In order to analyze the spatial distribution characteristics of the cultural landscape of the Yangtze River (Nanjing section) and show the role of the Yangtze River culture in promoting regional economic development and cultural radiation, Based on the Knowledge graph technology and 3S technology, this paper conducts geographical positioning and spatial analysis of the Yangtze River cultural landscape in Nanjing, and analyzes the surrounding environment by combining remote sensing images and topographic data. Researches show that: The Yangtze River cultural landscape in Nanjing includes 74 landscape points of seven landscape types, and the distribution of landscape points shows a clustering trend, but the spatial distribution and aggregation degree of different types of cultural landscapes are different. Due to the influence of climate environment and water resources distribution, the surrounding cultural landscape has a low altitude and high vegetation coverage, showing obvious distribution characteristics along the river. This study is helpful to improve the coordination degree between cultural landscape protection and planning management, and can provide useful reference for the protection of cultural landscape of the Yangtze River.

Innovative strategies to control malaria are urgently needed. Exploring the interplay between the Plasmodium sp. parasites and host red blood cells (RBC) offers opportunities for novel antimalarial interventions. Pyruvate kinase deficiency (PKD), characterized by heightened 2,3-diphosphoglycerate (2,3-DPG) concentration, has been associated with protection against malaria. Elevated 2,3-DPG levels, a specific mammalian metabolite, may hinder glycolysis, prompting us to hypothesize its potential contribution to PKD-mediated protection. We investigated the impact of the extracellular supplementation of 2,3-DPG on the Plasmodium falciparum intraerythrocytic developmental cycle in vitro. Results showed an inhibition of parasite growth, resulting from significantly less progeny from 2,3-DPG-treated parasites. We analyzed differential gene expression and the transcriptomic profile of P. falciparum trophozoites, from in vitro cultures submitted or not submitted to the action of 2,3-DPG, using Nanopore Sequencing Technology. The presence of 2,3-DPG in the culture medium was associated to a significant differential expression of 71 genes, mostly associated to GO terms nucleic acid binding, transcription, or monoatomic anion channel. Further, several genes related to the cell cycle control were downregulated in treated parasites. These findings suggest that the presence of this RBC-specific glycolytic metabolite impact the expression of genes transcribed during the parasite trophozoite stage and the number of merozoites released from individual schizonts, which supports the potential role of 2,3-DPG in the mechanism of protection against malaria by PKD.

Virtual Reality (VR) technology in education has the potential to revolutionize the Indian school education system. This research study investigates the present state of VR adoption, perceived benefits, concerns, and future expectations among both students and educators. The survey-based approach collected responses from 45,000 students and 2,000 educators across a diverse range of schools in India. The findings highlight a mixed current landscape with significant room for expansion in VR utilization. Both students and educators express optimism regarding the benefits of VR, recognizing its capacity to enhance engagement, comprehension, and motivation in the learning process. However, challenges, including budget constraints, the need for training and support, and concerns about student safety, must be addressed to effectively integrate VR into education. Expectations for the future emphasize inclusivity, accessibility, and customized learning experiences. The research underscores the transformative potential of VR in Indian education while emphasizing the necessity of addressing practical challenges for its successful implementation.

Efficient traffic management at signalized intersections is integral to urban infrastructure development, requiring accurate estimation of delay times to mitigate congestion and enhance overall transportation systems. Traditional methodologies, including empirical observations and microsimulation software, have been prevalent in assessing delay times; however, their limitations have prompted the exploration of novel technologies like LiDAR (Light Detection and Ranging) sensors. This research study investigates and compares the accuracy of delay time estimations obtained from LiDAR sensor technology with those derived from microsimulation in AIMSUN. LiDAR sensors, known for their high-resolution, real-time data collection capabilities, offer a promising avenue for precise measurement of delay times at signalized intersections. Nonetheless, challenges in sensor placement, environmental influences, and data processing complexities suggest the need for further development and validation. In parallel, microsimulation software, exemplified by AIMSUN, provides a virtual platform for scenario testing but relies on assumptions that may not always mirror real-world traffic dynamics accurately. The comparative analysis conducted in this study aims to critically examine the discrepancies and potential complementarity between delay times obtained from LiDAR sensor technology and those derived from microsimulation in AIMSUN. The research involves an in-depth evaluation of real-time, high-resolution data collected by LiDAR sensors, assessing their accuracy in capturing the intricate movements and behavior of vehicles at signalized intersections. Simultaneously, AIMSUN microsimulation delay time models are scrutinized for their ability to accurately replicate these observed delay times. The disparities identified serve as critical insights into the challenges of both methodologies, prompting the discussion on the prospects of integrating LiDAR-derived data and microsimulation calibration processes to enhance the precision and reliability of delay time estimations. Future traffic management strategies can significantly benefit from a more accurate understanding of delay times, and this study endeavors to contribute to the advancement of methodologies in traffic engineering for more effective urban transportation systems.The paper's findings illuminate the potential and limitations of both LiDAR sensor technology and microsimulation in estimating delay times at signalized intersections. The results highlighted that the LiDAR sensors could accurately calculate delay times at a signalized intersection. Furthermore, the calculated delay time differences by LiDAR and AIMSUN at three days with the highest vehicle volumes (counts) are always less than 6.5%.

This study investigates the application of Light Detection and Ranging (LiDAR) sensor technology for data collection at signalized intersections characterized by a high rate of traffic crashes. The research aims to provide valuable insights into the potential of LiDAR-based data analysis to enhance road safety and traffic management at signalized intersections. The research methodology involved the deployment of LiDAR sensors at Marlboro Pike & Brooks Dr. signalized intersection in Coral Hills, Maryland. Two LiDAR sensors installed in this intersection to collect high-resolution, three-dimensional data of the intersection area from June, 1^st to July, 7^th 2023. The data included information on vehicle trajectories, speeds, and behaviors, as well as pedestrian and cyclist movement patterns. Concurrently, historical traffic crashes recorded and traffic flow data were obtained for the same intersection.The analysis of LiDAR data involved several key aspects including LiDAR data allowed for a precise evaluation of traffic flow patterns, including congestion points, traffic volume fluctuations, and peak-hour behavior. This information provided insights into potential factors contributing to crashes. By analyzing LiDAR data, the study identified near-miss incidents, which are often precursors to actual crashes. This proactive approach could assist in identifying crash-prone areas within the intersection. The LiDAR data analysis also focused on pedestrian and cyclist movements, including jaywalking and bike lane usage. The aim was to identify areas where infrastructure improvements could enhance safety for vulnerable road users. LiDAR data was compared with historical crash data to identify specific locations within the intersection that exhibited a high frequency of crashes. This information can guide targeted safety interventions. Last but not least, the study explored opportunities to optimize traffic signal timings based on real-time traffic data from LiDAR. Adaptive signal control could help mitigate congestion and reduce the risk of crashes.The results of this study demonstrated the potential of LiDAR sensor technology in collecting detailed data for traffic analysis in signalized intersections. By combining LiDAR data with historical crash records and traffic flow data, traffic engineers and urban planners can develop evidence-based strategies to reduce the frequency and severity of crashes in high-risk areas. Ultimately, this research contributes to a comprehensive understanding of how LiDAR technology can be employed to enhance road safety and traffic management, providing valuable insights for traffic engineers, urban planners, and policymakers seeking to improve the safety and efficiency of signalized intersections with a history of high traffic crashes.

Traffic congestion is a persistent and challenging problem in urban areas, leading to increased travel times, fuel consumption, and environmental pollution. Signalized intersections play a pivotal role in regulating traffic flow, and their efficiency has a direct impact on the overall traffic performance of a city. This study investigates the effect of traffic signal in managing traffic volume and reducing congestion and delays at signalized intersections through a comprehensive analysis of existing research, data collection, and simulations.The research begins by analyzing the traffic characteristics by an installed LiDAR sensor at E Cold Spring Ln – Hillen Rd intersection in Baltimore City, MD. When the signal at this intersection stopped working for some hours during a working day in September 2023, the LiDAR recorded vehicle and pedestrian counts, vehicle-vehicle and vehicle-pedestrian conflicts, and jaywalking events conflicts. The research aims to assess the impact of traffic signal failures on traffic flow, congestion, safety (V2V and V2P conflicts), and the frequency of jaywalking events before, during, and after improper performance of the traffic signal. Furthermore, this study explores the factors influencing traffic signal performance, including traffic demand, geometric layout, pedestrian interactions, and the integration of emerging technologies. The analysis results highlighted the importance of signal control systems existence at this intersection that can adjust signal timing in response to changing the real-time traffic conditions.Reduced congestion, minimized delays, and enhanced traffic flow are observed outcomes, contributing to a more sustainable and efficient urban transportation system. However, it is crucial to consider the trade-offs and challenges associated with traffic signal optimization, such as the potential for increased travel times for certain modes of transportation and the need for ongoing maintenance and updates. In conclusion, this study underscores the pivotal role of traffic signals in managing traffic volume and reducing congestion and delays at signalized intersections. Through evidence-based analysis and innovative signal control strategies, urban planners and transportation authorities can work towards creating more efficient, sustainable, and less congested transportation networks. The insights derived from this research can inform policy decisions and guide the development of future traffic management solutions, ultimately leading to improved quality of life in urban areas.

Robotics and autonomous technologies enable space travel. Robotics change space colonization. We study space-based robotics. Human-centric missions need robotics. Vision, decision-making, movement, and manipulation follow. These developments influence resource utilization, extravehicular activities, planetary surface exploration, long-duration space missions, and colonization. Robots improve research, productivity, and astronaut safety but present problems. Highlighting research and knowledge gaps. Space ethics, human-robot interaction, and failure recovery are gaps. This extensive study showed how robots and autonomous systems may transform space exploration and colonization. Researchers, engineers, and mission planners may benefit. Robotics and autonomy will improve space exploration.

This article explores how digitalisation is impacting the hospitality industry and assesses the evolving role of Information Technology (IT) strategy in the digitalisation process. The research approach is qualitative and inductive, based on six in-depth interviews with senior IT professionals in the hospitality industry. Findings indicate significant differences in the role of IT strategy in guiding digitalisation in the companies studied. The depth of information provided by the interviewees supports the development and application of a model that profiles the companies regarding their degree of digitalisation and technology integration. Analysis of interview material allows the identification of key properties for successful digitalization: process agility, workforce adaptability, and technology manageability, along with a clear data culture and ensured cybersecurity. However, disparate systems and technologies, and a lack of data integrity, are key issues that leave hospitality companies with difficult choices in progressing digitalisation initiatives. The applied model and identification of key properties for successful digitalisation contribute to the development of related theory and can also be used as a reference point for senior IT professionals working in the industry.

Findings primarily drawn from literature review and interviews with professional resource persons suggest that although the RMG industry of Bangladesh has made substantial progress in correcting structural risks within factory buildings, fire still remains an unresolved issue posing unceasing threat to safety. These findings are significant for all stakeholders within the global supply chain network of Bangladesh, concerned with improving sustainability of the RMG industry and seeking to outline the responsibilities for each group of actors towards preventing building disasters. Both Tazreen Fashion fire incident and the Rana Plaza building collapse served as ‘critical junctures’ in rapid transfer of physical technology to enhance structural safety and streamline production planning within the RMG manufacturing factories within Bangladesh. However, the transfer of social technology within the supply chain network of a developing nation in areas such as development of organisational safety culture or promoting workplace ethics, requires long-term planning and prolonged practices. The paper thus concludes that in developing countries, transfer of physical technology is more readily achievable than the adoption of social technology.

Global climate change and associated environmental extremes present a pressing need to understand and predict social-environmental impacts while identifying opportunities for mitigation and adaptation. In support of informing a more resilient future, emerging data analytics technologies can leverage the growing availability of Earth observations from diverse data sources ranging from satellites to sensors to social media. Yet, there remains a need to transition from research for knowledge gain to sustained operational deployment. In this paper, we use the Wisdom-Knowledge-Information-Data (WKID) Innovation framework to inform solutions-oriented science in an integrated Research to Commercialization (R2C) model that explores market viability for value-added analytics. We conduct a case study using this R2C model to address the wicked wildfire problem. By integrating WKID and human centered design (HCD), through an industry-university partnership called the Climate Innovation Collaboratory between the University of Colorado Boulder and Deloitte Consulting, we systematically evaluated 39 different user stories across 8 user personas and identified common gaps, how to define information technologies that add value, and how to develop a marketable product. This R2C model could enable transition of knowledge to operational implementation informing policy and decision makers, tasked with addressing some of our most challenging environmental problems.

The global prevalence of insulin resistance (IR) is increasing continuously, influencing metabolic parameters and fertility as well. The metabolic changes due to IR can alter the molecular composition of plasma and other body fluids. Follicular fluid (FF) is derived mainly from plasma, and it is a critical microenvironment for the developing oocytes. It contains various metabolites and amino acids, and the quality of the oocytes is linked at least partially to amino acid metabolism. Our goal was to determine quantitatively the amino acid (AA) profile of FF in IVF patients and to compare IR and non-insulin resistance (NIR) groups to investigate the AA changes in their FF. By UHPLC-based method we quantified the main 20 amino acids from human FF samples in the IR and NIR groups. Several amino acids (aspartate, glycine, glutamate, and cysteine) differed significantly (p<0.05 or less) between the two groups. The most significant alterations between the IR and NIR groups were related to the glutathione metabolic pathway involving glycine, serine, and threonine. Since insulin resistance alters the amino acid composition of the FF, the oocytes may undergo metabolism-induced changes resulting in poor oocyte quality and less fertility in the insulin resistance groups.

