The purpose of the research is to investigate the unique solvability of a nonlocal boundary value problem for a loaded equation of parabolic-hyperbolic type in a special domain. Methods: Using representations of a general regular solution, the existence and uniqueness of the problem posed is proved. Results: A new method for proving the unique solvability of nonlocal boundary value problems for one loaded equation of mixed type in a special domain has been formed and developed. Conclusions: The obtained results make it possible to solve some problems of genetics, immunology, transonic gas dynamics and thermal physics, which are associated with displacement.

The cluster randomized trial ARena (Sustainable reduction of antibiotic-induced antimicrobial resistance, 2017-2020) promoted the appropriate use of antibiotics for acute non-complicated infections in primary care networks (PCNs) in Germany. A process evaluation aimed to provide insights into determinants of practice and explored factors associated with antibiotic prescribing patterns. In a nested mixed-methods approach, a three-waves survey used study-specific questionnaires for participating physicians and medical assistants to assess potential impacts and uptake of the complex intervention program. Stakeholders received a one-time online questionnaire to reflect on network-related aspects. Semi-structured, open-ended interviews with a purposive sample of physicians, medical assistants and stakeholders explored aspects regarding the acceptance of the program components for daily practice and the perceived sustainability of intervention component effects. The intervention components were perceived to be smoothly integrable into practice routines. The highest uptake was reported for the educational components: feedback reports, background information, e-learning modules, and disease specific quality circles. Participation in PCNs was seen as motivational factor for guideline-oriented patient care and the adoption of new routines Future approaches to fostering appropriate use of antibiotics by targeting health literacy competencies and clinician’s therapy decisions should combine evidence-based information sources, audit and feedback reports and QCs.

Resilience is a particularly important quality for supply chains in this turbulent environment. Resilience in supply chain is the ability to retain, resume, and recover operations after an intense destructive incident. One of the strategic solutions for managing supply chain disruptions is to establish collaboration and strategic alliances in order to achieve competitive advantage. Therefore, given the increasing publication of articles in areas of strategic alliances and supply chain resilience, it is a good opportunity to review these articles, identify gaps in the current literature, demonstrate links between the two areas, and provide suggestions for future research. For these purposes, a bibliometric analysis has been performed on literature available on the Web of Science database. The distribution of articles based on year and country, influential journals, research areas, authors, affiliations, keywords, citations, and reference co-citation analysis are discussed. Results indicate that studies about strategic alliances, meant to increase resilience, are growing in areas such as “Management”, “Operations research”, “Management science”, and “Business”. Furthermore, the sources could be categorized in five clusters; namely “From knowledge concept to value creation”, “Internal and external relationships”, “Logistics and supply chain performance”, “Intellectual capital and strategic management”, and “Critical success factors and alliances”. This article can be useful for both practitioners and academics who explore the topic of strategic alliances and resilience in supply chain and also offers managers the opportunity to overcome supply chain disruptions and negative consequences of risks by becoming familiar with the key concepts of resilience. The persistence of businesses and supply chains is guaranteed through communicating with partners and even competitors in the light of alliance according to the findings of this research. Managers can pay attention to the integration of the supply chain to improve resilience and increase collaboration between suppliers and customers. Given the research results, strategic alliances can be noted in expanding organizational entrepreneurship, and shaping strategic collaboration networks in light of strategic alliances.

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, also surface waves retrieved through the application of seismic interferometry are exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a two-dimensional grid of localized depth-dependent velocity profiles are obtained. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation on the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. Also, it adapts model resolution to the amount of noise on the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from (time-averaged) station-station cross correlations by the Reykjanes seismic network.

Traditional travel agencies and tour operators are recognized as relevant stakeholders in the tourism distribution chain, even though their role as transforming agents in the achievement of more sustainable tourism is beginning to be accepted. This document collects the main topics and the most recent approaches from the academic literature in its analysis of Corporate Social Responsibility (CSR) practices developed by these intermediaries. The work has been structured around six recurring themes in most of the studies carried out: the new intermediaries that operate on the Internet; the role of travel agencies and tour operators in tourism sustainability; the influence of the size of the company; CSR as a disruptive innovation in this sector; the potential of the sustainable tourism supply chain; and the motivations and attitudes of the managers of these businesses when they engage with responsibility. This last topic is developed in greater detail since it is closely linked to the previous ones and dictates in most cases the meaning and function of the sustainable performance.

In the present work we study the existence of solutions for hybrid nonlinear fractional integrodifferential equations. We developed an algorithm by using the operator theoretical techniques in order to obtain the approximate solutions. The main results depend on the Dhage iteration method that were incorporated with the modern hybrid fixed point theorems. The approximate solutions were obtained by using Lipschitz conditions and weaker form of mixed partial continuity. Further, we provide some examples to explain the hypotheses and the related results.

Due to the increased use of memristors, and its many applications, the use of emulators has grown in parallel to avoid some of the difficulties presented by real devices such as variability and reliability. In this paper, we present a memristive emulator designed using a Switched Capacitor (SC), this is, an analog component/ block and a control part or block implemented using stochastic computing (SCo) and therefore fully digital. Our design is thus a mixed signal circuit. Memristor equations are implemented using stochastic computing to generate the control signals necessary to work with the controllable resistor implemented as switched capacitor.

Bacterial Calcium-carbonate Precipitation (BCP) has been studied for multiple applications such as remediation, consolidation and cementation. Isolation and screening of strong calcifying bacteria is the main task of BCP-technique. In this paper we studied CaCO₃ precipitation by different bacteria isolated from a rhizospheric soil in both solid and liquid media. It has been found, through culture-depending studies, that bacteria belonging to Actinobacteria, Gammaproteobacteria and Alphaproteobacteria are the dominant bacteria involved in CaCO₃ precipitation in this environment. Pure and mixed cultures of selected strains were applied for sand biocementation experiments. Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) analyses of the biotreated samples revealed the biological nature of the cementation and the effectiveness of the biodeposition treatment by mixed cultures. X-ray diffraction (XRD) analysis confirmed that all the calcifying strains selected for sand biocementation precipitated CaCO₃, mostly in the form of calcite. In this study Biolog® Eco-plate is evaluated as a useful method for a more targeted choice of the sampling site with the purpose of obtaining interesting candidates for BCP applications. Furthermore, ImageJ software was investigated, for the first time to our knowledge, as a potential method to screen high CaCO₃ producer strains.

Raw material logistics reflects an important aspect of global trade. Raw materials form an essential basis for society, for daily life, and range from apples to zinc. This paper addresses the analysis and optimization of supply chains of raw materials in terms of their economic viability and their sustainability. Type representatives are chosen according to annual transported quantities. Hard coal represents bulk goods, aluminum primary raw materials with medium quantities, and rare earths primary raw materials with small quantities. Their respective supply chains are analyzed and subsequently possible strategies and methods and their application are discussed. The paper shows for the first time that the selection and application of optimization priorities (e.g. profitability or sustainability) depends on the primary raw material and its integration into global production chains.

Malaria is a long-standing disease and one of the top life-threatening diseases, yet its treatment has not changed, while the world has already embraced the Fourth Industrial Revolution (4IR). A wave of research on digitizing monitoring mechanisms of such a deadly disease has surfaced. Automated malaria screening is one of the detection processes which are gaining popularity in the research domain. However, the process needs to be coupled with other processes aiming a nationally or regionally contextualised malaria monitoring system. This paper proposes a digital malaria monitoring system in the context of an African country or region. One advantage of such a digital system is that is enables a novel disease spread forecasting model based on the dynamics of different malaria types. The architecture of the diagnosis system is described, and the disease spread model is mathematically modelled in terms of a SPITR (Susceptible- Protected- Infected-Treated- Recovered) epidemic model which is further analysed. The forecasting model is expressed and analysed whereas experiments are conducted using a Monte Carlo simulation method. The design of the monitoring system has inspired how predictions can be made in the complex cases such as mixed infections. Results show that reinforcing the model parameter makes a significant improvement on the disease prediction.

The path towards decarbonization requires a progressive adaptation of all refrigeration systems, but only stationary ones have been intensely studied to improve their environmental performance. However, refrigerated transport is a vital piece of the cold chain, and it must be considered in the green transition. In this paper, we propose a model for a hybrid refrigerated van that includes photovoltaic panels and electric batteries to decrease total greenhouse gas emissions from the engine. Thermal, electrical, and battery sub-models are considered and integrated into the comprehensive hybrid solar-powered refrigerated van model. Different technologies are compared in economic terms, including Lithium and Lead-acid batteries and three different types of photovoltaic panels. The model was validated regarding van fuel consumption, showing a 4% deviation. Single and multiple delivery scenarios are considered to assess the energetic, economic, and environmental benefits. Monthly CO2,e emissions could be reduced to 20% compared to a standard refrigerated van. Despite the environmental benefits provided by this sustainable solution, the payback period is still too long (above 20 years) because of the necessary investment to adapt the vehicle and considering fuel and electricity prices currently.

Research focused on succinate dehydrogenase (SDH) and its substrate, succinate, culminated in the 50’s accompanying the rapid development of research dedicated to bioenergetics and intermediary metabolism. This allowed to uncover the implication of the SDH in both the mitochondrial respiratory chain and the Krebs cycle. Nowadays this theme is experiencing a real revival following the discovery of the role of SDH and succinate in a subset of tumors and cancers in human. The aim of this review is to enlighten the many questions yet unanswered, ranging from fundamental to clinically oriented aspects, up to the danger of the current use of SDH as a target for a sub class of pesticides.

Today’s export-based manufacturers face the need to implement green supply chains more efficiently in order to overcome environmental barriers in increasingly competitive export markets and to improve export performance. This study examines the structural relationship between environmental collaboration, green innovation capacity, and performance based on the findings of previous studies in order to identify the factors affecting the green supply chain management (GSCM) performance of Korean export-based manufacturers. The study finds that environmental collaboration in the green supply chain environment is an important driver of green innovation capacity for export-based Korean manufacturers. It also finds that green innovation capacity has a positive effect on export performance through environmental performance. This study establishes a theoretical basis for the systematic study of the structural mechanisms of green supply chains and suggests strategic directions for export-based manufacturing firms’ successful GSCM implementation.

Economic expedience of waste heat recovery systems (WHRS), especially for low temperature difference applications, is often questionable due to high capital investments and long pay-back periods. By its simple design isobaric expansion (IE) machines could provide a viable pathway to utilize otherwise unprofitable waste heat streams for power generation and particularly for pumping liquids and compression of gases. Different engine configurations are presented and discussed. A new method of modelling and calculation of the IE process and efficiency is used on IE cycles with various pure and mixtures as a working fluid. Some interesting cases are presented. It is shown in this paper, that the simplest non-regenerative IE engines are efficient at low temperature differences between a heat source and heat sink. Efficiency of non-regenerative IE process with pure working fluid can be very high approaching Carnot efficiency at low pressure and heat source/heat sink temperature differences. Regeneration permits to increase efficiency of the IE-cycle to some extent. Application of mixed working fluids in combination with regeneration permits to significantly increase the range of high efficiencies to much larger temperature and pressure differences.

Efficient alternatives in energy production and consumption are constantly investigated by increasingly strict policies. In this way, the pollutant emissions that contribute to the greenhouse effect reduce and sustainability of the electricity sector increase. With more than a third of the world's energy consumption, buildings have great potential to contribute these sustainability goals. Additionally, with growing incentives in the Distributed Generation (DG) and Electric Vehicle (EV) industry, it is believed that Smart Buildings (SBs) can be a key in the field of residential energy sustainability in the future. In this work, an energy management system in SBs are developed to reduce the power demanded of a residential building. In order to balance the demand and power provided by the grid, microgrids such as Battery Energy Storage System (BESS), EVs and Photovoltaic Generation panels (PV) are used. Here, a Mixed Binary Linear Programming formulation (MBLP) is proposed to optimize the charge and discharge scheduling of EVs and also BESS. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis is considered. The results point a 65% reduction in peak load consumption supplied by grid and a 28.4% reduction in electricity consumption costs.

Antibiotic resistance (ABR) is concerning issue due to its direct and indirect repercusions on public health, since decreased therapeutic effect of certain antibiotic to treatment complications that can cause death. There are several mechanism as to how ABR can be transferred from one microoorganisms to another, and many of them are dependant many environmental factors. The food supply chain is a environment in which ABR gene transfer can occur is multiple pathways, which generate concerns regarding food safety. Here, we summarize relevant mechanisms which are implied in ABR in food supply chain but also we are addressing routes of transmission and prevalence of ABR, implications on public health, and the application of new alternatives to antibiotics such as antimicrobial peptides, mainly bacteriocins, in order to countermeasure ABR.

