Frontal Polymerization (FP) is recognized as a polymer synthesis method capable of generating a highly localized and self-propagating exothermic front, considered a more rapid and energy-efficient manufacturing scheme for polymer-based fiber-reinforced composite materials. This study conducts a numerical investigation based on the Finite Element Method into the initiation and propagation of frontal polymerization of acrylamide. Utilizing Differential Scanning Calorimetry (DSC) experiments, the study phenomenologically tests the curing kinetics reactions of acrylamide (AM) in deep eutectic solvent (DES)-based polymerizable systems, thereby establishing a curing kinetics model for the autocatalytic reaction of polyacrylamide. By coupling the heat conduction diffusion equation of the frontal polymerization reaction, the Finite Element Method is employed to solve the reaction-diffusion model, aiming to explore the evolution of temperature and degree of curing during the manufacturing process. The results demonstrate the reliability and accuracy of the nth-order autocatalytic model in the study of curing kinetics for DES-based synthesis, indicating that the front propagation speed of the AM-based FP reaction is influenced by the activation temperature, duration of activation temperature, and initial temperature of the solution. Experimental validation of the polyacrylamide manufacturing through frontal polymerization corroborates the accuracy and reliability of the model predictions, providing a reference for the numerical model study and temperature control in the synthesis of acrylamide composite hydrogels via FP.

Spermatogenesis is critical for insect reproduction and is regulated by many different genes. In this study, we found that Forkhead transcription factor Fd59a functions as a key factor in spermatogenesis of Drosophila melanogaster. Fd59a contains a conversed Forkhead domain, and it is clustered to the FoxD subfamily with other FoxD members from some insect and vertebrate species. Mutation in Fd59a caused swelling in the apical region of the testis. More importantly, only a few mature sperm were present in the seminal vesicle of Fd59a mutant flies compared to the control flies, and the fertility of Fd59a2/2 mutant males was significantly lower than that of the control flies. Immunofluorescence staining showed that the homeostasis of testis stem cell niche in Fd59a2/2 mutant and Fd59a RNAi flies was disrupted, and apoptosis of sperm bundles was increased. Furthermore, results from RNA-sequencing and qRT-PCR suggest that Fd59a can regulate expression of genes related to reproductive process and cell death. Taken together, our results indicated that Fd59a plays a key role in the spermatogenesis of Drosophila.

There is a growing trend among consumers to seek out natural foods and products with natural ingredients. This shift in consumer preferences had a direct impact on both food and pharmaceutical industries, leading to a focus of scientific research and commercial efforts to meet these new demands. The aim of this work is to review recent available scientific data on foods of interest, such as artichoke, gooseberry, and polygonoideae plants, as well as olive oil and red raspberries. Interestingly, the urgency of solutions to the climate change emergency has brought new attention to by-products of grapevine bunch stem and cane, which have been found to contain bioactive compounds with potential health benefits. There is a pressing need for a faster process of translating scientific knowledge from the laboratory to real-world applications, especially in the face of the increasing societal burden associated to non-communicable diseases (NCDs), environmental crises, the post-pandemic world, and ongoing violent conflicts around the world.

This study focuses on the potential medicinal properties of Campsis radicans L. extracts and its aim is to investigate the antioxidant and antiproliferative effects of these extracts on the human colon adenocarcinoma cell line (HT-29). Cytotoxic activity in the HT-29 cell line was evaluated, and the 3-dimensional structures of phenolic compounds were obtained using the GC-MS method. Docking simulations were performed with AutoDock Vina, targeting proteins that are crucial in the apoptotic pathway (Bax, Bcl-2, and Caspase-3). Drug similarities and ADMET estimates of the phenolic compounds were obtained from databases. The highest antioxidant activity of Campsis radicans L. plant was observed in ethanol and water extracts, with notable inhibition capacities. While the total phenolic content was highest in ethanol, water, and ether extracts respectively the total flavonoid content was highest in ethanol, then ether, and water extracts. Certain elements were undetectable in mineral determination, and others exceeded the toxic doses for plants. The water extract exhibited dose-dependent cytotoxic activity in the HT-29 cell line, with an IC50 value of 4.47 mg/mL. Molecular docking results revealed the binding of phenolic molecules to the active sites of apoptotic pathway proteins. The findings suggest that Campsis radicans L. plant possesses cytotoxic properties, significant phenolic and flavonoid content, and a high antioxidant capacity. These properties make it a potential candidate for treatment use, emphasizing its potential therapeutic value in the HT-29 cell line. Further research and exploration on the identified phenolic compounds could contribute to the development of novel therapeutic agents.

Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target the risker samples. We first apply a Naive Bayes classifier to classify data into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring the representativeness of audit evidence. The user-based approach denotes the selection of samples between two percentiles in a class as audit evidence. It may be equivalent to a combination of monetary and variable sampling methods. The item-based approach represents the choice of risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary sampling methods. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples, handling complex patterns, correlations, and unstructured data, and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.

The need to consider sustainability has substantially increased the complexity of implementing construction and infrastructure projects and new management practices have emerged during the past decade to tackle the global sustainability challenges, where the engagement and coordination of broader competences from stakeholders throughout the supply chain is required. This new project management paradigm has been accompanied by greater attention to the concept of collaborative business arrangements, often called partnering, that has emerged in construction and infrastructure projects to improve project deliveries. However, there are uncertainties about the optimal strategy to foster, integrate and maintain the required collaboration, particularly in sustainable management practices in infrastructure maintenance projects. This paper addresses these uncertainties, based on a single case study of an infrastructure maintenance contract involving an extensive collaborative business arrangement. The findings reveal that different collaborative practices affect diverse aspects of sustainable project management. Further, the extensive collaborative business arrangement has promoted sustainable deliveries based upon organizational learning and continuous improvements. Thus, this study offers an encouraging example of how extensive collaboration can be fostered and play a key role in sustainable project management practices.

ESG (Environmental, Social, and Governance) responsibility fulfillment increasingly affects enterprise valuation. Although researchers debate about the precise effects, the prevailing view suggests a linear relationship between ESG performance and enterprise value. This study introduces a novel ESG responsibility performance metric through the Regulated Intermediary Model to delve into this relationship within the Chinese context. Our findings reveal an inverted U-shaped relationship between ESG performance and enterprise value, with financing constraints having a significant moderating effect. These findings remain robust after employing instrumental variables to mitigate potential endogeneity. Heterogeneity analysis demonstrates that this inverted U-shaped relationship is particularly pronounced in non-polluting and non-state-owned enterprises. Moreover, a comparison between equity and debt financing mechanisms underscores that improved ESG performance is associated with lower cost of equity financing, thereby enhancing enterprise value. Financial institutions are encouraged to leverage innovative financial instruments to diversify enterprise financing channels and alleviate financing constraints of enterprises that fulfill their ESG responsibilities.

Blockchain technology (BCT) has the potential for sustainable development, enhancing business efficiency, reducing costs, and strengthening data security. Despite its potential, adoption among small and medium-sized enterprises (SMEs) is low due to the need for significant changes in technology infrastructure and the challenge of interoperability. A cross-sectional survey was done with 226 Hong Kong SMEs. The PLS-SEM results highlighted favorable transformation conditions as the most critical factor for SMEs considering the adoption of BCT. These conditions address both internal and external readiness for adopting the disruptive strategy. Other contributing factors to BCT adoption include trust in BCT developers, perceived usefulness and ease of use, government support, and perceived security. The research results contributed to the literature on disruptive technology acceptance, adoption, transformation conditions, technology readiness, and SMEs’ technology adoption. Government-supported policies and initiatives can promote BCT adoption, including educational programs, case studies, and resources for readiness. Financial support and regulatory frameworks can further encourage adoption. BCT developers can demonstrate the value of their systems, effectively communicate potential ROI and cost savings, and provide user-friendly interfaces to increase SMEs’ intention to adopt BCT.

Microwave technology has a potential application in the extraction of zinc from sulphide ores, knowledge of the dielectric properties of these ores plays a major role in the microwave design and simulation for any process. The dielectric properties of zinc sulfide concentrate for two different apparent densities—1.54 and 1.63 g/cm³—have been measured by using the resonance cavity perturbation technique at 915 and 2450 MHz during the roasting process for the temperature ranging from room temperature to 850 °C. The variations of dielectric constant, the dielectric loss factor, the dielectric loss tangent and the penetration depth with the temperature, frequency and apparent density have been investigated numerically. The results indicate that the dielectric constant increases as the temperature increases and temperature has a pivotal effect on the dielectric constant, while the dielectric loss factor has a complicated change and all of the temperature, frequency and apparent density have a significant impact to dielectric loss factor. Zinc sulfide concentrate is high loss material from 450 to 800 °C on the basis of theoretical analyses of dielectric loss tangent and penetration depth, its ability of absorbing microwave energy would be enhanced by increasing the apparent density as well. The experimental results also have proved that zinc sulfide concentrate is easy to be heated by microwave energy from 450 to 800 °C. In addition, the experimental date of dielectric constant and loss factor can be fitted perfectly by Boltzmann model and Gauss model, respectively.

During choriogenesis in insects, chorion (eggshell) is formed by surrounding follicular epithelial cells in ovarioles. However, the regulatory endocrine factor(s) activating choriogenesis and the chemical components on eggshell deserve further exploration. In two representative Coleopterans, a Coccinellid Henosepilachna vigintioctopunctata and a Chrysomelid Leptinotarsa decemlineata, genes encoding the 20-hydroxyecdysone (20E) receptor heterodimer, ecdysone receptor (EcR) and ultraspiracle (USP), and two chitin biosynthesis enzymes UDP-N-acetylglucosamine pyrophosphorylase (UAP) and chitin synthase (ChS1), were highly expressed in ovaries of the young females. RNA interference (RNAi)-aided knockdown of either HvEcR or Hvusp in H. vigintioctopunctata inhibited oviposition, suppressed the expression of HvChS1, and lessened the positive signal of Calcofluor staining on the chorions, which suggests the reduction of a chitin-like substance (CLS) deposited on eggshells. Similarly, RNAi of LdEcR or Ldusp in L. decemlineata constrained oviposition, decreased the expression of LdUAP1 and LdChS1, and declined CLS contents in the resultant ovaries. Knockdown of LdUAP1 or LdChS1 caused similar defective phenotypes, i.e., reduced oviposition and CLS contents in the L. decemlineata ovaries. These results, for the first time, indicate that 20E signaling activates choriogenesis in two Coleopteran species. Moreover, our findings propose the deposition of a CLS on the chorions.

Rice, as a staple crop feeding billions, faces constant threats from various diseases jeopardizing global food security. Precise understanding of disease resistance mechanisms is crucial for developing resilient rice varieties. Traditional genetic mapping methods, such as QTL mapping, provide valuable insights into the genetic basis of diseases. However, the complex nature of rice diseases demands a holistic approach to gain accurate knowledge of it. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, enable a comprehensive analysis of biological molecules, uncovering intricate molecular interactions within the rice plant. Integration of various mapping techniques using multi-omics data has revolutionized our understanding of rice disease resistance. By overlaying genetic maps with high-throughput omics datasets, researchers can pinpoint specific genes, proteins, or metabolites associated with disease resistance. This integration enhances the precision of disease-related biomarkers with better understanding of their functional roles in disease resistance. Improvement of rice breeding for disease resistance through this integration represents a significant stride in agricultural science because better understanding of the molecular intricacies and interactions underlying disease resistance architecture leads to more precise and efficient development of resilient and productive rice varieties. In this review, we explore how the integration of mapping and omics data can give a transformative impact on rice breeding for enhancing disease resistance.

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

Enterprise risk management (ERM) was introduced in the 1990s and has become an expectation by boards of directors and regulators as a sign of good management and good corporate governance. However, many organizations struggle to implement ERM, and still seek practical ad-vice on ERM implementation. This article explains many of the reasons why organizations are unsuccessful in their efforts at implementation and provides practical solutions by an experienced risk manager and consultant, an ex-Chief Risk Officer, and an academic, all who has writ-ten extensively in the subject. This article should be of interest to practitioners involved in implementing ERM, to consultants in ERM, and to academics teaching courses on ERM, risk management, and related topics. This article also provides a base against which further future re-search can be done as ERM best practices continue to evolve.

