC2022). The conference took place in Porto, Portugal in 27–29 June 2022 (https://www.isep.ipp.pt/Page/ViewPage/ICMASC). [ABSTRACT FROM AUTHOR]

[Display omitted] • This review addresses the important bioactive ingredients recovered from different major crustacean's by-products. • A comprehensive application of crustacean's by-products in various fields is presented. • Nowadays, many newly developed techniques have been applied in crustacean's by-products recovery. • A combination of innovative extraction techniques with industrially applicable technologies can efficiently recover these valuable components. The processing of the three major crustaceans (shrimp, lobster, and crab) is associated with inevitable by-products, high waste disposal costs, environmental and human health issues, loss of multiple biomaterials (chitin, protein hydrolysates, lipids, astaxanthin and minerals). Nowadays, these bioresources are underutilized owing to the lack of effective and standardized technologies to convert these materials into valued industrial forms. This review aims to provide a holistic overview of the various bioactive ingredients and applications within major crustaceans by-products. This review aims to compare various extraction methods in crustaceans by-products, which will aid identify a more workable platform to minimize waste disposal and maximize its value for best valorization practices. The fully integrated applications (agriculture, food, cosmetics, pharmaceuticals, paper industries, etc.) of multiple biomaterials from crustaceans by-products are presented. The pros and cons of the various extraction methods, including chemical (acid and alkali), bioprocesses (enzymatic or fermentation), physical (microwave, ultrasound, hot water and carbonic acid process), solvent (ionic liquids, deep eutectic solvents, EDTA) and electrochemistry are detailed. The rapid development of corresponding biotechnological attempts present a simple, fast, effective, clean, and controllable bioprocess for the comprehensive utilization of crustacean waste that has yet to be applied at an industrial level. One feasible way for best valorization practices is to combine innovative extraction techniques with industrially applicable technologies to efficiently recover these valuable components. [ABSTRACT FROM AUTHOR]

This paper reports recent advancements in chitosan‐based antimicrobial biomaterials that aim to address the issue of antimicrobial resistance (AMR). Today, AMR is one of the most significant public health challenges the world is facing. To combat the overuse of antibiotics, a range of materials, including advanced nanosized polymers, have been explored as potential antimicrobial agents. In this direction, chitosan scores highly because of its unique combination of properties such as biodegradability, biocompatibility, bioactivity, non‐toxic, and, most importantly, its intrinsic antibacterial and antifungal activity. Herein, an overview of chitosan and its derivatives as potential alternatives to conventional antimicrobial therapeutics is reported. This review starts with understanding the AMR mechanism, which is critical for developing suitable materials for treating infectious diseases. Then, the inherent characteristics, modes of antimicrobial action, and factors that impact the antimicrobial effectiveness of chitosan and its derivatives are discussed. The authors further summarize various clinical trial results of chitosan‐based materials as antimicrobial agents. Finally, various antimicrobial applications of chitosan‐based materials are reported. In summary, this review offers new insights into the design of chitosan‐based sustainable materials for various antimicrobial applications. [ABSTRACT FROM AUTHOR]

In this paper, the research progress of surface-enhanced Raman spectroscopy (SERS) research in the nervous system in recent years is reviewed. Firstly, the current status of neurotransmitter testing is briefly introduced, and the advantages of SERS detection technology are proposed. Secondly, the development status of SERS technology for neurotransmitters is reviewed, such as monoamines and amino acids. Thirdly, the SERS used to detect neurological diseases are mainly introduced, and SERS based microdevices are further introduced. In addition, the diagnostic applications of SERS in malignant tumors of the nervous system are analyzed. [ABSTRACT FROM AUTHOR]

The intestine is the main site of oral drug absorption, and the epithelial cells of the intestine contain villi and microvilli, which promote secretion, cell adhesion, and absorption by increasing surface area and other factors. Traditional twodimensional/three-dimensional (2D/3D) cell culture models and animal models have played an important role in studying drug absorption, but their application is limited due to the lack of sufficient predictability of human pharmacokinetics or ethical issues, etc. Therefore, mimicking the core structure and key functions of the human intestine based on in vitro live cells has been the focus of research on constructing a microfluidic chip-based intestinal model. The model is a microfluidic chip bionic system that simulates the complex microstructure, microenvironment, and physiological functions of the human intestine using microfabrication technology. Compared with 2D cell culture and animal experiments, the intestinal microarray model can effectively simulate the human in vivo environment and is more specific in drug screening. The research progress and applications in disease modeling, drug absorption and transport of intestinal microarray models and intestine-related multi-organ coupled microarray models at home and abroad were reviewed in this paper. The current challenges of intestinal chip simulating intestinal homeostasis and diseases were summarized，in order to provide reference for the further establishment of a more reliable in vitro intestinal chip model. [ABSTRACT FROM AUTHOR]