The involvement of the angiotensin II type 1 receptor in the Frank-Starling Law of the Heart, where the various activations are very limited, allows simple analysis of the kinase systems involved and thence extrapolation of the mechanism to that of angiotensin control of activation of cardiac and skeletal muscle contraction. The involvement of phosphorylation of the myosin light chain in the control of contraction is accepted but not fully understood. The involvement of troponin-I phosphorylation is also indicated but of unknown mechanism. There is no known signal for activation of myosin light chain kinase or Protein Kinase C-βII other than Ca²⁺/calmodulin but the former is constitutively active and thus has to be under control of a regulated inhibitor, the latter kinase may also be the same. Ca²⁺/calmodulin is not activated in Frank-Starling, i.e. there are no diastolic or systolic [Ca²⁺] changes. I suggest here that that the regulated inhibition is by myosin light chain phosphatase and/or β-arrestin. Angiotensin activation is by translocation of the β-arrestin from the sarcoplasm to the PM thus reducing its kinase inhibition action in the sarcoplasm, this reduced inhibition has been wrongly attributed to a mythical downstream agonist property of β-arrestin.

The mutualistic interactions between the oleaginous yeast Lipomyces starkeyi and the green mi-croalga Chloroidium saccharophilum in mixed cultures were investigated to exploit possible syner-gistic effects. As a matter of facts, microalga could act as an oxygen generator for the yeast, while the yeast could provide carbon dioxide to microalga. A lignocellulosic hydrolysate from steam exploded Arundo donax (Giant reed) was used as low cost feedstock. The overall lipid content and lipid productivity obtained in the mixed culture treating the hydrolysate of Arundo donax were equal to 0.081 glipid.gbiomass-1 and 37.2 mglipid.L-1.d-1, respectively. They represented promising re-sults if compared to the model systems where synthetic media were used. This study provided new input for the integration of Single Cell Oil (SCO) production with agro-industrial feedstock and the fatty acid distribution mainly consisting of stearic (C18:0) and oleic acid (C18:1) allows promising applications in biofuels, cosmetics, food additives and other products of industrial interest.

E-commerce is a rapidly evolving global trend that is having a significant impact on consumer behavior and business strategies. Despite its growing impact, e-commerce adoption by Moroccan firms remains low and research on this topic in this context is scarce. This study aims to fill this gap by investigating the main determinants influencing e-commerce adoption by Moroccan firms. We use logit, probit, and conditional mixed process-probit models to identify the critical factors driving e-commerce adoption. Our results reveal five key findings. First, newer firms that are more open to innovation and change are more likely to adopt e-commerce. Second, firms with a higher proportion of highly educated employees are more likely to adopt e-commerce. Third, the digital skills of new employees do not directly influence the likelihood of e-commerce adoption. Fourth, being listed on digital platforms increases the likelihood of e-commerce adoption. Finally, there is a positive relationship between firms engaged in innovation activities and e-commerce adoption. These findings highlight the need for additional investment in promoting modern organizational practices, reskilling workers, and implementing advanced technologies to facilitate effective e-commerce integration among Moroccan SMEs. By addressing these challenges, Moroccan firms can harness the full potential of e-commerce and contribute to the country’s economic growth and digital transformation.

This review article aims at improving understanding of the theoretical discussion on technonationalism. Reviewing conventional works of the literature proposes protectionist, innovationist, and strategic industrial approaches toward high-tech industries. The findings show that technonationalism is a concept linking technology and national security, seeking geoeconomic interests in the integrated global market to exert state power for economic statecraft. The nature of industry highly relies on the global value chain, and technological innovation in the high-tech sectors occurs mainly in the private sector; thus, this article points out the issue of embracing business interests into the state’s strategic addenda as a critical criterion of technonationalism. Also, technonationalism is a narrowly defined concept with state actors involved in national security affairs and high-tech business actors.

This paper mainly analyzes the design and control of the rotational inverted pendulum, and presents a state space expression. Since the system is highly unstable a feedback control system is used. Augmentations with weighting functions based mixed sensetivity and H2 optimal control methods are used to make the system stable for uprise position. The rotational inverted pendulum have been simulated and compared with the proposed controllers and a promising results have been analyzed sussesfuly.

Green innovation has become an important combination of high-quality economic growth and sustainable development of ecological environment. In this paper, the super-efficiency network SBM model is used to measure the two-stage green innovation efficiency of industrial science and technology R&D and achievement transformation in 30 provinces and cities from 2009 to 2019, and exploratory Data Analysis (ESDA) and spatial econometric model are used to investigate the spatial-temporal evolution characteristics and influencing factors of green innovation efficiency. The results show that: firstly, the overall efficiency of industrial green innovation is low, and the efficiency of scientific research and development and achievement transformation has experienced three stages of "upward-declining-revitalized period". The low efficiency of achievement transformation is an important factor hiding the improvement of the efficiency of industrial green innovation. Secondly, The industrial green innovation efficiency gradually increases from northwest to southeast, forming a centralized "line" and "block" distribution. The high efficiency area is still concentrated in the eastern coastal region, and the balanced development trend is obvious in the central and western regions. Finally, openness has a positive impact on the two-stage green innovation efficiency; Industrial structure and government investment in science and technology have a positive impact on the efficiency of science and technology research and development, but have no significant effect on the efficiency of achievement transformation. Enterprise size has a positive effect on achievement transformation efficiency, but has no significant effect on R&D efficiency. Environmental regulation has a positive impact on R&D efficiency and a negative impact on achievement transformation efficiency.

The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.

Ribosomes are macromolecular complexes important to protein translation, and thus, essential to life. Comprising an ensemble of ribosomal proteins and RNA molecules, ribosomes are conserved in structure and function across all domains of life, but recent structural studies have revealed differentiated structures of ribosomes from bacterial, archaea and eukaryotes. Additionally, unique ribosomal protein mass fingerprints have been found for individual species; thereby, indicating that ribosomes are differentiated in structure amongst different species. Given that structure defines function, differentiated function likely exists amongst ribosomes of different species, which could manifest as differences in translation efficiency that could impact on cell growth rate. But ribosomal proteins also hold phylogenetic significance in informing the evolutionary trajectory of each species. Such ribosomal proteins are thus not highly conserved and offers sufficient sequence space for the evolution of differentiated structure and function in different species. Using ribosomal proteins that hold phylogenetic significance as templates, this study sought to understand the mutational and conformational limits that define functional ribosomes. Specifically, ribosomal proteins in Bacillus subtilis that hold phylogenetic cues would be mutated through error-prone polymerase chain reaction to generate variants that are subsequently transformed into Escherichia coli. To help assess the functional properties of the heterologous ribosomal proteins, endogenous ribosomal protein genes would be inactivated by multiplex CRISPR interference. Since variants in ribosomal proteins would likely impact on ribosome function and translation efficiency, live/dead screening on LB agar would be effective as a preliminary screen for functional mutants. These mutants would subsequently be inoculated into liquid LB medium in 96 well plates to quantify relative growth rates between different strains harbouring different heterologous variants of ribosomal proteins. Plasmids containing different ribosomal protein mutants would be extracted from each functional strain and subjected to Sanger sequencing for determining the specific mutations involved. Collection of such mutations would provide a comprehensive mutational map that define the limits of ribosomal protein sequence space important to ribosome function. Furthermore, biochemical isolation of ribosomal proteins and their structural characterization by X-ray crystallography or cryo-electron microscopy would further illuminate the structural significance of each mutation on ribosome structure and function; thereby, elucidating the structural tolerance space for functional ribosomes. Overall, generating a diverse pool of mutant ribosomal proteins in viability assays followed by sequencing and structural characterization would help define the mutational and conformational limits of a functional and efficient ribosome.

Leishmania parasites present astonishing adaptative abilities that represent a matter of life or death within disparate environments during the heteroxenous parasite life cycle. From an evolutionary perspective, organisms develop methods of overcoming such challenges. Strategies that extend beyond the genetic diversity have been discussed and include variability between parasite cells during the infections of their hosts. The occurrence of Leishmania subpopulation fluctuations with variable structural genomic contents demonstrates that a single strain might shelter the variability required to overcome inconsistent environments. Such intrastrain variability provides parasites with an extraordinary ability to adapt and thus survive and propagate. However, different perspectives on this evolution have been proposed. Strains or species living in the same environment can cooperate but also compete. These interactions might increase the replication rate of some parasites but cause the loss of more aggressive competitors for others. Adaptive responses to intra- and interspecific competition can evolve as a fixed strategy (replication is adapted to the average genetic complexity of infections) or an optional strategy (replication varies according to the genetic complexity of the current infection). This review highlights the complexity of interspecies and intrastrain interactions among Leishmania parasites as well as the different factors that influence this interplay.

Fatty acid desaturase 2 (Fads2) is the key enzyme of long chain polyunsaturated fatty acid (LC-PUFA) biosynthesis. Endogenous production of these biomolecules in vertebrates, if present, is insufficient to meet demand. Hence, LC-PUFA are considered as conditionally-essential. At present however, LC-PUFA are globally-limited nutrients due to anthropogenic factors. Attention of research is given therefore to find ways to maximize endogenous LC-PUFA production especially in production species, whereby deeper knowledge on molecular mechanisms of enzymatic steps involved is being generated. This review first briefly informs about the milestones in the history of LC-PUFA essentiality exploration before it focuses on the main aim – to highlight the fascinating Fads2 potential to play roles fundamental to adaptation to novel environmental conditions. Investigations are summarized, which elucidate the evolutionary history of fish Fads2 providing an explanation for the remarkable plasticity of this enzyme in fish. Further, structural implications of Fads2 substrate specificity are discussed and some relevant studies performed on organisms other than fish are mentioned in cases when such studies have so far not been conducted on fish models. The importance of Fads2 in the context of growing aquaculture demand and dwindling LC-PUFA supply is depicted and a few remedies in the form of genetic engineering to improve endogenous production of these biomolecules are outlined.

Nowadays, frameworks and models are critical to enabling organizations to identify their current sustainability integration into business and to follow up on these initiatives over time. In this context, the maturity models offer a structured way of analyzing how a supply chain meets specific sustainability requirements and which areas demand attention to reach maturity levels. This study proposes a five-level maturity model to help supply chains identify their level of engagement with sustainability practices combining three perspectives: intra and inter-organizational sustainability practices, triple-bottom-line approach and critical areas for sustainability. All the steps followed in constructing the maturity model were based on a literature review, and case studies supported its improvement, application, and testing. The proposed model presents many advantages, such as being used as a self-assessment tool, a roadmap for sustainability behaviour improvement, and a benchmarking tool to evaluate and compare standards and best practices among organizations and supply chains.

A premise of statistical learning research is that learners attend to and learn the frequencies of repeating or co-occurring elements in the input. When the input is a series of words, participants readily learn the frequencies of phoneme sequences, that is, to learn phonotactic frequencies. Inherent to the concepts of both frequency and phonotactics is order, or the temporal structure of the input. Order is similarly inherent to statistical learning, yet the effect of order on statistical learning is not well understood. In the present study, adult participants learned the relative frequencies of eight item-medial consonant sequences, for example, the /mk/ in /nʌmkət/. Across five ordering conditions, both familiarization and test stimuli were independently ordered and randomized, thus allowing for a relatively broad search for order effects in an established statistical learning paradigm. Participants learned the target frequencies equivalently across the five ordering conditions, indicating no modulating effect of order. Nevertheless, participants also approached the task by applying idiosyncratic, structured orders to their responses. The result is an unexpected but robust effect of order. Both the results and the design of the study also allow for increased integration of statistical learning with memory and other aspects of cognition.

The purpose of this paper is to explore which financial performance indicators (FPIs) evaluate the level of supply chain capability (SCC) that explicitly touches all of the business functions and processes within and beyond the company. The authors investigated nine FPIs that were selected from the financial statements of 155 companies within nine industries. The authors find that suitable FPIs to measure SCC for shareholders’ value are return-on-assets (ROA), days-sales-outstanding (DSO), and current ratio (CR). This means that higher ROA, shortened DSO, and an appropriate level of CR could reach a sustainable supply chain. These results will help the industry to avert a major disruption in supply chain processes and activities using suitable financial performance indicators.