Bridging the gap between traditional education and matching the pace of education with the rest of the world, Govt. of India implemented a new education policy this year which was much awaited for a long time. The new education policy is a big step to change India's overall education scenario by changing the examination pattern. However, this new type of decision-making process seeks to ensure that it achieves great benefits covering all uncovered elements while keeping technology as a parameter, so this new policy in the previous education system is also missing some key issues that must be addressed in the next amendments. Making it an example of impact, this paper describes salient issues where new educational policies are silent or those grey areas have been only superficially touched upon.

Brewers’ spent grain (BSG) is an important waste produced in beer companies with a high po-tential to be transformed into commercial by-products. The present paper reports a forecasting technology study with the aid of bibliographic review and patent analysis tools aiming to in-vestigate the maturity of certain technologies, considering the use of BSG on a closed-loop bio-refinery and circular bioeconomy concept integrated into a brewery. To evaluate the possibili-ties of production of high-added value products in Brazil, it was presented an overview of BSG’s scientific, technological, and marketing products and applications. The comparison between numbers of articles versus patents shows that the solutions proposed by research articles are not being transformed into maturated viable technologies. The results suggest that there is a gap between the scientific research in the institutions and their applications in industry, which lead to the destination of the BSG for more economically attractive investments when compared to research in Brazil. Ultimately, from the carried-out analysis, it was possible to propose a brew-ing process connected to the biorefinery system, showing the possibility to the newly arising brewery industries.

Rooftop solar (RTS) projects have the potential to contribute to climate change mitigation and sustainable development objectives. In India, grid-connected RTS capacity has been targeted at 40 GW by the end of the year 2022 however, the installed capacity is limited to 8.2 GW only. As a result, the country missed its 2022 target of installing 100 GW of solar power capacity, largely due to inadequate uptake of RTS. The prevailing practices of RTS implementation is observed to be complex, repetitive, tedious, and time-consuming for potential consumers and there is a lack of coordination among implementing agencies. Therefore, even with vast potential, supportive measures, dedicated policies, and regulations the penetration of RTS systems is far below their respective potential. The introduction of information technology (IT) intervention in the RTS sector would integrate key stakeholders at a single platform so as to reduce the administrative burden of implementing agencies, optimization of processing time, handle multiple consumers simultaneously, and connect consumers with authentic vendors, etc. This would help them to understand and perform their shared roles and responsibilities and enhance the RTS implementation across the state. In this study, the scope for IT interventions in the existing RTS implementation process of the Odisha Renewable Energy Development Agency (OREDA) has been assessed and a simplistic approach has been developed for the execution of the RTS projects in relatively lesser time with the least human interface as well as resources. This approach has been successfully demonstrated with OREDA and a cumulative capacity of around 5 MWp (individual project of 1-2 kWp) residential grid-connected RTS projects implemented through the web platform. Currently, other state nodal agencies are also adopting the model for RTS execution and consumer proliferation through IT interventions.

There are increasing calls in education for deeper integration of disciplines and better preparation for the personal and job challenges of a fast-changing and smarter society. Thus, we need to search for new effective didactic strategies. However, current classrooms are isolated. They practically never connect. This hinders the exchange of ideas. It inhibits imitation and recombination, the basic blocks of cultural evolution and innovation. In this paper, we analyze online inter-class tournaments. These are lessons where entire elementary or middle school classes interconnect synchronously and play an educational game. These are new types of academic activities, and only possible thanks to digital communication technology. In this paper, we examine four online tournaments, we analyze how feasible it is to carry them out and the benefits they bring. One tournament is for teaching machine learning and statistics. The second one teaches the conservation of momentum in physics and an engineering optimization challenge. The third tournament is for learning to solve word problems. The fourth one is for teaching natural and sexual selection along with developing statistical and population thinking. We found that these inter-class tournaments are feasible to implement in schools and that they are a promising mechanism to facilitate imitation, recombination, and innovation of teaching strategies.

This study aimed to identify the influencing factors that drive the adoption of smart construction technologies by highway construction companies. Using expert interviews and expert scoring, interview data were collected from 25 experts in the field, and the TOSE framework was proposed based on the TOE framework, identifying four dimensions and fourteen influencing factors. The results were analyzed using the Fuzzy-DEMATEL-ISM method, and the findings were then summarized according to the evaluation criteria to determine the validity of the fourteen hypotheses and the extent to which they drive the adoption of intelligent construction technologies by motorway construction companies. The findings of this paper will be of great value to decision-makers and participants in highway construction companies, as well as to other companies in the construction industry, in their decision to adopt smart construction technologies.

This study evaluated the use of filtration and UV-A photocatalysis for the reduction of particulate matter (PM) and airborne bacterial pathogens in swine barns. Two MERV filters (8 and 15) were used to mitigate PM concentrations measured at the PM 1, PM 2.5, respirable PM, and PM 10 ranges. Filtration was also used to generate different levels of airborne pathogens to be treated by UV-A. Results show that MERV 8 and 15 filters effectively reduced PM concentrations (96-98%) in air exhausted from a swine barn (p ranged from < 0.01 to 0.04). UV-A photocatalysis did not mitigate PM concentrations. UV-A photocatalysis treatment reduced measured colony-forming units (CFUs) by 15-95%. The CFU percent reduction was higher when airborne PM concentration was low. The numeric results suggested a real mitigation effect despite p-values that did not meet the usual statistical cut-off of <0.05 for significance due to the large variability of the CFU control samples. Normalization of measured airborne pathogen concentrations by smaller PM size range concentrations led to emerging significant treatment differences for CFUs. A significant decrease (~60% reduction; p < 0.03) in the concentration of viable airborne bacteria was shown for all PM below the 10-micron range.

With the onset of the COVID19 pandemic, information technology has played a critical role in healthcare. A broad spectrum of information technology tools and applications played an essential role to create awareness of the COVID19 vaccination drive and its health benefits. We use the COVID-19 Global Beliefs, Behaviors, and Norms Survey for analysis of prevalence and factors associated with vaccination drives among men and women aged 20-80 years in 60 countries worldwide. Our analysis of the global survey offers a unique perspective about the role of information technology associated with vaccination drives involving social norms and human behavior among 437,236 respondents. The international survey was organized using a pre-registered randomized experiment demonstrating the role of technology in reaching out to people based in diverse communities and evaluating their beliefs, behavior, and social norms. The study shows that vaccine acceptance can vary due to descriptive norms. Our analysis shows 65.06% of people all over the globe are willing to get vaccinated and a large proportion of the population thinks that the COVID19 pandemic is a viable threat to the community and preventive measures need to be taken including vaccination drives.

The global coronavirus (COVID-19) pandemic has created a whole new set of risks in construction industries generating unprecedented delays, disruptions, and uncertainty on construction projects, and has forced the industries in adopting more sophisticated technologies while combating the reduced workforce on job sites. Further, the post-pandemic era of construction is expected to be a lot different as the industries will embrace the technology as the augmentation and collaboration strategy. Thus, it will be extremely hard to sustain for construction industries in the absence of effective risk management. The existing risk plans need to be inspected for their capability of handling new risks arising from COVID-19 and the project managers will need to make the necessary revisions as needed. This paper discusses on past (NORM), present (NEW NORM), and future (Post COVID-19 NORM) of the construction industry and highlights key strategies for managing projects and construction risks during and post COVID-19 pandemic.

Social media HPV vaccination interventions show promise for increasing HPV vaccination rates. An important consideration for the implementation of effective interventions into real-world practice in the translation potential, or external validity, of the intervention. To this end, we conducted a systematic literature review to describe the current body of evidence regarding the external validity of social media HPV vaccination-related interventions. Constructs related to external validity were based on the RE-AIM (reach, effectiveness, adoption, implementation, maintenance) framework. Seventeen articles published between 2006 and 2020 met inclusion criteria. Three researchers independently coded each article using a validated RE-AIM (reach, effectiveness/efficacy, adoption, implementation, maintenance) framework. Discrepant codes were discussed with a fourth reviewer to gain consensus. Of these 17 studies, three were pilot efficacy studies, 10 were RCTs to evaluate effectiveness, one was a population-based study, and three did not explicitly state which type of study was conducted. Reflecting this distribution of study types, across all studies the mean level of reporting RE-AIM dimensions varied with reach recording 90.8%, effectiveness (72.1%), adoption (40.3%), implementation (45.6%), and maintenance (26.5%). This review suggests that while the current HPV vaccination social media-driven interventions provide sufficient information on internal validity (reach and effectiveness), few have aimed to gather data on external validity needed to translate the interventions into real world implementation. Our data suggest that implementation research is needed to move HPV vaccination-related interventions into practice. Included in this review are recommendations for enhancing the design and reporting of these HPV vaccination social media-related interventions.

This article presents a quantitative assessment of pedagogical support aimed at improving collaborative education at a modern technical university. The article analyzes the structural composition of the universal communicative competence in a foreign language to identify the advantages of the proposed content detailization. An algorithm for constructing educational and speech actions of students with the use of collaborative digital technology, regarding the monitoring and control of tools, is developed and theoretically justified. Microsoft Teams is offered as a platform for implementing digital collaborative learning technology. The didactic possibilities and methodological functions of Microsoft Teams in foreign language teaching are revealed. The digital technology of the collaborative learning algorithm is relevant for building collaborative actions is relevant, since it contributes to the development of the ability to solve common professional tasks. The algorithm of the dialogic communication, including problem, contradiction, conflict, intellectual difficulty, having general professional context as a stimulus to enhance the interaction in pair work is proposed as pedagogical support. The analysis and quantitative assessment of students' oral responses showed that the dialogue in a foreign language, based on the algorithmic component, is more structured and stimulates students' communication on relevant professional-oriented topics.

Ovarian hypofunction or primary ovarian insufficiency (POI) is a common cause in the etiology of female infertility. It is a heterogeneous disorder, affecting approximately 1% of women before the age of 40. The characteristics of POI are menstrual disorders, including amenorrhea and delayed menstruation, accompanied by a raised gonadotrophin level and decreased estradiol level. In recent years, electrophysiology (EP) technology has been advancing rapidly in the diagnosis and treatments of numerous diseases. According to studies, bioelectrical stimulation (BES) therapy is an electrophysiology technology that plays significant roles in numerous diseases, including on the thin endometrium in patients with POI. In this review, the overall research progress of this electrophysiological technology has been discussed in relation to the advancement of primary ovarian insufficiency.

Circulating tumor cells (CTC) and circulating tumor microemboli (CTM) have been shown to correlate negatively with patient survival. Actual CTC counts before and after treatment can be used to aid in prognosis of patient outcomes. The presence of circulating tumor materials (CTMat) can advertise the presence of metastasis before clinical presentation, enabling early detection of relapse. Importantly, emerging evidence is indicating that cancer treatments can actually increase the incidence of CTCs and metastasis in pre-clinical models. Subsequently, the study of CTCs, their biology and function are of vital importance. Emerging technologies for the capture of CTC/CTMs and CTMat are elucidating vitally important biological and functional information that can lead to important alterations in how therapies are administered. This paves the way for the development of a “liquid biopsy” where treatment decisions can be informed by information gleaned from tumor cells and tumor cell debris in the blood.

The aim of this study was to determine the impact of information technology in management of risks in the capital market-listed company is in Tehran Stock Exchange. The purpose of the present study is an applied descriptive approach. The target population for the survey, companies that from 2009 to the first half of 2015 have been a member of the Tehran Stock Exchange, through Cochranʼs sample size of 140 companies, respectively. We used cluster sampling method. In order to collect data from two questionnaires: risk management questionnaire Foakeh (2013) has 38 items and a standard questionnaire Chanvyas (2006) has 40 items, the whole five-item Likert scale questionnaire is above has been used. Data gathered through the questionnaire, sign the application was 21spss. For inferential analysis of the variables and to analyze the data from different statistical tests and regression was used Kolmogorov-Smirnov test. The results showed that information technology on risk management and its dimensions (primary market risk, market risk and the risk of secondary non-financial) impact.

Plasma being the fourth and most abundant form of matter extensively exists in the universe in the inter-galactic regions. It provides an electrically neutral medium of unbound negative and positive charged particles, which has been produced by subjecting air and various other gaseous mixtures to strengthen the electromagnetic field and by heating compressed air or inert gasses for creating negative and positive charged particles known as ions. Nowadays, many researchers are paying attention to the formation of artificial Plasma and its potential benefits for mankind. The literature is sparsely populated with the applications of Plasma. This paper presents specific methods of generation and applications of Plasma, which benefits humankind in various fields, such as in electrical, mechanical, chemical and medical fields. These applications include hydrogen production from alcohol, copper bonding, semiconductor processing, surface treatment, Plasma polymerization, coating, Plasma display panels, antenna beam forming, nanotechnology, Plasma Torch, Plasma pencils, low-current non-thermal Plasmatron, treatment of prostate cancer, Plasma source ion implantation, cutting by Plasma, Plasma etching, pollution control, neutralization of liquid radioactive waste, etc. Resultantly, worth of Plasma technology in the medical industry is increasing exponentially that is closing the gap between its benefits and cost of equipment used for generating and controlling it.

Agricultural product like cassava produces huge amounts of waste when processed to consumable goods. The waste generated is generally considered to contribute largely to environmental pollution. This study therefore investigates the waste management practice that is adopted by cassava processors in Ogun State, Nigeria. Five (5) Local Government Areas (LGAs) dominant in processing cassava were selected for the study on the basis of spatial location distribution; landmass and population. The survey involved the use of structured questionnaires administered to cassava processors of the selected LGAs. The Statistical Package for Social Sciences (SPSS) software application and descriptive statistics were used for data analysis. Results of the analysis show that majority (70%) of the cassava processors are females. Cassava peel constitutes 10% of the waste produced, of which 91% are heaped at refuse dump in most communities. Results also reveal that 86.3% of cassava residues are used for animal feeds. Other findings show that the peels when dried are used as bio-fuel for cooking and there is a significant potential for biogas production. From the data captured from respondent during the study, most processors are willing to pay for an improved waste management system. The study therefore suggests proper waste management of cassava waste to minimize environmental pollution.

