This qualitative inquiry explores how, during the early stage of the COVID-19 pandemic in Lithuania (European Union), the stakeholders in education system – university teachers, general education teachers, students and children’s parents – coped with the encountered challenge and what was important to them under changed conditions. This paper uses a communication management objective to describe how participants in the education system respond to the emerging distance learning situation and its challenges.The phenomenographic research approach was chosen to carry out the qualitative study. The 37 interviews from higher education teachers, university students, school teachers and parents of minor school-aged children were conducted during the early stage of COVID-19 quarantine. The research allows concluding that after a successful transition to distance learning the dimensions of communion and supportive collaboration acquired importance among stakeholders in education. Starting new activities, a need for communion and mobilization for joint activities under the crisis situation emerged. The research showed that the adaptation period was necessary at the beginning of the new activity. Competent leadership was expected from the teacher also advance preparation of all the actors in education process was needed. The data do offer a window into the dynamics of online teaching in crisis situation and experiences in new activity that are key to success.

: TiAl6V4 alloy is widely used in selective laser melting and direct laser melting. In turn, works devoted to the issue of how the track stacking scheme affects the value of mechanical properties is not enough. The influence of the Ti6Al4V alloy track trajectories on the microstructure and mechanical properties during direct laser deposition is studied in this article for the first time. The results were obtained on the influence of «parallel» and «perpendicular» technique of laying tracks in direct laser synthesis. All studied samples have a microstructure typical of the hardened two-phase condition titanium. It is shown that the method of laying tracks and the direction of load application during compression testing relative to the location of the tracks leads to a change in the ultimate strength of the Ti-6Al-4V alloy from 1794 to 1910 MPa. The plasticity of the Ti-6Al-4V alloy obtained by direct laser alloying can vary from 21.3 to 33.0% depending on the direction of laying the tracks and the direction of the compression test. The hardness of alloys varies in the range from 409 to 511 HV and depends on the method of laying the tracks and the direction of hardness measurements.

Hepatitis B virus (HBV) infection remains a global public problem despite the availability of effective vaccine. In the past decades, nonalcoholic fatty liver disease (NAFLD) has surpassed HBV as the most common cause of chronic liver disease worldwide. The prevalence of concomitant chronic hepatitis B (CHB) and NAFLD, thus, reaches endemic in geographic regions where both conditions are common. Patients with CHB and NAFLD are at increased risk of liver disease progression to cirrhosis and hepatocellular carcinoma. Due to complexity of the pathogenesis, accurate diagnosis of NAFLD in CHB patients can be challenging. Liver biopsy is considered the gold standard for diagnosing and determining the disease severity, but it is an invasive procedure with potential complications. There is a growing body of literatures on the application of novel noninvasive serum biomarkers and advanced radiological modalities to diagnose and evaluate NAFLD, but most have not been adequately validated especially for patients with CHB. Currently, there is no approved therapy for NAFLD though many new agents are in different phases of development. This review provides a summary of the epidemiology, clinical features, diagnosis and management of the NAFLD and highlights the unmet needs in the areas of CHB and NAFLD coexistence.

The recent outbreak of a new Coronavirus has developed into a global pandemic with about 10,5 million reported cases and over 500,000 deaths worldwide. Our prospective paper reports an updated analysis of the impact that this pandemic had on the Italian agri-food sector during the national lockdown and discusses why and how this unprecedented economic crisis could be a turning point to deal with the overall sustainability of food and agricultural systems in the frame of the forthcoming European Green Deal. Its introductory part includes a wide-ranging examination of the first quarter of pandemic emergency, with a specific focus on the primary production, to be understood as agriculture (i.e. crops and livestock, and their food products), fisheries and forestry. The effect on the typical food and wine exports, and the local environment tourism segments is also taken into account in this analysis, because of their old and deep roots into the cultural and historical heritage of the country. The subsequent part of the paper is centered on strategic lines and research networks for an efficient socio-economic and territorial restart, and a faster transition to sustainability in the frame of a circular bio-economy. Particular emphasis is given to the urgent need of investments in research and development concerning agriculture, in terms of not only a fruitful penetration of the agro-tech for a next-generation agri-food era, but also a deeper attention to the natural and environmental resources, including forestry. As for the rest of Europe, Italy demands actions to expand knowledge and strengthen research applied to technology transfer for innovation activities aimed at providing solutions for a climate neutral and resilient society, in reference to primary production to ensure food security and nutrition quality. Our expectation is that science and culture return to play a central role in national society, as their main actors are capable of making a pivotal contribution to renew and restart the whole primary sector and agri-food industry, addressing also social and environmental issues, and so accelerating the transition to sustainability.

The landscape of centralized cloud computing is now changing to distributed and decentralized clouds with promising impacts on energy consumption, resource availability, resilience, and customer experience. This research highlights the impacts of emerging IT trends, namely, 5G wireless technology, blockchain, and industrial Artificial Intelligence (AI) in development and realization of the next generation of cloud computing. Integration of these technologies in cyber-physical system and cloud manufacturing paradigms is explained and a unified edge-fog-cloud architecture is proposed for successful implementation in manufacturing systems.

This conceptual article is aimed at evaluating the COVID19 impacts on the global economy and to postulating an ‘economic paradigm shift’. We argue that the existing economic, political, and trade principles have been challenged due to the global pandemic issue. We also compare the COVID19 impact on Western countries and Eastern countries with their control mechanisms. The emerging of new economies is due to the travel restrictions and disrupt of the global economies are discussed that pave a gateway to the economic paradigm shift. The article finally assesses the advent of 5G technology and its implications to face any future health threats that will lead to the next economic paradigm shift in the modern world.