The concentration of all-trans-retinoic acid, the bioactive derivative of vitamin A, is critically important for the optimal performance of numerous physiological processes. Either too little or too much of retinoic acid in developing or adult tissues is equally harmful. All-trans-retinoic acid is produced by the irreversible oxidation of all-trans-retinaldehyde. Thus, the concentration of retinaldehyde as the immediate precursor of retinoic acid has to be tightly controlled. However, the enzymes that produce all-trans-retinaldehyde for retinoic acid biosynthesis and the mechanisms responsible for the control of retinaldehyde levels have not yet been fully defined. The goal of this review is to summarize the current state of knowledge regarding the identities of physiologically relevant retinol dehydrogenases, their enzymatic properties and tissue distribution, and to discuss potential mechanisms for the regulation of the flux from retinol to retinaldehyde.

‘‘Sustainable Supply Chain Management’’ (SSCM) has become a hot topic on which eminent researchers are working on every day. However, it is clear that we still observe in this field of research, an artistic vagueness on the fundamental differences between Sustainable Supply Chain Management and Green Supply Chain Management (GSCM) Moreover, it is regrettable to note that previous researchers haven't yet thought about having a specific theory which can be applied to SSCM, the use of macro theories still being observed. In addition, we observe a lack of research in the oil and gas industry especially in Developing Countries when we know that this industry is the most lucrative and polluting. Therefore, this paper’s purpose consists to make a Systematic Literature Review (SLR) of 38 papers published from 2005 to 2023 especially in oil and gas industry and in Developing Countries, in order to make a clear distinction between SSCM and GSCM while highlighting the practices related to them and at the same time, generating a united theory which will bring together the triple bottom line of the SSCM. As findings, the authors built a Conceptual Framework that applies the triple bottom line of the SSCM in oil and gas industry by demonstrating that GSCM which is more related to environmental issues and is a part of the SSCM. Therefore, in order to be more efficient and to have a great impact on their performances, Oil and gas companies should apply SSCM practices rather than GSCM practices which are very different from what is applied in Developed Countries because of certain barriers and pressures.

Mitochondrial disorders, although heterogeneous, are traditionally described as conditions characterized by encephalomyopathy, hypotonia and progressive postnatal organ failure. Here we provide a systematic review of Linear Skin Defects with Multiple Congenital Anomalies (LSDMCA), a rare unconventional mitochondrial disorder which presents as a developmental disease; its main clinical features include microphthalmia with different degrees of severity, linear skin lesions, and central nervous system malformations. The molecular basis of this disorder has been elusive for several years. Mutations were eventually identified in three X-linked genes, i.e., HCCS, COX7B, and NDUFB11, which are all endowed with defined roles in the mitochondrial respiratory chain. A peculiar feature of this condition is its inheritance pattern: X-linked dominant male-lethal. Only female or XX male individuals can be observed, implying that nullisomy for these transcripts is incompatible with normal embryonic development in mammals. All three genes undergo X-inactivation that, according to our hypothesis, may contribute to the extreme variable expressivity observed in this condition. We propose that mitochondrial dysfunction should be considered as an underlying cause in developmental disorders. Moreover, LSDMCA should be taken into consideration by clinicians when dealing with patients with microphthalmia with or without associated skin phenotypes.

Risk modelling along with multi-objective optimization problems have been at theepicenter of attention for supply chain managers. In this paper, we introduce a datasetfor risk modelling in sophisticated supply chain networks based on formal mathematical models. We have discussed the methodology and simulation tools used to synthesize the dataset. Additionally, the underlying mathematical models are discussed in granular details along with providing directions to conducting statistical analyses or neural machine learning models. The simulation is performed using MATLAB ™Simulink and the models are illustrated as well.

There is a huge interest in developing novel hollow fiber (HF) membranes able to modulate neural differentiation to produce in vitro blood-brain barrier (BBB) models for biomedical and pharmaceutical research, due to the low cell-inductive properties of the polymer HFs used in current BBB models. In this work, poly(ε-caprolactone) (PCL) and composite PCL/graphene (PCL/G) HF membranes were prepared by phase inversion and were characterized in terms of mechanical, electrical, morphological, chemical, and mass transport properties. The presence of graphene in PCL/G membranes enlarged the pore size and the water flux and presented significantly higher electrical conductivity than PCL HFs. Biocompatibility assay showed that PCL/G HFs significantly increased C6 cells adhesion and differentiation towards astrocytes, may be attributed to their higher electrical conductivity in comparison to PCL HFs. On the other hand, PCL/G membranes produced a cytotoxic effect on the endothelial cell line HUVEC presumably related with a higher production of intracellular reactive oxygen species induced by the nanomaterial in this particular cell line. These results prove the potential of PCL HF membranes to grow endothelial cells and PCL/G HF membranes to differentiate astrocytes, the two characteristic cell types that could develop in vitro BBB models in future 3D co-culture systems.

The opioid crisis in the United States has had devastating effects on communities across the country, leading many states to pass legislation that limits the prescription of opioid medications in an effort to reduce the number of overdose deaths. This study evaluates the impact of two categories of PDMP and Pill Mill regulations on the supply of opioid prescriptions at the level of dispensers and distributors (excluding manufacturers) using ARCOS data. The study uses a difference-in-difference method with a two-way fixed design to analyze the data. The study finds that both of the regulations are associated with reductions in the volume of opioid distribution. However, the study reveals that these regulations may have unintended consequences, such as shifting the distribution of controlled substances to neighboring states. For example, in Tennessee, the implementation of Operational PDMP regulations reduces in-state distribution of opioid drugs by 3.36% (95% CI, 2.37 to 4.3), while the out-of-state distribution to Georgia, which did not have effective PDMP regulations in place, increases by 16.93% (95% CI, 16.42 to 17.44). Our studies emphasize that policymakers should consider the potential for unintended distribution shifts of opioid drugs to neighboring states with laxer regulations as well as varying impacts on different dispenser types.

We derive a quantum speed limit for unitary evolution for the case of mixed quantum states using the stronger uncertainty relation for mixed quantum states. This bound can be optimized over different choices of Hermitian operators for a better bound. We illustrate this with some examples and show its better performance with respect to three existing bounds for mixed quantum states.

Water resource is considered as a significant factor in development of regional environment and society. Water consumption prediction can provide important decision basis for the regional water supply scheduling optimisations. According to the periodicity and randomness nature of the daily water consumption data, a Markov modified autoregressive moving average (ARIMA) model is proposed in this study. The proposed model, combined with the Markov chain, can correct the prediction error, reduce the continuous superposition of prediction error, and improve the prediction accuracy of future daily water consumption data. The daily water consumption data of different monitoring points are used to verify the effectiveness of the model, and the future water consumption is predicted, in the study area. The results show that the proposed algorithm can effectively reduce the prediction error compared to the ARIMA.

Violence against paramedics is increasingly recognized as an important occupational health problem, but pervasive and institutionalized underreporting hinders efforts at risk mitigation. Earlier research has shown that the organizational culture within paramedicine may contribute to underreporting and researchers have recommended involving paramedics in the development of violence prevention policies, including reporting systems. Eighteen months after the launch of a new comprehensive violence reporting system in Peel Region, Ontario, Canada, we surveyed paramedics about their willingness to report violent encounters. A total of 204 (33% of eligible) paramedics chose to participate, of whom 67% (N=137) had experienced violence since the launch of the new reporting process, with 83% (N=114) reporting the incidents at least some of the time. In choosing to report, participants cited the accessibility of the new reporting process and the desire to promote accountability among perpetrators while contributing to a safer workplace as motivating factors. Their decisions to file a report, however, could be influenced by the perceived ‘volitionality’ and severity of the violent encounters, particularly in the context of (un)supportive co-workers and supervisors. Ultimately, the participants’ belief that the report would lead to meaningful change within the service was a key driver of reporting behavior.

Migrant population have always been vulnerable for high burden of social exclusion, mental disorders, physical illness and economic crisis. The current COVID-19 pandemic has further created the frantic plight among them, particularly for the undocumented migrant workers in global south. We have conducted a mixed method study among the undocumented Myanmar migrant workers (UMMWs) in Thailand to explore how the COVID-19 disruption has impacted on their mental health and what are the coping strategies adopted by them. Following the onset of COVID-19 and the recent coup d'etat in Myanmar, our current study is the first attempt to understand the mental health status and predicament of this neglected migrant group. A total of 398 UMMWs were included in the online survey among whom 23 participated in qualitative interviews. The major mental health issues reported by the study participants were depression, generalised anxiety disorder, frustration, stress and panic disorder while loss of employment, worries about the pandemic, social stigma, refused access to healthcare, lockdown and fear of detention were the predominant contributing factors. In response, we identified two key coping mechanisms- coping at personal layer (listening to music, playing online game, praying, self-motivation) and social layer (chatting with family and friends, visiting religious institutions). These findings point to the importance of policy and intervention programs aimed to uphold mental health at such humanitarian conditions. Sustainable institutional mental health care support and social integration for the migrant workers irrespective of their legal status should be ensured.

This paper focuses on hyperglycemic hyperosmolar syndrome (HHS), a unique hyperglycemic state requiring divergent diagnosis and treatment approaches from diabetic ketoacidosis (DKA), despite some shared characteristics. We introduce the mnemonic DI-FF-ER-EN-CE-S to encapsulate unique HHS management and complications. 'DI' emphasizes the need to delay and reduce initial insulin therapy until serum glucose decline is managed by fluid resuscitation alone. 'FF' and 'ER' stress the importance of fluid and electrolyte replacement due to severe dehydration and imbalances. 'EN' denotes the potential for encephalopathy and the requirement for a controlled serum osmolality reduction. 'CE' indicates that cerebral edema is rare but necessitates aggressive fluid therapy. 'S' signifies systemic multiorgan failure. We categorize the associated risks into three mnemonic groups: the 3Rs (renal failure, respiratory distress, rhabdomyolysis), the 3Hs (heart failure, hypercoagulation, hyperthermia), and AP (arrhythmias, pancreatitis) to facilitate awareness and screening of HHS.

In this study, Mg-Al and Mg-Al-Ni - layered double hydroxides (LDHs) were successfully synthesized for efficient removal of Mn²⁺ from synthetically wastewater. LDH adsorbents (Mg-Al and Mg-Ni-Al) were prepared by co-precipitation method. The formation of the layered double hydroxide, the adsorption of manganese on both LDH (Mg-Al and Mg-Ni-Al) were observed by XRD, SEM and EDX analysis. The various parameters such as the effect of shaking time, initial Mn²⁺ concentration, temperature were controlled and optimized to removal of Mn²⁺ from synthetic wastewater. The kinetics and adsorption isotherms for Mn²⁺ removal from wastewater were studied in batch mode. At temperatures of 10 °C and 20 °C the adsorption equilibrium was reached after 24 h. Adsorption isotherms of Mn²⁺ are well fitted by Langmuir and Freundlich isotherm equation. The adsorption capacity of Mn²⁺ from synthetic wastewater of 80.607 mg/kg was obtained for (Mg-Al-Ni)-LDH. It is found that the adsorption kinetics is best described by the pseudo-second order model. These results prove that LDHs can be considered as a potential material for adsorption of Mn²⁺ from wastewater.

Yijing possesses inherent principles and logic, and it has achieved consensus as an auxiliary decision-making function. Research on Yijing has been validated in the field of superpsychology, primarily focusing on individuals. However, the universal value of Yijing extends beyond individual divination or telepsychological induction, and there are untapped scientific potential values associated with it. Consequently, many scholars studying Yijing, including those in Chinese medicine, attempt to decipher its internal scientific mechanism through quantitative methods. In summary, scientific quantitative analysis of Yijing can be categorized into several approaches. These include quantification based on Yijing itself (binary and hexagram order), as well as quantification based on mathematical statistics, probability, and calculus. Another approach involves quantification based on expert knowledge, as well as the quantification of timewave curves and Yi-globle. Significant progress has been made in all of these quantitative research areas within the scientific paradigm. Nevertheless, future quantification of Yijing may explore rule-based evolutionary analysis, incorporating artificial intelligence technology, and conduct quantitative analysis based on the evolutionary process and results. There is even potential to deepen this research with tools such as ChatGPT. Additionally, the focus of Yijing divination may shift from individual events to group events, accompanied by space-time modeling and analysis through the construction of a new coordinate system.