While the mobile phone is the world’s most popular media device, it is actually not one single medium, but is effectively used as a different medium by different user groups. The article characterizes polymodal differences in mobile apps usage among different user groups, including gender, education, occupation, screen size, and price. We monitored the complete app usage of 10,725 smartphone users for one month each (56 million sessions, recording almost 1 million hours). Our key contribution consists in developing and analyzing a theoretical framework to classify the over 16,000 apps used into five categories. Exploring nine research questions we provide a broad characterization by asking who, with which characteristics, uses which kinds of apps in what extensity and intensity? For example, it is not the young and high occupational grades that use the mobile phone as a human-to-machine computer (including gaming and artificial intelligence tools). Large screen size is related to extensive long sessions, while a small screen size is related to intensive frequent usage. The results go beyond providing ample empirical evidence for the inherently polymodal nature of the mobile phone, but also proposes a framework on how to possibility deal with it analytically.

As a result of decades of austerity, the economies of the Eurozone are experiencing under-investment and crumbling infrastructures in an era of extremely severe emergencies as the cli-mate change and aggressive global competition. The private savings glut of the rich and the strict fiscal rules suggest a crowding-in approach in partnership with big finance in a new age of in-fra-structures. If governments mint public infrastructures into investable assets, they can gen-erate steady returns for investors and asset managers who look after pensions and insurances schemes and unlock trillions now devoted to welfare state. For the big finance to accept to be partner, however, governments must take the task of de-risking returns. Innovation technology and macro-financial literacy can synergically act to enhance this new de-risking role to address in a financially sustainable way the intense phenomena of Natural Hazards (NHs) that can severely compromise economic growth. This is precisely the aim of our Public-Private Partnership (PPP) among the Department of Economics, Management and Institutions of the University of Naples and a Knowledge Transfert Management, the Department of Engineering and the Aca-demic Spin-Off “STRAIN”, of the University of Campania. Our PPP has been contributing to the eval-uation and mitigation of NHs such as floods, landslides and earthquakes since 2012. The ex-tremely advanced results of this multi-stakeholder partnership ensure a better knowledge of NHs which, as evidenced in the paper, is the fundamental input for the desired Public-Private In-surance Programmes (PIPPs).

(1) Background: The development of generative artificial intelligence (GAI) is transforming higher education. This systematic literature review synthesizes recent empirical studies on the use of GAI, focusing on its impact on teaching, learning, and institutional practices. (2) Methods: Following PRISMA guidelines, a comprehensive search strategy was employed to locate scientific articles on GAI in higher education, published by Scopus and Web of Science between January 2023 and January 2024. (3) Results: The search identified 102 articles, with 37 meeting the inclusion criteria. These studies were grouped into three themes: the application of GAI technologies, stakeholder acceptance and perceptions, and specific use situations. (4) Discussion: Key findings include GAI’s versatility and potential use, student acceptance, and educational enhancement. However, chal-lenges such as assessment practices, institutional strategies, and risks to academic integrity were also noted. (5) Conclusions: The findings help identify potential directions for future research, including assessment integrity and pedagogical strategies, ethical considerations and policy development, the impact on teaching and learning processes, perceptions of students and instructors, technological advancements, and the preparation of future skills and workforce readiness. The study has certain limitations, particularly due to the short time frame and the search criteria, which might have varied if conducted by different researchers.

The No. 3 coal seam in the Yuxi Coal Mine has a measured maximum gas content of 25.59 m3/t, along with a maximum gas pressure of 2.9 MPa, indicating its high risk to gas and outbursts. To mitigate outburst risks of the coal seam, the 1301 working face has been implemented gas pre-drainage measures by grid boreholes from underlying roadways. After one year of extraction, it was confirmed that the gas content at all 33 test sites was below 8 m3/t, meeting the outburst prevention standards. However, during subsequent coal tunnel excavation, the gas desorption index K1 value frequently exceeded the standard, resulting in numerous occurrences of abnormal gas emission or small-scale outbursts. To tackle the challenges associated with safe excavation following the first round regional outburst prevention measures, a research and industrial trial of CO2 gas fracturing(CO2-Frac) technology for secondary outburst prevention and rapid excavation was completed. Results show that the dual-hole and high-pressure (185MPa) CO2-Frac considerably contribute to outburst prevention. K1 exceedances per hundred meters of tunnel excavations were from average 2.54 without CO2-Frac to average 0.28 after the new technology being implemented, leading to a eight fold reduction. Additionally, the monthly excavation footage increased from average 81.64 m without CO2-Frac to average 162.42 m with CO2-Frac, resulting in a 2-fold improvement. The dual-hole and high-pressure CO2-Frac is an advanced technology for safe and efficient excavation for secondary outburst elimination in highly outburst-prone coal seams in the Yuxi Coal Mine, with potential for widespread application in similar coal seam conditions.

Background: Amidst escalating climate change concerns, sustainable practices in healthcare logistics are critical. This study evaluates the ecological impact and efficiency of medical sample transportation using drones, combustion cars, and electric cars across diverse terrains and weather in Liechtenstein and Switzerland. Methods: We conducted a comparative analysis of CO2 emissions, transport distances, and delivery times for each transportation modality. Data collection involved multiple runs under various conditions, with CO2 emissions measured using onboard systems, and transport efficiency assessed via GPS tracking and time monitoring. Results: Combustion cars exhibited the highest average CO2 emissions at 159.5 grams per kilometer (g/km). Electric cars emitted significantly less, averaging 3.43 g/km, which is 2.15% of combustion car emissions. Drones were the most environmentally friendly, with an average emission of 0.09 g/km, representing 0.07% of combustion car emissions and 2.6% of electric car emissions. Drones also showed substantial transport efficiency, covering 17% shorter distances on flat terrain and 24% shorter in mountainous areas, with time savings ranging from 13% to 80%. Conclusion: This study highlights the potential of drone technology to revolutionize healthcare logistics by reducing environmental impact and optimizing operational efficiency. Integrating drones can significantly lower the carbon footprint, improve sample integrity, and enhance patient care, promoting a greener, more resilient healthcare system.

This qualitative study explores the intricacies of building sustainable supplier relationships in the e-commerce sector, focusing on best practices and strategic approaches. Through in-depth interviews with procurement managers, supply chain experts, and supplier representatives, the research identifies four critical themes: trust, technology integration, ethical practices, and performance measurement. Trust is found to be the foundation of effective supplier relationships, fostering open communication and collaboration, which are essential for addressing challenges and co-creating solutions. The integration of digital technologies such as supply chain management software, blockchain, and the Internet of Things significantly enhances transparency, decision-making, and operational efficiency, providing a competitive edge. Ethical practices, including adherence to fair labor standards and environmental sustainability, are increasingly crucial as consumer and regulatory expectations evolve, necessitating alignment between e-commerce companies and their suppliers. Performance measurement and continuous improvement are vital for maintaining quality and efficiency, with clear metrics and regular evaluations driving constructive feedback and optimization of supply chain processes. The study underscores the interdependence of these elements in fostering resilient and adaptable supplier relationships. The findings offer practical guidance for e-commerce businesses and suppliers, emphasizing the need for a holistic approach to supplier management that balances trust, technology, ethics, and performance. This approach not only enhances operational effectiveness but also ensures the long-term sustainability of supplier relationships in the dynamic e-commerce landscape. The research contributes to the theoretical understanding of supplier relationship management, providing a comprehensive framework for future studies and practical applications in the e-commerce industry.

Agile procurement has emerged as a transformative strategy for organizations striving to maintain competitiveness in a rapidly evolving marketplace. This qualitative research investigates the implementation, benefits, challenges, and outcomes of agile procurement practices in supply chain management. Through semi-structured interviews and case studies across diverse industries, this study explores how agile procurement enhances organizational adaptability and responsiveness. Key findings reveal that agile procurement enables organizations to swiftly adjust strategies in response to market fluctuations and customer demands, fostering increased customer satisfaction and loyalty. The integration of advanced technologies, including AI and blockchain, facilitates real-time data analysis, optimizing procurement processes and enhancing supply chain efficiency. Organizational culture emerges as a critical factor in successful agile procurement, with leadership support and a collaborative environment driving cultural change towards agility and innovation. Despite its benefits, challenges such as resistance to change and the need for significant technology investments are identified, requiring careful change management and strategic alignment. Case studies illustrate the versatility of agile procurement across sectors, showcasing its role in enhancing operational efficiencies, innovation capabilities, and overall supply chain performance. In conclusion, agile procurement offers organizations a strategic framework to navigate complexities and uncertainties effectively, capitalizing on market opportunities while mitigating risks. Embracing agile principles fosters a resilient organizational culture capable of adapting to dynamic market conditions. Future research should focus on further refining agile procurement strategies to address emerging challenges and sustain competitive advantage in the global marketplace.

Aligning supply chain and marketing functions is crucial for high-tech startups aiming to successfully launch new products in competitive markets. This qualitative research explores the strategies, challenges, benefits, and best practices associated with supply chain and marketing alignment in high-tech startups. Through a detailed analysis of case studies and semi-structured interviews with industry professionals, the study identifies key insights into how startups can effectively integrate these functions to enhance operational efficiency, market responsiveness, customer satisfaction, and risk management. The findings reveal that successful alignment requires the formation of cross-functional teams, leveraging integrated technologies like CRM and ERP systems, establishing regular inter-departmental communication, and developing joint performance metrics. These strategies foster collaboration and ensure that supply chain and marketing efforts are coordinated towards shared goals. However, startups face challenges such as differing departmental objectives, resource constraints, communication barriers, and technological limitations, which hinder effective alignment. Benefits observed from effective alignment include improved operational efficiency through streamlined processes, enhanced market responsiveness to adapt quickly to changing demands, increased customer satisfaction by delivering products that meet market expectations, and better risk management through proactive identification and mitigation of supply chain and market risks. Best practices identified include fostering a culture of collaboration, investing in technology for data integration and transparency, aligning strategic objectives across functions, and continuously monitoring and adjusting alignment strategies. Integration of broader elements such as sustainability, entrepreneurship, emotional intelligence, marketing, and supplier relationship management further enriches the alignment framework. This study contributes to a deeper understanding of how high-tech startups can strategically align their supply chain and marketing functions to achieve competitive advantage and sustainable growth in dynamic market environments.

This qualitative research explores consumer perceptions of supply chain responsiveness and its impact on brand loyalty within the apparel industry. The study investigates how consumers perceive supply chain practices such as reliability, agility, and sustainability, and examines their influence on brand loyalty decisions. Thirty participants, representing diverse demographics and purchasing behaviors, were interviewed to gather insights into their awareness, expectations, and experiences related to supply chain responsiveness. Findings reveal that consumers prioritize supply chain reliability, expecting brands to consistently deliver high-quality products, accurate sizing, and timely responses to market trends. Sustainability practices also emerged as a significant factor, with consumers favoring brands that demonstrate ethical sourcing and environmental responsibility. Technology plays a crucial role in enhancing supply chain responsiveness, as consumers value real-time updates, personalized experiences, and seamless transactions. Moreover, the study underscores the impact of supply chain disruptions on brand trust and loyalty, highlighting the importance of resilience and contingency planning in supply chain management. Brands that effectively navigate disruptions through agile strategies can enhance consumer trust and loyalty, even in challenging circumstances. Overall, this research contributes to understanding the intricate relationship between supply chain dynamics, consumer perceptions, and brand loyalty in the apparel industry. It offers practical implications for apparel brands seeking to enhance consumer satisfaction, differentiate themselves in a competitive market, and foster sustainable growth through strategic supply chain management.

As the largest contributor of carbon emissions in China, the building sector currently relies mostly on enterprises’ own effort to report carbon emissions, which usually results in challenges related to information transparency and workload for regulatory bodies, who play an otherwise vital role in controlling the building sector’s carbon footprint. In this study, we established a novel regulatory model known as QCEPM (Quantitative Carbon Emission Prediction Model) by conducting multiple linear regression analysis using the quantities of concrete, rebar, and masonry structures as independent variables, and the embodied carbon emissions of a building as the dependent variable. We processed the data in the detailed quantity list of 20 multi-story frame-structure buildings and fed them to QCEPM for solution. Comparison of the QCEPM-calculated results against the time-consuming and error-prone manual calculation results suggested a mean absolute percentage error (MAPE) of 2.26%. Using this simplified model, regulatory bodies can efficiently supervise the embodied carbon emissions in multi-storey frame structures by setting up carbon quota for a project in its approval stage, allowing the construction enterprise to carry out dynamic control over the audited three most important building materials throughout a project’s planning and implementation phase.

The commercialization of historic streets constitutes a pivotal aspect of urban cultural heritage, and the comprehension of their visual perception serves as a valuable asset to urban planning and cultural conservation efforts. However, current research concerning the disparities in visual perception among diverse demographics within historic streets, as well as their spatiotemporal dynamics, remains insufficient. This study aims to utilize mobile eye-tracking technology to delve deeply into the visual perception characteristics of diverse demographics within commercialized historic streets, while also analyzing their spatiotemporal dynamics. We explore the disparities in visual perception of historic streets among groups with varying degrees of architectural knowledge and professional literacy. Through meticulous observation using mobile eye-tracking technology, we elucidate the visual perception patterns of different demographic characteristics through statistical analysis and spatiotemporal modeling. The findings reveal significant discrepancies in visual attention and perception among various groups. Participants with a higher understanding of architecture tend to focus more on architectural details and structures within the streetscape compared to those with a lower understanding, who exhibit greater interest in elements such as shops and signage. Moreover, during the process of perceiving the streetscape, participants’ eye movements transition from surrounding landscapes and historical edifices upon initial entry to the district, gradually shifting towards the commercial activities and distinctive architecture within the district. This study delves deeply into the visual perception characteristics and spatiotemporal dynamics of commercialized historic streets, providing invaluable insights for urban planning and cultural preservation endeavors. By revealing the impact of different demographic characteristics on the visual perception of historic streets, it offers new insights for urban planning and cultural heritage conservation.