Abstract. The COVID-19 has turned in to a global human tragedy and economic devastation. Governments have implemented lockdown measures, blocked international travel, and enforced other public containment measures to mitigate the virus morbidity and mortality. As of today, no drug has the power to fight the infection and bring normalcy to the utter chaos. This leaves us with only one choice namely an effective and safe vaccine that shall be manufactured as soon as possible and available to all countries and populations affected by the pandemic at an affordable price. There has been an unprecedented fast track path taken in R&D by the World community for developing an effective and safe vaccine. Platform technology has been exploited to develop candidate vaccines in a matter of days to weeks and as of now, 108 such vaccines are available. Six of these vaccines have entered clinical trials. As clinical trials are ‘rate-limiting’ and ‘time-consuming’, many innovative methods are in practice for a fast track. These include parallel phase I-II trials and obtaining efficacy data from phase IIb trials. Human ‘challenge experiments’ to confirm efficacy in humans is under serious consideration. The availability of the COVID-19 vaccine has become a race against time in the middle of death and devastation. There is an atmosphere of tremendous hype around the COVID-19 vaccine and developers are using every moment to make claims, which remain unverified. However, concerns are raised about a rush to deploy a COVID-19 vaccine. Applying ‘Quick fix’ and ‘short cuts’ can lead to errors with disastrous consequences.

Regular exercise can reduce depression. However, the uptake of exercise is limited in patients with end-stage renal disease undergoing hemodialysis. To address the gap, we designed a gamified non-weight-bearing exercise program (Exergame), which can be executed during hemodialysis treatment. The Exergame is virtually supervised based on its interactive feedback via wearable sensors attached on lower extremities. We examined the effectiveness of this program to reduce depression symptom compared to supervised exercise in 73 hemodialysis patients (age=64.5±8.7years, BMI=31.6±7.6kg/m2). Participants were randomized into an Exergame group (EG) or a Supervised-exercise group (SG). Both groups received similar exercise tasks for 4-week, 3-session per week, 30-min per session, during hemodialysis treatment. Depression symptom was assessed at baseline and 4-week using Center for Epidemiologic Studies Depression (CES-D). Both groups showed significant reduction in depression score (37%, p<0.001, Cohen’s effect size d=0.69 in EG vs. 41%, p<0.001, d=0.65 in SG) with no between-group difference for the observed effect (p>0.050). The EG expressed a positive exercise experience including fun, safety, and helpfulness of sensor-feedback. Together, results suggested that the virtually-supervised low-intensity Exergame is feasible during routine hemodialysis treatment. It is as effective as supervised-exercise to reduce depression symptom, while reducing burden of administrating exercise in dialysis clinics.

This study contributes to the literature by exploring challenges to implementing ISO 20000-1 in an emerging economy context, and suggests ways to overcome these challenges. A survey-based methodology was adopted. The data were analyzed using principal component analysis. The results indicated that senior management support was the most significant challenge for the successful implementation of IT Service Management (ITSM) systems. Other significant challenges were the justification of significant investment, premium customer support, co-operation and co-ordination among IT support teams, proper documentation, and effective process design The findings help managers introduce IT service management system (ISO 20000-1:2011) as well as improving IT service delivery system in IT support organizations for managing big data in an emerging economy. In the future, cross-firm and cross-country studies on challenges to ISO 20000 can be conducted. Also, interpretive structural model (ISM) can be formulated to examine the interrelationships among the identified challenges to ISO 20000.

In the industrial sector, the financial gain is generally considered at the cost of environmental degradation. The environmental protection and economic benefit are common conflicting objectives in many optimization problems. In any multi-criteria problem, the most challenging part is to optimize the conflicting goals. But if these objectives become non-conflicting, then the problem can be solved with ease. This paper is all about minimizing the environmental impact of industrial processes while maximizing the net economic benefit. There is a general misconception of linking the environmental protection with a financial loss. This is not always true; the Eco-Efficiency or Cleaner Production Technology (CPT) is a perfect example to disprove this notion. Economics of CPT regarding water savings for the textile-processing sector in Pakistan has been analyzed in this paper. Changes in water use before and after the implementation of water conserving technologies in the textile sector of Pakistan from a study conducted by the Cleaner Production Institute (CPI) are utilized to perform a cost-benefit analysis. Direct financial benefits that could be achieved through the application of these technologies are presented only. Other environmental benefits, though not described here, are of no less importance. The study results reveal that very high potential of water savings exists for most of the investments on CPT.

In this study, the prevalent methodology for design of the industrial policy in developing countries was critically assessed, and it was shown that the mechanism and content of classical method is fundamentally contradictory to the goals and components of the endogenous growth theories. This study, by proposing a new approach, along settling Schumpeter's economic growth theory as a policy framework, designed the process of entering, analyzing and processing data as the mechanism of the industrial policy in order to provide "theoretical consistency" and "technical and Statistical requirements" for targeting the growth stimulant factor effectively.

The world is progressing towards a more advanced society where end-consumers have access to local renewable-based generation and advanced forms of information and technology. Hence, it is in a current state of transition between the traditional approach to power generation and distribution, where end-consumers of electricity have typically been inactive in their involvement with energy markets and a new approach that integrates their active participation. This new approach includes the use of distributed energy resources (DER) such as renewable-based generations and demand response (DR), which are being rapidly adopted by end-consumers, where incentives are strong. This paper presents the role of DR aggregator to effectively integrate DER technologies as a new source of energy capacity, into the electricity networks using information communication technology and industry knowledge. This framework based on DR aggregators will facilitate renewable energy integration and customer engagement in electricity market efficiently. To this aim, advantages and disadvantages of DR aggregators are discussed in this paper from political, economic, social and technological (PEST) point of views. Based on this analysis, a strengths, weaknesses, opportunities, and threats (SWOT) analysis for a typical DR aggregator is presented.

myfood24 is a comprehensive self-completed online 24-hour dietary recall tool currently used for nutritional assessments in epidemiological research. However, its clinical application has been unexplored. This mixed methods prospective observational study explores the acceptability and usability of myfood24 in a clinical population, women with gestational diabetes (GDM). Women were recruited at their first diabetes antenatal clinic appointment. To assess acceptability and usability, they were asked to complete five 24-hour dietary recalls using myfood24 over two weeks and a user experience questionnaire; with a subset invited to participate in a one-to-one semi-structured interview. Of the 199 participants, mean maternal age was 33 years, mean booking BMI 29.7kg/m2, 36% primiparous, 57% White, 33% Asian. Of these 121 (61%) completed myfood24 at least once and 73 (37%) completed the user questionnaire; 15 were interviewed. Usability of myfood24 was measured using the System Usability Scale (SUS) and found to be good (mean 70.9, 95%CI 67.1, 74.6). Interviews identified several areas for improvement, including optimising its use for mobile devices. myfood24 appears to be acceptable and have potential to support self-management and behaviour change for women with GDM but requires adaptation to record blood glucose results alongside real-time tracking of diet.