Polyglycolic acid (PGA) is a promising polymer in the packaging field owing to excellent hydrolysis, heat resistance and gas barrier properties, but there are limited in application due to poor toughness. For this reason, a covalently bonded chain extender is introduced to increase compatibility with flexible polymers. However, covalent bonds are unfavorable for application to degradable plastics because of require a lot of energy for reverse reactions. Therefore, it is intended to effectively control the ductility of blending plastics by using a novel ionic chain extender having a relatively weaker non-covalent bond than the existing covalent bond. Polycaprolactone (PCL), which has biodegradability and flexibility, was selected as a blending polymer. For comparison, a covalently reactive chain extender (G-CE) and a non-covalently ionic chain extender (D-CE) were synthesized and compounded to blending plastics. Each chain extenders were improved the compatibility between PGA and PCL, and the ductility of the PGA/PCL blending plastics were greatly enhanced with non-covalently bonding D-CE than with covalently bonding G-CE. At this time, the ductility of PGA/PCL blending plastic without CE is 7.2%, the ductility of 10D with D-CE is 26.6%, and the ductility of 10G with G-CE is 18.45%. Therefore, it was confirmed that the novel ionic chain extender inducing non-covalent bonds improves the compatibility between PGA and PCL and is more advantageous in enhancing ductility through a reversible reaction.

The copper end paste used in multilayer ceramic capacitors sintered in nitrogen atmosphere will lead to carbon residue of organic vehicle, which will lead to the reduction of electrode conduc-tivity and high scrap rate. With an attempt to leave no residue in the sintering, the compatibility of solvents and thickeners should be improved because it has an important influence on the hi-erarchical volatilization and carbon residue of organic vehicles. In this work, the volatility of different solvents was compared and several solvents were mixed in a definite proportion to prepare an organic vehicle with polyacrylate resins. The hierarchical volatility and solubility parameters of mixed solvents were adjusted effectively by changing proportions of different components, the thermogravimetric curves of resins and organic vehicles were measured by thermogravimetric analyzer, the effect of solubility parameter on the dissolvability of resins in the solvent and the residual of organic vehicles were studied. Results showed that the hierar-chical volatilization of solvents can be obtained by mixing different solvents; the intrinsic vis-cosity of the organic vehicle is higher and the thermal decomposition residue of polyacrylate resins is lower when the solubility parameters of mixed solvents and polyacrylate resins are closer. The low residual sintering of organic vehicles can be achieved by using the mixed solvent with hierarchical volatility and approximate solubility parameters as resins.

Non-timber forest products (NTFP) have contributed in various ways to the living, livelihoods, and trading of households and communities who live in rural and urban areas all over the world. This paper analyses the value chain of Jiaogulan (Gynostemma pentaphyllum) in the Cao Bang Geopark, Vietnam. 106 actors were surveyed using a semi-structured questionnaire: experts (agricultural extension officers, farmers' associations), harvesters, traders, primary processors, processors, distributors, and consumers. The results show that a map of Jiaogulan value chain, value added of households in main market channels, and impact of value added and distribution of Jiaogulan products on household income.

In this paper, a solenoid based linearly movable armature system is designed using robust control theory in order to improve the performance of the system. Reference track method is the best performance analysis for position control systems. Among the robust controllers, H infinity mixed-sensitivity and Mixed H 2 /H∞ with Regional Pole Placement Controllers are used to improve the performance of the system. Comparison of the proposed controllers for tracking a reference displacement signals (step and sine wave) and a promising simulation result have been obtained.

Forage fish are crucial to human nutrition, especially in developing countries. However, in these countries, most forage fish catches are used to make aquafeeds for aquaculture, which leaves only a small quantity for direct human consumption. This practice increases fish prices in local markets and undermines people's nutrition. Overfishing forage fish for industrial purposes harms the ecosystem, reduces the catch of larger fish, and marginalizes local fishermen. Although previous discussions have touched qualitatively on the ethics and injustice of this practice, this article provides quantitative scales to measure the impact of the practice on the finances and forage fish consumption of low-income consumers using reasonable assumptions and literature values. Increasing the annual supply of forage fish by 25% to the 5 million MT of fresh fish markets globally could save consumers several billion US dollars annually. Families could consume a higher percentage of nutritious fish for less money. Furthermore, leaving forage fish in the sea could benefit wildlife and increase the capture of larger fish, such as mackerel, which are in demand in local markets and fished by local fishermen. The unintentional and involuntary contributions of low-income societies to enable the growth of high-value fish and shrimp for affluent societies seem unjust and warrant further investigation.

Indonesia has emerged as one of the leading producers and exporters of palm oil, as supported by data from the Central Bureau of Statistics in 2021, which indicate that Indonesian palm oil exports reached an impressive value of US$ 18.44 billion, or IDR 258 trillion, in 2020, marking an 18.43 percent growth compared to the previous year. Furthermore, the domestic market for palm oil and palm kernel oil remains substantial, despite improvements in export quantities. Various industries, including cooking oil refineries, specialty fats, shortening, margarine, bath soaps, and oleochemicals, present potential markets for palm oil (CPO) and palm kernel oil (PKO). The palm oil industry encompasses four related sub-sectors, namely growers, millers, refiners, and oleochemicals, forming an integrated value chain from upstream to downstream. The current focus on environmental, economic, and social sustainability is driving companies to adopt internal green activities and expand their efforts into sustainability supply chain management (SSCM). Implementing SSCM practices is often seen as economically beneficial, as research has demonstrated their positive impact on firm performance from a resource perspective. Within the palm oil industry, a wide range of green management applications are being utilized. This study aims to examine and highlight the existing sustainable management practices across the entire palm oil supply chain, with a particular emphasis on producing high-quality palm oil. To achieve this objective, the paper utilizes a systematic review methodology, The number of papers analyzed were 62 articles published which involves an extensive review of relevant literature to identify research trends, gaps, and issues. The study seeks to contribute to the body of knowledge by expanding the theory of organizational readiness in preparing globally competitive palm oil products. The research findings hold practical significance for practitioners and academics, providing a comprehensive roadmap for implementing green management applications at the organizational level in the palm oil industry's upstream-to-downstream chain.

Background: Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2. In Colombia, many commercial methods are now available to perform the RT-qPCR assays, and the laboratories must evaluate its diagnostic accuracy to ensure reliable results to suspected COVID-19 patients. The purpose of the study was to compare four commercial RT-qPCR assays for detection of SARS-CoV2 virus, from nasopharyngeal swab samples referred to Laboratorio Carvajal IPS, SAS of Tunja, Boyacá - Colombia. Methods: This prospective study was conducted on 152 samples of respiratory tract samples (Nasopharyngeal Swab) from patients with suspected SARS-CoV-2 infection. Diagnostic accuracy of GeneFinderTM COVID-19 Plus RealAmp (In Vitro diagnostic), One-Step Real-Time RT-PCR (Vitro Master diagnostica), Berlin modified protocol and gold standard Berlin protocol (Berlin Charite Probe One-Step RT-qPCR Kit, New England Biolabs) as reference was assessed. Operational characteristics were estimated in terms of sensitivity, specificity, agreement, and predictive values. Results: Using Berlin Charite Probe One-Step RT-qPCR Kit as reference, the sensitivity/specificity for the diagnostic tests were found to be GeneFinderTM COVID-19 Plus RealAmp Kit 100%/92.7%, One-Step Real-Time RT-PCR, One-Step Real-Time RT-PCR 92.75%/67.47%, and Berlin modified protocol 100%/96.39%. The results of four commercially available methods were found to be consistent with those obtained from Berlin Modified protocol analysis for % of the samples and showed good agreement (κ= 0.96). Concordant SARS-CoV2 negative and positive RT-qPCR results were reported for xxx and xxx samples, respectively. Summarize something about the Ct. Conclusion: Our data demonstrate that all commercially available methods are rapid and reliable for the identification of SARS-CoV-2 virus associated with COVID-19. One-Step RT-qPCR Kit and GeneFinderTM COVID-19 Plus RealAmp assay show optimal sensitivity compared with Belin modified protocol. In addition, there is no significant correlation between xxxxx

Fixed offshore wind turbines continue to be developed for high latitude areas where not only wind and wave loads need to be considered, but also moving sea ice. Current rules and regulations for the design of fixed offshore structures in ice-covered waters do not adequately consider effects of ice loading and its stochastic nature on fatigue life of the structure. Ice crushing on such structures results in ice-induced vibrations, which can be represented by loading the structure using a variable-amplitude loading (VAL) sequence. Typical offshore load spectra are developed for wave and wind loading. Thus, a combined VAL spectrum is developed for wind, wave, and ice action. To this goal, numerical models are used to simulate the dynamic ice-, wind-, and wave-structure interaction. The stress time-history at an exemplarily selected critical point in an offshore wind energy monopile support structure is extracted from the model and translated into a VAL sequence, which can then be used as a loading sequence for the fatigue assessment or fatigue testing of welded joints of offshore wind turbine support structures. This study presents the approach to determine combined load spectra and standardized time series for wind, wave, and ice action.

Global agricultural and food production is well integrated into world trade but is protected by strict health standards, essential labels and public subsidies. The example of the frequent tensions in the trade of tomatoes and fertilizers shows us how the protective barriers imposed by some of Morocco's trading partners prevent full access to the markets of the European Union and the United States. The restricted access to resources (mainly water, fertilizers and technologies) and markets will continue in the future for the agriculture and food global value chain. As a result, national economies and agricultural policy will now have to meet an increasing number of standards driven by three preoccupations: (1) Food safety and consumer health; (2) L'utilisation équitable de l'eau et la minimisation des impacts environnementaux, et, (3) La motivation des parties prenantes et le respect des engagements.

Art organizations are increasingly focusing on enhancing the visitor experience to attract a wider audience. The aim objective of this study was to explore the key factors that influence the visitor experience of offline art exhibitions and to use a mixed methods to data collection and analysis. The research process was divided into three stages. In the first stage, we conducted semi-structured interviews with 12 respondents by dividing the exhibition experience into three time periods: pre, during, and post-visit. We extracted seven factors affecting visitor experience through qualitative content analysis including marketing, motivation, physical environment, exhibit quality, participation, technology and service facilities; in the second stage, we developed an assessment scale and pretested it; in the third stage, we collected 725 questionnaires to validate the factors of visitor experience in art exhibitions. The results of linear regression analyses showed that all seven key factors had a significant impact on visitor experience. This study constructed a scale to assess the factors of art exhibition experience, which provides theoretical sup-port for in-depth study of art exhibition experience and useful guidance for planning and design-ing art exhibitions to improve the quality of visitors' experience of art exhibitions.

In the transition towards sustainable energy sources, hydrogen has emerged as the predominant alternative after fossil fuels. This comprehensive literature review delves into the evolving landscape of hydrogen launching strategies within the energy market. Numerous countries have strategically initiated efforts to introduce products based on hydrogen, underscoring the global acknowledgment of the potential inherent in hydrogen. Despite witnessing significant growth in the adoption of hydrogen energy worldwide, impediments to its widespread commercialization persist. This review identifies key barriers, including cost structures, technical complexities, and marketing challenges, hindering the establishment of a robust hydrogen energy market. The article critically examines the actions already undertaken to harness hydrogen energy for commercial purposes, leveraging scientific insights and statistical data. By carefully examining the current state of hydrogen energy initiatives, the review highlights gaps in existing strategies that require thoughtful consideration. Insights derived from scientific and statistical analyses inform the identification of barriers and contribute to a nuanced understanding of the challenges faced in the journey towards hydrogen energy commercialization. Ultimately, the article presents a strategic proposal outlining marketing actions geared towards expediting the commercialization and widespread adoption of hydrogen energy. Grounded in a thorough review of existing literature and supported by scientific and statistical evidence, this comprehensive analysis offers valuable insights for stakeholders seeking to navigate the intricate landscape of hydrogen energy in the global energy market.

Red beetroot, is a well-recognized and established source of bioactives (e.g., betalains and polyphenols) with anti-inflammatory and antimicrobial properties. It is proposed as a potential alternative to zinc oxide, with a focus on gut microbiota modulation and metabolite production. In this study, weaned pigs aged 28-days were fed either a control diet, diet supplemented with zinc oxide (3,000 mg/kg), or 2% and 4% pulverized whole red beetroot (CON, ZNO, RB2 and RB4; respectively) for 14 days. After the pigs were euthanized, blood and digesta samples were collected for microbial composition and metabolite analyses. Results showed, red beetroot supplemented diet at 2% improved the gut microbial richness relative to other diets, but marginally influenced the caecal microbial diversity compared to zinc oxide supplemented diet. Further increase in red beetroot levels (4% -RB4) lead to loss of caecal diversity, decreased short chain fatty acids and secondary bile acid concentrations. An increased Proteobacteria abundance, presumably due to increased lactate/lactic acid producing bacteria was also observed. Summarily, red beetroot contains several components conceived to improve the gut microbiota and metabolite output of weaned pigs. Future studies investigating individual components in red beetroot will better elucidate their contributions to gut microbiota modulation and pig health.