Based on the goals of "high reliability, high frequency, rapid launch, and low cost" for space launch site, and drawing inspiration from the design principles of SpaceX's Starship launch test facility, an integrated dual-sided deflector system for convective cooling and thermal protection is presented. The interaction process between the gas jet and liquid water jet and its effect on the flow field environment are thoroughly studied using numerical calculation methods. Furthermore, Regarding the phase-change heat transfer issue in a compressible gas-liquid two-phase flow and the varying distribution of different bubble shapes and sizes at the gas-liquid interface, a modified Lee model is derived. The rationality and accuracy of the phase-change mass-transfer coefficient values can be improved by adjusting the equivalent diameter and shape factor of the bubbles. The research results demonstrate that compared to the classical Lee model, the modified Lee model can achieve a higher numerical accuracy in predicting the heat and mass transfer processes in gas-liquid two-phase flows. Through comparative analysis with traditional dual-sided deflector and conventional cooling system, the integrated dual-sided deflector system for convective cooling and thermal protection exhibits significant performance advantages in gas flow regulation, flow field environment improvement and erosion protection in the near-ground region of the launch site. Particularly, regarding the thermal environment of the dual-sided deflector, it not only achieves effective flow deflection, but also mitigates the degree of erosion caused by the gas jet on the deflector. This conclusion can provide theoretical references for the thermal protection design of commercial launch vehicle system at space launch site.

Eco-agricultural technology is crucial to alleviating agricultural resource scarcity and environ-mental pressures. However, financial constraint affects its successful promotion. Digital finance has a significant impact on farmers, but existing research lacks an exploration of the impact of digital finance on farmers' adoption of eco-agricultural technology. This study focuses on Rice–Crayfish Co-cultivation Technology as an example. It utilizes survey data from 1,063 households in China. An Endogenous Switching Probit model is employed to solve self-selection bias. The results reveal several key findings. First, the average treatment effect on the treated is 51.5%. This indicates that if farmers who use digital finance were to stop using it, the probability of adopting rice–crayfish co-cultivation technology would decrease by 51.5%. Therefore, digital finance is beneficial for farmers in adopting this technology. Second, heterogeneity analysis reveals that digital finance has a greater promoting effect on older farmers, those with lower education levels, and higher proportions of agricultural income. This suggests a greater reliance on digital financial services among vulnerable groups. Third, digital finance promotes farmers' adoption of rice–crayfish co-cultivation technology by alleviating financial constraints, expanding information channels, and increasing social capital accumulation. Overall, the findings offer valuable insights for for-mulating supportive policies.

he paper offers an innovative cooking utensil design for remote, isolated, and even peri-urban communities at a low price, with high reliability and simple construction. It can alleviate energy poverty and improve food security. This utensil uses only local solar energy directly and allows comfortable indoor cooking. This paper provides the design principles of a solar cooker/frying pan or generic heater, based on a PV panel or a plurality of them, which are directly connected to a plurality of Positive Thermal Coefficient (PTC) resistors to match the power. PTCs are nowadays produced in massive quantities and are widely available at low cost. The proposed device does not require an electronic controller or a battery for its operation. The aim is for family use, although the design can be easily scaled to a larger size or power, maintaining its simplicity. Electric heating inside or attached to the cooking pot, plus the temperature self-limiting effect of PTCs, allows for thermally insulating the cooking pot from its outside using ordinary materials. Insulation en-hances energy efficiency during cooking and keeps cooked food warm for a long time. Clean development would receive a significant impulse with its application. A simple mathematical model describes its functioning and states guidelines for adequate design. The results indicate a successful proof of concept and high efficiency both for water and oil as representatives of cooking.

This paper presents a comprehensive study on the application and optimization of automotive thermoelectric generators (ATEGs), focusing on the crucial role of heat exchangers in enhancing energy conversion efficiency. Recognizing the substantial waste of thermal energy in internal combustion engines, our research delves into the potential of TEGs to convert engine waste heat into electrical energy, thereby improving fuel efficiency and reducing environmental impact. We meticulously analyze various heat exchanger designs, assessing their influence on the TEG's output power under different exhaust gas flow rates and temperatures. Furthermore, we explore the impact of TEG material properties on the overall energy conversion effectiveness. Our findings reveal that specific heat exchanger designs significantly enhance the efficiency of waste gas heat exchange, leading to an improved performance of the TEG system. We also highlight the importance of thermal insulation in maximizing TEG output. This study not only contributes to the ongoing efforts to develop more sustainable and efficient vehicles but also provides valuable insights into the practical application of thermoelectric technology in automotive engineering. Through this research, we aim to pave the way for more environmentally friendly transportation solutions, aligning with global efforts to reduce fossil fuel dependence and mitigate environmental pollution.

The feasibility of recovering bioactive antioxidants from Phyllantus emblica leaves using ethanol -water mixture (0 – 100%) and heat-assisted extraction technology (HAE-T) was investigated in this present study. To this effect, the process parameter of operating temperature (OT: 30 -50 oC), solid -to-liquid ratio (S:L: 1:20 - 1:60 g/mL) and extraction time (ET: 45 - 180 min) were investigated on the extract total phenolic content (TPC, mg GAE/g d.w), yield (EY, %) and antioxidant activity (μM AAE/g d.w) by employing the Box-Behnken experimental design (BBD) available in response surface methodology (RSM). Multi-objective process optimization using the desirability function algorithm to determine set of process variables that simultaneously optimize process responses of TPC, EY and AA was also investigated. The recovery process was thereafter modeled with BBD-RSM and multi gene genetic programming (MGGP) algorithm and model reliability assessment via Monte Carlo simulation were conducted for the best performing set of models for predicting TPC, EY and AA values. The HPLC characterization of the recovered extract was carried out to ascertain the phenolic compound constituents of the Phyllantus emblica leaf extract. The 50% ethanol solution was found to be the best for the optimal extraction of antioxidants from Phyllantus emblica leaves. The HAE-T was suitable for recovering bioactive extract from Phyllantus emblica leaves and investigated process parameters have impacts on the recovery process. The process parameters that simultaneously gave the optimum EY of 21.6565%, TPC of 67.116 mg GAE/g and AA of 3.68583 µM AAE/g were OT of 41.61 oC, S:L of 1:60 g/mL and ET of 180 min. The HPLC extract profiling revealed that the bioactive constituents present in the recovered extract were betulinic acid, gallic acid, chlorogenic acid, caffeic acid, ellagic acid, and ferulic acid. Both the developed BBD-RSM and evolved MGGP-based models predicted the observed process response of TPC, EY and AA satisfactorily with BBD-RSM models marginally better in their predictions. The reliability results showed that the BBD-RSM models predicted TPC, EY and AA values with high certainty of 99.985%, 97.569% and 98.661%, respectively.

Cancer is the second major cause of disease-related dead worldwide, and its accurate early diagnosis and therapeutic intervention are fundamental for saving the patient’s life. Cancer, as a complex and heterogeneous disorder, results from disruption and alteration of a wide variety of biological entities, including genes, proteins, mRNAs, miRNAs, and metabolites that eventually emerge as clinical symptoms. Traditionally, diagnosis is based on clinical examination, blood tests for biomarkers, histopathology of biopsy, and imaging (MRI, CT, PET, US). Additionally, omics biotechnologies help to further characterize the genome, metabolome, microbiome traits of the patient that could have an impact on the prognosis and patient’s response to the therapy. The integration of all these data relies on gathering of several experts and may require considerable time, and, unfortunately, it is not without the risk of error in the interpretation and therefore in the decision. Systems biology algorithms exploit Artificial Intelligence (AI) combined with omics technologies to perform a rapid and accurate analysis and integration of patient’s big data and support the physician in making diagnosis and tailoring the most appropriate therapeutic intervention. However, AI is not free from possible diagnostic and prognostic errors in the interpretation of images or biochemical-clinical data. Here, we first describe the methods used by systems biology for combining AI with omics and then discuss the potential, challenges, limitations, and critical issues in using AI in cancer research.

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 objective of this study was to compare the pathogens and susceptibilities of the current automated rule-based technology (RBT) antibiogram with one manually collected through chart review with additional rules applied. This study was a 2-year, retrospective cohort study and included all bacterial cultures within the first 30 days from patients admitted to a single Burn Center. The current RBT antibiogram served as the control and new antibiogram versions were created using additional rules and compared to the control. Six-hundred fifty-seven patients were admitted (61% excluded for lack of cultures). Fifty-nine percent had at least one hospital acquired risk factor with over one-third having recent illicit drug use and one-third having a recent hospitalization. Of the 410 cultures included, 57% were Gram-negative and half were from wound infections. Sensitivities were significantly different when comparing manual and the RBT version after including factors, such as days since admission, presence of hospital acquired risk factors, or previous antibiotic courses. Recommended empiric Gram-negative antibiotics changed from double coverage to a single β-lactam with > 90% susceptibility. The susceptibilities between first and subsequent courses were dramatically different. Before developing an antibiogram or interpreting the output, it is important to consider which automated criteria are utilized, especially for units with extended lengths of stay.

This study analyzes the academic performance of students from an official school in Bogotá (Colombia) who had asymmetric access to Information and Communication Technologies during the first year of the Covid-19 pandemic. The Classical Linear Regression Model is employed using data from a survey of a representative group of students in the year 2020. Results show technological gaps between students that are associated with asymmetric academic performance against students with limited or null access to the Internet and electronic devices. Results also show that, among students with permanent access to the Internet, women have better scores compared to men’s scores, which implies that women can achieve better academic results than men in virtual education. It is also noted that the sole access to an electronic device does not guarantee good academic achievements if there is no full access to the Internet, and if ICT-use skills have not been developed.

We investigate the effect of geopolitical risk on the returns of the Information Technology, Communication Services, and Consumer Staples sector firms within the S&P 500 index. We use the event study methodology and perform more than 17,000 regressions to provide empirical evidence at the sector level that geopolitical risk leads to different responses across these 3 sectors. The response of the Information Technology sector is negative for all event windows under study, except the one spanning 10 days prior to the geopolitical event and 10 days after. The Communication Services sector has positive returns as a result of geopolitical events for all event windows, except the one from the geopolitical event date and 5 days after. The Consumer Staples sector shows a negative impact on geopolitical risk for all event windows except the one from the geopolitical event date and 5 days after, demonstrating a negative correlation to the Communication Services sector.

An introductory course of Arka Dhyana, also known as Intuitive Meditation (IM), consisting of five sessions, was offered to an international audience via Zoom technology. Participants were shown how to connect to their deeper self, essence or soul by bringing their I-ego-awareness from the thinking mind, often associated with the frontal part of the brain, to 19 energetic stations in the body including the heart centre. In this limited study, evaluation was both process and outcome orientated and included HeartMath (HM) Inner Balance or emWave2 electronic technology to measure mean coherence and achievement before and after each session. A highly significant increase in both coherence and achievement in six participants was found, which was also reflected in a reported increase in wellbeing related to feelings in qualitative statements indicating changes in levels of consciousness and individual transformative experiences as predicted by the Theory of the Six Main Levels of Consciousness.

It is essential to mitigate gaseous emissions that result from poultry and livestock production to increase industry sustainability. Odorous volatile organic compounds (VOCs), ammonia (NH3), hydrogen sulfide (H2S), and greenhouse gases (GHGs) have detrimental effects on the quality of life in rural communities, the environment, and climate. This study's objective was to evaluate the photocatalytic UV treatment of gaseous emissions of odor, odorous VOCs, NH3, and other gases (GHGs, O3 – sometimes considered as by-products of UV treatment) from stored swine manure on a pilot-scale. The manure emissions were treated in fast-moving air using a mobile lab equipped with UV-A and UV-C lights and TiO2-based photocatalyst. Treated gas airflow (0.25 to 0.76 m3/s) simulates output from a small ventilation fan in a barn. Through controlling the light intensity and airflow, UV dose was tested for techno-economic analyses. The treatment effectiveness depended on the UV dose and wavelength. Under UV-A (367 nm) photocatalysis, the percent reduction of targeted gases was up to i) 63% of odor, ii) 51%, 51%, 53%, 67%, and 32% of acetic acid, propanoic acid, butanoic acid, p-cresol, and indole, respectively, iii) 14% of nitrous oxide (N2O), iv) 100% of O3, and 26% generation of CO2. Under UV-C (185+254 nm) photocatalysis, the percent reductions of target gases were up to i) 54% and 47% for p-cresol and indole, respectively, ii) 25% of N2O, iii) 71% of CH4, and 46% & 139% generation of CO2 & O3, respectively. The results proved that the UV technology was sufficiently effective in treating odorous gases, and the mobile lab was ready for farm-scale trials. The UV technology can be considered for the scaled-up treatment of emissions and air quality improvement inside livestock barns.

The utilization of eco-fonts for office printing is a sustainable, “green” printing concept, which has obvious economic benefits. As a result, it has a significant effect on environmental sustainability. This practice's fundamental problem is the decreased quality of text printed using eco-fonts compared to those printed with regular fonts. The aim of this research is eco-font efficiency estimation, i.e. determination of toner usage reduction level of inkjet-printed documents typed with this font type, as well as estimation of the extent humans perceive differences between text printed with eco-font and the one printed by its “non-eco“ equivalent. Combining the instrumental measuring method and digital image analysis, it was found that this simple principle (eco-font utilization) enables substantial toner usage reduction for an inkjet printing system. At the same time, a visual test showed that the visual experience of text printed using eco-font was sufficient. In addition, awareness of the benefits that eco-font utilization brings, change users’ attitude towards eco-font quality. The concept of removing the black pixel from this commonly used Thai font has a great potential for the sustainability printing process, and this simple solution could be applied to other languages as part of the GIT campaign.