The goal of the study was to assess the farmers’ acceptance of three sustainable production strategies, namely ‘Agro-forestry’, ‘Alternative protein source’ and ‘Prolonged maternal feeding’. Data on the acceptance of these strategies were collected by a survey of dairy farmers in six EU countries (AT, BE, DK, FI, IT, UK). An extended version of the Technology Acceptance Model (TAM) was applied by means of Structural Equation Modelling to testing various hypotheses on attitudes and intentions of dairy farmers towards these novel production strategies, as well as the influence of organic practices and collaborative behaviours along the supply chain. We found that the most preferred strategy - across all countries - was soy substitution by alternative protein sources. We also found that the intention to adopt a sustainable production strategy may derive from the influence of opinions (and behaviours) of relevant others, showing the role of interactions among farmers and other stakeholders in the adoption of innovations. Finally, the perceived usefulness of all investigated strategies is higher for organic farmers, while collaborative patterns reduce the impact of subjective norm on usefulness and overall acceptance. Our findings should encourage policy makers to consider the important role of supply chain management practices, including collaboration, to enhance the sustainability of dairy farming systems.

Under the main features required on portable devices in electrochemical instrumentation is to have a small size, low power consumption, economically affordable, and precision in the measurements. This paper describes the development of a programmable Embedded Potentiostat System (EPS) capable of performing electrochemical sensing over system-on-a-chip platforms. Furthermore, the study explains a circuit design and develops some validation of the entire system. The hardware validation is performed by electrochemical experiments such as Double Step Chronoamperometry (DSC), Linear Sweep Voltammetry (LSV) and Cyclic Voltammetry (CV); moreover, a comparison of the experimental signals between a commercial potentiostat and the EPS was done by analysis of errors on the response signal. Results illustrate that the EPS is capable of handling currents in the range of absolute values of 86.44 to 3000 nA, and having control voltages in the range of ± 2 V. The device can support from 50 to 2000 samples per second. The EPS capabilities were compared with other compact potentiostats. The programmable EPS is an original approach which hugely reduces the hardware complexity and leads the way to create new applications for Point-of-Care or industrial developments with a reusable full electronics module.

Thoracic aortopathy encompasses a spectrum of conditions affecting the aorta, ranging from aneurysms to dissections, posing significant challenges in management and care. In recent years, remote care, facilitated by telemedicine and digital health technologies, has emerged as a promising approach to overcome barriers in delivering timely and efficient healthcare services. This paper explores the practical considerations and challenges associated with implementing remote care strategies in the management of thoracic aortopathy in India with the largest population in the world. By evaluating existing literature and drawing upon clinical experiences, we discuss the potential benefits, limitations, and best practices for incorporating remote care into the management of patients with thoracic aortopathy. Additionally, we address important factors such as patient engagement, technology integration, privacy concerns, and regulatory requirements to optimize the delivery of remote care in this specialized field.

Recent research emphasises the importance of Artificial Intelligence applications as supporting tools for students in higher education. Simultaneously, an intensive exchange of views has started in the public debate in the international educational community. However, for a more proper use of these applications, it is necessary to investigate the factors that explain their intention and actual use in the future. With the Unified Theory of Acceptance and Use of Technology (UTAUT2) model, this work analyses the factors influencing students' use and intention to use artificial intelligence technology. For this purpose, a sample of 199 Greek students at the School of Humanities and Social Sciences from the University of Patras participated in a survey. The findings highlight that expected performance, habit, and enjoyment of these Artificial Intelligence applications are key determinants influencing teachers' intentions to use them. Moreover, behavioural intention, habit, and facilitating conditions explain the usage of these Artificial Intelligence applications. The study did not reveal any moderating effects. The limitations, practical implications, and proposed directions for future research based on these results are discussed.

From grape cultivation to ripening and harvest timing to processing, each step can be a critical point when it comes to wine quality and phenolic composition. In this study, the influence of winemaking technology on resveratrol and quercetin content, as well as other polyphenolic compounds, was investigated. Resveratrol is a non-flavonoid polyphenolic stilbene synthesized by grape skin when damaged by infectious diseases or ionizing radiation. Quercetin is a phenol found in grape skins and stems and is produced to protect grapes from UV light damage. Trans-resveratrol and quercetin are known to act as antioxidants, reduce the risk of atherosclerosis and type 2 diabetes, inhibit the growth of cancer cells, and prevent the release of allergic and inflammatory molecules. However, the question was whether red wine could be enriched with these phenols using an innovative winemaking technology. The innovative idea was to completely replace the cold maceration process with maceration with the addition of wild yeast (Torulaspora delbrueckii, Td). Maceration with the addition of wild yeast (Td) offers the following advantages over traditional cold maceration: (1) higher concentrations of trans-resveratrol (>35-40%) and quercetin (>35-40%) in the final wine, (2) the new wine has a higher potential for human health, (3) the wine has a better aroma and stability due to the higher mannoprotein content, and (4) the better energy efficiency in the production process. The study of stability during storage and aging also included derivatives of benzoic acid and hydroxycinnamic acid, piceid, catechin, naringenin, rutin, kaempherol, hesperetin, and anthocyanins. The study found that younger wines had higher phenolic content, while storage of the wine resulted in a decrease in total phenolic content, especially monomeric stilbenes and quercetin.