With the development of big data analysis, blockchain and other technologies, the supply chain of enterprises is transforming to lean and intelligent. As an important link in the enterprise supply chain, the intelligent transformation of procurement plays an important role in the improvement of the supply chain efficiency, therefore, the construction of a common method supporting the intelligent upgrade of the enterprise procurement business has become a key concern for enterprise managers. Based on the balanced scorecard theory and the supply chain maturity model, this study combines the actual situation of procurement management in Chinese energy enterprises and constructs a procurement benchmarking system that balances the development direction of the industry and the actual needs of enterprises. Meanwhile, based on the grounded theory, three major themes of the intelligent procurement system (digital business module, procurement synergy mechanism and procurement ecosystem) are extracted to provide a methodological reference for the construction of intelligent procurement systems of energy enterprises. The study concludes with a case study of China National Energy Group Materials Company to demonstrate the application of the intelligent procurement system built in this paper, with a view to providing methodological reference for the intelligent procurement management in energy enterprises.

Robotic systems have been widely used in various industries, so the security of communication between robots and their components has become an issue that needs to be focused on. As a framework for developing robotic systems, the security of ROS2 can directly affect the security of the upper-level robotic systems. Therefore, it is a worthwhile research topic to detect and analyze the security of ROS2. In this paper, we adopt a formal approach to analyze the security of the communication mechanism of ROS2. First, we use a state transition system to model the potential vulnerabilities of ROS2 based on the ROS2 communication mechanism and the basic process of penetration testing. Secondly, we introduce the CIA model on the basis of the established vulnerability model and use LTL to define its security properties. Then, we design and implement a vulnerability detection tool for ROS2 applications based on the vulnerability model and security properties. Finally, we experimentally test some ROS2-based applications, and the results show that ROS2 has vulnerabilities without additional protection safeguards.

A systematic and comprehensive review of critical applications of Blockchain Technol-ogy with Differential Privacy integration lies within the privacy and security enhancement. This paper aims to highlight the research issues in the e-health domain (e.g., Electronic Medical Rec-ords) and to review the current research directions in Differential Privacy integration with Blockchain Technology.(1) Background: The current state of the art in the e-health domain is identified as follows: (a) healthcare information poses a high level of security and privacy concerns due to its sensitivity; (b) due to vulnerabilities surrounding the healthcare system, a data breach is common and presents a risk for attacks by an adversary; and (c) the current privacy and security apparatus needs further fortification. (2) Methods: The methodology uses a systematic literature review (SLR) to identify and select relevant research papers and academic journals in DP and BT. (3) Results: The results are categorized into: e-Health Record Privacy, Real-Time Health Data, and Health Survey Data Protection to identify inherent issues with Differential Privacy integra-tion with Blockchain and technical challenges.(4) Conclusion: This review thoroughly surveyed and summarized Differential Privacy mechanisms in EMR privacy, real-time health data, and health survey data protection while highlighting challenges.

In recent years, Web APIs have become a de facto standard for exchanging machine-readable data on the Web. Despite this success though, they often fail in making resource descriptions interoperable due to the fact that they rely on proprietary vocabularies that lack formal semantics. The Linked Data principles similarly seek the massive publication of data on the Web, yet with the specific goal of ensuring semantic interoperability. Given their complementary goals, it is commonly admitted that cross-fertilization could stem from the automatic combination of Linked Data and Web APIs. Towards this goal, in this paper we leverage the micro-service architectural principles to define a SPARQL Micro-Service architecture, aimed at querying Web APIs using SPARQL. A SPARQL micro-service is a lightweight SPARQL endpoint that provides access to a small, resource-centric, virtual graph. In this context, we argue that full SPARQL Query expressiveness can be supported efficiently without jeopardizing servers availability. Furthermore, we demonstrate how this architecture can be used to dynamically assign dereferenceable URIs to Web API resources that do not have URIs beforehand, thus literally ``bringing'' Web APIs into the Web of Data. We believe that the emergence of an ecosystem of SPARQL micro-services published by independent providers would enable Linked Data-based applications to easily glean pieces of data from a wealth of distributed, scalable and reliable services. We describe a working prototype implementation and we finally illustrate the use of SPARQL micro-services in the context of two real-life use cases related to the biodiversity domain, developed in collaboration with the French National Museum of Natural History.

In recent decades, as eutrophication in inland and coastal waters (ICWs) has increased due to anthropogenic activities and global warming, so has the need for timely monitoring. Compared with traditional sampling and laboratory analysis methods, satellite remote sensing technology can provide macro-scale, low-cost, and near real-time water quality monitoring services. The Geostationary Ocean Color Imager (GOCI), integrated onboard the Communication Ocean and Meteorological Satellite (COMS) from the Republic of Korea, was the first geostationary ocean color observation satellite and was operational from April 1, 2011 to March 31, 2021. Over ten years, GOCI has observed oceans, coastal waters, and inland waters within its 2,500 km×2,500 km target area centered on the Korean Peninsula. The most attractive feature of GOCI, compared with other commonly used watercolor sensors, was its high temporal resolution (1h, eight times daily from 0 UTC to 7 UTC), providing the opportunity to monitor the quality of ICWs, where optical properties can change rapidly throughout the day. This systematic review aims to comprehensively review GOCI features and applications in ICWs, analyzing progress in atmospheric correction algorithms and water quality monitoring. Analyzing 123 articles from the Web of Science and China National Knowledge Infrastructure (CNKI) through a bibliometric quantitative approach, we examined GOCI’s strength and performance with different processing methods. These articles reveal that GOCI played an essential role in monitoring the ecological health of ICWs in its observation area in East Asia. GOCI has led the way to a new era of geostationary ocean satellites, providing new technical means for monitoring water quality in oceans, coastal zones, and inland lakes. We also discuss the challenges encountered by geostationary satellites in monitoring water quality and provide suggestions for improvements.

The objective of this study was to carry out the extraction and characterization of chitin and chitosan from the exoskeletons of the Farfantepenaeus californiensis species of shrimp, as well as its application in the formulation of polymeric films plasticized with glycerol used in the process of food packaging. The characterization of the extracted polymer was made by Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and physicochemical analysis of chitin and chitosan, resulting in a theoretical performance of 29.33% and 16.46%, respectively. In terms of quality, it was determined that the extracted chitosan had a molecular weight of 1.10 x105 g/mol and a deacetylation degree of 80.23%, which classifies it as a low-molecular weight chitosan, suitable for food packaging. It was shown that the extracted chitosan is fit for the production of the films by using the casting method, presenting a tension resistance of 1 MPa. The Antibacterial analysis was carried out using Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli), bacterial models commonly found in food. The results showed an effective inhibition capability of the polymeric materials. Overall, the results for both chitosan and the films indicate a high potential for application in the food packaging sector.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

In response to the fire protection design challenges faced by the integrated station-city engineering under the new model of station-city fusion, such as large building volume, diverse traffic types, functional integration, spatial complexity, and inapplicable standards, this paper selects Chongqing East Station as a typical engineering case. The fire safety engineering methods and performance-based fire protection design ideas were used. The paper summarized the fire protection difficulties, such as multifunctional combination construction, large fire protection distance, large fire protection zoning area, long evacuation distance, and design of evacuation (quasi) safety zones. Combining with the actual situation of the engineering, this paper analyzed the basic technical measures taken to address these design challenges. By adopting the method of fire safety engineering, the safety of the design scheme is verified, which can provide a solution approach for the current fire protection design challenges in the integrated station-city engineering.

This study delves into the critical domain of public procurement, specifically focusing on Sustainable Public Procurement (SPP) and Environmental, Social, and Governance (ESG) considerations within the context of South Korea. The aim of this research is to empirically scrutinize the factors influencing the impact index of SPP, with a particular emphasis on services related to labor standards. The investigation spans three years, from January 1, 2019, to July 31, 2021, encompassing state agency orders and post-implementation legal changes. Leveraging the comprehensive Korea On-line E-Procurement Sys-tem(KONEPS) platform, we meticulously collected data, ultimately culminating in 21,573 services meeting our criteria, from which 250 cases underwent an in-depth analysis. The study sheds light on the influence of social responsibility evaluation cri-teria on overall procurement scores, while also uncovering the moderating effects of various factors. The outcomes of this study offer valuable insights into the impact index of social responsibility evaluation criteria within South Korea's public procurement landscape. Factors including procurement year, classification, service period, and estimated price were identified as significant influencers. Moreover, the number and location of evalu-ation criteria items, inclusion of sincerity elements, and the evaluating agency were deemed pivotal determinants of the influence index. These findings hold profound implications for policymakers, procurement practitioners, and researchers and provide a roadmap for optimizing the utilization of social responsibility evaluation criteria to advance responsible and sustainable procurement practices. Future research avenues include conducting further study of additional moderat-ing variables, expanding datasets to encompass a broader spectrum of procurement contexts, and evaluating the long-term repercussions of social responsibility evaluation on procurement outcomes. These endeavors promise to further refine and advance public procurement practices in South Korea and beyond.

One way to reduce the negative impact of human activity on the natural environment is to use natural, easily available and relatively cheap to produce compounds in industrial processes. One such compound is naturally occurring calcium carbonate (CaCO3). This compound has adsorption properties so that it can be an alternative to commonly used adsorbents. The aim of this work is to determine the possibility of using CaCO3 to remove pharmaceutical substances such as sulfadiazine and tetracycline from water. The CaCO3 used in this work was synthesised using our own method, which allows the production of CaCO3 particles with nanometric size. In the conducted research, calcium carbonate was used in the form of a suspension in purified solutions and as an inorganic filling of the developed membranes. The mass of pharmaceutical substances removed from their aqueous solutions was determined in the tests carried out. Based on the results obtained, it can be concluded that CaCO3 has the ability to adsorb both tetracycline and sulfadiazine. In suspension tests, the mass of the removed substances per unit mass of adsorbent was 1.52 mg/g and 6.85 mg/g, respectively. In turn, in the case of the process using the developed membranes, the mass of the removed substances per unit mass of adsorbent was 232 mg/m2 and 524 mg/g, which is a several times greater increase in the mass of the removed substance compared to the process using an unmodified membrane.

Sensory integration is an essential function of human life, and its decline causes difficulties in the quality of life, especially in older adults. In this study, we proposed an arm-reaching task based on a virtual reality head-mounted display (VR-HMD) system to assess sensory integration in daily life, and examined whether reaching task performance was associated with age and resting-state functional connectivity (rsFC) between the brain regions of interest involved in sensory integration. We hypothesized that performance during a reaching task with multiple cognitive loadings would be affected by aging. The gap angle between the reaching hand and target positions was compared between older and middle-aged adults as a measure of sensory integration function. In addition, rsFC, which was significantly correlated with the gap angles of individual participants in the older adult group, was identified using resting-state functional magnetic resonance imaging data. The mean gap angle was significantly larger in the older adults than in the middle-aged group and was also significantly correlated with connections between the left primary motor area and the left inferior temporal gyrus, temporo-occipital part. Because the connectivity between the areas is known to be related to visuomotor integration, the results suggest the involvement of visuomotor integration in the decline of sensory integration function in old age and the validity of the gap angle during the proposed VR-HMD task as an index for the decline in function.

Surface initiated atom transfer radical polymerization (SI-ATRP) is one of the most versatile technique to modify the surface properties of material. Recent developed metal free SI-ATRP makes such technique more widely applicable. Herein photo-induced metal-free SI-ATRP of methacrylates, such as methyl methacrylate, N-isopropanyl acrylamide, and N,N- dimethylaminoethyl methacrylate, on the surface of SBA-15 was reported to fabricate organic-inorganic hybrid materials. SBA-15 based polymeric composite with adjustable graft ratio was obtained. The structure evolution during the SI-ATRP modification of SBA-15 was monitored and verified by FT-IR, XPS, TGA, BET, and TEM. The obtained polymeric composite showed enhanced adsorption ability for the model compound toluene in aqueous. This procedure provides a low cost, ready availability, and facile modification way to synthesize the polymeric composites without the contamination of metal.

The effective Supervisory Control and Data Acquisition (SCADA) system can improve the reliability, safety and economic benefits of microgrid operation. In this research, the lower central controller and upper WEB monitoring system are connected by the SCADA system which is as the hub of microgrid intelligent monitoring platform. This system contains a set of specific functions programmed by Java as a middleware which can provide control and communication between the central controller and the upper monitoring system. The system realizes the real-time data acquisition and storage, the control instructions parsing and transmitting, the microgrid security and stability, the load balancing and resource recovery of the microgrid. All that functions have been tested and verified in the actual operation.

With the development of organizational biology and forced from the EU Cosmetic Regulation (EU/1223/2009) with the complete ban of animal testing for cosmetic purposes, 3D skin models have been widely developed due to their similar physiological structure and metabolic function to native human tissue. 3D skin models for in vitro cosmetic evaluation are still promising alternative methods for evaluating phototoxicity, corrosivity and irritation. These models have been used for early screening and later validation of toxicity and efficacy evaluation by many well-known cosmetic companies. 3D skin models have become an important tool in cosmetic evaluation research. This article reviews the development of 3D skin models and their application in cosmetic evaluation. An outlook on the current application and future technological development directions in the cosmetic field is also presented.