Due to the continuous trade friction between China and the United States, for domestic enterprises in China, the cost of importing foreign technologies is increasing. Thus, the independent research and development (R&D) becomes particularly important for the realization of green technology innovation (GTI). This paper establishes a non-linear mediating effect model based on the data of various regions in China from 2012 to 2018. The main results are shown in the following. Firstly, there is an inverted U-shaped relationship between the intensity of intellectual property protection (IPP) and the level of GTI. Furthermore, the independent R&D investment has a masking effect between them. Secondly, by taking the independent R&D investment as a threshold variable, we prove our findings. Considering that the intensity of IPP is at a high level in most regions of China, the above statements mean that the enterprises need to continuously increase their investment in R&D, in order to further improve the regional ability in GTI. Meanwhile, local governments should also stimulate enterprises' willingness to expand their scale in R&D by issuing incentive policies, such as R&D tax incentives and government subsidies.

As we know, the economy of science is to achieve optimal gains using scarce resources. Similarly, a problem where economies of the world are trying to resolve it is the issue of how to achieve an optimal economic contribution from limited tourism resources. According to the fact that global studies and statistics indicate that good governance is considered as the most important factor in developing countries and is considered as a strong governance of the development and as Information and Communication Technology (ICT) is effective in the interactions and economic and social exchanges of any society, it is the link between the tourism industry and the technology under the form of a robust tool and utilitarian in the tourism process called E-tourism can play a significant role. Therefore, the aim of this study was to investigate the effect of network Readiness Index and good governance on income from tourism industry. In this study, data and information about 14 selected countries were collected from Southwest Asia in the annual period of 2016-2011 in the form of panel data and the proposed model was used and estimated by the generalized torques system method. The estimated results of the model indicate that both hypotheses have a positive and significant impact on the amount of Network Readiness Index in the income of tourism industry, as well as the positive and significant effect of the index the amount of income from the tourism industry is confirmed, and their impact has been positive and significant, as well as exchange rate variables, revenue and commercial openness, also have a positive and significant effect on revenues of the tourism industry.

This paper reports 2 × 4 hybrid Mach-zehnder interferometer (MZI) - multi-mode interferometers (MMI) based compact thermo-optical switch consisting of slab waveguides on silicon-on-insulator, SOI, platform. The device consists of two identical MMIs, each of 6 μm wide and 140 μm long connected with two phase shifters MMIs each with 2 μm wide and 8 μm long and linear tappers each 4 μm long, connected at both ends of the MMIs to minimize the power coupling loss. The loss for linear taper is found to be below 0.02dB. The footprint of the whole device is six 6 μm × 324 μm. This structure is based on unique multimode region shape, which leads optical switch to have less coupling loss and reduced cross-talk. The average thermo-optical switching power consumption is 1.4 mW, the excess losses are 0.8 dB, and the imbalances are 0.1 dB. Aluminum is used as a heating pad, and a trench is created around this pad to prevent from spreading of heat and reduce power loss almost by a factor of 2 to the adjacent phase shifter. Our new heating method has advantages of compact size and ease of fabrication with the current CMOS technology.

This paper analyses and evaluate the precision and the accuracy the capability of low-cost terrestrial photogrammetry by using many digital cameras to construct a 3D model of an object. To obtain the goal, a building façade has imaged by two inexpensive digital cameras such as Canon and Pentax camera. Bundle adjustment and image processing calculated by using Agisoft PhotScan software. Several factors will be included during this study, different cameras, and control points. Many photogrammetric point clouds will be generated. Their accuracy will be compared with some natural control points which collected by the laser total station of the same building. The cloud to cloud distance will be computed for different comparison 3D models to investigate different variables. The practical field experiment showed a spatial positioning reported by the investigated technique was between 2-4cm in the 3D coordinates of a façade. This accuracy is optimistic since the captured images were processed without any control points.

Polluted rivers are a primary problem in Changhua County, Taiwan, due to rapid and massive developments in agriculture and industry. In this study, samples consisted of water influent from the Yangzi-Cuo River, Ci-Tong Jiao, Changhua County. Ecology technology, a combination of gravel contact oxidation and surface flow constructed wetlands, was employed to enhance the water quality. Ecology technology is a useful and ordinary process that focuses on original treatment of pollution through chemical, physical, and biological procedures based on the mediums of soil, plant, water, and microorganisms from pure environments. Moreover, this study aimed to minimize the river pollution index (RPI) of the Yangzi-Cuo River by using combinations of gravel contact oxidation and surface flow constructed wetlands. The inflow volume of the water samples in situ was found to be 1534–2261 cubic meters per day (CMD). The pollution in the water sample mostly involved suspended solid (SS), ammoniacal nitrogen (NH₃–N), total phosphorus (TP), total nitrogen (TN), and biochemical oxygen demand (BOD), and the values of the above indexes were found to be 10.0–26.7 mg/L, 0.9–14.0 mg/L, 1.2–14.1 mg/L, 11.1–18.2 mg/L, and 0.5–3.6 mg/L, respectively. Efficiencies of pollution elimination in SS, NH₃–N, TP, TN, and BOD were found to be 24.2–93.1%, 58.3–86.2%, 5.2–85.0%, 59.4–77.2%, and 46.3–76.4%, correspondingly, after purification treatment via ecology technology. Thus, ecology technology is a valid means of purification treatment for polluted rivers.

Infertility affects approximately 15% of couples worldwide, an estimated 30% of which is related to male factor infertility. Application of low level laser therapy (LLLT) to improve fertility status is a rapidly growing discipline in medicine. Laser therapy triggers a variety of biological processes through interaction with primary cellular photoacceptors. The present review aims at evaluating the literature available in the MEDLINE/ PubMed on cellular and molecular mechanisms of photobiomodulation in the domains of reproductive and veterinary medicine. We primarily focused on the clinical application of laser treatment on seminal quality, in particular its role in promoting spermatozoa motility, as well as the role of phototherapy in modulating assisted reproduction (ART). Additionally, we investigated the strength of evidence in support of the positive impact of photobiomodulation on facilitating ART.

The purpose of this study is to investigate the moderating effect of technology configuration capability on the relationship between strategic flexibility and organizational performance through different stages of technological life cycle. Through the empirical research on the 439 Chinese high-tech organizations, it shows that a technological configuration capability has enhanced the effect of strategic flexibility to the organizational performance in the complex dynamic environment. However, the impact on the different stages of technological life cycle is different. In addition, this paper explored strategic flexibility on different stages of technological life cycle on the basis of empirical study.

The thermoelectric generator (TEG) has much potential as a renewable energy technology that could be used in ocean thermal energy conversion (OTEC). This technique employs TEGs and heat exchangers as substitutes for the intricate elements found in conventional OTEC systems, including pressure valves, evaporators, condensers, and turbine generators. By harnessing the temperature difference between warm surface seawater and cold deep seawater, it facilitates the conversion of this thermal gradient into electrical energy. This study used computer simulations to look at and compare three different types of heat exchangers: a cavity-type heat exchanger, a heat exchanger with flat fins, and a heat exchanger with longitudinal vortex generators (LVGs). The objective was to evaluate the influence of these designs on the thermoelectric conversion performance when implemented in OTEC systems. The study's findings indicate that using heat exchanger configurations featuring flat fins, or LVGs, enhances the efficiency of thermal energy transfer from warm seawater to TEGs, resulting in a notable enhancement in the output power of TEGs. Furthermore, the efficiency of TEG thermoelectric conversion is influenced by varying seawater flow rates in relation to the performance of flat fins and LVGs. In contrast to the cavity-type heat exchanger, the utilization of a heat exchanger equipped with flat fins has been found to yield a notable enhancement in the output power of TEGs by approximately 22.92%. Furthermore, this configuration demonstrates a substantial improvement in thermoelectric conversion efficiency, exhibiting an increase of around 40.01%. These improvements are observed under certain conditions pertaining to flow rates and fin heights. Utilizing heat exchangers equipped with LVGs has been found to enhance the output power of TEGs by 13.02% and improve the overall thermoelectric conversion efficiency by 17.72%. These improvements are observed under certain conditions, including specific flow rates, LVG tilt angles, and locations.

Power sources that can consistently deliver high levels of energy over extended periods are crucial for various space applications. Among the many methods of energy generation, direct heat-to-electricity conversion without intermediate steps or moving components shows particular promise but also presents significant challenges. The aim of this research is to address these challenges by enhancing the energy efficiency of thermionic conversion, which transforms thermal energy into electrical energy, through the development and utilization of a novel class of emission nanomaterials known as multilayer carbyne-enriched 3D-shaped nano-interfaces. By manipulating the topological, physicochemical, and functional characteristics of these interfaces, we seek to optimize their thermionic conversion capabilities. Building on the recent discovery of collective atomic vibrations called phonon waves within transition domains of multilayer nanostructures, we have devised a new approach to enhance the efficiency of thermionic energy converters. This involves unlocking the predictive functionality of 2D-ordered linear-chain carbon-based multilayer emitters through the excitation and fine-tuning of collective atomic vibrations and nanoarchitecture. To achieve this, we propose employing a combination of techniques that leverage interface effects, enable phonon wave propagation, facilitate energy exchange, and capitalize on synergistic effects offered by the multilayer nano-enhanced interfaces. The resulting devices for thermionic energy conversion have the potential to significantly surpass the efficiency of existing plasma thermionic converters by several orders of magnitude. Moreover, these electricity-generating sources based on thermionic conversion represent fundamental options for the advancement of Lunar and Martian research missions, opening up possibilities for sustainable energy production in extraterrestrial environments.

IT strategic planning is a critical driver of performance for small and medium-sized enterprises (SMEs), improving operational efficiency, decision-making, and innovation. This systematic review synthesizes findings from eighty studies, highlighting the varied impacts of IT strategic planning on SME performance. Quantitative analysis was used in 45% of studies, while thematic analysis was applied in 25%, showing the growing preference for data-driven insights. Cloud-based solutions, adopted in 11.25% of cases, and hybrid IT setups (17.5%) were identified as key enablers of flexibility and cost-efficiency. SMEs aligning IT strategies with business goals reported up to 20% reductions in operational costs and 15% improvements in customer satisfaction. However, 60% of studies identified resource constraints as a major challenge to IT adoption. Despite these barriers, 60% of studies demonstrated that effective IT planning enhances long-term sustainability and competitive advantage. This review provides actionable insights and strategic frameworks to guide SMEs in optimizing their IT investments for sustainable growth.

In an era where digital technologies are integral to daily life, developing higher-order thinking skills with appropriate information and communication technology (ICT) support is crucial. The purpose of this study was to examine synergies of systems thinking and technology-enhanced learning from the perspective of flow theory. For that purpose, we surveyed more than 65 pre-service preschool teachers engaged in a design, technology, and engineering (DTE) course at the University of Ljubljana. Mapping of systems thinking revealed that pre-service preschool teachers needed support with regard to feedback and understanding the interrelationship dimen-sion of systems thinking. Predictive and mediation analyses yielded some interesting results. Those who participated in the ICT-enhanced DTE course showed higher cognitive and social engage-ment, which is correlated with better systems thinking, while their aesthetic engagement was lower. Experiencing a flow state during ICT activities positively influenced systems thinking, par-ticularly in terms of clear goals and autotelic experiences. Flow theory seems to be a solid and ap-propriate framework to use for studying synergies in technology-enhanced systems thinking for sustainable education. These findings underscore the importance of integrating systems thinking into curricula to enhance learning outcomes and prepare students for future challenges toward the achievement of Sustainable Development Goals.

This research explores the impact of 5G technology on supply chain efficiency and marketing innovations, highlighting its transformative potential and associated challenges. The study delves into how 5G enhances real-time tracking and monitoring within supply chains, significantly improving inventory management, reducing stockouts and overstocking, and ensuring optimal conditions during product transit. The advanced communication capabilities of 5G enable seamless collaboration among supply chain partners, facilitating quicker decision-making and improved risk management. Additionally, the integration of 5G technology with data analytics has optimized processes, improved forecasting accuracy, and led to cost reductions, showcasing the value of data-driven decision-making. In the marketing domain, 5G technology has driven the development of immersive augmented reality (AR) and virtual reality (VR) applications, enhancing customer engagement through interactive and experiential content. Personalized and targeted marketing strategies, supported by real-time data and deeper customer insights, have led to higher customer satisfaction and increased sales. The proliferation of connected devices, such as smart speakers and wearables, has further enabled personalized interactions and convenience, fostering brand loyalty and driving growth. Despite these advancements, the implementation of 5G presents challenges, including significant infrastructure investment, cybersecurity risks, and privacy concerns. Companies must navigate these issues by investing in robust security measures and developing comprehensive policies. The research concludes with an optimistic outlook on the future impact of 5G technology, emphasizing its potential to drive innovation, enhance operational efficiency, and transform customer experiences, ultimately shaping the future of business operations.