This study aimed to evaluate the effects of Blazepod technology when incorporated with various training regimens on the essential elements of physical fitness in volleyball, such as agility, speed, visual response time, and vertical leap. Thirty-six participants (age :17.33±0.48 y, height: 183.78±6.34 cm, weight: 77.14±5.16 kg) were in-volved in this study. In randomized design, three equal groups with two experimental groups and one control group were involved in the study over a period of six weeks: (GE1) used Blazepod technology to workout at a low level; (GE2) used Blazepod technology to workout at a higher intensity; (CG) did not employ Blazepod technology, but it adhered to the same fundamental training curriculum. We conducted agility, speed, reaction time, and vertical jump tests before, midway and after the study to determine optimal training volume, intensity, and frequency. A significant main effect of time (P0.01), and time×group interaction (P>0.001) were found for all tests. Post hoc test showed that the two experimental groups gadget significantly improved in all performance variables (P

This study investigates the effect of scaffold architecture on bone regeneration, focusing on 3D-printed polylactic acid-bioceramic calcium phosphate (PLA-bioCaP) composite scaffolds in rabbit femoral condyle critical defects. To assess their influence on bone healing and scaffold performance, we explored two distinct scaffold designs, alternate and helical laydown patterns. The scaffolds were meticulously characterized for pore size, strut thickness, porosity, pore accessibility, and mechanical properties. The in vivo efficacy of these scaffolds was evaluated using a rabbit femoral condyle critical defect model. Our findings indicate that both scaffold architectures are biocompatible and support bone formation. The helical scaffolds, characterized by larger pore sizes and higher porosity, demonstrated significantly greater bone regeneration than the alternate structures. However, their lower mechanical strength presented limitations for use in load-bearing sites. This study highlights the importance of scaffold architecture in bone tissue engineering and underscores the need to balance porosity and mechanical strength for optimal bone regeneration. The findings provide crucial insights for the design of 3D- printed scaffolds in clinical applications, particularly in the context of critical-sized bone defects. The study also outlines potential areas for future research, including exploring hybrid scaffold designs to achieve optimal porosity without compromising mechanical integrity.

This dossier is aimed at individuals involved in the development, implementation, and application of AI-supported systems in the field of education, particularly those who are dealing with metadata in this context. The insights and recommendations described in this dossier are based on interviews with five experts from the USA and UK, research on metadata standards, and our personal experiences in the context of the INVITE competition. This dossier provides an overview of the current development of learning metadata and existing standards. It shows the efforts and obstacles to introducing those metadata standards from an international perspective based on interviews with five experts in the field. Furthermore, this dossier shows the international experiences in selecting and using metadata standards and how these findings can inspire discussions in the German-speaking discourse regarding the use of metadata in education.

The retrospective noninterventional study investigated the kinetic energy of video images of 18 fertilized eggs (7 were normal and 11 were abnormal) recorded by a time-lapse device leading up to the beginning of the first cleavage. The norm values of cytoplasmic particles were measured by the optical flow method. Three phases profile for normal cases were found regarding the kinetic energy that were 2.199×10⁻²⁴±2.076×10⁻²⁴, 2.369×10⁻²⁴±1.255×10⁻²⁴, and 1.078×10⁻²⁴±4.720×10⁻²⁵ (J) for the phases 1, 2, and 3, respectively. In phase 2, the energies were 2.369 × 10⁻²⁴ ± 1.255 × 10⁻²⁴ and 4.694 × 10⁻²⁴ ± 2.996 × 10⁻²⁴ (J) (mean ± SD, P = 0.0372), and the time required was 8.114 ± 2.937 and 6.018 ± 5.685 (H) (P = 0.0413) for the normal and abnormal cases, respectively. The kinetic energy change was considered a condition for applying the free energy principle that states that, for any self-organized system to be in equilibrium in its environment, it must minimize its informational free energy. The kinetic energy while interpreting it in terms of the free energy principle suggesting clinical usefulness would further our understanding of the phenomenon of fertilized egg development with respect to the birth of human life.

In the scientific community, it is difficult to find a consensus on defining BIM. Just as the acronym BIM is developed in different ways, it is also understood in different ways. Depending on its understanding, different definitions emerge. It is defined differently by organizations and standards, still differently by academics. Many years of academic discourse on the subject have failed to produce a solution. Despite the fact that the acronym BIM has already done its work for the construction industry, it still stirs up excitement. There is still no clear definition, as the view of BIM varies from one perspective to another. This article attempts to sort out the definitions cited so far by important organizations and key academics. The review was based on deep literature study has attempted to be inclusive and consistent. The question still remains open: do we need a single, correct definition of BIM? The aim of the article is to try to answer this question, open up a renewed discussion and come to a satisfactory consensus. BIM can be identified with an activity, product or system. The article breaks down the definitions of BIM, identifies six key attributes of BIM, presents the evolution of the understanding of BIM and proposes new definitions in a narrow and broad approach.

There are four categories of medical waste that cannot be mixed as this will cause serious problems such as environmental pollution or infection. In the past, the classification of medical waste often involved a lot of human and material resources to process, with workers at risk of exposure to infectious substances. Therefore, an augmented reality (AR) and artificial intelligence (AI) medical waste classification system and method were developed. This innovative medical waste classification system and method combines AR and AI identification technology to reduce the risk of manual judgment errors by clinical staff when handling medical waste.