This paper describes the first results of an Image Recognition Based Location (IRBL) for mobile application focusing on the procedure to generate a Database of range images (RGB-D). In an indoor environment, to estimate the camera position and orientation, a prior spatial knowledge of the surrounding is needed. In order to achieve this objective a complete 3D survey of two different environment (Bangbae metro station of Seoul and E.T.R.I. building in Daejeon – Republic of Korea) was performed using LiDAR (Light Detection And Ranging) instrument and the obtained scans were processed in order to obtain a spatial model of the environments. From this, two databases of reference images were generated using a specific software realized by the Geomatics group of Politecnico di Torino (ScanToRGBDImage). This tool allow to generate synthetically different RGB-D images) centered in the each scan position in the environment. Later, the external parameters (X, Y, Z, ω, φ, κ) and the range information extracted from the DB images retrieved, are used as reference information for pose estimation of a set of acquired mobile pictures in the IRBL procedure. In this paper the survey operations, the approach for generating the RGB-D images and the IRB strategy are reported. Finally the analysis of the results and the validation test are described.

Reducing the hardness of hard water is of great concern nowadays due to some adverse effects on water pipes, boilers and soap consumption. Using the method of biomineralization to precipitate calcium and magnesium ions to become carbonate minerals was one of the most important innovations for reducing the hardness of hard water. The present study sought to explore the physical and chemical conditions of carbonates bio-precipitation and the potential use of Bacillus licheniformis SRB2 strain (GenBank: KM884945.1) isolated from sludge sample of Moshui River (Shandong University of Science and Technology, Qingdao, China) in reducing the hardness of hard waters by the induction of carbonate minerals. In this study, B. licheniformis SRB2 strain was identified based on the morphological, biochemical and 16S rDNA gene sequence homology analysis. The carbonate minerals induced by B. licheniformis bacteria in the liquid culture medium with 3% NaCl and Mg/Ca molar ratio of 0, 6, 8, 10 and 12 were investigated. The culture medium was inoculated with the bacterial liquid seed was set as the experimental group and the other culture medium was inoculated with the same volume of distilled water was set as the control group. The mineral phases, micromorphologies, and crystal structures were analyzed using X-ray powder diffraction, scanning electron microscope, energy dispersive X-ray detector, high resolution transmission electron microscopy and selected area electron diffraction. The bacterial concentrations and pH values of the solution were measured by a spectrophotometer and a pH meter, respectively. The urease secreted by B. licheniformis SRB2 was found to greatly increase the pH values of the liquid medium, which favored the formation of calcium carbonate.As a result, Mg²⁺ and Ca²⁺ ion concentrations decreased greatly due to the biomineralization of calcium carbonate and nesquehonite minerals in the presence of B. licheniformis SRB2 bacterium. There were only few calcium carbonates and no nesquehonite minerals in the control groups. It was also found that the minerals of nesquehonite induced by B. licheniformis SRB2 had a phenomenon of preferred orientation. What was more, even though Mg²⁺ ions inhibited the precipitation of Ca²⁺ ions, but under the action of B. licheniformis SRB2 bacteria, the inhibition effect was significantly declined. The bio-precipitation of calcium carbonate and nesquehonite minerals may represent a new method of pretreatment for the hardness reduction of hard water. The accomplished study is of certain interest for interpretation of the carbonates biomineralization in natural environment, and maybe also has a certain application value in the former processing of hard water

Accelerating the green transformation of the economic development mode and promoting high-quality economic development is an international trend and the general direction. This article utilizes data from manufacturing companies listed on the Shanghai and Shenzhen stock exchanges from 2011 to 2021, based on dynamic capability theory, to explore the impact of enterprise digital transformation on green technological innovation. Furthermore, dynamic capabilities are further subdivided into absorptive capacity, innovative capacity, and adaptive capacity to investigate their mediating role. The research findings demonstrate that enterprise digital transformation has a significant positive impact on green technological innovation. Moreover, enterprise digital transformation positively influences the absorptive capacity, innovative capacity, and adaptive capacity, with these three factors playing a mediating role in the impact of enterprise digital transformation on green technological innovation. The results of the bootstrap test confirm this mediating effect. The conclusions of this study are validated through a series of robustness tests. This research not only provides theoretical support for the impact mechanism of digital transformation on green technological innovation but also offers practical insights for enterprises to achieve sustainable development.

The work safety standardization of enterprises based on the traditional work safety theory has played a significant role in reducing the number of accidents and improving work safety to some extent in China. However, some problems are coming with the work safety standardization of enterprises developing constantly in China. On the one hand, it is not combined with the actual situation of the enterprise, lacking pertinence and specificity, these defects resulted that it is not integrated with original safety production management system of enterprise and make it difficult to carry out. On the other hand, there is a lack of systematic management methods for the work safety management system of enterprise, most of enterprises only pay attention to the inspection result rather than the process control. This means after the check of the government, many enterprises will relax to carry out the system. This paper puts forward a new method for optimizing the standardization management mode of work safety based on the Viable System Model(VSM), which can solve the defects of work safety standardization of enterprises management system. An optimization model of work safety standardization based on VSM was construct for explaining the process optimization and control of work safety standardization management. It can improve the connectivity between the enterprise and the government. The conclusion of this paper can provide reference for achieving the development and optimization of work safety standardization of enterprises in China.

Product innovation is a crucial factor in enterprise survival. Even though there are sources from strategic theory that guides the clear comprehension towards appreciating the nexus between these two variables (product innovation and enterprise survival), there are still many lacunas that should be addressed and filled. Consequently, the need for additional empirical corroboration or support is pertinent. This study aimed at verifying the nexus between product innovation and enterprise survival, and how they are affected by the existence of antecedent variables such as competitive intensity and competitive advantage. In the methodology, this study adopts the conduct of explanatory and cross-sectional investigations through the use of structural equation modelling (SEM) to a sample of selected food and beverages enterprises in Lagos, Nigeria. Regarding the food and beverage enterprises in Lagos, Nigeria, this study discovered that competitive intensity has huge positive implication on product innovation at (0.39; t = 5.69, p < 0.05). This gives numerical evidence that, in the face of more market competition, enterprises will be pressured to adopt the model of costs reduction on products which will enhance the reduction of product prices, and will have significant impact on profit. However, the findings reveal that there is no significance between competitive advantage and product innovation at (0.002; t = 0.203, p > 0.05), and there is no significance between product innovation and enterprise survival at (-0.035; t = -1.583, p > .05). As a result, the food and beverage enterprises should concentrate more on product innovation so that they will be able to stand the intensity of competition. The results emanated from the study is germane as it make significant contribution to literature and the body of knowledge and on strategic management by enlightening that competitive intensity is a necessary inducement for product innovation.

In the world's first pig-to-human cardiac xenotransplant, the elevated levels of porcine cytomeg-alovirus (PCMV) are considered key factors contributing to patient mortality. This has renewed attention to PCMV, a virus widely prevalent in pigs. Currently, there are no effective drugs or vaccines targeting PCMV, and its high detection difficulty poses challenges for prevention and control research. In this study, antiviral small hairpin RNA (shRNA) was selected and inserted into the Rosa26 and miR-17-92 loci of pigs via a CRISPR/Cas9-mediated knock-in strategy. Further in vitro viral challenge experiments demonstrated that these genetically edited pig cells could effec-tively limit PCMV replication. Through this process, we constructed a PCMV-infected cell model, validated partial viral interference sites, enhanced gene knock-in efficiency, performed gene editing at two different gene loci, and ultimately demonstrated that RNA interference (RNAi) technology combined with CRISPR/Cas9 has the potential to generate pig cells with enhanced antiviral infec-tion capabilities. This opens up possibilities for the future production of pig populations with anti-viral functionalities.

Technology has transformed aeroponics, providing numerous advantages over traditional soil-based agriculture. However, there remains a need for comprehensive information on the types of technology employed in aeroponics and their impact on the growing process. This paper presents a literature review of 47 studies published between 2012 and 2023 in peer-reviewed journals and conference proceedings. As a result, it identifies the status and tendencies in the usage of technology in aeroponics as well as the main opportunities and challenges. Furthermore, this paper introduces the Technology Adoption and Integration in Sustainable Agriculture (TAISA) model. TAISA is a model that identifies the degree of technology integration in any sustainable agriculture system to determine how technology affects production and quality. Overall, the systematic review suggests that technology can play a vital role in improving the efficiency and sustainability of aeroponic farming. However, careful consideration must be given to the costs and technical requirements associated with using these technologies. Moreover, the TAISA model reveals that technology has primarily been employed in creating new processes that are not possible to implement without the help of technology. Therefore, we conclude that technology use has taken root in aeroponics and can be promoted to improve sustainable agriculture.

The purpose of this paper is to explore the implementation of Retrieval-Augmented Gen- 14 eration (RAG) technology with open-source Large Language Models (LLMs). For this purpose, a 15 web-based application named PaSSER that integrates RAG with three models - Mistral:7b, 16 Llama2:7b: Orca2:7b, is developed. In its development various technologies are used, including 17 Blockchain for managing and storing assessment results of built-in testing modules. PaSSER em- 18 ploys a set of evaluation metrics for LLMs’ performance - METEOR, ROUGE, BLEU, Perplexity, 19 Cosine similarity, Pearson correlation, and F1 score. The specialized knowledge base is in the smart 20 agriculture domain. As an illustration, the paper presents results and analysis of two tests. First one 21 is assessing the performance of LLMs across different hardware configurations, the other is deter- 22 mining the model that delivers most accurate and contextually relevant responses within the RAG. 23 The paper also discusses the integration of blockchain technology with LLMs to manage and store 24 assessment results within a blockchain environment. The tests revealed that Mistral:7b demon- 25 strates the best results across most of the evaluated metrics. The discussion section comments on 26 technical and hardware considerations that affect the performance of LLMs. Future development 27 will focus in leveraging new larger pre-trained open-source LLMs, exploring different finetuning 28 approaches, and further integration with Blockchain and IPFS.

Cloud computing refers to applications delivered as services over the Internet. Cloud systems employ policies that are inherently dynamic in nature and that depend on temporal conditions defined in terms of external events, such as the measurement of bandwidth, use of hosts, intrusion detection or specific time events. In this paper, we investigate an optimized resource management scheme named v-Mapper. The basic premise of v-Mapper is to exploit application-awareness concepts using software-defined networking (SDN) features. This paper makes three key contributions to the field: (1) We propose a virtual machine (VM) placement scheme that can effectively mitigate the VM placement issues for data-intensive applications; (2) We propose a validation scheme that will ensure that a service is entertained only if there are sufficient resources available for its execution and (3) We present a scheduling policy that aims to eliminate network load constraints. An evaluation was carried out with various benchmarks and demonstrated that v-Mapper shows improved performance over other state-of-the-art approaches in terms of average task completion time, service delay time and bandwidth utilization. Given the growing importance of supporting large-scale data processing and analysis in datacentres, the v-Mapper system has the potential to make a positive impact in improving datacentre performance in the future.

In this paper we investigate into the possible resurrection for the aether and it’s compatibility with the theory of relativity. We revisit the Michelson-Morley experiment and expose some of the major inadequacies. In this regard, we have presented the true/corrected form of the Michelson-Morley experiment. We have tried to revise the interpretational aspect of the mathematical formalism regarding the metric of Minkowskian space-time in addendum with it’s relationship to the two theories of time. We herein have also tried to restrain some of the quantum mechanical issues arising from the mainstream understanding of the mathematical formalism of the Minkowskian manifold. Essentially, we have argued in favour of aether to be incorporated into our mathematical formalism as well the physical understanding of the universe.

This paper presents a study about the integration of Piezoelectric Energy Harvesting Systems (PE-EHS) in building envelopes for powering Fiber Bragg Grating (FBG) sensors, enabling efficient and low-consumption monitoring with the objective to leverage Structural Health Monitoring (SHM). The research includes preliminary tests conducted in a real environment to validate the PE-EHS when fully integrated into the façade, capturing mechanical vibrations generated mainly by wind loads. Based on these activities, the final configuration of PE-EHS is defined to provide a complete system for façade monitoring. This integrated system includes the Piezoelectric Generator (PEG), Supercapacitor (SC), Power Conditioner Circuit (PCC), Fibre Optic Sensing (FOS) Interrogator, and the IoT Gateway trans-mitting measurement data within an Internet of Things (IoT) monitoring platform. This configuration is tailored to address the challenges related to the structural integrity of building envelopes. Results demonstrate a potential for a stand-alone solution in the façade sector, but, raising issues for certain limitations, requiring further investigation. In particular, the study emphasizes constraints related to the energy production of PE-EHS for façade integration. It highlights the necessity to carefully consider these limitations within the broader context of their applicability, providing insights for the informed deployment of Piezoelectric Energy Harvesting technology in building envelope monitoring.