Waste management is a critical issue globally, and Bangladesh is no exception, facing significant challenges due to rapid urbanization, population growth, and inadequate infrastructure. This article explores comprehensive waste management strategies, including waste segregation, recycling, composting, and waste-to-energy technologies, emphasizing their environmental and health benefits. It examines the past and present waste management conditions in Bangladesh, highlighting the progress made and the persistent challenges. The article also compares waste management practices in neighboring countries like India, Bhutan, Sri Lanka, and Nepal, offering insights into potential improvements for Bangladesh. Emphasizing the need for public awareness, community involvement, and modern infrastructure, it calls for collaborative efforts to achieve sustainable waste management and environmental preservation in Bangladesh. This article examines the critical issue of waste management, emphasizing its importance in mitigating environmental pollution, conserving resources, and protecting public health. It provides a detailed analysis of various waste management strategies, including waste segregation, recycling, composting, and waste-to-energy technologies, highlighting their benefits and implementation challenges. Focusing on Bangladesh, the article traces the evolution of the country's waste management system, from past inadequacies to recent improvements, while acknowledging persistent issues such as rapid urbanization and insufficient infrastructure. Comparisons with waste management practices in neighboring countries like India, Bhutan, Sri Lanka, and Nepal offer valuable insights and potential strategies for Bangladesh to adopt. The article underscores the necessity of public awareness, community involvement, and robust infrastructure to achieve effective waste management. It calls for a collaborative approach involving government, private sector, NGOs, and local communities to develop sustainable solutions. By investing in modern waste management technologies and fostering responsible consumption and disposal habits, Bangladesh can address its waste management challenges, ensuring environmental preservation, public health, and overall national well-being.

The rapid evolution of financial technology (fintech) has significantly transformed the financial services landscape, creating opportunities for innovation and introducing new risks. Traditional financial institutions and fintech companies operate under different paradigms, resulting in disparate risk management practices. This paper proposes a comprehensive framework for integrating operations and risk management practices between traditional financial institutions and fintech companies. By leveraging advanced technologies such as artificial intelligence (AI) and machine learning (ML), the framework aims to ensure consistent and effective risk assessment across the financial sector. The financial services industry is characterized by rapid innovation, primarily driven by fintech companies offering various services that enhance efficiency, accessibility, and customer satisfaction. However, the growth of fintech brings substantial risks, including cyber threats, data privacy concerns, regulatory compliance challenges, and operational vulnerabilities. Traditional financial institutions prioritize stability, security, and compliance within established risk management frameworks. The divergence in operational models and risk management approaches creates a fragmented risk landscape, posing significant challenges to the financial system's stability and security. This paper identifies the critical need for a unified framework integrating the risk management practices of traditional financial institutions and fintech companies. The proposed framework leverages AI and ML to enhance the accuracy and comprehensiveness of risk assessments, utilizing a centralized data repository for real-time risk assessment. Unified risk management policies covering cybersecurity, operational risk, regulatory compliance, financial crime, and real-time monitoring and reporting tools ensure robust risk management protocols and prompt response to potential risks. Aligning with regulatory requirements and incorporating best practices from both sectors, the integrated risk management approach enhances the financial ecosystem's stability, security, and public confidence.

This study investigates the adoption of emerging technologies in procurement within supply chain management, focusing on the transformative potential of artificial intelligence (AI) and blockchain. Through a qualitative approach, involving semi-structured interviews with procurement professionals and technology experts, the study explores how these technologies enhance operational efficiency, optimize inventory management, and improve supply chain transparency and trust. AI-driven predictive analytics were found to significantly enhance demand forecasting, inventory optimization, and supplier performance evaluation, fostering data-driven decision-making and proactive risk management. Blockchain technology ensures secure and transparent transactions, facilitating compliance with ethical sourcing standards and reducing risks associated with counterfeit goods. Despite these benefits, organizations face substantial challenges in adopting these technologies, including data security concerns, integration complexities with existing IT infrastructure, and skills shortages in AI and blockchain expertise. Leadership commitment and organizational readiness are identified as crucial enablers for overcoming these barriers and driving successful technology adoption. The study also highlights the strategic importance of supplier relationship management, emphasizing how emerging technologies enhance real-time collaboration, performance insights, and contractual transparency. By addressing these challenges and leveraging technological innovations strategically, organizations can achieve sustainable growth, resilience, and competitive advantage in an increasingly digital and interconnected global economy. The findings contribute to advancing knowledge on procurement innovation and offer valuable insights for organizations seeking to navigate the complexities of technology-driven procurement practices. Future research directions may explore the long-term impact of technology adoption on supply chain dynamics, sustainability initiatives, and organizational performance.

Global stress is widespread in todays post-pandemic world of political and economic uncertainty. Vibroacoustic technology is a vibrotactile intervention with multiple uses, and its impact on stress lacks interpretation. This research assessed if the vibroacoustic technology of a Vibroacoustic Sound Massage (VSM) can reduce psychological, physiological and cognitive stress. The Perceived Stress Scale (PSS-10), and electrocardiogram (ECG) and electroencephalogram (EEG) biosignals were used to quantify results. Participants were divided into Low Stress and High Stress groups. ECG results show VSM increased parasympathetic activity for all participants, with the Low Stress group more effected. EEG results indicate increased concentration (TBR), reduced arousal and increased relaxation (BAR), and non-significant effects on participant well-being (FAA), though variability in this metric was homogenised after VSM. Together, these results validate VSM as an effective support tool for stress management and further research is required.

Background: Extracellular Vesicles are pivotal mediators in intercellular communication, facilitating the exchange of biological information among healthy, pathological and tumor cells. Between the diverse subtypes of extracellular vesicles, exosomes have unique properties, clinical and therapeutical applications, even towards cancer. Breast cancer ranks as one of the most prevalent malignancies across the globe. Both the tumor core and its surrounding microenvironment engage in a complex, orchestrated interaction that facilitates the cancer’s growth and spread. Methods: The most valuable and significant PubMed Literature about extracellular vesicles and adipose–derived stem cells exosomes was selected and analyzed in order to report their biological properties and potential applications, in particular on the Triple–Negative Breast Cancer. Results: Adipose–derived stem cells exosomes represent a potential tool to target the tumor core of the Triple–Negative Breast Cancer, its microenvironment and surrounding tissues including metastasis. The authors are developing a supportive Triple–Adipose–derived stem cells Exosomes [T.A.E.] Technology against breast cancer in order to perform a selective preconditioning of the cancer before or while the traditional oncological treatments are running. Conclusion: The possibility to exploit the impact of Adipose–derived stem cells exosomes within the T.A.E. Technology against the Triple–Negative breast cancer is real, highlighting a new era for supportive measures against breast cancer.Keywords: Extracellular vesicles; Exosomes; Adipose–derived stem cells, Tumor microenvironment, Triple–Negative Breast Cancer, T.A.E. Technology.

Amid the swift progression of the global automobile industry, the aspiration for lightweight vehicle design has surfaced as a crucial approach to boost fuel efficiency and curtail environmental impact. The objective of this study revolves around achieving holistic optimization of vehicle structure via detailed scrutiny of vehicle process characteristics, amalgamated with a Back Propagation neural network (BPNN) optimized by a genetic algorithm (GA) and a topology optimization (TO) method.The process initiates with an examination of the vehicle's technical characteristics, succeeded by an optimization protocol that couples GA with BPNN. This exhaustive optimization procedure derives the best-fit values of design parameters and identifies the globally optimal lightweight design approach. Subsequently, a comprehensive structural optimization is actualized by modifying the topological distribution of the structure.A simulation experiment of the conceptual car body beam skeleton is conducted as a conclusive step, and the anti-collision capacity of the car body beam skeleton is assessed by measuring deformation intrusion. The findings reveal that in the vehicle topology optimization, a comparative analysis of pre and post-optimization results indicates an improved topological density across diverse sections. The topological density of the vehicle's frontal structure escalates from 0.75 to 0.8. Following optimization, the stiffness assessment records a marginal increase (within the range of 0.02–0.05), implying that the lightweight design does not compromise the general rigidity of the structure.The optimized body structure manifests superior crashworthiness in the crash test: the deformation intrusion diminishes by 27% in front-end collisions. In side impacts, the deformation and intrusion at critical points are reduced by 13.15% to 10% respectively. The comprehensive method proposed herein proves to be an efficient strategy to actualize the lightweight design of vehicles.

This study examines the moderating effect of trained human capital on the associations of accounting information systems, generalized auditing software, and technology adoption with the performance of external auditors among Saudi listed companies. This study used a survey-based methodology. The final sample consisted of 136 responses with an 8% response rate. Using Smart-PL4 analysis, the results showed that there is a positive correlation between accounting information systems and external auditors. Conversely, a negative relationship between generalized auditing software and external auditors has been documented. In addition, this study reported a negative association between technology adoption and external auditors. However, the results highlight the positive relationship between trained human capital and external auditors. Overall, this study provides valuable insights for accounting and auditing policymakers on how external auditors’ performance is influenced by several factors in the Saudi audit market.

X-linked myotubular myopathy (XLMTM) is a rare congenital myopathy resulting from dysfunction of the protein myotubularin encoded by the MTM1 gene. XLMTM has a high neonatal and infantile mortality rate due to a severe myopathic phenotype and respiratory failure. However, in a minority of XLMTM cases, patients present with milder phenotypes and achieve ambulation and adulthood. Regarding wide phenotypic variability, we investigated the genotype-phenotype correlations in newly diagnosed XLMTM patients in a patients' cohort (previously published data plus three novel variants, n=414). We found a significant association between severe phenotype and truncating variants (p < 0.001), frameshift variants (p < 0.001), nonsense variants (p = 0.006), and in/del variants (p = 0.036). On the contrary, missense variants were significantly associated with the mild and moderate phenotype (p < 0.001). We found no significant association between phenotype and the MTM1-specific functional domain, contrasting with previously published data. Based on the significant facial gestalt difference between XLMTM patients and unaffected controls (p = 0.001), we consider the Face2Gene application as an effective diagnostic tool in XLMTM when using the correct algorithm. The Face2Gene application seems to be a practical, non-invasive diagnostic approach in XLMTM.

With the widespread Application of Virtual Reality (VR) in education, optimizing foreign language learning in VR has become a focal point of research. This paper introduces a comprehensive theoretical framework (VR-CCL) based on constructivism and cognitive load theory to enhance foreign language learning in VR. Through a literature review, we explore the applications of VR in education, foreign language learning theories, and prior works on technology-assisted language learning. We further detail the three main components of the VR-CCL framework and validate its effectiveness through two case studies: Duolingo VR and Rosetta Stone VR. Finally, we discuss the strengths and limitations of the framework and its implications for educators and developers.

In 2020 the world experienced the threat of the COVID-19 epidemic, as seniors and chronic disease patients typically try to reduce their exercise and social activities to avoid increasing the risk of infection, which could lead to increased loneliness and even many diseases. This research combining golf croquet games with AIoT companion robots constructs a home-based intelligent exercise system thus uses the Technology Acceptance Model (TAM), deduces users’ intention to use this system based on perceived usefulness and perceived ease of use, and adds the needs of love and belonging, esteem, cognitive, aesthetic, and self-actualization in Maslow’s needs theory to conduct system needs analysis. The analysis results show that participants have a high level of acceptance of this system, believing that it is easy to learn and operate, can increase interaction with others, also found that this system can improve self-confirmation, satisfying the third for knowledge, feeling happy, and self-actualization needs are easier to fulfill. In the future, we shall collect and record the seniors in the process of use, so as to find out their health problems as soon as possible, expand their daily life through this exercise, and achieve the goal of happy living and health care.

This article sets out to examine how digital twins have been used in a multi-national corporation, what technologies have been used, what benefits delivered and the significance of people and process related issues in achieving successful implementation. A qualitative, inductive research method is used, based on interviews provided by key personnel involved in three digital twin projects. The article concludes that digital twin projects are likely to involve incremental rather than disruptive change, and that successful implementation is usually underpinned by ensuring technology, people and process change factors are progressed in a balanced and integrated fashion. Building upon existing frameworks, three “properties” are identified as being of particular value in digital twin projects - workforce adaptability, technology manageability and process agility – and a related set of steps and actions is put forward as a template and point of reference for future digital twin implementations. The findings are a contribution to the developing theory around digital twins and digitalization in general, and are also of relevance to professionals embarking on DT projects.

Background and Objectives: Elders’ needs are rarely examined beforehand, and thus, although technology-based tools can enhance self-management, acceptability rates are still low. This study aimed to examine and compare self-reported needs, priorities, and preferences of elders with heart failure (HF), diabetes mellitus (DM), and chronic obstructive pulmonary disease (COPD) toward technology use to enhance self-management. Materials and Methods: A convenience sample of 473 participants over 60s (60.5% females), diagnosed with HF (N=156), DM (N=164), or COPD (N=153) was recruited. They were administered a questionnaire about the usefulness of technology in general and in specific areas of disease management. Results: Most participants (84.7%) admitted that technology is needed for better disease management. This was equally recognized across the three groups both for the overall and specific areas of disease management (in order of priority: ‘Information’, ‘Communication with Physicians &amp; Caregivers’, and ‘Quality of Life &amp; Wellbeing’). Sociodemographic differences were found. Cell phones and PCs were the devices of preference. The four common features prioritized by all three groups were related to ‘information about disease management’ (i.e., monitoring symptoms, reminders for medication intake, management and prevention of complications), whereas the fifth one was related to ‘communication with physicians and caregivers (i.e., in case of abnormal or critical signs). The top disease-specific feature was also monitoring systems (of respiratory rate or blood sugar or blood pressure, oxygen), whereas other disease-specific features followed (i.e., maintaining normal weight for HF patients, adjusting insulin dose for DM patients, and training on breathing exercises for COPD patients). Conclusions: Elders in these three samples seem receptive to technology in disease management. mHealth tools, incorporating both common and disease-specific features and addressing different chronic patients, and being personalized at the same time, could be cost-saving and useful adjuncts in routine clinical care to improve self-management.