“All diseases originate in the gut.” Hippocrates (400 BC) A healthy gut microbiome via the gut-brain-axis (GBA) elevates heart rate variability (HRV), a general measure of health and well-being. A dysbiotic gut microbiome, low in biodiversity and butyrate producers, alters tryptophan metabolism with release of proinflammatory cytokines, predominantly TNF-α, IL-6, and IL-1β. These also characterize chronic inflammation, oxidative stress, and a multitude of diseases, all exhibiting low HRV. Gut dysbiosis upregulates IFN-γ and with it IDO (indoleamine 2,3 dioxygenase). Tryptophan pivots from serotonin synthesis to that of IDO induced kynurenine, increasing the kynurenine to tryptophan ratio (KTR). An elevated KTR is positively linked to neurodegenerative and autoimmune diseases and negatively linked to HRV. Elevated IDO activity is not only enzymatic but also an intracellular signal transducer potentiated by TGF-β. This cytokine is the primary determinant of the TME. Also proposed is the gut-lung dysbiosis concept and consequent degradation of ACE2 (richest in lungs and gut). Leaky gut induced autoantibodies related to G-protein coupled receptors (GPCRs) in combination with increased Ang II further potentiate oxidative stress. Aldosterone and paroxysmal orthostatic tachycardia syndrome (POTS) paradoxes are highlighted in the context of GPCR and gut dysbiosis, and the role of Candida is explored. The triple play of a prebiotic (d-mannose), probiotic (bifidobacteria and lactobacilli), and postbiotic (butyrate) might improve intestinal barrier integrity, oppose entry of GPCR antigens, suppress the inflammatory cytokine triad, balance IFN-γ and TGF-β, suppress oxidative stress, depress KTR, elevate HRV, and extend lifespan and its quality.

There is an overall scientific consensus that public space and, mainly, space with a high ecological index – most notably experienced in green areas – positively affects individual and collective well-being and urban dwellers’ physical and mental health. However, the ‘reality check’ indicates difficulties in translating the assumed benefits of green space into implementable interventions in urban environments. To examine such an ‘implementation gap’ on the case of Zurich seems valid, given that the ‘green urban agenda’ debate has been embedded in numerous Swiss policies (from the federal to the municipal levels). In narrow terms, the research first focuses on Zurich’s district 9 consisting of two neighborhoods (Altstetten and Albisrieden) – the area under ongoing densification yet with a variety of green spaces, to then elucidate four green space clusters and their 400-meter catchment areas in the mentioned district. The mixed-method approach has been applied at three analytical levels: 1) documentary analysis of multi-scale national policy toolkits, to identify the critical tenets associated with the ‘green urban agenda’, 2) assessment of green spaces in Zurich’s district 9 based on online available quantitative data and on-site observation, to determine their provision, types, size and mutual connectivity, and 3) analysis of four green space clusters within the mentioned district through on-site observation, to identify green space attributes and main activities. Through critical mutual examination of the identified ‘green urban agenda’ principles in the national policies, on the one hand, and green space attributes, on the other, the research findings reveal the extent of the convergence and/or divergence between the ‘green urban agenda’ policy trends and their implementation in practice.

Binary mixtures of surfactants build a binary mixed micelle in which the ratio of surfactants usually differs from the initial ratio of surfactants in their binary mixture. The thermodynamic stabilization of the binary mixed micellar pseudophase about the hypothetical ideal state (intermolecular interactions between the different particles and the conformational states of the particles are identical to those of monocomponent states) is described by the molar excess Gibbs free energy (gE). The dependence of gE on the molar fraction of surfactant i (xi) from the binary mixed micelle can be described by a symmetric function (symmetry is described to the line parallel to the y-axis and passes through xi = 0.5) or by an asymmetric function. Theoretical analysis (canonical partition function, conformational analysis) examines how the presence of different polar functional groups, some of which are sterically shielded from the steroid skeleton of bile salt (surfactant), affect the symmetry of the function gE of the binary mixed micelle of the cholic acid anion (bile salt) and classical cationic surfactant (hydrophobic tail and polar head). Suppose the steroid skeleton of the bile salt contains non-sterically shielded polar groups (or the temperature is relatively high). In that case, gE is a symmetric function. At the same time, if the steroid skeleton also contains sterically shielded polar groups, then the gE function is asymmetric.

Abstract:The digital landscape is rapidly reshaping under the influence of AI-powered cloud-based e-commerce platforms (PCEPs). These platforms leverage the transformative power of AI to personalize customer experiences, optimize pricing strategies, enhance security, and streamline operations, offering businesses a significant competitive edge. However, challenges surrounding data privacy, algorithmic bias, and potential job displacement raise crucial ethical questions regarding widespread AI adoption in e-commerce.This study delves into the untapped potential and ethical considerations of PCEPs, distinguishing itself by proposing practical strategies for responsible development and ethical implementation.Objectives: Investigate the transformative potential of PCEPs: Personalized product recommendations:Analyze effectiveness and potential bias. Dynamic pricing strategies:Explore impact on consumer fairness and market stability. Enhanced fraud detection:Evaluate accuracy and privacy implications. Optimized supply chain management:Assess efficiency gains and job displacement risks. Critically analyze the ethical considerations of AI in e-commerce: Data privacy:Assess current practices and develop mitigation strategies. Algorithmic bias:Identify potential sources and propose solutions for fairer decision-making. Job displacement:Evaluate impacts and propose reskilling initiatives. Propose comprehensive and practical strategies for responsible PCEP development and implementation: Transparency:Enhance user awareness and control over data usage. Fairness:Design AI systems to mitigate bias and uphold consumer rights. Accountability:Establish clear guidelines and oversight mechanisms for ethical AI development.Conclusion: While PCEPs offer a plethora of transformative benefits, their ethical implementation is paramount. By adhering to principles of transparency, fairness, and accountability, businesses can unlock the full potential of PCEPs while minimizing potential risks and shaping the future of online commerce in a sustainable and equitable manner

This paper explores the ethical imperative of rehoming all healthy animals of sentient species after experiments have finished or when they have become otherwise redundant. We take into account disparate perspectives in animal ethics and see how they point in the same direction. We illustrate our case with our own rehoming experience from the joint Animal Welfare Body of Utrecht University and the University Medical Centre Utrecht, the Netherlands. The primary pilot proved successful, after which the principle of rehoming became standing policy and common practice. We discuss several challenges and our responses to those through continuous evaluation of the adoption program.

Green supply chain management (GSCM) is fundamentally growing as a key component of sustainability, owing to its ability to improve supply chain competitiveness and performance within firms. The body of literature on GSCM within the manufacturing sector in developing countries such as South Africa is still limited. The study examined the relationships between GSCM practices, dynamic capabilities, and supply chain performance in the South African manufacturing sector. The study was quantitative, involving a sample of 402 supply chain professionals drawn from the manufacturing sector across the four provinces of the country. Hypotheses were tested using structural equation modelling based on the SMART PLS technique. Eco-design Green distribution and green training impacted positively on dynamic capabilities, the latter of which in turn is linked to improved agility, reliability, and reduced supply chain costs. The study validates the importance of GSCM as a driver of dynamic capabilities and performance in manufacturing environments within developing countries such as South Africa.

Given the recent emergence of Rift Valley Fever (RVF) in Rwanda and its profound impact on livelihoods and health, improving RVF prevention and control strategies is crucial. Vaccinating livestock is one of the most sustainable strategies to mitigate the impact of RVF on health and livelihoods, yet vaccine supply chain constraints severely limit the effectiveness of vaccination programs. In the human health sector, unmanned aerial vehicles, i.e., drones, are increasingly being used to improve supply chains and last-mile vaccine delivery. We investigated perceptions on whether delivering RVF vaccines by drone in Rwanda might help to overcome logistical constraints in the vaccine supply chain. We conducted semi-structured interviews with stakeholders in the animal health sector and Zipline employees in Nyagatare District in the Eastern Province of Rwanda and used content analysis to identify key themes. We found that stakeholders in the animal health sector and Zipline employees believe that drones could improve RVF vaccination in Nyagatare. The main benefits study participants identified included decreased transportation time, improved cold chain maintenance, and cost savings.

This paper explores the coordination of the agricultural cooperative to supermarket or E-commerce sup-ply chain, under the condition of quantity loss with a mixed decay function of exponential and logistical distribution. The nature of this process is analyzed, and the corresponding demand and supply functions with single- and multi-stage discount strategies are constructed respectively to create a working model. The optimal discount ratios for supermarkets and agricultural cooperatives in decentralized and central-ized decision-making modes coupled with single- and multi-stage discounts are calculated respectively. Finally, a universal optimal strategy is designed, which can be applied to various quantity decay scenarios and makes the discount strategy more generalized. The results show that discounts can coordinate supply chains more effectively; not only is fresh agricultural produce sold before it starts to rot, but the benefit conflicts arising from both supermarkets vs. cooperatives and traditional vs. E-commerce channels are equilibrated. Further, multi-stage discounts are more effective than single-stage ones, but optimal discount ratios rely on the initial quantity of fresh agricultural produce in the supply chain; its market share in the traditional distribution channel; the potential market size; retail price; the price sensitivity coefficient of the channel; the cross-elasticity coefficient of prices between different channels; and the properties of the quantity loss.

With the continuous growth of electric and electronic appliances’ usage, the waste produced with obsolete material (e-waste) has an increasing environmental impact. Also, the production of such appliances bears to increased consumption of natural resources and produces a multitude of toxic and hazardous substances, which typically are not properly treated. One of the approaches that may be adopted to reduce such problems relies on the circularization of the current linear model, commonly adopted in the EEE value chain. This includes recovering eol products and reintroducing its parts, components, or raw materials into the value chain (e.g. semiconductors, circuit boards, raw metals, etc.), thus contributing to a more sustainable value chain. In this article, we present a state-of-art review that focuses on approaches and solutions for the EEE value chain traceability, and analyses the technologies that may be beneficial for promoting and implementing the CE model in this value chain.

The production of fuels and other industrial products from renewable sources has intensified the search for new substrates or for the expansion of the use of substrates already in use, as well as the search for microorganisms with different metabolic capacities. In the present work, we isolated and tested a yeast from the soil of sugarcane irrigated with vinasse, that is, with high mineral content and acidic pH. The strain of Meyerozyma caribbica URM 8365 was able to ferment glucose, but the use of xylose occurred when some oxygenation was provided. However, some fermentation of xylose to ethanol in oxygen limitation also occurs if glucose is present. This strain was able to produce ethanol from molasses substrate with 76% efficiency, showing its tolerance to possible inhibitors. High ethanol production efficiencies were also observed in acidic hydrolysates of each bagasse, sorghum, and cactus pear biomass. Mixtures of these substrates were tested and the best composition was found for the use of excess plant biomass in supplementation of primary substrates. It was also possible to verify the production of xylitol from xylose when the acetic acid concentration is reduced. Finally, the proposed metabolic model allowed calculating how much of the xylose carbon can be directed to the production of ethanol and/or xylitol in the presence of glucose. With this, it is possible to design an industrial plant that combines the production of ethanol and/or xylitol using combinations of primary substrates with hydrolysates of their biomass.

Phosphorus (P) is the most important substance in inorganic fertilizers used in agriculture industry. In this study, a multi-product and multi-objective model is presented considering economic and environmental concerns to design a renewable and sustainable P-fertilizer supply chain management (PFSCM). To handle complexities of the proposed model, an ensemble knowledge-based three-stage heuristic-metaheuristic algorithm utilizing heuristic information available in the model, whale optimization algorithm, and variable neighborhood search (named H-WOA-VNS) is proposed. At first, a problem-dependent heuristic is designed to generate a set of near-optimal feasible solutions. These solutions are fed into a population-based whale optimization algorithm which benefits from both exploration and exploitation strategies. Finally, a single-solution metaheuristic based on variable neighborhood search is applied to further improve the quality of the solution using local search operators. The objective function of the algorithm is formulated as a weighted average function to minimize total economic cost, while increasing crop yield and P use efficiency. Experimental results over five synthetic datasets and a real case study of the P-fertilizer supply chain confirm the superiority of the proposed method against the state-of-the-art techniques. The results demonstrate that the proposed method performs well in optimizing both the economic cost and environmental issues.