Traffic signal control plays a key role in managing urban traffic flow, enhancing safety, and minimizing congestion and conflicts. Effective green time allocation is a critical element of this control process. This research explores the utilization of LiDAR sensor technology in the optimization of green time allocation for one phase of a traffic signal at a signalized intersection. LiDAR sensors provide precise and real-time data on vehicle presence and traffic patterns, enabling a data-driven approach to traffic signal control. The study begins with an analysis of the limitations of traditional traffic signal control strategies, which often rely on fixed-time plans or rudimentary vehicle detection systems. These approaches can lead to suboptimal green time allocation, resulting in inefficient traffic management and increased vehicle delays.The integration of LiDAR sensors provides detailed information on vehicle queues, arrival rates, and vehicle types. The research presents a practical framework for green time allocation optimization, considering factors such as intersection geometry, traffic volumes, and signal coordination. An intelligent control algorithm was developed that uses LiDAR data to determine the optimal green time for a specific phase, thereby reducing unnecessary waiting times and enhancing intersection efficiency. The effectiveness of the proposed LiDAR-based green time allocation strategy is demonstrated through extensive field tests. The results indicate significant improvements in intersection throughput, reduced delays, and enhanced traffic safety. In conclusion, this research highlights the transformative potential of LiDAR sensor technology in traffic signal control, specifically in the context of optimizing green time allocation. The findings support the notion that adaptive and data-driven strategies, when integrated with LiDAR sensors, can contribute to more efficient, sustainable, and safe urban traffic management. This research aims to provide valuable insights for transportation engineers, policymakers, and researchers seeking innovative solutions for modern urban traffic control.

Once discovered, cancer stem cells have become a hot topic in the research of cancer therapy. These cells possess stem cell-like self-renewal and differentiation capacities and are important factors that dominate cancer metastasis, therapy- resistance and recurrence. What's worse, their own characteristics make them difficult to be eliminated. Colorectal cancer is the third most common cancer and the second leading cause of cancer death worldwide. Targeting colorectal cancer stem cells (CRCSCs) can inhibit colorectal cancer metastasis, enhance therapeutic efficacy, and reduce recurrence. Here, we introduced the origin, marker proteins, identification, cultivation and research techniques of CRCSCs, summarized the signaling pathways that regulate the stemness of CRCSCs, such as Wnt, JAK/STAT3, Notch, and Hh signaling pathway. In addition to these, we also reviewed anti-CRCSC drugs targeting signaling pathways，markers，and other regulators in recent years. These will help researchers gain insight into the current agents targeting to CRCSCs, explore new cancer drugs, and propose potential therapy.

Outcome of redo-mitral valve replacement in the small mitral annulus with the use of the chimney technology is not well documented. From 2019 to 2020, 77 consecutive patients underwent redo-mitral valve replacement with the use of the chimney technology because of a small mitral annulus. To evaluate heart structural integrity and clinical outcomes, postoperative clinical data and echocardiograms were examined. Mean age was 56.7 ± 15.98 years. All patients underwent mitral valve surgery of which 62 were mitral valve replacements, 7 mitral valve repairs, and 8 double valve replacements. Preoperative Mitral valve mean gradient was 18.07 ± 9.40 mmHg. Postoperative mitral prosthesis size 28.51 ± 1.22 mm. The median increment of mitral size enlargement was 4 (0, 6) valve sizes. Mean mitral gradient coming out of the operating room was 10.34 ± 2.12 mmHg and at follow-up echocardiogram performed at 3 years after the procedure was 10.36 ± 1.70 mmHg. One-year survival was 93.3%, while 4-year survival was 89.3% with no reoperation. Use of the chimney technology in small mitral valve re-mitral valve replacement results in larger valve sizes. Moreover, the mean gradients over the mitral valve are acceptable intraoperatively and over time.

Demonstrating biosimilarity entails comprehensive analytical evaluations, clinical pharmacolo-gy profiling, and efficacy testing for at least one medical indication in patients. These require-ments are stipulated by the U.S. Biologics Price Competition and Innovation Act (BPCIA). The costliest element—efficacy testing—can be waived if other compliance benchmarks are satisfied, including comparing functional pharmacodynamic (PD) biomarkers, even when they do not di-rectly correlate with clinical outcomes. Most biological drugs, such as monoclonal antibodies (mAbs), lack identifiable PD biomarkers. The FDA has employed various 'omics' technologies to identify potential PD biomarkers, including proteomics, glycomics, transcriptomics, genomics, epigenomics, and metabolomics. Although these efforts provide a robust scientific basis for estab-lishing biosimilarity, they are neither practical nor necessarily superior to existing functional biomarkers, such as receptor binding and mode-of-action outcomes. As we report for the first time, these functional biomarkers can effectively serve as PD indicators for all FDA-licensed bio-logical drugs. We recommend that the FDA consider officially listing these functional biomarkers to expedite and reduce the cost of biosimilar development, thereby increasing the accessibility of biological drugs. PD surrogates, like the receptor binding and pharmacokinetic profiles, are more robust and offer a rational solution to finding PD markers to compare for establishing biosimi-larity.

Background: Alzheimer's disease causes great changes, with the prefrontal cortex be-ing frequently damaged zones, affecting physical and cognitive behavioural and compromising autonomy and quality of life. Objective: To evaluate the effectiveness of feedback-based tech-nology on the improvement of physical-cognitive capacities in Alzheimer. Methods: Forty pa-tients with Alzheimer were recruited from the Santa Elena Alzheimer's Association, Seville, of which 15 ended up being pilot participants, divided randomly into controls (8) and experi-mental (7). They were evaluated with: Cognitive Mini-Examination Scale, Oddball Test and At-tention Network, Berg Scale, Tinetti, Timed up and Go and Geriatric Deterioration Scale. The experimental group was treated with feedback-based technology under the supervision of physiotherapists, during 16 thirty-minute sessions, twice a week. The control group performed their usual care. Result: A significant improvement was observed in the experimental group (Cognitive Mini-Examination and Tinetti). In the group of control, a worsening of physical and motor skills was evidenced because of the degenerative disease. Discussion/Conclusion: This treatment could be a strategy to keep the patient in early stages for longer, and improve quali-ty of life delaying dependency. It creates intergenerational bonds and use at home to promote treatment adherence.