Purpose: Auxetic sandwich structures are gaining attention because of the negative Poisson's ratio effect offered by these structures. Re-entrant core was one configuration of the auxetic structures. There is a growing concern about the design and behavior of re-entrant cores in aerospace, marine and protection applications. Several researchers proposed various designs of re-entrant core sandwiches with various materials. The purpose of this study is to review the most recent advances in re-entrant core sandwich structures. This review serves as a guide for researchers conducting further research in this wide field of study. Design/methodology/approach: The re-entrant core sandwich structures were reviewed in terms of their design improvements, impact and quasi-static crushing responses. Several design improvements were reviewed including 2D cell, 3D cell, gradient, hierarchical and hybrid configurations. Some common applications of the re-entrant core sandwiches were given at the end of this paper with suggestions for future developments in this field. Findings: Generally, the re-entrant configuration showed improved energy absorption and impact response among auxetic structures. The main manufacturing method for re-entrant core manufacturing was additive manufacturing. The negative Poisson's ratio effect of the re-entrant core provided a wide area of research. Originality/value: Generally, re-entrant cores were mentioned in the review articles as part of other auxetic structures. However, in this review, the focus was solely made on the re-entrant core sandwiches with their mechanics. [ABSTRACT FROM AUTHOR]

The use of remote sensing imagery for land cover and land use classification has made significant advancements in recent years. However, it becomes particularly challenging to enhance the semantic representation of high-resolution networks while dealing with uneven land categories and merging multi-scale data without compromising the accuracy of semantic segmentation. To tackle this challenge, this paper presents a novel method for classifying high-resolution remote sensing images based on a deep neural network that performs semantic segmentation of urban construction lands into five categories: vegetation, water, buildings, roads, and bare soil. The network incorporates a U-shaped high-resolution neural network and the advanced high-resolution network (HRNet) framework. The parallel storage of feature maps with different resolutions enables the exchange of information between them. The data pre-processing module addresses the issue of data imbalance in the semantic segmentation of urban construction lands, resulting in an increase in Intersection over Union (IoU) values for different land types by 3.75%-12.01%. Additionally, a target context representation module is introduced to enhance the feature representation of pixels by calculating the relationship between pixels and multiple target regions. Moreover, a polarization attention mechanism is proposed to extract the characteristics of geographical objects in all directions and achieve a stronger semantic representation. This method provides a novel approach to accurately and effectively extract information on construction lands and advance the development of monitoring algorithms for urban construction lands. To validate the proposed U-HRNet-OCR+PSA network, a comparative analysis was conducted with six classical networks, including DeepLabv3+, PSPNet, U-Net, U-Net++, HRNet, and HRNet-OCR, as well as the relatively new ViT-adapter-L, Oneformer and InternImage-H. The experiments demonstrate that the U-HRNet-OCR+PSA network achieves higher accuracy compared to the aforementioned networks. Specifically, the corresponding IoU values for the buildings, roads, vegetation, bare soil, and water in the multi-scale dataset are 89.79%, 90.05%, 94.89%, 85.91%, and 88.36%, respectively. [ABSTRACT FROM AUTHOR]

Chiral carbon quantum dots (cCQDs) , as a new type of carbon nano-functional material with tunable emission wavelength, superior photostability, low toxicity, biocompatibility and chirality, are playing an increasingly important role in the fields of chemistry, biology and medicine. This paper reviews the preparation methods (one-step and two-step), optical properties (UV, fluorescence, chirality) and applications in chiral catalysis, chiral recognition, targeted imaging as well as other fields, while lists some of the issues and challenges in the research of chiral carbon quantum dots. Finally, due to its good fluorescence and other properties, it is expected that chiral carbon quantum dots will have broad commercial prospects in future applications. [ABSTRACT FROM AUTHOR]