There are two purposes for this article. The first purpose is to perform a reiew of previous research on global supply chain management (GSCM) principles that can adapt and survive adversity, such as the COVID-19 pandemic. The second purpose is to put forth a conceptual framework for the GSCM that is sustainable in the event of future turbulence similar to that experienced during the COVID-19 pandemic. With regard to the issues raised, the article posits the following questions. Is there, perhaps, a sustainable post-COVID-19 pandemic GSCM? Can the COVID-19 pandemic-related international logistics system (GSC) turbulences be predicted with certainty using these sustainable post-COVID-19 pandemic GSCM concepts? Putting it all together, the paper concludes that, while debatable, sustainable GSCM is feasible and can be accomplished utilizing JIT, supply chain mitigation, and supply chain visibility, as demonstrated by the manufacturing firms referenced in the article.

Sustainable supply chain management (SSCM) represents a critical strategy for the electronics industry to balance economic objectives with environmental and social responsibility across complex global production networks. This multiple case study analysis investigates SSCM integration within leading Korean electronics manufacturers Samsung, LG, and Hyundai. In-depth qualitative data, focus groups, and sustainability report analysis reveals the policies, practices, results and implementation barriers related to incorporating sustainability criteria across procurement, manufacturing, distribution and recycling functions. Findings show sustainability considerations increasingly driven by cost, risk, reputational and regulatory factors, with vertical coordination initiatives helping transfer knowledge to assist suppliers on compliance and emissions reductions. Yet substantial obstacles persist around monitoring, coordination, transparency and technical capabilities, especially amongst lower tiers. The paper discusses how common reporting standards, ethical sourcing certification and partnerships can accelerate electronics supply chain sustainability. By mapping integration achievements and gaps, this study informs managerial best practices and policy reforms toward promoting socially and ecologically responsible models for Korea's vital export industry as it navigates rising stakeholder pressures.

Palmitoylethanolamide (PEA) has been prescribed for neuropathic pain for several years. This study is mainly addressed to summarize what has been published on the topic in the last decades, and how appropriate the numerous prescriptions are. Among others, it examines the innovative EquiPEA^® patent, which aims to address obstacles encountered with conventional PEA formulations. EquiPEA^® seems to partially ameliorate the bioavailability and the targeted distribution. It seems to introduce novel advancements that have the potential to enhance the therapeutic effectiveness of PEA in terms of its anti-inflammatory, antioxidant, and analgesic properties. The deep literature analysis aims to examine the potential advantages of this innovative formulation, in the context of several pathological conditions that may benefit from this molecule. In particular, it investigates the potential enhanced bioavailability and targeted delivery system of EquiPEA^®. Also, it tries to understand if it can modernize the field of therapy based on PEA, thus offering a better treatment option for individuals with long-term inflammation, oxidative stress, and neuropathic or mixed pain with a neuropathic component. The study examines the possible impact of EquiPEA^® on personalized medicine strategies and its potential for translation into clinical practice. It analyses the possibilities that EquiPEA^® has in enhancing patient outcomes in a range of central nervous system and inflammatory conditions. This narrative review makes a valuable contribution to the ongoing comprehension of PEA therapy. It establishes a foundation for further exploration in research and potential uses in clinical settings.

The microbiome is critical to the function of higher organisms and the gastrointestinal microbiome in chief among them. We do not know what impact the spaceflight GI microbiome has on organismal health in the absence of other confounding factors. We used a fecal transplant model to address this question and we found that we can recapitulate some of the functional aspects of the spaceflight microbiome on the ground but the impact on organismal health was ambiguous showing neither a defined improvement nor a impairment to lymph transport, growth, or immune populations. Histidine treatment was able to alter some of the functional aspects of the microbiome. Overall it we can conclude that the spaceflight microbiome is not pathological but has distinct impacts on organismal health.

Autism spectrum disorder (ASD) is a neuropsychiatric condition characterized by impaired social interactions and repetitive stereotyped behaviors. Growing evidence highlights an important role of the gut-brain-microbiome axis in the pathogenesis of ASD. Research indicates an abnormal composition of the gut microbiome and the potential involvement of bacterial molecules in neuroinflammation and brain development disruptions. Concurrently, attention is directed towards the role of short-chain fatty acids (SCFAs) and impaired intestinal tightness. This comprehensive review emphasizes the potential impact of maternal gut microbiota changes on the development of autism in children, especially considering maternal immune activation (MIA). The following paper evaluates the impact of the birth route on the colonization of the child with bacteria in the first weeks of life. Furthermore, it explores the role of pro-inflammatory cytokines, such as IL-6 and IL-17a and mother’s obesity as potentially environmental factors of ASD. The purpose of the present analysis is to advance our understanding of ASD pathogenesis, while also searching for the positive implications of the latest therapies, such as probiotics, prebiotics or fecal microbiota transplantation, targeting the gut microbiota and reducing inflammation. This review aims to provide valuable insights that could instruct future studies and treatments for individuals affected by ASD.

In modern times, sustainability in supply chain management is one of the keys to boosting the performance of the supply chain, and it enables the accomplishment of SSCM. It has been found in recent years that SSCM with assist of industry 4.0 applications, can benefit splendid productivity and efficiency in the supply chain. The numerous industry 4.0 applications that are involved are Artificial intelligence (AI), Machine Learning (ML), Internet of Things (IoT) Big Data Analytics (BDA), etc. Industry 4.0 with SSCM has gained a lot of interest from various authors and scholars across the world. Healthcare is one of the most critical sectors due to its importance in handling public health. More recently, the COVID-19 pandemic and other viruses (SARS and Ebola) have highlighted supply chain vulnerabilities that are further mitigated by their lean and globalized structures. Covid-19 underlined the need for supply chain visibility problems within the healthcare sector. When the need for medical supplies became urgent and global distribution was disrupted, companies faced the consequences of needing the technology, systems, and plans in place to correctly predict the onslaught. One report shows that about 94 percent of Fortune 1000 companies reported supply chain disruptions due to the COVID-19 global outbreak. Existing studies have discussed supply chain issues and the importance of AI in addressing these challenges. AI, like Industry 4.0 in the healthcare supply chain, is proving to be a game-changer. This paper aims to review and present the various aspects of SSCM and industry 4.0 applications to get a comprehensive literature review, which contains the analysis of multiple articles published from 2010-2020. In addition, the various challenges SSCM and industry 4.0 applications face are identified and discussed. Also, the impact of Industry 4.0 and sustainable practices brings together the healthcare supply chain. This study will help in getting a good understanding of the different industry 4.0 technologies that are important for setting up SSCM.

This investigation introduces an efficient method for assessing the reliability of semi-rigid steel frame connections in existing buildings, explicitly targeting the Top Angle and Seat Pad (TA-SP) semi-rigid connection commonly used in Australian cities' high-rise buildings. The moment capacity of these connections was examined through parameter power model testing, meticulously considering the bending, shear, and prying forces actions to determine the weakest elements in the connection system. A plastic hinge model was applied to ensure computational efficiency and accuracy in assessing the connections' ultimate strength. Comparatively, the finite element (F.E) method M−θ curves were introduced to scrutinise the nonlinear behaviour of the connection, providing validation for the predicted analytical approach. Further emphasis was placed on identifying the reliability of the weakest elements in the connection system, employing the First-Order and Second-Order Reliability Methods models to estimate their reliability index. The correlation between the model's failure probability and a percentile error was also explored, utilising Monte Carlo simulation reference for refined validation. Novel formulas and methodologies were introduced to compute the locked-chain-series system reliability, which accounts for the inherent material and geometric variability. The findings highlight the critical significance of the weakest element in determining the overall reliability of the existing TA-SP connection.

Locust is a pest that attacks human and animal food and endangers national security by threatening food security. Spraying is the easiest and fastest way to deal with them. But the easiest way is not always the best way. With chemical resistance, not only will permanent immunity from locust attacks not arise, but they will also become resistant to poisons. While we have to pay billions of dollars annually for this strategy, we will also cause water and soil pollution. Therefore, the research results of other researchers were used and modeled to measure the possibility of hunting invasive locusts to investigate the possibility and benefits of this action. So, this study was conducted in the field method. The obtained results indicate that it is possible to hunt invasive locusts. If traps are placed on time and in the right place, the possibility of preserving crops after the pest attack increases by 2.3 times more in protected fields than in unprotected fields. By hunting locusts, fields and even pastures are preserved, poisons are prevented from entering the food chain and ecosystem, part of the economic loss of farmers affected by the invasion of locusts will be compensated, and by providing animal feed through hunting locusts, water consumption will be reduced, soil erosion and energy consumption are saved.

The main aim of this study is to predict whether the type of breast cancer is “benign” or “malignant” by classical generalized linear model (GLM) approach and an extended family of GLM called generalized linear mixed model (GLMM) approach for binomially distributed response variable with binary link functions. In this study, an advanced statistical modeling approach based on the GLMM to the traditional statistical modeling approach based on the GLM for binomially distributed response variable with various binary link functions is proposed to investigate the relationships between the “malignant or benign diagnosis of the BC in patients” and “nine attributes” of 699 BC diagnosed patients. This study also focuses on the statistical significance of the accurate classification of the BC diagnosed patients in cancer studies in medicine in “benign” or “malignant” type based on the WBC dataset. In this study, the superiority of the GLMM approach over the GLM approach for the binary response variable especially belonging to the WBC dataset is emphasized in the field of cancer diagnosis in medicine. Also the importance and the power of the IC and performance metrics as the goodness-of-fit test statistics are strongly emphasized for accurate statistical inferences from the “best” fitted model. In this study, from the main findings, the best fitted model among the GLM and GLMM approaches for the binary response variable is determined as the GLMM under “logit” link function with “id” random effect with the most statistically significant odds of the occurance of the BC being “malignant” as 7.9104, 5.6888, 5.6643, 4.9842, 4.1212, 2.0679, 1.8755, and 1.3970 times more than being “benign” for every one-unit increase in the quantities of “clump thickness”, “bland chromatin”, “mitoses”, “bare nuclei”, “cell shape”, “marginal adhesion”, “epithelial cell size”, and “cell size”, respectively.

Quality control is a critical component in industrial manufacturing, directly influencing efficiency, product reliability, and ultimately, customer satisfaction. In the dynamic environment of industrial manufacturing, traditional methods of inspection may not adequately meet the evolving complexity, necessitating innovative approaches to bolster precision and productivity. In this study, we explore the application of mixed reality (MR) technology for real-time quality control in the assembly process. Our methodology involved the integration of smart glasses with a server-based image recognition system, designed to conduct real-time component analysis. The innovative aspect of our study lies in the harmonization of MR and computer vision algorithms, providing immediate visual feedback to inspectors and thereby improving the speed and accuracy of defect detection. YOLOv8 have been adopted in this study for detection object model. The project implementation occurred in a controlled environment to enable a comprehensive evaluation of the system functionality, the identification of possible problems and improvements in the system performance. The results indicated the viability of mixed reality as a powerful tool for enhancing traditional inspection processes. The fusion of MR and computer vision offers possibilities for future advancements in industrial quality control, paving the way for more efficient and reliable manufacturing ecosystems.

Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems. In this paper, it is considered that a CPS is a heterogeneous robot multi-agent system that cooperatively performs a formation task through a wireless network. The goal of this research is to evaluate the system's performance when the number of agents increases. To this end, two different mixed reality frameworks developed with the open-source tools Gazebo and Webots are used. These frameworks enable combining both real and virtual agents in a realistic scenario allowing scalability experiences. They also reduce the costs required when a significant number of robots operate in a real environment, as experiences can be conducted with a few real robots and a higher number of virtual robots by mimicking the real ones. Currently, the frameworks include several types of robots being the aerial robot Crazyflie 2.1 and differential mobile robots Khepera IV those used in this work. To illustrate the usage and performance of the frameworks, an event-based control strategy for rigid formations varying the number of agents is analyzed. The agents should achieve a formation defined by a set of desired Euclidean distances to their neighbors. To compare the scalability of the system in the two different tools, the following metrics have been used: formation error, CPU usage percentage, and the ratio between the real-time and the simulation time. The results show the feasibility of using Robot Operating System (ROS) 2 in distributed architectures for multi-agent systems in mixed reality experiences regardless of the number of agents and their nature. However, the two tools under study present different behaviors when the number of virtual agents grows in some of the parameters, and such discrepancies are analyzed.