The aim of this work was to determine the potential of using a pulsed electric field (PEF) and ultra-sound (US) apparatus to produce mitragynine extracts from Mitragyna speciosa dried leaves. Four modes of the device were tested: PEF, US, US + PEF, and PEF + US. The results were compared with extracts obtained using a conventional technique (maceration, as the control). Changes in the mitragynine content were determined with the liquid chromatography/mass spectrometry (LC-MS/MS) method. The LC-MS/MS analysis showed that the mitragynine contents from kratom extracts using four different modes were different. The highest extraction (106.63 ± 0.85 mg/L) of mitragynine was achieved by the PEF + US procedure, followed by US + PEF (97.27 ± 1.33 mg/L), with increased extraction efficiencies of 45.81 ± 0.59% and 33.00 ± 1.85%, respectively. Moreover, the total energy consumption under the combination technique was 25.0% lower than that with PEF assistance. Furthermore, scanning electron microscopy (SEM) and Fourier Transform Infrared Spectroscopy (FTIR) provided confirmatory evidence for the extraction of M. speciosa by the prototype. This study confirmed that PEF and US devices can be considered a green alternative method and may contribute to the application of agricultural products.

With the popularization of intelligent sensing and the improvement of modern medical technology, intelligent medical sensing technology has emerged as the times require. This technology combines basic disciplines such as physics, mathematics, and materials with modern technologies such as semiconductors, integrated circuits, and artificial intelligence, and has become one of the most promising focuses in the medical field. The core of intelligent medical sensor technology is to make existing medical sensors intelligent, portable, and wearable with full consideration of ergonomics and sensor power consumption issues, for conforming to the current trends in cloud medicine, personalized medicine, and health monitoring. With the development of automation and intelligence in measurement and control systems, it is required that sensors have high accuracy, reliability, stability, as well as certain data processing capabilities, self-checking, self-calibration, and self-compensation，while traditional medical sensors cannot meet such requirements. In addition, in order to manufacture high-performance sensors, it is also difficult to improve the material process alone, and it is necessary to combine computer technology with sensor technology to make up for its performance shortcomings. Intelligent medical sensing technology combines medical sensors with microprocessors to produce powerful intelligent medical sensors. On the basis of the original sensor functions, intelligent medical sensors also have functions such as self-compensation, self-calibration, self-diagnosis, numerical processing, two-way communication, information storage, and digital output. This review focuses on the application of intelligent medical sensing technology in biomedical sensing detection from three aspects: physical sensor, chemical sensor, and biosensor.

The accelerated pace with which new diagnostic possibilities are produced and the budget re-strictions of the healthcare sector require that the decision-making process of acquiring new technologies becomes systematic in nature. There are some methodologies such as the Health Technology Assessment (HTA) that encompasses technological domains, clinical effectiveness, patient safety, organizational and financial aspects, among others. However, these methods do not contemplate the learning curve (LC) which is a differential factor in operator-dependent technologies. An assessment model was conceived based on the assessment domains of the AdHopHTA project with the addition of LC. The model was validated and calibrated through System Dynamics (SD) and using as case study the assessment of Point-of-care Ultrasound (POCUS) equipment in dengue screening. The model helped identify the influence of the LC and patient demand on the income and costs for the healthcare system regarding dengue screening as well as the cost-benefit indicator. The control charts LC-CUSUM and CUSUM are graphic tools to intuitively assess the learning curve which can be used for real-time monitoring once students reach a certain skill level.

Mucosal vaccines offer several advantages over injectable conventional vaccines, such as adaptive immunity induction, secretory IgA production at the entry site of most pathogens, and needleless vaccinations. Despite their potential, only a few mucosal vaccines are currently used. Developing new effective mucosal vaccines strongly relies on identifying innovative anti-gens, efficient adjuvants, and delivery systems. Several approaches based on phages, bacteria, or nanoparticles have been proposed to deliver antigens to mucosal surfaces. Bacterial spores have also been considered antigen vehicles, and various antigens have been successfully exposed on their surface. Due to their peculiar structure, the spores conjugate the advantages of live microorganisms with synthetic nanoparticles. When mucosally administered, spores expressing anti-gens have been shown to induce antigen-specific, protective immune responses. This review accounts for recent progress in the formulation of spore-based mucosal vaccines, describing the spore's structure, specifically the spore surface, and the diverse approaches developed to improve its efficiency as a vehicle for heterologous antigen presentation.

Changing climate conditions and rapidly increasing carbon dioxide emissions have severely affected the global ecosystem and world economy. Governments around the world have paid attention to these resulting challenges and enacted many policies to reduce environmental pollution and carbon dioxide (CO2) emissions. This study aimed to determine and understand the relationship between innovation, foreign direct investment, economic growth, renewable consumption and CO2 emission in Vietnam. Information was collected annually based on the annual data of the General Statistics Office of Vietnam and World Bank from 2000 to 2022. Data processing was conducted using the STATA 17.0 software. The innovation affects Vietnam’s environmental pollution. Innovation positively affect environmental pollution in Vietnam; if Vietnam’s innovation were to increase by 1%, CO2 emissions would increase by 0.68%. The empirical research results of this study also show that renewable energy consumption has a negative effect on environmental pollution in Vietnam; if renewable energy were consumed at a 1% increase, CO2 emission would decrease by 0.51%. In addition, FDI inflows and economic growth have strongly positive affecting to environmental pollution; if Vietnam’s FDI inflows were to increase 1%, CO2 emissions would increase 1.39%; if Vietnam’s GDP increase 1% then CO2 emission would increase 1.26%. This paper also provides some recommendations that can assist Vietnam in developing a green and sustainable economy in the technology revolution 4.0 to achieve the United Nations Sustainable Development Goals (SDGs) over a long-term period.

Recent years have seen dramatic growth in the number of scholarly scientific works dedicated to the topic of Artificial Intelligence (AI), banking, and finance. With the development of scientometric tools, it is now possible to map, visualize, analyze, and assess scientific activities in many fields of engineering and social sciences including Islamic banking and finance. Based on data retrieved from the Scopus database and using a qualitative method, this study investigates, evaluates, and identifies significant development, trends, and players in the application of AI in Islamic banking and finance using the Visualization Of Similarities Method (VOS) between objects in VOSviewer. From 2006 to 2022, 387 documents were retrieved from the Scopus database; Results revealed that the top five most active countries in terms of publications are Malaysia (117 documents), Indonesia (89 documents), the United Kingdom (36 documents), the USA (24 documents), and Saudi Arabia and Bahrain (24 documents each). The International Islamic University Malaysia and Universitas Indonesia came out on top of active institutions while the top funding source came from the Ministry of Higher Education, Malaysia. The comprehensive findings and analysis reported in this study serve as a roadmap for future academics to create theory and practice for applying AI in Islamic banking and finance.