The standard binomial distribution is based on a sequence of Bernoulli trials. The probability of success is the same for each trial. In the Generalized Binomial Distribution (GBD), the probability of success changes by the history of successes up to that point. For example, if a student correctly answers a large proportion of the first few questions, the probability of correctly answering the next question increases because the history of successes may indicate skill. The Bernoulli events are correlated. Alternatively, the standard binomial distribution does not consider the history of successes, and assumes that successes are not correlated. In this paper we prove some new properties of the GBD and apply the concept to five new areas in sport competition, finance, biology, meteorology, and testing pseudo-random number generators. We prove that the GBD predicts the results in the collected data significantly better than the standard binomial distribution thus proving that the events are indeed correlated. We provide an R code, and a supplementary Excel file that provide users with an easy way to analyze any collected data set based on Bernoulli processes. [ABSTRACT FROM AUTHOR]

new net-cationic polyacrylamide dry strength agent was synthesized through free radical polymerization using acrylamide (AM), itaconic acid (IA), N,N-dimethylacrylamide (F), and sodium methallyl sulfonate (T). Ethylene diamine tetraacetic acid was used as a chelating agent; dimethylaminoethyl methacrylate methyl chloride (DMC) solution was used as a cationic monomer, and ammonium persulfate (APS) was used as an initiator. Orthogonal design and single-factor experiments were utilized to study the effect of many factors, such as reaction time, the ratio of monomers, and the dosage of APS and DMC on the cationic polyacrylamide. The synthesized products were characterized by Fourier transform infrared spectroscopy (FTIR), gel permeation chromatography (GPC), particle charge detector (PCD), and zeta potential analysis. The results showed that the optimum conditions were as follows: optimal monomer proportion: m(AM):m(IA):m(T):m(F) = 23.79:2.39:0.21:0.32; w (DMC) = 28%; w (APS) = 1.0%, reaction time was 3 hours, reaction temperature was 93 oC, stirring speed was 130 rpm, and reaction pH value was 3.0. The solid content of the polymer was 21.2%. By adding the cationic polyacrylamide to old corrugated container pulp, the tensile index increased by 29.7% and the burst index increased by 66.1%, displaying the obvious enhancement of the paper. [ABSTRACT FROM AUTHOR]

The fabrication of composite materials is an effective way to improve the performance of a single material and expand its application range. In recent years, graphene-based materials/polymer composite aerogels have become a hot research field for preparing high-performance composites due to their special synergistic effects in mechanical and functional properties. In this paper, the preparation methods, structures, interactions, properties, and applications of graphene-based materials/polymer composite aerogels are discussed, and their development trend is projected. This paper aims to arouse extensive research interests in multidisciplinary fields and provide guidance for the rational design of advanced aerogel materials, which could then encourage efforts to use these new kinds of advanced materials in basic research and commercial applications. [ABSTRACT FROM AUTHOR]

Definition: Phyllosilicates are common minerals that include the most widely known micas and clay minerals. These minerals are found in several natural environments and have unique physical-chemical features, such as cation exchange capacity (CEC) and surface charge properties. When phyllosilicates are nano-sized, their physical-chemical properties are enhanced from those of the micro-sized counterpart. Because of their unique crystal chemical and physical-chemical features, kinetics, and particle size, nano-sized clay minerals (i.e., kaolinite, montmorillonite/illite) and micas (i.e., muscovite) are of great interest in several fields spanning from environmental applications to engineered materials. This paper aims to overview the recent developments of environmental protection and technological applications employing nano-sized natural micas and clay minerals. Emphasis is given to the role that the unique physical-chemical properties of montmorillonite, vermiculite, kaolinite, and muscovite play in nanoparticle formulations, manufacture, and technical performance. [ABSTRACT FROM AUTHOR]

COVID-19 has impacted the mental health of the general public negatively, associated with preventative measures, restricting life activities. These restrictions, such as the stay-at-home strategy, resulted in heightened stress, depression, loneliness, substance abuse, and domestic violence, violating people's occupational and personal lives. During the pandemic, the demands for role-play games (RPGs) have increased: for example, the sales of "Dungeons & Dragons" tripled, underscoring the potential mental health benefits of such games. However, research into the mental health benefits of such games remains under-developed, needing more scientific attention. Accordingly, this commentary paper reviews the existing literature, and suggests areas for application and research about RPGs and mental health including psychotherapy, career guidance, education, and people with disabilities. Insights offered can help practitioners and researchers in RPGs and mental health conduct empirical research and develop alternative approaches for mental health in stressful times. [ABSTRACT FROM AUTHOR]