This study examines the impact of GenAI tools on the daily tasks of designers within corporations. It investigates both the operational changes and employee anxieties regarding job security. The research employs a qualitative approach: one without the use of ChatGPT and one with its use. The findings indicate significant improvements in operational experience and subjective perceptions across various tasks, as demonstrated through a user experience map. Moreover, the study highlights the potential of AI for enhancing managerial efficiency, streamlining workflows, and improving collaboration. However, it also addresses challenges concerning information authenticity, copyright protection, and professional identity. The goal of this study is to comprehend AI's current role in businesses, evaluate its effects on designers, and offer balanced recommendations that emphasize the integration of AI thinking into future corporate workflows from a human-centric perspective.

Despite being under development for decades, RNA therapeutics have only recently emerged as viable platform technologies. The COVID-19 mRNA vaccines have demonstrated the promise and power of the platform technology. In response, novel RNA drugs are entering clinical trials at an accelerating rate. As the skin is the largest and most accessible organ, it has always been a preferred target for drug discovery. This holds true for RNA therapies as well, and multiple candidate RNA-based drugs are currently in development for an array of skin conditions. In this mini review, we catalog the RNA therapies currently in clinical trials for different dermatological diseases. We summarize the main types of RNA-related drugs and use examples of drugs currently in development to illustrate their key mechanism of action.

Human longevity is an important but difficult goal due to the extreme complication of human body. If people could repeatedly transfer their consciousness from old bodies to new ones, their lifespan might be prolonged extremely. However, there are several difficulties which prevent the achievement of such a technique. In this paper, we propose an approach that can transfer human consciousness indirectly, and avoid or significantly relieve those difficulties. The strategy of our approach is to integrate the consciousnesses of two bodies (old and new) into a unique consciousness. By doing so, the consciousness is extended to the new body. After that, the consciousness shrinks and remains in the new body when the old body dies. This may also apply to integrating more than two bodies of human, or animal, or even across different species. After investigating thousands of literatures, we find quite strong evidence (related discoveries and technologies) that can support the proposed approach and its advantages. Beside prolonging human lifespan, the approach could also have other meaningful applications.

Intelligent systems are increasingly present in various areas of society, gaining special relevance in healthcare environments. In this work, grounded on previous developments proposed by the authors, the evolution and improvement of a novel intelligent system focused on the diagnosis of obstructive sleep apnea (OSA) is addressed. To do this, starting from two packages of information of a heterogeneous nature, and deploying a set of Machine Learning classification algorithms, focused each of them on different levels of the apnea-hypopnea index (AHI), as well as a set of cascaded expert systems, it is possible to obtain a series of risk metric pairs (Statistical Risk, Symbolic Risk) for each AHI level, understood as a warning forecast associated with the early detection of the pathology. The risk indicators of each pair are subsequently aggregated by means of a symbolic inference system, whose knowledge base was determined using the automatic rule generation approach proposed by Wang and Mendel. At the output of each inference system, a risk indicator is obtained for each AHI level, the Apnea Risk, whose interpretation makes it possible to discriminate between patients who could suffer OSA and those who do not, as well as to generate the appropriate recommendations. For the initial tests of the system, the design and development of a specific software artifact was carried out using data from 4,400 patients from the Álvaro Cunqueiro Hospital in Vigo, obtaining when applied to the test set AUC values within the range 0.74–0.88, which invites optimism and points to the benefits expected from the architecture of the proposed intelligent system.

This paper studies the duration patterns of unemployment spells for immigrants and the determinants of unemployment’s completion into one of a number of studied labour market states in Finland. We estimate a duration model for unemployment with competing risks of its terminating into employment, labour market training or economic inactivity. Taking into account the wide period of observation and opportunities to analyse processes of labour market integration during various periods of economic development in Finland, in combination with the individualistic character of the labour careers of immigrants, this research is beneficial owing to the many various findings concerning labour market integration of immigrants. The approach undertaken in this research has a dualistic “descriptive-dynamic” character under which integration is understood as a never-ending process, which is conditioned by a time period of long-term existence and a context of solitary action. We find that transitions out of unemployment spells have a cyclical character; after every new “cycle” in unemployment, the probability of terminating unemployment decreases further. We also find that ascriptive factors make sense in the process of job-placement of immigrants from unemployment. Therefore, the gender, education and age of immigrants, as well as the effect of the period in which first unemployment occurred, potentially predict transitions out of unemployment and further labour market integration of immigrants.

Shear dynamics simulation under extreme pressure was used to optimise the composition of ester-based lubricant base oil and extreme pressure additives. As a result, the ester-based lubricant in the weak-gel drilling fluid achieves reduction and increases the efficiency in drilling construction, and the field operation efficiency improves. The results of base oil lubrication simulation show that three base oils, namely, methyl oleate, ethyl oleate and butyl oleate, can be stably adsorbed on the surface layer of the shear surface. Methyl oleate has the lowest system temperature after shear stabilisation and has a high load-bearing capacity. The shear stress of methyl oleate decreases by changing the initial shear temperature and speed. It increases by 6.36 MPa when the speed increases from 10 m/s to 30 m/s. At this time, the shear stress of butyl oleate increases by 10.11 MPa. The results of the four-ball friction experiments show that the radius of the abrasion spot of methyl oleate is 179.83 μm, which is smaller than that of the other two base oils. Moreover, the friction coefficient of methyl oleate is 0.0018, which is approximately 1/3 of that of butyl oleate. Methyl oleate has better lubrication efficiency. The shear simulation results are consistent with the experimental results. The simulation can be used for the molecular design of lubricant materials. The oleic acid amide–containing amine group and the glyceride oleic–containing hydroxyl group were selected as the extreme pressure functional components for shear simulation. Results show that the shear stress of oleic acid amide is much lower than that of oleic acid glyceride when the initial shear temperature and speed change. The extreme pressure lubrication component–containing amine group is better than the extreme pressure lubrication material–containing hydroxyl group. The effects of different oleamide contents in the two-component mixtures on the lubricating properties were investigated through shear simulation, with methyl oleate as the base oil and oleamide as the extreme pressure functional component. The simulation results show that the lubricant has the optimal shear stress when 10% oleamide is added to the lubricant. The base properties of the lubricant were tested using a mixture of 90% methyl oleate and 10% oleamide, formulated as a lubricant. Results show that the friction coefficient can be reduced to 0.03 when 0.5% of the lubricant is added to the base mud. Moreover, the lubricant film formed shows high strength. Then, 1% lubricant was added to the weak-gel drilling fluid to evaluate the effect of the lubricant on the gel structure of the drilling fluid. Results show that adding lubricant does not affect the rheological properties of the drilling fluid. The gel structure of the system also remains stable even after 7 days of continuous ageing. The results of the field experiments in Hua3-01 well show that adding 1% ester-based lubricant to the field drilling fluid reduces the drilling friction by 33%. Thus, the efficiency of directional side drilling can be effectively improved, complicated accidents, such as poor starting and stopping of drilling and stuck jamming, can be avoided, and the goals of reducing quantity and increasing efficiency can be completed.

Field of ResearchThis research study investigates the role of distributed leadership and culture within small enterprises in Malta, an area in which there has been very limited research. It focuses on the interaction between these two elements and their impact on organizational behaviour and effectiveness. Several studies (Jardon et al 2019; Cope et al., 2011; de Oliveira et al., 2015; Mohanty et al., 2012;) suggest that effective leadership and culture are vital elements in the successful endeavours of small organizations. Schein (2006) further asserts that they are two different faces on the same coin and the dyadic interaction characterizes “how leaders create culture and how culture defines and creates leaders”. Distributed Leadership is a systematic practice of interactions and synergies between leaders, followers, and the situation (Spillane 2013). It is different from traditional leadership, which involves top-down management because it tends to be more democratic and participatory, whereby influence and decision-making are shared among multiple individuals rather than being controlled by a single leader. (Xhemajli et al. 2022) MethodologyAdopting a naturalistic approach and guided by an interpretivist, constructivist epistemological stance, this research delves into the intricate interplay between leadership and culture within small businesses. The chosen research methodology employs Grounded Theory, recognized for its robust and systematic process facilitating the observation of patterns through intensive iterative and highly analytical procedures (Charmaz, 2015).In the initial stages of field research, characterized by 'responsive interviewing' (Rubin and Rubin, 2012), data sampling commenced with convenience sampling. This initial phase gradually evolved into a refined strategy incorporating selective sampling and theoretical sampling (Corbin and Strauss, 2015). The shift in sampling approaches reflects a deliberate focus on collecting data based on its specific contribution to the development and comprehension of the dimensions, properties, and characteristics of key concepts.The induction of theory is a product of successive comparative analyses, involving the systematic comparison of data points to identify both similarities and variations. Abductive reasoning is integral throughout the analytical process, with particular emphasis during constant comparative analysis of categories, leading to theoretical integration (Charmaz, 2006). This meticulous approach aligns with the assertion of Strauss and Corbin (2015) that grounding theory in data enhances the likelihood of deriving theories that authentically reflect reality.The key advantage of using this approach is that the analysis carried out goes beyond deep exploration and rich description and actually develops a framework that explains the phenomena observed (Parker and Roffey, 1997, p.218). This is very important if the findings are to contribute to the knowledge enhancement of any field of practiceThe culmination of this research effort is the presentation of a set of interconnected concepts, intricately woven together into an emergent parsimonious model (Corbin and Strauss, 2015). This model serves to explain the dynamic interplay between leadership and culture, elucidating its tangible impact on the effectiveness of small enterprises. Research Contribution:Implications for PracticeThis research contributes to the literature on leadership and organizational culture in small enterprises, particularly in the context of Malta where such studies are scarce. By providing an initial exploration of these phenomena and their impact on organizational behavior, this paper lays the groundwork for further inquiry into this important area. Furthermore, the study offers practical insights for leaders of small enterprises by elucidating leadership behaviors observed in established organizations. Through applied cases, it demonstrates how the abstract concept of culture can be translated into a practical instrument that supports leadership and organizational development. This not only enriches the understanding of leadership dynamics but also provides tangible strategies for implementation. Moreover, the research contributes empirical evidence on the development of leadership functions within small enterprises, emphasizing the potential of shared and distributed leadership models. By grounding its findings in data, the study equips leaders with a deeper understanding of how these leadership approaches can shape organizational development, fostering more effective management practices in small businesses. Methodologically, the adoption of Grounded Theory methodology showcases its efficacy in exploring complex management phenomena. By employing this approach, the researchers were able to gather rich descriptions and develop an explanatory framework, highlighting its applicability in studying nuanced organizational dynamics. Implications for Policy and TheoryThis research also holds significant implications for policymakers, academic researchers and institutions involved in supporting small businesses. By providing insights into distributed leadership and cultural influences on organizational effectiveness, it offers a basis for informed policy formulation and support mechanisms. The conceptual model emerging from this study serves as a foundation for designing more targeted policies that cater to the unique needs of small enterprises. By understanding the intricacies of leadership dynamics and cultural contexts, policymakers can develop interventions that foster a conducive environment for small business growth and sustainability. Additionally, academic researchers can use these findings to further refine theoretical frameworks and empirical studies in the field, contributing to ongoing scholarly dialogue and knowledge advancement.

Digital transformation provides new drivers for economic performance growth in enterprises, but can it further improve ESG performance and support sustainable development? Based on the perspective of resources and capabilities, this paper uses the relevant data of 1588 listed companies in strategic emerging industries from 2011 to 2021 to study the differential impact of digital transformation on enterprise ESG performance, and further tests the mediating role of absorptive capacity and the moderating role of regional digital level. The research results indicate that: firstly, digital transformation of enterprises can positively promote the improvement of ESG performance; Secondly, there are significant differences in the impact of digital transformation on the ESG performance of enterprises in terms of property rights and industry characteristics. The ESG performance of state-owned enterprises and high-end equipment manufacturing enterprises is more sensitive to digital transformation; Thirdly, absorptive capacity plays a mediating role between digital transformation and corporate ESG performance; Fourthly, the positive regulation of regional digital level promotes the ESG performance of enterprises through digital transformation. The research conclusion is based on a digital perspective, providing relevant insights for improving the ESG performance of strategic emerging industry enterprises and expanding their ESG development paths.