With the rapid development of industry, Cr has become one of the major heavy metal pollutants in soil, which has caused serious effects on the soil's ecological environment. However, the effects of Cr stress on bacterial communities in plant rhizosphere soils remain unclear. In this study, I. tectorum was selected as the research object, and 16S rRNA high-throughput sequencing technology was used to analyze the effects of Cr stress on the structure and diversity of the bacterial community in the rhizosphere soil of I. tectorum. The results showed that I. tectorum had strong tolerance and enrichment to Cr. However, under Cr stress, the diversity and abundance index of rhizosphere bacteria decreased by 8.5% and 6.8% on average, and the Sobs index decreased by 7.6%. Moreover, the bacterial community changed by 20.1% due to the addition of Cr, further leading to a 15.9% decrease in the common species of the bacterial community, among which Proteobacteria, Actinobacteria, Chloroflexi and Acidobacteriota accounted for more than 74.8% of the total sequence. According to the symbiosis network diagram, it was found that under a two-cultivated pattern, the synergizing effect between dominant bacteria was significantly enhanced, and the soil microenvironment was improved. Redundancy analysis showed that C, N, and P nutrient elements and Cr contents in uncontaminated and contaminated soils were the primary driving factors for the succession of I. tectorum rhizosphere bacterial community, and the response was stronger after Cr(Ⅵ) was added. In conclusion, the results of this study will provide insights into the response of rhizosphere bacterial communities to heavy metal Cr and the interactions between wetland plants and rhizosphere bacteria in wetland phytoremediation.Keywords: Cr stress; rhizosphere bacterial community; Iris tectorum; 16S rRNA sequencing technology; Phytoremediation

For the soil in different regions, the nutrient fertility contained in it is different, and the detection and zoning management of soil nutrients before tillage every year can improve grain yield. In this paper, an integrated learning strategy model based on black soil hyperspectral data is designed for rapid classification of organic matter content classification of black soil. Soil hyperspectral image dataset of Xiangyang Experimental Base was collected; by changing the internal structure of the stacking model, an LSVM-stacking model with (MLP, SVC, DTree, XGBl, kNN) five classifiers as the L1 layer was built, and the simulated annealing algorithm was used for hyperparameter optimization. Compared to other stacking models, the LSVM-stacking metrics are significantly improved. The accuracy rate of hyperparameter optimization is improved by 38.6515%, the accuracy rate of the independent test data set is 0.9488, and the comparison of individual learners can improve the recognition classification accuracy of label"1" to 1.0.

This paper focuses on the comparative analysis of lithium-ion batteries (LIB) thermal management with aim to maintain working temperature in the range 15 ℃ – 35 ℃. This is to prevent thermal runaway and high temperature gradients. The proposed approach is to employ the biodiesel, situated inside the diesel/LIB powered hybrid electric vehicle, to supply as fuel and coolant. A 3S2P LIB module is simulated using Ansys-Fluent CFD software tool. The system without a coolant shows that LIB has exceeded the optimum maximum temperature, which leads to shortened life-cycle and poor performance. Four fatty acid methyl ester biodiesels are used as coolants, namely palm, karanja, jatropha, and mahua oils. When compared with conventional methods of cooling, using air and 3M Novec liquid, the palm biodiesel coolant proves to be the best option to maintain LIB temperature within the optimum working range. With the use of palm biodiesel, the system is estimated to lightweight the BTMS by 43%, compared to the case when 3M Novec is used to maintain the same temperature range.

Intrusion Detection Systems (IDS) plays a part in modern cyber security, as a result of the increasing need for cyber security systems in the “real” world due to the increasing number of cyber attacks, more sophisticated systems are required in order to prevent these attacks - an IDS can provide this protection. Due to the sophistication of these systems, they must be properly understood, developed and analyzed - research papers can be used as a tool to improve IDS systems. This paper is composed of two main sections: a survey and a taxonomy, providing information, reviews and interpretations from relevant papers, a timeline of important papers, a discussion on the future of IDS and a classification on IDS and how to apply this.

Renewable energy technologies (RET) are critical to the sustainable development of modern societies. Hong Kong has set up a RET theme park so as to fulfill the needs of and impart knowledge on RET through entertainment and educational activities. Such understanding aids in formulating appropriate future park designs and neuromarketing strategies to maximize the attractiveness of the park. Therefore, this study attempts to investigate potential visitors’ preferences with regard to cartoon characters in the RET theme park, especially for student groups to meet the “edutainment” theme of the park. A total of 400 people have participated in this study. Findings indicate that Snoopy, Mickey Mouse, and Donald Duck show a high degree of likeness of presence in the RET theme park.

In the current business environment, firms are eager to adopt new technology as they witness and perceive more and more successful business applications of new technologies, e.g., Big Data, Artificial Intelligence (A.I.), Cloud Computing, etc. As one of the disruptive technologies, Blockchain technology (BCT) is now drawing public attention owing to the cryptocurrency phenomenon (e.g., Bitcoin), for which Blockchain serves as the backbone technology. Given certain innovative features of BCT, especially its transparency, traceability, security, efficiency, confidentiality, and immutability, BCT holds out the promise of impacting supply chain operational and financial efficiencies. Recently, the burgeoning of Metaverse and Non-Fungible Token (NFT) has boosted the BCT as state-of-the-art technology to another notch. Motivated by the proliferating adoption of BCT, we conduct a holistic literature review with a focus on the status of research on BCT in the context of Supply Chain Management (SCM). In particular, this Blockchain-centered research reviews the research up to date on the Blockchain application in SCM. It provides holistic review in terms of (1) the functionality of BCT and its salient features; (2) the prevailing and potential applications of BCT; (3) and the business benefits and impact of BCT in SCM. Finally, we substantiate and highlight a variety of research directions.