A major challenge of augmented and mixed reality applications is identifying the context and semantics of the real environment. Studies on object and action recognition were developed based on the improvement of machine learning techniques, allowing them to be annotated and recognized. This study aims to characterize current knowledge on the use of machine learning for recognizing objects and actions in augmented and mixed reality environments, increasing context awareness. Therefore, a systematic literature review of works related to these topics was made, using the Scopus and Web of Science knowledge bases. We searched articles and conference reviews or papers published between 2018 and 2022 and selected fifteen studies to be reviewed. The results indicate that there is a great demand for using machine learning to immersive technologies in factories, engineering, entertainment, education, health, among other application domains. However, these real-time interactive systems still have challenges and limitations to be solved, involving network communication, prediction time and the creation of a model that recognize objects and actions in broad contexts. Furthermore, additional research is needed to investigate how object and action recognition can increase context awareness in augmented reality applications.

Recently dairying becomes an important farming activity in the districts. Even if these districts are potential in milk production and marketing activities, little was known about determinates of participation and level of participation in milk value addition. This study was analyzing determinates of participation and level of participation in milk value addition in the study areas. Both primary and secondary data were used. Primary data were collected from 244 producers, 50 traders and 20 consumers by using semi-structured questionnaires. Data were analyzed by using descriptive statistics and econometrics model. Results from Heckman selection model first step revealed that milk producers’ participation decision on milk value addition was significantly affected by religion, distance the market, cooperative membership, volume of milk produced per day and market access. Whereas milk producers’ participation decision on the volume of milk value addition was significantly affected by religion, level of education, number of children less than six years, membership for milk cooperatives, volume of milk produced per day, access to market information, access to credit and access to livestock extension. Therefore, dairy sector development programs should take in to account determinants of participation decision on milk value addition as well as on volume of milk production.

The total tree height (h) and diameter at breast height (dbh) relationship is an essential tool in forest management and planning. The height—diameter (h-dbh) relationship had been studied with several approaches and for several species worldwide. The nonlinear mixed effect modeling (NLMEM) has been extensively used and lately the resilient backpropagation artificial neural network (RBPANN) approach has been a trend topic for modeling this relationship. The artificial neural network (ANN) is a computing system based in artificial intelligence and inspired in biological neural network for supervised learning. In this study the NLMEN and RBPANN approaches were used for modeling the h—dbh relationship for Durango pine species (Pinus durangensis Martínez) in mixed-species forest from Mexico. The total dataset considered 1,000 (11,472 measured trees) randomly selected from 14,390 temporary forest inventory plots and the dataset was randomly divided into two parts; 50% for training and 50% for testing. An unsupervised clustering analysis was used to grouped the dataset into 10 clusters based on k-means clustering method and plot-variables like density, basal area, mean dbh, mean h, quadratic mean diameter, altitude and aspect. The RBPANN was performed for tangent hyperbolicus (RBPANN-tanh), softplus (RBPANN-softplus), and logistic (RBPANN-logistic) activation functions for functions in cross product of the covariate or neurons and the weights for the ANN analysis. For both training and testing, 10 classical statistics (e.g., RMSE, R2, AIC, BIC, logLik) were computed for the residual values and assess the approaches for h—dbh relationship. For training and testing, the ANNs approach outperformed the NLMEM approach, and the RBPANN-tanh has the best performance in both training and testing phases.

Keywords: Cocoa value chain; Fair trade; Chocolate; Sustainable development; SDGs

Ontological premises have profound theoretical implications. This analysis posits a single, universal structure composed of two ontic entities: discrete, quantized units of space ("Planck Spheres") and a State of Absolute Nothingness (the "SOAN"). Planck Spheres and the SOAN form a physical, ultra-high (3 x N) dimensional space ("Planck Space") and a discrete 3D space (or "4D spacetime"). Together, Planck Space and 4D spacetime form a tightly integrated ((3 x N) + 3) hyperspace (the "Dual Ontology"). Critically, a one-to-one mapping and identity exists between the Planck Spheres comprising 4D spacetime and Planck Space. The Dual Ontology conjecture supports radically simplified physical explanations for three distinct areas of theoretical physics: First, the conjecture reconciles fundamental issues in Special Relativity and quantum mechanics by explaining why single and N-body quantum states (a) dynamically evolve in 4D spacetime subject to the speed of light and (b) instantaneously collapse in a physical Planck Space that is not subject to Special Relativity. Second, the temporal and physical asymmetry between the dynamic evolution of quantum states in 4D spacetime subject to Special Relativity and the instantaneous collapse of quantum states in a Planck Space where Special Relativity is inapplicable explains quantum path irreversibility and the arrow of time. Third, at or near the heat death of 4D spacetime, the instantaneous collapse of the energy content of Planck Space and the simultaneous transition of 4D spacetime's extremely widely dispersed energy content to a non-singular, generally localized volume at t = 0 explains 4D spacetime's isotropy, homogeneity, extremely high energy, pressure, and temperature, flatness, and low gravitational entropy. It also explains the horizon and fine-tuning problems.

This mixed-methods research article explores the influence of ChatGPT, a state-of-the-art AI language model, on the development of maladaptive learning habits in users. The study combines quantitative and qualitative data to provide a comprehensive understanding of how engaging with ChatGPT may inadvertently foster detrimental learning behaviors. Findings suggest that while ChatGPT can be a valuable learning tool, it has the potential to exacerbate or create bad learning habits if not used mindfully.

New digital interventions have shown potential in managing asthma and improving patients' quality of life compared with conventional interventions. Our objective was to conduct an exhaustive survey of the application of digital health technologies in evaluating, treating, and self-managing psychological and psychopathological elements linked to asthma. We analyzed a compendium of research papers and systematic reviews pertaining to asthma, encompassing themes such as outdoor air pollution, early life wheezing disorders, atopic dermatitis, digital strategies for asthma self-management, psychiatric conditions and asthma, familial impacts on pediatric asthma, and the utilization of mobile health apps for managing asthma. We scrutinized eight chosen studies to evaluate the capacity of digital health technologies to enhance the man-agement and treatment outcomes of psychological factors related to asthma. The studies under review indicate that eHealth interventions, mixed reality instruments, mHealth technolo-gy-augmented nurse-led interventions, and smartphone apps incorporating Bluetooth-enabled sensors for asthma inhalers can markedly enhance self-management of symptoms, quality of life, and mental health outcomes, particularly in children and adolescents with asthma. Nonetheless, additional research is required to ascertain their efficacy and practicability across diverse populations and environments. Customized interventions that cater to the unique needs and preferences of asthma patients and associated psychological elements are vital to ensure the persistent and equitable adoption of these technologies. We underscore the significance of addressing psychological elements in the management and treatment of asthma and advocate for ongoing research and development in this domain.

The local and global order in dense packings of linear, semi-flexible polymers of tangent hard spheres are studied by employing extensive Monte Carlo simulations at increasing volume fractions. Chain stiffness is controlled by a tunable harmonic potential for the bending angle whose intensity dictates the rigidity of the polymer backbone as a function of the bending constant and equilibrium angle. The studied angles range from acute to obtuse ones, reaching the limit of rod-like polymers. We analyze how packing density and chain stiffness affect the ability of chains to self-organize at the local and global levels. The former corresponds to crystallinity as quantified by the Characteristic Crystallographic Element (CCE) norm descriptor, while the latter is computed through the scalar orientational order parameter. In all cases, we identify the critical volume fraction for the phase transition and gauge the established crystal morphologies, developing a complete phase diagram as a function of packing density and equilibrium bending angle. A plethora of structures is obtained, ranging from random hexagonal closed packed morphologies of mixed character and almost perfect face centered cubic (FCC) and hexagonal close-packed (HCP) crystals at the level of monomers, to nematic mesophases, with prolate and oblate mesogens at the level of chains. For rod-like chains, hysteresis is observed between the establishment of long-range nematic order and crystallization, while for right-angle chains both transitions are synchronized. A comparison is also provided against the analogous packings of monomeric and fully flexible chains of hard spheres.

Public Health Officers' (PHO) experiences in reaction to the COVID-19 pandemic can be based on whether the PHO is passive or active. Therefore, the study’s objectives are to identify the types of experiences and analyse the predictors of proactive practical experiences in solving COVID-19 among PHOs in the upper southern region of Thailand. Methods: An explanatory mixed-methods approach was used to collect data, through questionnaires and online in-depth interviews. The study was conducted from August 4, 2020, to August 3, 2021. Results: The results included 60 PHOs from 60 PCUs in 6 provinces, with 41 (68.3%) females and an average age of 35.57 years (SD = 11.61). The PHOs’ knowledge, understanding, and participation experience aspects were mostly proactive rather than passive. Factors that significantly predicted proactive practical experiences included sex (ORadj = 1.52, 95% CI = 1.04–2.21), age (ORadj = 1.69, 95% CI = 1.16-2.48), married status (ORadj = 1.69, 95% CI = 1.16-2.48), education level (ORadj = 1.50, 95% CI = 1.02–2.20), and position for work (ORadj = 1.69, 95% CI = 1.16-2.48). Conclusions: PHOs’ knowledge, understanding, opinion, and participation experiences were significant predictors of practical experience. Primary health care systems should promote proactive experiences in all four aspects to increase proactive practical experiences.

Sorption of pure CO2 and CH4 and CO2/CH4 binary gas mixtures in amorphous glassy Poly(2,6-dimethyl-1,4-phenylene) oxide (PPO) at 35°C up to 1000 Torr is investigated. Sorption experiments were carried out using an approach that combines barometry with FTIR spectroscopy in the transmission mode to quantify the sorption of pure and mixed gases in polymers. The pressure range is chosen to prevent any variation of the glassy polymer density. The solubility within the polymer of the CO2 present in the gaseous binary mixtures is practically coincident with the solubility of pure gaseous CO2, up to a total pressure of the gaseous mixtures equal to 1000 Torr and for CO2 mole fraction of ~0.5 mol mol-1 and ~0.3 mol mol-1. The Non-Equilibrium Thermodynamics for Glassy Polymers (NET-GP) modelling approach has been applied to the Non-Random Hydrogen Bonding (NRHB) lattice fluid model to fit the solubility data of pure gases. We have assumed here that no specific interactions are occurring between the matrix and the absorbed gas. The same thermodynamic approach has been then used to predict the solubility of CO2/CH4 mixed gases in PPO resulting in a deviation lower than 9.5% from the experimental results for CO2 solubility.

Supply Chain Management (SCM) encompasses a wide variety of decision-making problems that affect business and supply chain performance as a whole. Since most of these problems involve uncertainty and hesitation on the part of Decision Makers (DMs), various studies have emerged recently that present SCM applications of techniques based on Hesitant Fuzzy Linguistic Term Sets (HFLTSs) and HFLTS extensions. Given the relevance of this subject and the lack of literature review studies, this study presents a systematic review of HFLTS and HFLTS extension applications to SCM decision-making problems. In order to answer a set of research questions, the selected papers have been classified in accordance with a group of factors that are pertinent to the origins of these studies, SCM, HFLTSs, and decision-making. The results demonstrate that the Source and Enable processes have been studied with greater frequency, while the most common problems have to do with supplier selection, failure evaluation, and performance evaluation. The companies of the automotive sector and Sustainable SCM and Green SCM strategies predominate in the analyzed studies. Even though most of the studies use techniques based on HFLTSs, we have identified applications of seven distinct HFLTS extensions, with Double Hierarchy Hesitant Fuzzy Linguistic Term Sets and Probabilistic Linguistic Term Sets being the most utilized. The identification of gaps in the literature presents avenues for future studies focused on innovative applications, integrations of techniques, comparisons of techniques, group decision-making, and validation procedures for new models. The results of this study offer a panorama of the state of the art in regard to this subject and can help researchers and practitioners develop new studies which involve the use of methods that employ HFLTSs and HFLTS extensions in SCM decision-making problems.

This study presents a systematic review of the impact of Industry 4.0, digitalization, and information systems on the procurement function with a focus on the Portuguese reality. Despite global trends emphasizing digital transformation and innovation, the procurement practices in Portugal seem to lag. The adoption of cutting-edge technologies and the comprehensive integration of digital solutions within the procurement and supply chain management sector are yet to materialize fully in the Portuguese SME context. The benefits and obstacles of these technologies in transitioning procurement into a more strategic role are analyzed. By examining existing literature, critical factors for organizations to consider when implementing these technologies and the potential benefits are identified. The results indicate that digitalization has resulted in a data-driven approach to procurement, with the aid of advanced analytics and artificial intelligence for decision-making. Industry 4.0 has facilitated smarter factories, warehouses, and logistics operations with a focus on automation, connectivity, and real-time data. Procurement can more efficiently manage suppliers, track contracts, identify cost-saving opportunities, and increase sustainability with the aid of information systems. The study also highlights potential challenges for organizations. Overall, this study provides insightful findings on the role of digitalization in transforming procurement and the challenges and opportunities that organizations may face.