Rebar cages form the skeletal framework of reinforced concrete structural members. They comprise longitudinal and transverse reinforcing bars, usually connected by tie wires. Past studies have identified tie-wire connections as the "weak links" in large, prefabricated rebar cages, leading to their failure during site handling and construction stages. Recent research has explored the use of mechanical U-bolt connectors to bolster stability and safety of rebar cages while reducing their vulnerability and risk of failure. This paper presents a comprehensive experimental and numerical investigation of a new type of mechanical connector, referred to as "Cage Clamp", to enhance rebar cage stability and safety. Component-level experimental tests are conducted to determine the force-displacement response of Cage Clamp connectors for crossbar connections in different degrees of freedom. The results highlight the remarkable strength and stiffness of Cage Clamp connectors, significantly outperforming traditional tie-wire connections. Furthermore, full-scale experimental tests are performed on a circular underground pile-shaft rebar cage with Cage Clamp connectors to assess its behavior under various site handling conditions. The data obtained from these experiments are used to construct and refine detailed 3D finite element models of the rebar cages, capable of capturing the complex behavior of rebar cages with Cage Clamp connectors. Using the numerical model, a sensitivity analysis is performed to assess the effect of the number of Cage Clamps on the deflection and stability of the rebar cage. The findings show that using cage clamps to connect pick-up rebar with lateral reinforcement at every 8 to 10 feet is sufficient to ensure the stability of the cage during typical site handling conditions. The results of this study serve as a basis for establishing analysis, design, fabrication, and handling guidelines for rebar cages, contributing to safe and efficient construction practices.

The technology for determining the point’s coordinates on the earth’s surface using the global navigation satellite system (GNSS) is becoming the norm along with ground-based methods. In this case, determining coordinates does not cause any particular difficulties. However, to identify normal heights using this technology with a given accuracy, special research is required. The fact is that satellite determinations of geodetic heights (h) over an ellipsoid surface differ from ground-based measurements of normal height (HN) over a quasi-geoid surface by a certain value called quasi-geoid height or height anomaly (ζ). In relation to determining heights of a certain territory, the concept of geoid height (N) is usually operated when dealing with a geoid model. In this work, geodetic and normal heights are determined for 5 control points in three different regions in Lebanon, where measurements are carried out using GNSS technology and geometric levelling. The obtained quasi-geoid heights are compared with geoid heights derived from the global Earth model EGM2008. The results obtained showed that, in the absence of gravimetric data, the combination of global Earth model data, geometric levelling for selected areas and satellite determinations allows the creation of a high accurate altitude network for mountainous areas.

Sustainability is essential for every business and organization, but how can it be achieved? This work is a study of sustainability based on the sufficiency economy philosophy, a valuable concept introduced by the Thai people. We apply it to the notion of sustainability in 400 agricultural community enterprise owners in Thailand, who participated in the study. An oblique rotation component analysis was performed, finding that the variables on the same side are related, and a confirmative component analysis with structural equation models was conducted. The results showed that the approach to applying the sufficiency economy philosophy among community enterprises consists of 11 components, as follows: 1) financial control, 2) planning, 3) member management, 4) morals, 5) prevention plan, 6) moderation, 7) knowledge and expertise, 8) market development, 9) care, 10) quality control and 11) value of investment. The confirmative component analysis with structural equation modeling was consistent with the empirical data. Agricultural community enterprises and entrepreneurs focus on the moral component, conduct business with honesty and avoid causing problems for others, value justice without taking advantage with diligence and adhere to moral principles in life, because all of the above will lead to sustainability in the future.

One of the key components of application performance monitoring (APM) software is 2 AI/ML empowered data analytics for predictions, anomaly detection, event correlations and root 3 cause analysis. Time series metrics, logs and traces are three pillars of observability and the valuable 4 source of information for IT operations. Accurate, scalable and robust time series forecasting and 5 anomaly detection are desirable capabilities of the analytics. Approaches based on neural networks 6 (NN) and deep learning gain increasing popularity due to their flexibility and ability to tackle complex 7 non-linear problems. However, some of the disadvantages of NN-based models for distributed cloud 8 applications mitigate expectations and require specific approaches. We demonstrate how NN-models 9 pretrained on a global time series database can be applied to customer specific data using transfer 10 learning. In general, NN-models adequately operate only on stationary time series. Application 11 to non-stationary time series requires multilayer data processing including hypothesis testing for 12 data categorization, category specific transformations into stationary data, forecasting and backward 13 transformations. We present the mathematical background of this approach and discuss experimental 14 results from the productized implementation in Wavefront by VMware (an APM software) while 15 monitoring real customer cloud environments.

The information technology has brought in a revolution in the area of digital agriculture and hydrological modeling . With the advent of IOT and AI such as machine learning is now capable of Predicating flood forecast , drought forecast and farms based water predications. In this article various machine learning algorithms , multiple sensors for environmental and agricultural has been proposed and used . The purpose is to acquire data of soil moisture , temperature , crop stages, irrigation and precipitation on a region constitute of two farms and then performed machine learning predications for total discharge predications at farms outlets so that in case of excessive rainfall or an irrigation event the water is adjusted in the second nearby farm or reroute to a reservoir for future use to avoid flooding. The focus is mostly to work on the concept and building of an andriod -ardiuno based mobile application for the endusers (agricultural system analyst, farmers) to provide an ease. The whole system of smart agricultural based on two farms and reservoir will provide an efficient ,fully automatic, proactive and decision support system to save water waste and reuse. In future the work is also in progress for developing a desktop based application .

The purpose of this article is to address two questions that will aid researchers in understanding FinTech’s inception, development, and potential impact on the stability of the financial system. First, it explains why financial technology is a current phenomenon. While many of the underlying technology for FinTech breakthroughs have been around for some time, it is only recently that financial institutions and entrepreneurs have begun to apply them to financial goods and services. Supply and demand factors in "conventional" financial innovation have been studied, and they have been found to converge, leading to a high rate of innovation. And second, this article explains why FinTech is being covered in greater depth than other types of innovation. This study introduces the concept of "depth" of innovation as a means of answering this question. The more fundamental the innovation, the more it will affect the financial sector. In this paper, we demonstrate that many recent developments in the field of financial technology (FinTech) are truly revolutionary advances, with far-reaching implications for the financial services industry. In addition to the benefits of more adaptability, higher transformational potential might bring increased risk to economic security.

The steep decline in the price of wind and solar photovoltaics provides a possibility to decarbonize electricity deeply and affordably. This study uses HOMER Pro energy modeling tool to model an optimized grid-connected renewable energy system for a community in southern Alberta, Canada. The study's goal is to identify the best renewable energy technology combinations that can provide electricity at the lowest levelized cost of energy (LCOE) and has lesser greenhouse gas emission as compared to the electricity produced by traditional fossil fuel. Gleichen, is a small town in southern Alberta and is near to numerous commercial wind and solar projects given the region’s high quality renewable resources. “Tri-brid” systems consisting of wind turbines, solar photovoltaics, and battery energy storage systems (BESS) are considered and compared based on electricity prices, net present cost, and greenhouse gas emissions savings. This tri-brid system is connected to the grid to sell excess electricity generated or buying electricity when there is less or no availability of solar and wind. The tri-brid energy system has an estimated LCOE of 0.0705 CAD/kWh which is competitive with the price of electricity generated by natural gas and coal which is 0.127 CAD/kWh.

This paper applied case study research to design architectures for green-field supply chain integration. The integration design is based on a case study of a supply chain integration of 5 companies, operating in different, but supply chain complimenting industry sectors. The case study research is applied to design and validate the architectures in a real world scenario. The supply chain integration architectures enable the conversion of individual into integrated strategies. The architectures are categorised and the process develops into a conceptual system for identifying the correlations between individual participants’ strategic areas of interest and the integrated supply chain areas of interest. The novelty of this paper is a conceptual system for green-field supply chain integration architectures, which can be applied in real world by supply chain practitioners.

With the trend of public infrastructure becoming more sustainable, large multi-purpose sports venues (LMPSVs) have become one of the world's most complex architectural projects and one of the landmark buildings of an international city. LMPSVs will lead the world in sustainable design, construction and operational innovations, and play a crucial role in raising awareness of sustainability around the world. System Thinking (ST), System Dynamics (SD) and Sustainable System Development (SSD) theories are three interrelated concepts that together form a methodological framework for solving complex system problems and driving strategies. The purpose of this study is to examine how LMPSVs can implement environmental, social, governance, and innovation (ESGI) enterprise transformation strategy (ETS) based on a sustainable systems development (SSD) framework. In view of the current global environmental challenges and social responsibility requirements, the motivation of this study is to provide an integrated transformation pathway for LMPSVs to achieve the goal of sustainable development and to contribute to the field of related disciplines. The methodology of this research adopts a combination of literature review and case study analysis, and the theoretical basis is mainly drawn from cutting-edge research in the fields of sustainable development, corporate social responsibility (CSR) and environmental management. Then, by analyzing successful transformation cases in China, we extract data and information to explore the application and effectiveness of these strategies in practice. The results of the study show that by implementing ESGI-based transformation strategy, LMPSVs can not only make significant progress in terms of environmental protection, social responsibility, and governance structure, but also drive long-term corporate growth and competitiveness through innovation. Specifically, these results are realized in terms of increased efficiency in energy use, improved waste management, community involvement and increased stakeholder satisfaction. The study concludes by emphasizing that the SSD-based ESGI Transformation Strategic framework provides a sustainable pathway for LMPSVs. In the future, the extension of this transformation strategy will help a wider range of industry sectors to achieve sustainable development goals, and has wide application potential and far-reaching social significance.

For an enterprise, the most critical aspect of development is resource management, which has a significant impact on all aspects of the enterprise. Therefore, enterprises must pay attention to resource management allocation, which can better promote the sustainable development of the enterprise and obtain optimal benefits. In the production and development of modern enterprises, the acquisition of benefits also involves the allocation of resources in enterprise management. This paper proposed a benefit optimization scheduling algorithm based on a macroeconomic prediction model under auction mechanism and a grid resource scheduling algorithm driven by a benefit function to allocate resources reasonably. This article used macroeconomic forecasting models to fully understand the resource needs of various departments and the resources held by enterprises, and rationally allocate various resources in various departments. This can improve the work efficiency of various departments, thereby reducing the cost of the enterprise, and achieving optimal benefits for the enterprise. The experimental results in this paper showed that the cost of resource management allocation for the benefit optimization scheduling algorithm and the grid resource scheduling algorithm based on the benefit function driven under the auction mechanism was 105.6 yuan and 46.8 yuan respectively when the task volume was 125 under the multi user environment. The time allocated for resource management was 36.6s and 18.9s respectively. It can be seen that the efficiency function driven grid resource scheduling algorithm had a lower cost and time for resource management allocation, so the efficiency function driven grid resource scheduling algorithm can achieve enterprise efficiency optimization.

In an era characterized by rapid technological advancements, economic fluctuations, and global competition, adaptability and resilience have become critical success factors for businesses navigating uncertainty and complexity. This article explores the role of enterprise agility in today’s business landscape at Latam branch of Tata Consultancy Services (TCS), where organizations face complex and diverse operations. We aim to examine how companies can become more agile in the face of emerging challenges and seize opportunities swiftly to drive growth and deliver value. Since 2014, the division has embarked on an agile transformation journey to drive growth, deliver value, foster innovation, and build resilience in an increasingly dynamic environment. We scrutinize an approach to measuring and enhancing enterprise agility, employing statistical analysis and continuous improvement methodologies to tackle real-world challenges while offering valuable insights and recommendations for organizations aiming to implement similar systems. The results of an agile transformation in a certain company’s Latam branch serve as a compelling case study, demonstrating how the implementation of targeted measures and continuous improvement can significantly bolster enterprise agility. Methodologically, our work applies a novel sequence of parametric statistical tests which, to the best of our knowledge, have not been used in the industry to validate the results of business agility metrics. In future work, we aim to create a new workflow considering non-parametric tests to address data with other statistical distributions. We conclude our work by proposing a sequence of steps for organizations to implement business agility metrics.

In large industrial plants, the trend is to move the position of the human to the area of service and diagnostics, in medium and smaller plants the trend is different and is mainly directed to the sphere of close cooperation between the human and the robotic system. This paper deals with the implementation of human-cooperating robots in manufacturing processes. The analytical part of the paper deals with theoretical knowledge, taking into account the latest trends in the subject area. To achieve a successful implementation of cobots based on the above-mentioned operating systems in manufacturing systems, it is necessary to pay attention specifically to the interfacing of the robotic operating system with the control systems of the manufacturing systems at the process level of the enterprise. Within the practical part, an algorithm with well-defined steps towards the successful implementation of cobots in holonic manufacturing processes is proposed. By setting up an experimental workstation in the laboratory, the proposed procedures are verified at the end of the paper. In the context of the implementation of collaborative robots in enterprises, the paper also discusses cloud computing. The creation of a design for the implementation of a collaborative robot with a human represents the missing link in the whole chain of commercial applications of the latest trends from the field of robotic systems in the industrial sphere.