Autonomous vehicles (AVs) may not only reduce parking demand, but also free up on-street parking spaces. From the perspective of bus priority, converting on-street parking lots into dedicated bus lanes can both ensure bus priority and accommodate non-bus traffic, helping to reduce congestion and pollution. In order to study the impact of conversion of on-street parking lots to bus lanes on traffic flow, a microscopic simulation framework based on VISSIM is proposed in this paper. Data was collected using the floating car method and video recording method to quantify the factors affecting traffic flow due to the conversion of on-street parking. The VISSIM simulation model was then calibrated. According to the proportion of the on-street parking lots into a bus lane, the on-street parking lots conversion simulation model of different scenarios was established, and the influence of different on-street parking lots conversion ratio on traffic efficiency and pollution emission was quantitatively analyzed. Finally, the optimization method based on bus lane network connectivity is discussed. The results indicate that: When the on-street parking lots conversion ratio is approximately 100%, bus speed increases by 21.03%, bus delays decrease by 14.27%, and bus parking instances decrease by 11.31%. Total emissions are negatively correlated with vehicle speed. As the conversion rate of on-street parking increases, the emissions of road segments and the entire road network gradually decrease. At a conversion ratio of 100%, the average total emissions for road segments have the highest reduction rate, decreasing by 4.12%. At a conversion ratio of 50%, the average emission total for the road network shows the largest reduction, falling by 2.88%.

With the spread of compulsory education emerged school management problems continued, and the quality of school management in compulsory education has attracted a great deal of attention in China. However, the application of information technology in the field is not yet detailed and wide, resulting in problems of heavy workload and high difficulty in the whole evaluation process. Accordingly, we use big data technologies such as Apache Spark, Apache Hive, and SPSS to carry out data cleaning, correlation analysis, dynamic factor analysis, principal component analysis, and visual display on 1760 sample data from 40 primary and secondary schools in Q Province in China, and constructs a model school management of quality evaluation in the compulsory education stage, which reduces the 22 management tasks required for previous evaluation to 5, greatly reducing the workload and difficulty of evaluation. It has improved the efficiency and accuracy of evaluation, and further promoted the simultaneous development of education of five domains and education equity in the compulsory education stage.

Pandemic scenario has significantly changed several factors of life, including teaching, and learning at university. The development of suitable teaching materials to support university studies is mandatory to overcome distance learning difficulties and improve traditional teaching methodologies. This work explains a novel method for the preparation of teaching materials for medical sciences, but also plausible for other learning fields. An encephalon was extracted and prepared by using this methodology for teaching purposes. More than 200 students evaluated several factors of the material prepared this way, indicating a better understanding (up to 80%) of theoretical contents related to this human section, together with a high usability and good physical appearance

In all areas of medicine, especially in radiology, computers are increasing year by year. Filmless radiology, speech recognition software, electronic application forms, and teleradiology are recent developments that have greatly improved radiologists' performance. This research explores radiology software trends, predictions, and the challenges posed by informatics and historical trend analysis. The rationale behind this research is that information technology (IT) is overgrowing almost every day. We must continuously seek new ways to apply IT to make more use of resources. Consequently, IT becomes increasingly crucial to radiology organizations' innovative thinking, workflow, and business models. This study aimed to analyze all radiology software publications in the Science Citation Index (SCI). From 1991 to July 2021, SCI was used to search for publications systematically. We have also widely used this historical method in radiology software research. The findings and discussions are base on an assessment of trends, predictions, contributions, and challenges in radiology software, and we are exploring radiology software with six evolutionary stages. The gift of this research is that radiology managers realize that the use of new information technologies is closely related to survival in a competitive environment. Radiology companies can review these new technologies to develop more innovative business models and services to improve operational deficiencies.

This article is an effort to scrutinize the role of Information Technology development in the chronological transformation of Urban Planning domain using the exploratory research approach. In this research, it is argued that the theoretical and practical understanding of Urban Planning should absorb and integrate the bright outcome of the rise of Information and Technology to foster congruent future urban development. The article addresses the trends of transformation in the urban planning domain through the myopic lens of the expansion of information and communications technology era followed by investigating the key drivers shaping the interaction between modern-day urban planning and information technology considering both the dark and bright sides into account.

Creating new business models is crucial for the implementation of clean technologies for industrial decarbonization. With incomplete knowledge of market processes and uncertain conditions, assessing the prospects of a technology-based business model is challenging. This study combines business model innovation, system dynamics and exploratory model analysis to identify new business opportunities in a context of socio-technical transition and assess their prospects through simulation experiments. Furthermore, insights are visualized in a roadmap to coordinate action among the actors involved. This combination of methods is applied to the case of a business model aiming at ensuring stability of the electrical grid by centralizing the management of flexible loads in industrial companies. A system dynamics model was set up to simulate the diffusion of flexible electrification technologies. Through scenario definition and sensitivity analysis, the influence of internal and external factors on diffusion was assessed. Results highlight the central role of energy costs and customer perception. The chosen combination of methods allowed the formulation of concrete recommendation for coordinated action, explicitly accounting for the various sources of uncertainty. We suggest testing this approach in further business model innovation contexts.

Late pear cultivars, such as ‘Conference’, can be stored for a long period, with their storability depending on storage conditions. A three-year study (2011-2013) compared the impact of half-year storage using four technologies – normal atmosphere, normal atmosphere + 1-methylcyclopropene (1-MCP), controlled atmosphere, controlled atmosphere + 1-MCP – on the quality parameters of ‘Conference’ pears, such as mass loss, firmness, total soluble solids, acidity, antioxidant capacity, and the incidence of diseases and disorders. Additionally, the study analysed different storage conditions in terms of profitability, based on the market prices for pears in the seasons during which the pears were stored. The storage conditions had a very strong influence on the fruit quality parameters, and was found to affect most visibly the mass loss and the incidence of postharvest diseases and disorders. The storage of ‘Conference’ pears for 180 days in normal atmosphere is not economically viable, even if the fruit is subjected to 1-MCP treatment.

Creating new business models is crucial for the implementation of clean technologies for industrial decarbonization. With incomplete knowledge of market processes and uncertain conditions, assessing the prospects of a technology-based business model is challenging. This study combines business model innovation, system dynamics and exploratory model analysis to identify new business opportunities in a context of socio-technical transition and assess their prospects through simulation experiments. Furthermore, insights are visualized in a roadmap to coordinate action among the actors involved. This combination of methods is applied to the case of a business model aiming at ensuring stability of the electrical grid by centralizing the management of flexible loads in industrial companies. A system dynamics model was set up to simulate the diffusion of flexible electrification technologies. Through scenario definition and sensitivity analysis, the influence of internal and external factors on diffusion was assessed. Results highlight the central role of energy costs and customer perception. The chosen combination of methods allowed the formulation of concrete recommendation for coordinated action, explicitly accounting for the various sources of uncertainty. We suggest testing this approach in further business model innovation contexts.

Increased proliferation of IT services in all sectors has reinforced the adoption and diffusion across all levels of education and training institutions. However, lack of awareness of and knowledge about the key challenges and opportunities of elearning, seem to allude policymakers, resulting in low adoption or increased failure rate of many e-learning projects. Our study tries to address this problem through a review of relevant literature in e-learning. Our goal was to draw from the existing literature, insights into the opportunities and challenges of e-learning diffusion, and the current state-of-research in the field. To do this, we employed a systematic review of literature on some of the salient opportunities and challenges of e-learning innovation for educational institutions. These results aimed to inform policymakers and suggest some interesting issues to advance the research and adoption and diffusion of e-learning. Moreover, the bibliometric analysis shows that the field is experiencing high research attraction among scholars. However, several research areas in the field witnessed relatively low research paucity. Based on these findings, we discussed topics for possible future research.

Land Surface Temperature is a one of the key variable of Global climate changes and model which estimate radiating budget in heat balance as control of climate model. It is a major influenced factor by the ability of the surface emissivity. In this study, were used Landsat 8 satellite image that have Operational Land Imager and Thermal Infrared Sensor to calculate Land Surface Temperature through geospatial technology over Ampara district, Sri Lanka. The Land Surface Temperature was estimated with respect to Land Surface Emissivity and Normalized Difference Vegetation Index values determined from the Red and Near Infrared channels. Land Surface Emissivity was processed directly by the thermal Infrared bands. Pixels based calculation were used to effort at LANDSAT 8 images that thermal Band 10 various dates in this study. The results were achievable to compute Normalized Difference Vegetation Index, Land Surface Emissivity, and Land Surface Temperature with applicable manner to compare with land use/ land cover data. It determines and predicts the changes of surface temperature to favorable to decision making process for the society. Study area faces seasonal drought in Sri Lanka, the prediction method that how land can be efficiently used with the present condition. Therefore, the Land Surface Temperature estimation can prove whether new irrigation systems for agricultural activities or can transformed source of energy into useful form that introducing solar hubs for energy production in future.

Ticks transmit a wide variety of pathogens including bacteria, parasites and viruses. Over the last decade, numerous novel viruses have been described in arthropods, including ticks, and their characterization has provided new insights into RNA virus diversity and evolution. However, little is known about their ability to infect vertebrates. As very few studies have described the diversity of viruses present in ticks from the Caribbean, we implemented an RNA-sequencing approach on Amblyomma variegatum and Rhipicephalus microplus ticks collected from cattle in Guadeloupe and Martinique. Among the viral communities infecting Caribbean ticks, we selected four viruses belonging to the Chuviridae, Phenuiviridae and Flaviviridae families for further characterization and designing antibody screening tests. While viral prevalence in individual tick samples revealed high infection rates, suggesting a high level of exposure of Caribbean cattle to these viruses, no seropositive animals were detected. These results suggest that the Chuviridae- and Phenuiviridae-related viruses identified in the present study are more likely tick endosymbionts, raising the question of the epidemiological significance of their occurrence in ticks, especially regarding their possible impact on tick biology and vector capacity. The characterization of these viruses might open the door to new ways of preventing and controlling tick-borne diseases.

The rapid emergence of Decentralized Finance (DeFi), driven by blockchain technology and smart contracts, is transforming the landscape of the financial industry by enabling peer-to-peer financial services without traditional intermediaries. This paper examines the impact of DeFi on traditional banking systems, focusing on the opportunities, challenges, and future directions of this revolutionary financial model. We explore how DeFi disrupts traditional financial intermediation by offering faster, cheaper, and more transparent financial services, potentially reducing the dominance of conventional banks. The study addresses critical issues such as regulatory challenges, including compliance with Anti-Money Laundering (AML) and Know Your Customer (KYC) requirements, and the importance of consumer protection in a decentralized environment. We also investigate collaboration opportunities between traditional banks and DeFi platforms, which could lead to innovative financial products and services. To provide a comprehensive analysis, the paper employs a mixed-method approach, combining a review of recent literature, empirical data, case studies, and expert interviews. The findings highlight significant gaps in current regulatory frameworks and emphasize the need for a balanced approach that fosters innovation while ensuring financial stability and consumer safety. This study concludes by offering recommendations for policymakers, financial institutions, and DeFi developers to harness the potential of DeFi while addressing its inherent risks, paving the way for the sustainable growth of decentralized finance in the broader financial ecosystem.

Embracing Fourth Industrial Revolution(4IR) techniques is a need for a long-term sustainability and to do automation in the processes of Industrial and education sector. Rapid advancement in the information technology and other engineering technologies demand more proactive steps in the education institutes. In the post pandemic world, there is an increasing demand of changes in teaching and learning methodologies with the support of modern digital technologies. So, all of the teaching institutes need to have a significant step change in the areas of learning and teaching. The impact of 4 IR is more on the education sectors compared to previous generation’s industrial revolution. Keeping track of key technologies can be quite a challenge as they keep evolving at a very fast pace. Fourth Industrial revolution is the current technological digital revolution in which major focus is on cyber physical and biological systems such as Artificial Intelligence, Robotics, Internet on Things, Virtual Reality etc., The educators and institutions should establish the pedagogies and teaching with the aid of Industry 4.0 techniques to evolve education 4.0. So, it is very important to understand the challenges and competencies required about the implementation of 4IR by the faculty members and students who are currently studying in Higher Education Institutes (HEIs). This paper aim is to do a systematic review about industry 4.0 techniques and its application in relate to the online learning and teaching, change in pedagogies, enhancement of data management in HEIs, digital and virtual laboratories etc.

Land transportation is contributing to global greenhouse gas (GHG) emissions significantly. Switching from gasoline-powered vehicles to electric vehicles (EVs) is the most practical way to decarbonize land transportation. Some regions of the world have seen significant advancements in the adoption of electric vehicles, largely due to government policies through subsidies and other rules and laws that globally made the cost of acquisition and ownership more advantageous for EV owners compared to their internal combustion engine (ICE) counterparts. The success of EV adoption in Norway, China, the United States of America (USA), the European Union (EU), and India has been linked to the favorable government policies. At present, China is the largest EV market in the world, enjoying a better advantage than any other market. It also has the highest manufacturing capacity and the largest number of EVs in operation. Norway has the highest EV penetration rate, with over 90% of newly registered cars, and one of the lowest costs of ownership globally. In this review, we present the current state of EV technology and performance, together with consumer perspectives and barriers, EV regulations in the regions with the highest penetration rates, and the decarbonization of land transportation. China is competing with the USA for leadership in manufacturing and technology, especially in the areas of artificial intelligence (AI) and batteries. In order to achieve the goal of decarbonizing road transportation, we proposed that a number of factors, including government energy policies and regulatory standard development, necessary infrastructure investments and developments, AI incorporation in EVs, innovation in EV and battery technologies, and consumer perspectives, play a crucial role.