Insulin-degrading enzyme (IDE) is a highly conserved metalloprotease mainly localized in the cytosol. Although IDE can degrade insulin and some other low molecular weight substrates efficiently, its ubiquitous expression suggests additional functions supported by experimental findings, such as a role in stress responses, cellular protein homeostasis. Translation of full-length (Met1) IDE transcripts has reported to result in targeting to mitochondria but the role of IDE in this compartment is unknown. To obtain initial leads on the function of IDE in mitochondria, here we used a proximity biotinylation approach to identify proteins interacting with wild-type and protease-dead IDE targeted to the mitochondrial matrix. We find that mitochondrial IDE interacts strongly with mitochondrial ribosomes as well as with proteins of the respiratory chain. The mitochondrial interactomes of wild type and mutant IDE are highly similar and do not reveal any proteolytic IDE substrates. We speculate that IDE could adopt similar functions in mitochondria as in the cytosol, acting as a chaperone and contributing to protein homeostasis and stress responses.

Textile and clothing is one of the most important industrial sectors, not only due to the significant number of jobs generated, but also because it addresses one of the people’s fundamental needs (clothing). It is, however, a sector with a huge environmental impact, all over the world, and also an important social impact, especially in developing countries. Sustainability in the Textile & Clothing value chain is a known issue, concerning both environmental, and economical-social facets of sustainability. One way to improve sustainability in this sector is by measuring the environmental, economic and social impacts of value chain activities and, ultimately, computing an Environmental and Circular score for each batch of textile and clothing product, and an Economical and Social score for each involved firm, reflected in their products. The consumer will then have the opportunity and responsibility for selecting products with the least negative environmental, economical and social impact. This article presents the results of STVgoDigital project - PPS1, developed in Portugal with the aim of implementing the traceability of textile and clothing products, boosting sustainability in this sector, and preparing the ground for the implementation of the circular economy. More exactly, a blockchain-based textile and clothing value-chain traceability platform is presented, for tracing textile product lots and activities, along the value chain, classifying them with a score, which measures their environmental and social impact. The environmental, economic and social impact scores are based on a set of proposed indicators. The results are assessed through the presentation of a case study of a face towel (home textile) and a case study of a T-shirt (clothing).

Chemical exposures from diverse sources merge on a limited number of molecular pathways described as toxicity pathways. Changes in the same set of molecular pathways in different cell and tissue types may generate seemingly unrelated health conditions. Today, no approaches are available to predict in an unbiased way sensitivities of different disease states and their combinations to multichemical exposures across the exposome. We propose an inductive in-silico workflow where sensitivities of genes to chemical exposures are identified based on the overlap of existing genomic datasets, and data on sensitivities of individual genes is further used to sequentially derive predictions on sensitivities of molecular pathways, disease states, and groups of disease states (syndromes). Our analysis predicts that conditions representing the most significant public health problems are among the most sensitive to cumulative chemical exposures. These conditions include six leading types of cancer in the world (prostatic, breast, stomach, lung, colorectal neoplasms, and hepatocellular carcinoma), obesity, type 2 diabetes, non-alcoholic fatty liver disease, autistic disorder, Alzheimer's disease, hypertension, heart failure, brain and myocardial ischemia, and myocardial infarction. Overall, our predictions suggest that environmental risk factors may be underestimated for the most significant public health problems.

The Textile and Clothing (T\&C) value chain is one of the most polluting in the world and one that produces the most waste. It is, therefore, important to encourage the Circular Economy (CE) model in this sector, to reduce pollution and mitigate the effects of waste production, and consequently increase environmental sustainability. For that, the involvement of the final consumer is essential. And, the final consumer's use of an Eco-gamified application for registering and promoting Consumer-to-Consumer (C2C) and Consumer-to-Business (C2B) activities, which extends the life time of textile products, is of utmost importance. In this article, we survey gamification frameworks for analyzing system design level techniques that enable engaging the final consumer in the CE process. Then, we select and use one of such frameworks, Gameful Design Heuristics (GDH), for defining the gamification structure needed to implement on a Business-to-Consumer-to-Consumer (B2C2C) context of a circular economy. As result, we present a B2C2C circular business process model for the T\&C value chain, and propose the design model of a gamified platform for the final consumers, which allows them to register the C2B and C2C activities, from the circular value chain's business process, and benefit from a game-like experience. All model features have been mapped to GDH framework heuristics, validating that it is possible to support a set of defined heuristics of applied gamification for promoting CE in the T\&C value chain.

Docosahexaenoic acid (DHA) is an essential fatty acid (FA) with proven health effects, whom bioavailability improvement is becoming a public health issue. Unlike fish oils, the bioavailability of DHA from microalgal (A) has not been fully assessed, particularly with regard to the molecular structuring capabilities offered by A-oil. We explored the impact of 5 formulas rich in DHA, different by i) the molecular structure: ethyl ester (EE) or monoglyceride (MG) or Triglyceride (TG) and ii) the supramolecular form: emulsified TG or TG+phospholipids (blend PL), on the lymphatic kinetics of DHA absorption and the lipid characteristics of resulting lipoproteins. We demonstrated that in rat, the DHA absorption of the conventional A-DHA TG structure was more effective than the EE structure (+ 23%). More, the A-DHA MG and A-DHA Emulsion were the most favourable DHA-vectors (AUC: 89% and +42%, respectively), thanks to an improved lipolysis. The A-DHA MG and -Emulsion presented the richest DHA content in TG (+40%) and PL (+50%) of lymphatic chylomicrons, which could impact the metabolic fate of DHA. We concluded that structuring A-DHA in TG or EE would be more prone for tissue and hepatic metabolism whereas in A-DHA MG and A-DHA Emulsion could target nerve tissues.

The contemporary landscape of eHealth is characterized by major concerns related to electronic medical records (EMRs). In an EMR, critical patient health information gets its own repository, which is the core of the eHealth system. Notably, the EMR not only retrieves health information generated in ambulatory clinical settings but also includes court-generated records. These overlapping records assume the role of a foundational data source for a comprehensive electronic health record (EHR). This scholarly review sheds light on recent trends in medical records and associated challenges, while at the same time providing insights into Saudi Arabia’s targeted approaches to healthcare delivery. Additionally, the talk expands to include a description of blockchain technology and its underlying conceptual framework. This demonstration positions blockchain technology as a promising approach that requires consideration for future use in the healthcare system.

Cross-species investigations on cancer invasiveness are a new approach that identified new biomarkers potentially useful for improving tumor diagnosis and prognosis in clinical medicine and veterinary science. In this study, we combined proteomic analysis of four experimental rat malignant mesothelioma (MM) tumors with analysis of ten patient-derived cell lines to identify common features associated to mitochondrial proteome rewiring. The comparison of significant abundance changes between invasive and non-invasive rat tumors rat tumors gave a list of 433 proteins, including twenty-six proteins reported to be exclusively located in mitochondria. Next, we analyzed the differential expression of genes encoding the mitochondrial proteins of interest in five primary epithelioid and five primary sarcomatoid human MM cell lines, and the most impressive increase was observed in the expression of the long-chain acyl coenzyme A dehydrogenase (ACADL). To evaluate the role of this enzyme in the migration/invasiveness, two epithelioid and two sarcomatoid human MM cell lines derived from patients with the highest and lowest overall survival were studied. Interestingly, sarcomatoid vs epithelioid cell lines were characterized by higher migration and fatty oxidation rates, in agreement with ACADL findings. These results suggest that evaluating mitochondrial proteins in MM specimens might identify tumors with higher invasiveness.

Backyard production systems (BPS) are highly distributed in central Chile. Poultry BPS have been previously characterized; however, swine BPS have not yet been deeply characterized in central Chile. In addition, there is evidence that zoonotic pathogens, such as influenza A virus and Salmonella spp., are circulating in both poultry and pigs kept these production systems. A total of 358 BPS located in central Chile were evaluated between 2013 and 2015 by interviewing farm owners. Severe deficiencies in biosecurity measures were observed. The value chain of swine backyard production identified feeding, products and veterinary visits, and replacement or breeding animals as the main inputs to the backyard. The most common origin of swine replacements was from outside the BPS (63%). Meat and live animals (piglets and breeding animals) were identified as the main outputs of the system. In 16% of BPS, breeding animals were lent to other BPS, indicating the existence of animal and animal products movement in and out of backyard farms. Results from this study suggest that swine BPS in central Chile represent an animal-human interphase that need special attention to direct preventive measures aimed at avoiding the introduction and dissemination of animal pathogens and the emergence of zoonotic pathogens.

Keywords: Green human resource management1; Green supply chain management2; Regulation and legislation3; Sustainable development goals4.

Allergies are a common and increasing health problem affecting millions of people worldwide. In addition to genetic predisposition, this increase in allergic cases is attributed to air pollution, climate change, more time spent indoors, lack of physical activity, and alterations in eating habits. The Mediterranean diet (MD), which includes a lot of fruits and vegetables, whole grains, legumes, nuts, olive oil and fish has been linked to a variety of health benefits, including a lower risk of chronic and allergic diseases. The purpose of this paper is to explore the effects of the dietary components of the MD on food allergies. Electronic databases PubMed, Scopus, Science Direct, and EBSCO were used to conduct this systematic review up to March 2023. 696 studies were initially identified and nine were included (five human and four animal studies). The findings of this review showed an overall beneficial effect between the food components of the MD and food allergies. Although the results are promising, the limited number of studies highlights the need for more research.

Convolution forms one of the most essential operations for the FPGA-based hardware accelerator. However, the existing designs often neglect the inherent architecture of FPGA, which puts forward an austere challenge on hardware resource requirements. Even though some previous works have proposed approximate multipliers or convolution acceleration algorithms to deal with this issue, the inevitable accuracy loss and resource occupation easily lead to performance degradation. Toward this, we first propose two kinds of resource-efficient optimized accurate multipliers based on LUTs or carry chains. Then targeting FPGA-based platforms, a generic multiply-accumulate structure is constructed by directly accumulating the partial products produced by our proposed optimized radix-4 Booth multipliers without intermediate multiplication and addition results. Experimental results demonstrate that our proposed multiplier achieves a maximum 51% look-up-table (LUT) reduction compared to the Vivado area optimized multiplier IP. Furthermore, the convolutional process unit using the proposed structure achieves a 36% LUT reduction compared to existing methods. As case studies, the proposed method is applied to DCT transformer and LeNet to achieves hardware resource saving without loss of accuracy.

This research aims to explore the complex interplay between supply chain resilience (SCR), digital supply chain (DSC), and sustainability, focusing on the moderating influence of supply chain dynamism. The goal is to understand how these elements interact within the framework of contemporary supply chain management and how they collectively contribute to enhancing sustainability outcomes. The sample size is 300 CEOs and managers. The study approach integrates quantitative research methods. Structural equation modeling (SEM) is utilized to quantitatively analyze the direct and indirect effects of SCR and DSC on sustainability. The numerous surveys we conduct among supply chain ecosystem stakeholders provide a rich picture of practical implications and contextual nuances. In sum, our early findings generally support a positive relationship between SCR and sustainability in and of itself decrying the need for more resilient supply networks for sustainability. We further find the beneficial impact of digital technologies in promoting sustainability via enhancing environmental control and controlling for efficiency in supply chains. We also offer evidence to show that supply chain dynamism compounds the positive logic between SCR and DSC and sustainability. As a final word, it must be noted that our work speaks to the burgeoning Supply Chain Dynamism as moderator literature by examining the direct and contingent effects of SCR and DSC on not only performance but sustainability. By shedding light on the moderating role of dynamism, the study provides fresh insights into the multifaceted nature of supply chain management and sustainability practices. The study's findings enhance theoretical understanding by elucidating the synergistic effects of SCR, DSC, and sustainability in dynamic supply chain settings. It augments existing theoretical frameworks by integrating concepts of resilience, digitalization, and sustainability into a comprehensive model. Practical and economical, the research offers actionable guidance for organizations aiming to improve sustainability performance through resilient and digitally advanced supply chains. By acknowledging the role of supply chain dynamism, managers can tailor strategies to manage disruptions effectively and leverage digital innovations. Economically, adopting sustainable practices can result in cost savings and competitive advantages. The research emphasizes the importance of aligning supply chain strategies with sustainability goals to drive long-term value and societal impact.