In this study, the impact of the addition of high-aspect-ratio nano-ettringite to photocurable epoxy acrylate resin was explored, with a specific focus on the changes observed in viscosity, shrinkage, tensile strength, and elongation at the break of composites formed. Herein, the nano-ettringite samples were modified using KH-570. The 3 wt% or 6 wt% KH-570-modified and unmodified nano-ettringite were dispersed into the resin by ultrasonic treatment in conjunction with mechanical stirring. The grafting effects of nano-ettringite onto KH-570 were analyzed through scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric (TG) analysis, and Fourier transform infrared spectroscopy (FTIR). The results demonstrate that increased dosages of unmodified and modified nano-ettringite led to increased viscosity of the composite while reducing shrinkage. At the same dosage, the photocurable resin with modified nano-ettringite demonstrated a lower shrinkage and a higher tensile strength. Notably, when the amount of modified nano-ettringite was 3 wt%, the highest tensile strength of the composite was 64.61 MPa, presenting a 72.57% increase compared to the blank sample. Furthermore, the incorporation of modified nano-ettringite as a filler provides a new perspective for improving the performance of photocurable epoxy acrylate resin composites.

As of not long ago, understanding the administrative conduct of cells has been sought after through autonomous investigation of the transcriptome or the proteome. In view of the focal creed, it was commonly accepted that there exist an immediate correspondence between mRNA records and produced protein articulations. In any case, late examinations have demonstrated that the relationship among's mRNA and Protein articulations can be low because of different factors, for example, unique half lives and post record apparatus. In this manner, a joint investigation of the transcriptomic and proteomic information can give valuable experiences that may not be translated from singular examination of mRNA or protein articulations. This article audits the current significant methodologies for joint investigation of transcriptomic and proteomic information. We order the various methodologies into eight primary classes dependent on the underlying calculation and last investigation objective. We further present analogies with different spaces and talk about the current exploration issues around there.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

Recent studies have demonstrated a relationship between poor vitamin D status and respiratory infections and diarrhea among young children. Acute lower respiratory infections (ALRI) and diarrhea are among the two most important causes of death in under-5 children. In this analysis, we examine the extent to which vitamin-D deficiency (<10 ng/ml) predicts these outcomes using data from a randomized controlled trial (RCT) of daily folic acid and/ or vitamin B12 supplementation for six months in 6 to 30 months old children conducted in Delhi, India. Of the 960 subjects who had vitamin-D concentrations measured, 331(34.5%) were vitamin-D deficient. We found, after controlling for relevant potential confounders (age, sex, breastfeeding status, wasting, stunting, underweight, anemia status at base line and season), the risk of ALRI was significantly higher among vitamin-D deficient (OR 1.26; 95% CI: 1.03 to 1.55) compared to vitamin-D-replete children in the six months follow-up period. Vitamin-D status was not significantly associated with episodes of diarrhea and clinical pneumonia. The extent of causal relationship of vitamin-D status and ALRI needs to be explored in further studies.

Fingerprints are essential for human identification and are valuable tools in criminal investigations. The pursuit of new materials for digital printing is expanding, with increasing interest in natural compounds such as bixin, sourced from annatto seeds. Despite its traditional use as a natural dye with medicinal properties, the potential of bixin in papilloscopy remains largely untapped. In this study, we meticulously extracted bixin from annatto seeds and meticulously developed composites incorporating zinc carbonate (bixin/ZnCO3) and kaolinite (bixin/kaolinite). UV-visible spectroscopy was used for characterization, and the extracted bixin showed absorption peaks at 429, 453, and 481 nm, which were very similar to standard peaks at 429, 457, and 487 nm. The two samples also had the same retention times (7.07 min) according to further liquid chromatography analysis. Sweat pores were easier to detect thanks to the effectiveness of the bixin/ZnCO3 and bixin/kaolinite composites in creating high contrast sebaceous and natural latent fingerprints. These results highlight the composites’ potential as novel and fascinating instruments for papilloscopy applications, which might also improve forensic investigations.

When dealing with limited sample sizes or missing values in time series data, achieving high accuracy in forecasting becomes challenging. This challenge is particularly common in wind energy forecasting, where many wind farms lack complete data. In this paper, we employ the widely-used ARIMA (Autoregressive Integrated Moving Average) model for time series forecasting. To address the difficulties posed by limited sample sizes and missing values, we adopt a unique approach by utilizing multiple ARIMA models for different datasets. A key distinction from other multiple models methods for time series forecasting lies in each model within our approach using its own dataset, making the fusion process more intricate. To overcome this, we incorporate neural networks and two techniques for model fusion: direct fusion with a learning mechanism and compensation for missing data through training. For each ARIMA model, we introduce a noise estimation method to circumvent the white noise assumptions inherent in ARIMA models. Finally, we apply these methods to wind energy prediction, and our experimental results showcase a significant enhancement in forecasting accuracy.

This paper focuses on optimal sensor positioning for monitoring activities of daily living and investigates different combinations of features and models on different sensor positions, i.e., the side of the waist, front of the waist, chest, thigh, head, upper arm, wrist, and ankle. Sixteen features are extracted and the feature importance is measured by using the Relief-F feature selection algorithm. Eight classification algorithms are evaluated on a dataset collected from young subjects and that collected from elderly subjects, with two different experimental settings. To deal with different sampling rates, signals with a high data rate are down-sampled and a transformation matrix is used for aligning signals to the same coordinate system. The thigh, chest, side of the waist, and front of the waist are the best four sensor positions for the first dataset (young subjects), with average accuracy values being greater than 95%. The best model obtained from the first dataset for the side of the waist is validated on the second dataset (elderly subjects). The most appropriate number of features for each sensor position is reported. The results provide a reference for building activity recognition models for different sensor positions, as well as for data acquired from different hardware platforms and subject groups.

We construct a Bayesian estimator for the dilution of a wastewater sample. When wastewater is diluted by rainwater an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows (CSOs) and wastewater storage tanks, which divert wastewater away from treatment plants when the flow is excessive. However, we also have proxies for the flow from various chemical markers (e.g.\ phosphate, ammonium, electrical conductivity), whose level per unit of population is fixed. The new flow estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

Genetic engineering has become an essential element in developing climate-resilient crops and environmental sustainable solutions to respond to the increasing need for global food security. Genome editing using CRISPR/Cas [Clustered regulatory interspaced short palindromic repeat (CRISPR)-associated protein (Cas)] technology is being applied to a variety of organisms, including plants. This technique has become popular because of its high specificity, effectiveness, and low production cost. Therefore, this technology has the potential to revolutionize agriculture and contribute to global food security. Over the past few years, increasing efforts have been seen in its application in developing higher-yielding, nutrition rich, disease resistant, stress-tolerant “crops” fruits and vegetables. Cas proteins such as Cas9, Cas12, Cas13, and Cas14, among others, have distinct architectures and have been used to create new genetic tools that improve features that are important for agriculture. The versatility of Cas has accelerated genomic analysis and facilitated the use of CRISPR/Cas to manipulate and alter nucleic acid sequences in cells of different organisms. This review provides the evolution of CRISPR technology exploring its mechanisms and contrasting it with traditional breeding and transgenic approaches to improve different stress tolerance. We have also discussed the CRISPR/Cas system and explored three Cas proteins that are currently known to exist: Cas12, Cas13, and Cas14 and their potential to generate foreign DNA free or non-transgenic crops that could be easily regulated for commercialization in most countries.

China is in the climbing phase of the "Inverted U" environmental Kuznets curve, from excessive environmental consumption to the development stage of governance and protection, and green innovation. It is the most complex period of environmental quality. Environmental and policy regulation are very important. Select panel data of 29 provinces of China (excluding Hong Kong, Macau, Taiwan, Hainan and Tibet) from 2008 to 2017, construct a nonlinear two-threshold regression model, empirically analyse the impact of environmental tax and government innovation subsidies to green processes innovation, and attempt to explore whether the implementation of these two policies at the same time can make enterprises more inclined to green process innovation and whether there is an optimal space for policy implementation. It is proposed that the synergy effect of environmental tax and government innovation subsidy policies on enterprise green process innovation should be fully utilized, and the enterprise green process innovation environment and incentive mechanism should be improved to promote the green transformation and sustainable development of enterprises.

Through the use of Smart Sensor Networks (SSN), Marine Observatories (MO) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of SSN devices’ hardware and software when combined with the Internet. Hence, SSN are regarded as complex distributed systems. As such, SSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed SSN. To this end, we describe in this article how we extended our previously proposed ArchiMO meta-model and design tool by extending an Enterprise Architecture Framework based on the ArchiMate Modeling Language. This extension proposes the incorporation of new Underwater Environmental Constraints (UEC) for SSN in ArchiMO which is coupled with the fusion of sensors with Artificial Intelligence. This serves as the basis for generating a new version of our ArchiMO design tool, which incorporates the new added constraints and invokes the AI created Database. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to handle and control the uncertainties and variances of the provided quality of service that may occur during the performance of the SSN, hence reducing the design activity’s complexity and time. It provides a way to share the different viewpoints of the designers in the domain of SSN.

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

Properties of time domain parameters of the vibration signal have been extensively studied for the fault diagnosis of rolling element bearings (REB). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters respectively, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock pulse index (SPI), is proposed in this paper. It integrates the mutual advantage of both parameters above and can help effectively identify fault related impulse components under the interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the interested transient information contained in the filtered signal can be highlighted through demodulation with Teager Energy Operator (TEO). Fault related impulse components can therefore be extracted accurately. Simulations and experiment analyses verify the effectiveness and correctness of the SPI.

The oil and gas industry in Nigeria, a vital contributor to the nation's economy, has long been associated with significant environmental challenges. Pollution, habitat destruction, and greenhouse gas emissions have raised global concerns about sustainability and corporate responsibility. This empirical study explores the relationship between environmental accounting practices and the financial performance of listed oil and gas companies in Nigeria. We investigated eight oil and gas companies that are publicly traded on the Nigerian Stock Exchange Market (NGX) as of January 17, 2022, from 2011 to 2022. The study employs Driscoll-Kraay standard errors and reveals that environmental accounting had significant effects on returns on assets, earnings per share, and liquidity ratio. The study revealed that the implementation of environmental accounting practices had diverse effects on the performance of oil and gas companies in Nigeria. The findings encourage policymakers and stakeholders in the sector to utilise the insights and design more effective regulations and incentives that promote environmental corporate responsibility. Also, valuable insights into the potential benefits and challenges associated with adopting environmental accounting practices, and influencing the decision-making processes of corporate stakeholders were provided to ensure sustainability in terms of improved financial performance of the oil and gas sector in Nigeria.

The teaching and learning environment have changed significantly over the last decade with the integration of an increasing amount of information and communication technologies, especially in distance education due to global pandemics, total lockdowns, isolation, and quarantine periods. The number of numerous virtual and non-virtual tools involved in educational processes is growing day by day. In terms of technological innovations used in learning environments, many researchers and educators are trying their best to bring more creative ideas into the technology- based learning environments. Although higher educational institutions have greatly benefited from the growing number of hardware and software resources in the educational process, they have also faced some setbacks that have harmed the learning processes. These technologies have in turn complicated some of the processes in the learning atmosphere. Therefore, we take Spanish teaching course as an example to present the challenging smarter teaching and learning systems that higher educational institutions face today.

This manuscript employs a surface stress-driven nonlocal model to explore the combined effects of long-range interaction and surface energy on higher vibration modes of functionally graded nanobeams. The nanobeam theory, based on Bernoulli-Euler kinematics, incorporates surface effects such as surface elasticity, surface residual stresses, surface density, and rotary inertia. Hamilton's principle is applied to derive the governing equation with size-dependent considerations. The main outcomes of a parametric investigation, considering four different kinematic boundary conditions (Cantilever, Simply-Supported, Clamped-Pinned, and Doubly-Clamped) while varying the nonlocal parameter and material gradient index, are presented and discussed. Additionally, the normalized natural frequencies for the second, third, fourth and fifth modes of vibrations are provided and analyzed for each case under study. The results underscore the model's effectiveness in capturing surface energy effects on the overall dynamic behavior of functionally graded Bernoulli-Euler nanobeams, offering a cost-effective approach for designing and optimizing nano-scaled structures.