Predictive maintenance technologies have emerged as a transformative force in retail supply chain management, offering the potential to significantly enhance operational efficiency, reduce costs, and improve customer satisfaction. This study explores the implementation and impact of predictive maintenance within the retail sector, focusing on its benefits, challenges, technological tools, and future directions. The findings indicate that predictive maintenance enables a proactive approach to equipment management, leading to substantial reductions in downtime and maintenance costs, extended equipment lifespan, and enhanced sustainability through reduced energy consumption and waste. However, the adoption of these technologies is not without challenges. High initial costs, the need for specialized skills in data analytics and IoT, issues with data quality and reliability, organizational resistance, and cybersecurity concerns present significant barriers to successful implementation. Technological tools such as IoT sensors, data analytics platforms, machine learning algorithms, and digital twins are crucial for the effective functioning of predictive maintenance systems, providing real-time data monitoring and analysis that improve decision-making and maintenance planning. The study also highlights promising future trends, including advancements in AI, machine learning, IoT, and blockchain technologies, which are expected to further enhance predictive maintenance capabilities. To fully realize the potential of predictive maintenance, companies must address the identified challenges, invest in workforce development, and implement robust data security measures. Future research should focus on exploring these advancements, understanding the broader environmental impacts, and conducting cross-industry analyses to identify best practices. Overall, while predictive maintenance offers substantial benefits, its successful integration requires a nuanced approach that balances technological innovation with strategic and operational considerations.

The advent of 5G technology represents a transformative leap in the realms of retail marketing and supply chain operations, offering unprecedented enhancements and posing unique challenges. This study explores the multifaceted impacts of 5G, focusing on its influence on customer experiences, operational efficiency, and supply chain management. The integration of 5G enables advanced technologies such as augmented reality (AR) and virtual reality (VR), significantly enhancing the interactivity and personalization of the shopping experience. Real-time data collection and analysis, facilitated by 5G, allow for more precise inventory management and optimized store operations, leading to improved customer satisfaction and reduced operational costs. In the supply chain domain, 5G technology offers enhanced visibility and control through real-time tracking and environmental monitoring, which improves logistics efficiency and product quality management. Despite these advancements, the adoption of 5G technology involves considerable challenges, including high infrastructure costs, data security concerns, and global disparities in technology deployment. Businesses must navigate these obstacles while leveraging the benefits of 5G to achieve competitive advantage. The study also highlights the role of 5G in integrating with other advanced technologies, such as artificial intelligence (AI) and blockchain, to drive further innovation. Additionally, 5G supports sustainability efforts by optimizing energy use and reducing waste. Overall, the successful implementation of 5G requires strategic investment and adaptability, but it holds the potential to revolutionize retail and supply chain operations, enhancing efficiency, customer engagement, and sustainability in a rapidly evolving digital landscape.

This study explores the intricacies of supplier relationships and inventory optimization within high-technology industries, offering a comprehensive analysis of the strategic imperatives and operational challenges faced by firms in these sectors. By adopting a qualitative research methodology involving semi-structured interviews with supply chain professionals and documentary analysis, the study provides in-depth insights into the evolving dynamics of supply chain management. Findings reveal a marked shift towards collaborative and strategic supplier relationships, characterized by trust, transparency, and joint innovation initiatives. These partnerships are essential for enhancing operational efficiency, driving product development, and navigating market uncertainties. Additionally, the research underscores the critical role of advanced technologies, such as artificial intelligence and the Internet of Things, in optimizing inventory levels and improving supply chain visibility. The integration of these technologies facilitates precise demand forecasting and proactive inventory management, thereby reducing costs and enhancing service levels. However, the study also highlights significant challenges, including geopolitical uncertainties, supply chain disruptions, and cultural barriers, which necessitate robust risk management strategies and adaptive supply chain practices. Strategic implications for organizational leaders and policymakers include the need to invest in supplier development, embrace digital transformation, and enhance risk management frameworks to build resilient and agile supply chains. This study contributes valuable insights into the complex interplay between supplier relationships, inventory optimization, and technological integration in high-technology industries, offering actionable recommendations for practitioners and researchers seeking to drive innovation and maintain competitiveness in a dynamic global marketplace.

This qualitative research investigates the pivotal role of Human Resource Management (HRM) in enhancing supply chain effectiveness. Through semi-structured interviews with 25 professionals across various industries, the study explores how HRM practices influence key aspects of supply chain management (SCM), including talent management, training and development, leadership, organizational culture, and technology integration. Findings highlight the strategic alignment between HRM and SCM as crucial for optimizing supply chain performance and responsiveness. Effective talent management strategies, such as recruitment, development, and succession planning, emerged as critical factors in ensuring operational stability and innovation within supply chains. Training programs were identified as instrumental in equipping employees with the necessary skills to navigate technological advancements and market complexities, fostering collaboration and enhancing decision-making capabilities. Leadership development initiatives were also found to be pivotal in promoting organizational effectiveness and fostering a culture of continuous improvement. The study further underscores the role of HRM in cultivating a collaborative and inclusive organizational culture that enhances communication, trust, and teamwork among supply chain stakeholders. Additionally, the integration of digital technologies and sustainability considerations emerged as transformative trends shaping modern supply chains, with HRM practices playing a crucial role in facilitating technological adoption and promoting environmentally responsible practices. Addressing challenges such as resource constraints, regulatory compliance, economic uncertainties, and global supply chain complexities remains crucial for organizations aiming to optimize HRM practices and achieve sustainable supply chain performance. Overall, this research contributes to a deeper understanding of how HRM can drive innovation, collaboration, and resilience within supply chains, positioning organizations for long-term success and growth.

Supply chain disruptions pose significant challenges to organizations, highlighting the critical importance of resilience in contemporary supply chains. This qualitative research explores the implications of supply chain disruptions on organizational resilience, drawing insights from interviews with supply chain managers and executives across various industries. The study identifies key factors that contribute to resilience, including agility, collaboration, risk management, strategic planning, technology integration, leadership, and organizational culture. Through thematic analysis, the research elucidates how these factors interact to enable organizations to manage and recover from disruptions effectively. Findings underscore the importance of agility in adapting to changing circumstances, collaboration with stakeholders to coordinate responses, and proactive risk management to anticipate and mitigate disruptions. Strategic planning and technology integration emerge as vital enablers of resilience, along with effective leadership and a resilient organizational culture that fosters adaptability and continuous improvement. The implications of supply chain disruptions extend beyond operational and financial impacts to include reputational and relational dimensions, emphasizing the importance of transparent communication and stakeholder engagement. The practical insights offered by this study provide guidance for organizations seeking to enhance their resilience and ensure continuity of operations in an increasingly complex and dynamic supply chain environment.

Cured-in-place pipe (CIPP) lining is a widely adopted method for pipeline renewal, offering advantages such as rapid installation and cost-effectiveness. However, concerns regarding the environmental impacts of volatile organic compound (VOC) emissions during the installation process have raised issues regarding the CIPP method. The literature review conducted in this paper indicated the need for stringent monitoring and management practices to mitigate adverse effects, emphasizing the importance of safe installation protocols. This paper presents the initial results of a case study focusing on VOC emissions, specifically investigating non-styrene polyester resins and water curing. To capture emissions from CIPP activities, the methodology involved air sampling using various equipment, including photoionization detectors (PID), summa canisters, passive worker sampler sorbent tubes, and method 13 cartridges. The preliminary findings indicate that non-styrene polyester resins do not exceed the exposure limits set out by the OSHA and USEPA. The future phases of this project will explore different resins and curing methods.

Globally, workplace stress and anxiety are at an all-time high, with 42% of employees experiencing daily work-related stress and anxiety. Drawing from workplace anxiety (WA) theory (Cheng &amp; McCarthy, 2018), we advance a model that considers four job demands – role ambiguity, work overload, job insecurity, and work-home conflict – as sources of daily WA, and in turn the downstream effects of WA on psychological capital (PsyCap). Our model posits gender as a moderator of the association between job demands and WA, and digital technology characteristics as moderators of the association between WA and PsyCap. We tested our predictions on a sample of 162 South African employees. Consistent with our predictions, we found positive effects of job demands on WA, with the relationship being stronger for females. Contrary to expectations, we found positive effects of WA on PsyCap, suggesting an adaptive function of WA. Perceived ease of use of digital technology moderated the association between WA and PsyCap, such that the association was strong at higher levels of perceived ease of use. This research advances our understanding of the sources of WA, the adaptive function of WA, and predictors of PsyCap. Broadly, our study adds to understanding emotions’ impact on workplace behavior.

Variability is the predisposition of phenomena to assume different values over time. Variability is higher when the differences of cases from each other are larger or diverge from a specific value, such as arithmetic mean. This study focuses on the variability of research topics within and between research fields to explain, whenever possible, how the variability shapes the structure and dynamics of technological trajectories. Analysis of variability here applies the entropy and variance decomposition on main research fields in quantum technologies. Empirical evidence shows that variability in research topics is inversely proportional to the age of research fields. Inductive implications are that higher variability in research topics of recent scientific fields is due to uncertain dynamics that generates a heterogeneity of different technological trajectories some of them can growth and develop towards fruitful directions others can be dismissed. Hence the variability seems to be one of the drivers that shapes technological evolution and can provide policy and managerial implications to improve the scientific and technological forecasting that may support appropriate decisions of R&D investments towards promising research fields and technologies.

This paper outlines the evolution of a learning technology interface from a Beta version to launch with educators and its alignment to pedagogical theory, designed to maximise collaboration between teacher and student. It explores how the “co-creation” of curricula via textual sources that underpin teaching and learning can be enhanced through interactive e-books and outlines the challenges involved in this praxis. With a number of stakeholders involved in the live use of the platform (including teachers, students, HE educators, course instructors, curriculum designers and software developers), iterative feedback loops informed real-time design improvements to both the interface and the-ory. This collaboration utilised a design-based research (DBR) approach (Wang and Hannafin, 2005), which is outlined here as explanation of how the tool developed and how iterative feedback helped to reconsider the challenges educators face in implementing pedagogical innovation across differing contexts. We propose how speculative design (Lukens and DiSalvo, 2012) and Activity Theory (Engeström, 1987) workshops can methodologically enhance the planning and evaluation phases inherent to DBR approaches, which involve students to prepare for educators’ innovation. Finally, we conclude with how educators can utilise these design principles using stratified approaches to help prepare organisational approaches for innovation.

Abstract: Microflora play an important role in the fermentation of blueberry wine, influencing the flavor and nutrient formation. Commercial yeasts give blueberry wines an average flavor profile that does not highlight the specific aroma and origin of the blueberry. In the present study, ITS1-ITS2 region sequencing analysis was performed using Illumina MiSeq high-throughput technology to sequence fermented blueberry wine samples of three Vaccinium ashei varieties, Gardenblue, Powderblue, and Britewell, from the Majiang appellation in Guizhou province to analyze the trends of fungal communities and the diversity of compositional structures in different periods of blueberry wine fermentation. The study's results revealed that 114 genera from 7 phyla were detected in 9 samples from different fermentation periods of blueberry wine. The main fungal phyla were Ascomycota, Basidiomycota, Kickxellomycota, Chytridiomycota, and Olpidiomycota. The main fungal genera were Hanseniaspora, Saccharomyces, unidentified, Aureobasidium, Penicillium, Mortierella, Colletotrichum, etc. Hanseniaspora was dominant in the pre-fermentation stage of blueberry wine, accounting for more than 82%; Saccharomyces was the dominant genera in the middle and late fermentation stages of blueberry wine, with Saccharomyces accounting for more than 72% in the middle of fermentation and 93% in the late fermentation stage. This study screened indigenous flora for the natural fermentation of blueberry wine in the Majiang production area of Guizhou, improved the flavor substances of the blueberry wine, highlighted the characteristics of the production area, and made the blueberry wine have the characteristic flavor of the production area.

Current and dynamic developments in green technologies have led to several innovation practices in the manufacturing sector only to become the top approaches used for achieving and accelerating sustainable development (SD) in the current business markets. In addition, manufacturing firms is in need of green innovation to be able to monitor and control their operations and enhance their environmental performance. However, regardless of its many benefits, the level of green innovation adoption and implementation is still lower than expected among manufacturing industries. Thus, this study aimed to minimize the gap by developing and validating a study model underpinned by Resource based view and Institutional theories, along with the Technology-Organization-Environment (TOE) framework in combination to convince firms to adopt green innovation. The study gathered data from 179 respondents using a survey distributed to manufacturing firms, after which data was exposed to Structural Equation Modeling (PLS-SEM) approach, for analysis. Based on the approach deliverables, all the integrated constructs of the model, namely perceived benefits, top management support, coercive pressure, normative pressure and mimetic pressure all predicted green management accounting practices. Moreover, green management accounting practices were found to directly and significantly affect green environmental performance. The developed integrated model provides a clear implication to decision-makers, indicating the importance of adopting and using green practices and innovative technologies for enhancing environmental performance. Based on the results from the reviewed advanced green technologies studies, there is considerable connection between green management accounting practices and environmental performance in the context of developing economies.

The textile and clothing (T&C) industry is not usually viewed as an exemplar of sustainable de-velopment and the circular economy, as the industry has hitherto made its products in linear fashion, with relatively little recycling of the finished goods. This article examines the industry’s approach to the core sustainability concept and the circular economy in particular, through a re-view of the available academic literature, evidence from corporate sustainability reports and websites, and feedback from an online survey of industry professionals. The role of digital technology deployment in engendering sustainability and the circular economy in the industry is also explored. The study finds that whilst sustainability is now firmly embedded at the strategic level in the vast majority of companies studied, attitudes towards the circular economy remain fickle. The use of digital technologies in support of sustainability objectives is also limited at present, but the article concludes that the need to meet compliance requirements and new cus-tomer perceptions of sustainability will speed the transition to circular economy activities, facili-tated by greater exploitation of digital technologies. Building upon the research findings, existing models and an initial conceptual framework, a simple operational model for initiating such a transition for small-to-medium sized enterprises in the T&C industry is put forward.