Agricultural greenhouse is largely answered in the agricultural sphere, despite the shortcomings it has, including overheating during the day and night cooling which sometimes results in the thermal inversion mainly due to its low inertia. The glasshouse dressed chapel is relatively more efficient than the conventional tunnel greenhouse. Its proliferation on the ground is more or less timid because of its relatively high cost[14-22]. Agricultural greenhouse aims to create a favorable microclimate to the requirements of growth and development of culture, from the surrounding weather conditions, produce according to the cropping calendars fruits, vegetables and flower species out of season and widely available along the year. It is defined by its structural and functional architecture, the quality thermal, mechanical and optical of its wall, with its sealing level and the technical and technological accompanying[12-13]. The greenhouse is a very confined environment, where multiple components are exchanged between key stakeholders and them factors are light, temperature and relative humidity[8]. This state of thermal evolution is the level sealing of the cover of its physical characteristics to be transparent to solar, absorbent and reflective of infrared radiation emitted by the enclosure where the solar radiation trapping effect otherwise called "greenhouse effect" and its technical and technological means of air that accompany. The socio-economic analysis of populations in the world leaves appear especially the last two decades of rapid and profound transformations These changes are accompanied by changes in eating habits, mainly characterized by rising consumption spread along the year[14]. To effectively meet this demand, greenhouse-systems have evolved, particularly towards greater control of production conditions (climate, irrigation, ventilation techniques, CO2 supply, etc ...). Technological progress has allowed the development of greenhouses so that they become increasingly sophisticated and of an industrial nature (heating, air conditioning, control, computer, regulation, etc ...). New climate driving techniques have emerged, including the use of control devices from the classic to the use of artificial intelligence[10-11] such as neural networks and / or fuzzy logic, etc... As a result, the greenhouse growers prefer these new technologies while optimizing the investment in the field to effectively meet the supply and demand of these fresh products cheaply and widely available throughout the year.

The analysis and simulation of water quality in distribution networks is a complex issue of great concern today. The analysis of the evolution of water age, as a simple indicator of water quality in the network, is of great interest in both design and operation phases. Understanding the factors that have the strongest influence on water quality is key to developing adequate strategies aimed at preserving it. This paper firstly analyses the factors with biggest influence in the tanks water age, to support the selection of the most appropriate configuration from the point of view of water quality during design phases. Then, the main considerations when modelling tanks following the different mixing models considered in Epanet have been presented. Also, a real tank behaviour has been characterised through field measurements and Epanet simulations in order to determine the best fitted mixing model.

The research aimed at the ecological assessment of the environment around uranium mining enterprises in the Turkestan region. The authors examined the state of the soil and vegetation for 2021-2023, their chemical composition and the effects of radiation. Excesses of background radiation were detected by alpha and beta studies. To study the structural organization of plant communities, we conducted floristic studies in the areas immediately adjacent to NAC “Kazatomprom” enterprises. The general habitus, size, number and shape of vegetative parts of plants were taken into account as comparison parameters. The flora growing in the study areas of the Suzak district of the region, which is distinguished by its uniqueness and narrow relevance to the ecological conditions of the area, was taken as biological objects of study. To determine the ecological state of the adjacent territories of NAC “Kazatomprom” and for physical, chemical and taxonomic analyses, 78 soil samples and 37 plant samples were obtained. The studied samples were taken near settlements N, B and S, which are closest to the territories of NAC “Kazatomprom”.

A multimodal detection system with complementary capabilities for efficient detection was developed for impurity detection. The system consisted of a visible light camera, a multispectral camera, image correction and registration algorithms. It can obtain spectral feature and color feature at the same time, and has higher spatial resolution than a single spectral camera. This system was applied to detect impurities in Pu ’er tea to verify its high efficiency. The spectral and color features of each pixel in the images of Pu ’er tea were obtained by this system and used for pixel classification. The experimental results show that the accuracy of Support Vector Machine (SVM) model based on combined features is 93%, which is 7% higher than that based on only spectral features. By applying median filtering algorithm and contour detection algorithm to the label matrix extracted from pixel-classified images, 8 impurities except hair were detected successfully. Moreover, taking advantage of the high resolution of visible light camera, small impurities can be clearly imaged. By comparing the segmented color image with the pixel-classified image, small impurities such as hair could be detected successfully. Finally, it is proved that the system can obtain multiple images to allow a more detailed and comprehensive understanding of the detected items, and has excellent ability to detect small impurities.

Within the past decade, the aerospace engineering industry has evolved outside the constraints of using single, large, custom satellites. Due to increased reliability and robustness of commercial off the shelf (COTS) printed circuit board (PCB) components, missions instead have transitioned towards deploying swarms of smaller satellites. This approach significantly decreases the mission cost by reducing custom engineering and deployment expenses. Nanosatellites are able to be quickly developed with a more modular design at lowered risk. The Alpha mission at Cornell Space Systems Studio is fabricated in this manner. However, for the purpose of this mission, only one satellite was initially developed. This manuscript will discuss a systems engineering approach to the development of this satellite. As a disclaimer, this manuscript is written from a systems perspective. Therefore it will follow many subsystems from a wide range of functionalities. The research in this manuscript was kept broad with the hope to contribute to the mission as a system, through a range of development phases including validation and verification of existing methods. The two systems that will be primarily focused on are the Attitude Control System (ACS) of the carrier nanosatellite (cubesat), and the RF communications on the ex-creted picosatellites (chipsat). Milestones achieved in chipsat RF include chipsat to chipsat communication, chipsat to SDR ground station communication, packet creation, error correction, appending a preamble, and filtering the signal. Achievements on the ACS side included controller traceability/verification and validation, software rigidity tests, hardware endurance testing, Kane damper and IMU tuning. These developments matured the technological readiness level (TRL) of our systems in preparation for satellite deployment.

Nowadays, animal breeders look for effective innovations to care animal health. Use of probiotics, postbiotics, parabiotics and the other beneficial natural substances are dominated. Mundticin-like substance EM 41/3 is thermo-stable bacteriocin (postbiotic) with a broad antimicrobial spectrum. In this study its effect in broiler rabbits was assessed. Rabbits represent food-derived animal and they are also suitable animal model. The parameters tested were analyzed by validated methods. Administration of MLS EM 41/3 produced by non-autochthonous strain Enterococcus mundtii EM 41/3 lead to significant increase of parameter immunity-phagocytic activity, while it did not influence microbiota composition. It also did not influence blood biochemistry and no oxidative stress was noted. Moreover, higher growth parameters were noted and also stimulated hydrolytic activity. Finally, no negative influence on rabbit meat quality was noted. Postbiotic MLS EM 41/3 administration in feeding strategy seems to be contributing fact for rabbit health status maintaining.

Cancer being a multi-factorial disease, a multi-target approach is needed to treat it with minimal side-effects. Therefore, combined use of a proven herbal formula with chemo-therapy could be the better therapeutic. It may maintain homeostasis by synergistically targeting multiple signaling pathways involved in tumorigenesis, thus circumventing recurrence, resistance, and immunosuppression. Here we aim to determine the effectiveness and safety of an FDA-approved herbal formula, SR033 in combination with 5-fluorouracil (5FU) and paclitaxel (PTX). We report chemo-sensitization and chemo-synergy in HeLa and MCF-7 cell lines, immunomodulation of COX-2, PD-L1, VEGF and TGFβ and overall survival in-vitro and in-vivo via oral and topical delivery of SR033. In-vitro, SR033/5FU significantly reverses 5FU and PTX-resistance, lower COX-2, and PD-L1, resulting in TGFβ/ VEGF axis modulation. Furthermore, the study suggests that due to anti-oxidative potential of SR033, oral administration exerts chemo-preventive activity and restores cellular compartment in solid tumor and ascites-bearing mice models. Furthermore, the topical application, SR033L with low-dose 5FU increases survival rate, reduces tumor growth, and completely restores local and peripheral neutrophil-lymphocyte ratio in solid tumor mice model. The study indicates that SR033 could be a strong candidate in combination with low-dose 5FU and PTX for a holistic approach to cancer management.

This study explores optimizing Synthetic Aperture Radar (SAR) satellite constellation scheduling for multi-imaging missions in densely targeted areas using an in-house developed Modified Dynamic Programming (MDP) algorithm. By employing Mixed-Integer Linear Programming (MILP) to define the mission planning problem, the research aims to maximize observation of high-value targets within restricted planning horizons. Numerical simulations, covering a wide range of target numbers and satellite configurations, reveal the MDP algorithm’s superior mission allocation efficiency, enhanced success rates, and reduced revisit times, compared to the Greedy algorithm. The findings underscore the MDP algorithm’s improved operational efficiency and planning robustness for complex imaging tasks, demonstrating significant advancements over traditional approaches.

Lately Silicon Carbide (SiC) and Galium Nitride (GaN) based high frequency power conversion has gained immense popularity which stems from relatively low switching energy, robustness to high temperature operation, wide-band gap and superior thermal limits. While this aspect inherently results in a high-density power stage design, the design of adjoining passive components, particularly magnetics, needs careful attention. This is especially true if the compatibility of core and winding options and their performance is limited with the use of higher switching frequency. In this regard, this paper presents a brief review of existent research conducted in materials, optimization and integration of magnetics for single and three phase applications, ranging from filters, resonant inductors to isolation transformers. Design knobs pertaining to medium voltage (MV) applications, low-voltage (LV) applications, e-mobility sector such as more electric aircrafts (MEAs) and electric vehicles (EVs) are discussed. Guidelines for magnetics design are summarized for each application with a projected roadmap on future trend for magnetics.

The paper delves into an extensive exploration of the integration of the circular economy paradigm within the realm of additive manufacturing (AM). The objective is to comprehensively investigate existing methodologies for structuring the symbiotic relationship between circular economy and additive manufacturing, while meticulously analyzing the current research gap concerning the implementation of circular economy principles in additive manufacturing practices. A thorough review focusing on the sustainability of additive manufacturing within the circular economy framework was conducted. This review aims to recognize and delineate pertinent aspects related to post-use material valuation in AM, recyclability of materials, and the environmental footprint associated with these processes. Emphasis was placed on the significance of examining circular economy facets concerning additive manufacturing processes to establish a holistic understanding. The overarching goal of this review is to augment knowledge regarding the potential advantages and benefits derived from the seamless integration of circular economy principles within AM. By elucidating the activities essential to attain compliance with the Sustainable Development Goals, this study endeavors to illuminate the pathway toward promoting sustainable development through the harmonious marriage of additive manufacturing and the circular economy.

The second article in the series presents the application of the Smoothed Particle Hydrodynamics (SPH) method to modelling of batch crystallisation in stirred tanks. A methodology to integrate the population balance equations (PBE) in parallel and independently from the Navier-Stokes equations is demonstrated. The benefits of the proposed methodology in terms of computational requirements, accuracy and availability of the crystal size distribution are discussed. The specific formulation of the SPH equations where the resulting system of ordinary differential equations is solved using the weighted contributions rather than numerically by solving a linear system of equations allows for massive parallelisation and a very loose coupling of the population balance and the fluid dynamics. It has been demonstrated, that the population balance equations can be solved on a Shared Memory Architecture (SMA) system using the OpenMP interface while the fluid dynamics equations being computed independently on a General Purpose Graphics Processing Unit (GPGPU) using the NVidia CUDA technology. This way, a significant portion of the computational overhead due to the large number of additional transport equations resulting from the discretisation of the population balance was removed: the SPH simulation coupled with 200 population balance equations was only 40% slower compared to SPH-only simulation. Two methods for the solution of population balance equations that preserve full crystal size distribution were implemented: discretised population balance (DPB) and method of characteristics (MOCH). The DPB equations are solved using the high-resolution finite-volume method with flux limiter and the effect of a large number of different flux limiters have been investigated. Both methods were validated using the case studies from the literature where an analytical solution can be derived. The developed models were applied to a numerical solution of coupled computational fluid dynamics and population balance equations to model a batch crystallization process. The effect of the hydrodynamics on the local temperature/supersaturation and the resulting crystal size distribution was captured and compared to the ideal mixing case. The simulation results from the DPB and MOCH methods were compared in terms of computational requirements and accuracy and MOCH selected as computationally more efficient and accurate.

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

Bat feces were reported in ancient Chinese medicine books to have the effect of reducing heat and improving eyesight, but the mechanism of vision improvement still needs further research. To this end, we used 2,2-diphenyl-1-picrylhydrazyl (DPPH) and liquid chromatography/tandem mass spectrometry (LC/MS/MS) to analyze the antioxidant capacity of and the types of vitamins in bat feces. We hoped to screen the pharmacological components of bat feces, and to explain the role that these components may play in the treatment of visual deterioration. Our results found that bat feces had a good antioxidant capacity and mainly contain vitamins B1 (thiamine), B2 (riboflavin), B3 (nicotinamide), B3 (nicotinic acid), and B5 (pantothenic acid). Although these vitamins may help maintain the health of the optic nerve and cornea, the vitamin content of bat feces is low, but the heavy metal content is high, as shown using inductively coupled plasma mass spectrometry (ICP-MS) analysis. Therefore, we suggest that the use of bat feces as traditional Chinese medicine to improve vision should be strictly restricted.

At present, countries around the world adopt digital strategy, so that enterprises apply digital technology, digital supply chain, blockchain, and a series of digital measures to enhance their competitiveness. By analyzing the relationship between digital transformation of manufacturing export enterprises, and their business performance and export performance, this paper focused on the current situation and existing problems of digital transformation of manufacturing export enterprises in China. Based on the Resource Based View theory and Trade theory, the impact of digital transformation of enterprises performance, proposing hypotheses, and building regression models were explored. With the samples of 1007 listed companies in Shanghai and Shenzhen Stock markets from 2012 to 2019, the regression analysis, intermediate effect test, robustness test, stage lag, and heterogeneity analysis were conducted. The results shew that: (1) Listed manufacturing export enterprises carried out digital transformation, which had a significantly positive effect on enterprise performance; (2) It was found that digital transformation could improve enterprise performance by reducing costs, improving R&amp;D intensity and improving human resources etc. (3) According to the fractal analysis, non-state-owned enterprises had more positive effects on enterprise performance, and digital transformation of manufacturing export enterprises in developed areas had a more significant impact on enterprise performance. Finally, according to the empirical results, relevant suggestions for digital transformation were provided.

The ongoing challenge to ensure a sustainable and affordable energy supply forces industrial companies to implement appropriate measures. These measures typically lead to an increased system complexity, which has to be addressed during operation. Whereas existing approaches from the field of supervisory and optimal control appear to be capable of mastering this issue, these are still not adopted in industry. Therefore, this work presents a procedure model for the systematic development of application-oriented operating strategies for industrial energy supply systems. The procedure model combines research approaches from the fields of sequencing control and approximate MPC to extract rule-based operating strategies. By splitting the procedure model into five phases, expert knowledge can be integrated in a target-oriented manner. Subsequently to the description, the procedure model is exemplary applied to the example of an industrial heating supply system. Throughout an optimization study, the developed operating strategy is compared to a MPC strategy as well as a baseline strategy. Whereas the conventional MPC approach is the upper bound with regard to optimality, the developed operating strategy is able to generate comparable results. Compared to the baseline strategy, a relative reduction in operating expenses of 5.4 % to 37.0 % are achieved in this specific use case.

The integration of artificial intelligence (AI) technologies into business practices presents both opportunities and challenges for Sabah, Malaysia. This dynamic abstract explores the latest research problem at the intersection of AI and business in Sabah, focusing on optimizing resource allocation in agriculture and enhancing tourism experiences through AI-driven solutions.In Sabah's agricultural sector, AI holds immense potential to revolutionize traditional farming practices. With limited arable land and unpredictable weather patterns, farmers face significant challenges in maximizing crop yields while minimizing resource inputs. Through the application of machine learning, remote sensing, and IoT devices, researchers aim to develop precision farming techniques that can analyze soil health, monitor crop growth, and predict pest outbreaks with unprecedented accuracy. By optimizing resource allocation and enhancing decision-making processes, these AI-driven solutions have the potential to revolutionize Sabah's agriculture industry, promoting sustainability and resilience in the face of environmental uncertainties.Moreover, the tourism industry in Sabah stands to benefit from AI integration, particularly in enhancing visitor experiences and destination management. With its diverse natural landscapes and rich cultural heritage, Sabah attracts tourists from around the globe. AI-powered recommendation systems, tailored to individual preferences and behavior, have the potential to provide personalized travel itineraries, optimize resource allocation, and boost visitor satisfaction. Additionally, natural language processing (NLP) algorithms can analyze online reviews and social media sentiments, providing valuable insights for destination marketing and management strategies. By harnessing the power of AI, Sabah can elevate its tourism offerings, attract more visitors, and enhance its reputation as a premier travel destination.However, alongside these opportunities, challenges abound in the integration of AI into Sabah's business landscape. Concerns regarding data privacy, cybersecurity, and ethical implications must be carefully addressed to ensure the responsible and sustainable deployment of AI technologies. Furthermore, the digital divide and limited access to technology in rural areas pose barriers to widespread adoption, necessitating comprehensive strategies for capacity building and infrastructure development.In conclusion, the advancement of AI integration in Sabah's business landscape holds immense promise for driving innovation, economic growth, and sustainability. By addressing the research problems outlined in this abstract, researchers, policymakers, and industry stakeholders can collaboratively navigate the opportunities and challenges of AI integration, paving the way for a prosperous and inclusive future for Sabah, Malaysia.

This study investigates the impact of financial integration on international dynamics from the perspective of volatility shocks. To achieve this, I employ an IRBC model with time-varying volatilities, recursive preferences, and a global bank. The model demonstrates that volatility shocks trigger precautionary saving incentives, but the specific effects vary based on the type of shock. In the presence of productivity volatilities, countries with a higher level of financial integration exhibit greater divergence in their business cycles, while financial integration tends to result in more synchronized business cycles in the face of financial volatilities. Disregarding volatility shocks would underestimate the impact of financial integration on the comovement of business cycles across countries. Furthermore, welfare analysis also indicates that financial markets play a crucial role in enhancing social welfare, regardless of the type of volatility.

In the modern world, stress has become a pervasive concern that affects individuals' physical and mental well-being. To address this issue, many wearable devices have emerged as potential tools for stress detection and management, by measuring heart rate, heart rate variability (HRV), and various matrices related to it. This literature review aims to provide a comprehensive analysis of existing research on HRV tracking and Biofeedback using smartwatches and finger monitor/sensor pairing with reliable 3rd party mobile apps like Elite HRV, Welltory, and HRV4Training specifically designed for stress detection and management. we apply various algorithms and methodologies employed for HRV analysis and stress detection is discussed, including time-domain, frequency-domain, and non-linear analysis techniques. Prominent smartwatches, such as Apple Watch, Garmin, Fitbit, Polar, and Samsung Galaxy Watch, are evaluated based on their HRV measurement accuracy, data quality, sensor technology, and integration with stress management features. We describe the efficacy of smartwatches in providing real-time stress feedback, personalized stress management interventions, and promoting overall well-being. To assist researchers, doctors, and developers use smartwatch technology to address stress and promote holistic well-being, we discuss the data's advantages and limitations, future developments, and the significance of user-centered design and personalized interventions. Keywords: smartwatch; stress; wearable device; heart rate variability; comparative analysis

Rural tourism plays an increasing role in maintaining sustainable rural development. In-11 tegrating culture into rural tourism is multifaceted. Local communities have often been regarded as 12 homogeneous, and different voices within them are selectively presented or re-interpreted by pow-13 ers. A better understanding of how and why cultures are integrated into rural tourism is urgently 14 needed. This paper aims to investigate (1) the aims and motives of tourism managers to integrate 15 cultural concepts into rural tourism; (2) who has participated in the cultural integration process; and 16 (3) how cultures have been integrated into rural tourism. Based on a scoping literature review, we 17 found that cultures could add more attractions, such as historical heritage, artwork, cultural land-18 scape, customs, food, and language, to the natural landscape and bring more tourists to rural areas. 19 However, integrating cultures into rural tourism is not always successful. Conflicts of interest 20 among different stakeholders are also often found. Some of the worst cases of cultural integration 21 have even destroyed the original natural landscape and local cultures. While cultural integration is 22 complicated, injustice and perverse effects do not have to be a consequence of integrating cultures 23 into rural tourism. Multi-way communication among tourism providers, managers, and consumers 24 can mitigate disruptive outcomes and unlock positive social outcomes.

Molecular methods have revolutionised virtually every area of biology, and metazoan phylogenetics is no exception: molecular phylogenies, molecular clocks, comparative phylogenomics, and developmental genetics have collectively transformed our understanding of the evolutionary history of animals. Moreover, the diversity of methods and models within molecular phylogenetics has resulted in significant disagreement among molecular phylogenies as well as between these and traditional phylogenies. Here, I argue that tackling this multifaceted problem lies in integrating evidence to infer the best evolutionary scenario. I begin with an overview of recent developments in early metazoan phylogenetics, followed by a discussion of key conceptual issues in phylogenetics revolving around phylogenetic evidence and theory. I then argue that integration of different kinds of evidence is necessary for arriving at the best evolutionary scenario rather than the best-fitting cladogram. Finally, I discuss the prospects of this view in stimulating interdisciplinary cross-talk in early metazoan research and beyond.

The growing interest in the use of energy storage systems to improve the performance of tramways has prompted the development of control techniques and optimal storage devices, displacement, and sizing to obtain the maximum profit and reduce the total installation cost. Recently, the rapid diffusion of renewable energy generation from photovoltaic panels has also created a large interest in coupling renewable energy and storage units. This study analyzed the integration of a photovoltaic power plant, supercapacitor energy storage system, and railway power system. Random optimization was used to verify the feasibility of this integration in a real tramway electric system operating in the city of Naples, and the benefits and total cost of this integration were evaluated.

We present a first formal analysis of specific and complete local integration. Complete local integration was previously proposed as a criterion for detecting entities or wholes in distributed dynamical systems. Such entities in turn were conceived to form the basis of a theory of emergence of agents within dynamical systems. Here, we give a more thorough account of the underlying formal measures. The main contribution is the disintegration theorem which reveals a special role of completely locally integrated patterns (what we call ι-entities) within the trajectories they occur in. Apart from proving this theorem we introduce the disintegration hierarchy and its refinement-free version as a way to structure the patterns in a trajectory. Furthermore we construct the least upper bound and provide a candidate for the greatest lower bound of specific local integration. Finally, we calculate the i-entities in small example systems as a first sanity check and find that ι-entities largely fulfil simple expectations.

This study reports on the development of bio-based hydrophobic coatings for packaging papers through deposition of polyhydroxybutyrate (PHB) particles in combination with nanofibrillated cellulose (NFC) and plant wax. In a first approach, PHB particles in micrometer range (PHB-MP) were prepared through a phase-separation technique providing internally nanosized structures. The particles were transferred as a coating by dip-coating filter papers in the particle suspension, followed by sizing with a carnauba wax solution. This approach allowed partial to almost full surface coverage of PHB-MP over the paper surface resulting in static water contact angles of 105° to 122° and 129° to 144° after additional wax coating. In a second approach, PHB particles with submicron sizes (PHB-SP) were synthesized by an oil-in-emulsion (o/w) solvent evaporation method, and mixed in aqueous suspensions with 0 to 7 wt% NFC. After dip-coating filter papers in PHB-SP/NFC suspensions and sizing with a carnauba wax solution, static water contact angles of 112° to 152° were obtained. The intrinsic properties of the particles were analyzed by scanning electron microscopy, thermal analysis and infrared spectroscopy, indicating higher crystallinity for PHB-SP than PHB-MP. The chemical interactions between the more amorphous PHB-MP particles and paper fibers were identified as an esterification reaction, while the morphology of the NFC fibrillar network was playing a key role as binding agent in the retention of more crystalline PHB-SP at the paper surface, hence contributing to higher hydrophobicity.

A scientific carbon accounting system can help enterprises reduce carbon emissions. This study took the enterprise in the Yangtze River basin as a case study. The accounting classification of carbon emissions in the life cycle of lime production was assessed, and the composition of the sources of carbon emission was analyzed, covering mining explosives, fuel (diesel, coal), electricity and high temperature limestone decomposition. Using the IPCC emission factor method, a carbon life cycle emission accounting model for lime production was established. We determined that a total of 354,200 tons of carbon emissions were generated from producing 321,000 tons of lime in a year. The decomposition of limestone at a high temperature was the largest carbon emission source, accounting for 62.34% of the total carbon emission. Coal combustion was also an important source of carbon emissions, accounting for 32.66% of total carbon emissions. The carbon emission for one ton of activated lime was 1.46kg, 1.49kg, 1100kg and 1102.95kg respectively for the open-pit, mining stage, crushing stage, and the calcination stage. Based upon the main sources of carbon emission for lime production, carbon emission reduction should focus on CO2 capture technology, fuel optimization and energy control. Using our analysis of carbon emissions, the carbon emission factor of producing unit quicklime of the lime enterprise in the Yangtze River basin was determined. Furthermore, the research into carbon emission reduction for lime production can provide a point of reference for the promotion of carbon neutrality in the same industry.

With the economic recession and the deterioration of the ecological environment becoming more and more prominent in the world, the sustainable operation of enterprises is facing the most difficult choice in history. For each responsible enterprise, it is crucial to choose the market power expansive strategy that can improve the realistic viability or the technological innovation strategy that can improve the future development potential. This is of great significance to reduce the negative external effects of the corporate social environment and ensure their sustainable development. In this paper, we select the data of 18 large listed petrochemical companies from 2003 to 2018 as samples and construct a linear regression model for empirical analysis. Meanwhile, we put forward more practical business management strategies for the sustainable development of petrochemical enterprises in developing countries in further research.