Industrial green technology innovation has become an important content in achieving high-quality economic growth and comprehensively practicing the new development concept in the new era. This paper measures the efficiency of industrial green technology innovation and regional differences based on Chinese provincial panel data from 2005 to 2018, using a combination of the super-efficient SBM model for considering undesirable outputs and the Dagum Gini coefficient method, and discusses and analyses the factors influencing of the industrial green technology innovation efficiency by constructing a spatial econometric model. The results show that: firstly, the industrial green technology innovation efficiency in China shows a relatively stable development trend, going through three stages: " stationary period", " recession period " and "growth period ". However, the efficiency gap between different regions is obvious, specifically in the eastern > central > western regions of China, and the industrial green technology efficiency innovation in the central and western regions is lower than the national average. Secondly, regional differences in the efficiency of industrial green technology innovation in China are evident but tend to narrow overall, with the main reason for the overall difference being regional differences. In terms of intra-regional variation, variation within the eastern region is relatively stable, variation within the central region is relatively low and shows an inverted 'U' shaped trend, and variation within the western region is high and shows a fluctuating downward trend. Thirdly, the firm size, government support, openness to the outside world, environmental regulations and education levels contribute to the efficiency of industrial green technology innovation. In addition, the industrial structure hinders the efficiency of industrial green technology innovation, and each influencing factor has different degrees of spatial spillover effects.

Thanks to rapid development of artificial intelligence technology in recent years, the current artificial intelligence technology is contributing to many part of society. Education, environment, medical care, military, tourism, economy, politics, etc. are having a very large impact on society as a whole. For example, in the field of education, there is an artificial intelligence tutoring system that automatically assigns tutors based on student's level. In the field of economics, there are quantitative investment methods that automatically analyze large amounts of data to find investment laws to create investment models or predict changes in financial markets. As such, artificial intelligence technology is being used in various fields. So, it is very important to know exactly what factors have an important influence on each field of artificial intelligence technology and how the relationship between each field is connected. Therefore, it is necessary to analyze artificial intelligence technology in each field. In this paper, we analyze patent documents related to artificial intelligence technology. We propose a method for keyword analysis within factors using artificial intelligence patent data sets for artificial intelligence technology analysis. This is a model that relies on feature engineering based on deep learning model named KeyBERT, and using vector space model. A case study of collecting and analyzing artificial intelligence patent data was conducted to show how the proposed model can be applied to real-world problems.

Among all economically important plant species in the world, grapevine (Vitis vinifera L.) is the most cultivated fruit plant. It has a significant impact on the economies of many countries through wine and fresh and dried fruit production. In recent years, the grape and wine industry has been facing outbreaks of known and emerging viral diseases across the world. Although high-throughput sequencing (HTS) has been used extensively in grapevine virology, the application and potential of third-generation sequencing have not been explored in understanding grapevine viruses and their impact on the grapevine. Nanopore sequencing, a third-generation technology, can be used for direct sequencing of both RNA and DNA with minimal infrastructure. Compared to other HTS methods, the MinION nanopore platform is faster and more cost-effective and allows for long-read sequencing. Due to the size of the MinION device, it can be easily carried for field viral disease surveillance. This review article discusses grapevine viruses and their diagnostic methods, the principle of nanopore sequencing technology and its application in grapevine virus detection, virus–plant interactions, as well as the characterization of viral RNA modifications.

This paper provides attempts to formalize Hayek’s theory of knowledge. It has been theoretically shown that exponential income distribution is a spontaneous order of the well-functioning market economy. We show that this theoretical result is supported by the empirical evidence from the United Kingdom and China. In particular, we empirically show how the income structure of China evolved towards an exponential distribution after the market-oriented economic reformation. Furthermore, we strictly prove that, if the income structure of an economy obeys an exponential distribution, the income summation over all households leads to an aggregate production function with Hicks-neutral-like technical progress, in which the technology factor is exactly equal to society’s information stock that is a result of combining all of decentralized decisions.

Visual Patient technology is a situation awareness–oriented visualization technology that translates numerical and waveform patient monitoring data into a new user-centered visual language. Vital sign values are converted into colors, shapes, and rhythmic movements—a language humans can easily perceive and interpret—on a patient avatar model in real time. In this review, we summarize the current state of the research on the Visual Patient, including the technology, its history, and its scientific context. We also provide a summary of our primary research and a brief overview of research work on similar user-centered visualizations in medicine. In several computer-based studies under various experimental conditions, Visual Patient transferred more information per unit time, increased perceived diagnostic certainty, and lowered perceived workload. Eye tracking showed the technology worked because of the way it synthesizes and transforms vital sign information into new and logical forms corresponding to the real phenomena. The technology could be particularly useful for improving situation awareness in settings with high cognitive demand or when users must make quick decisions. This comprehensive review of Visual Patient research is the foundation for an evaluation of the technology in clinical applications, starting with a high-fidelity simulation study in early 2020.

Background: Telemedicine (interconsultation between primary and hospital care teams) has been operating in the counties of Central Catalonia Bages, Moianès and Berguedà since 2011 in the specialties of teledermatology, teleulcers, teleeyelids and teleaudiometries. For the period until the end of 2019, a total of 52,198 visits have been recorded. Objective: To analyse the differential costs between telemedicine and usual care in a semi-urban environment. Methodology: A cost-minimization evaluation, including direct and indirect costs from a societal perspective, distinguishing healthcare and user’s costs, within a three-month period. Results: Telemedicine saved € 780,397 over the period analysed. A differential cost favourable to telemedicine of about € 15/visit has been observed, the patient being the largest beneficiary of this saving (by 85%) in terms of shorter waiting times and travel costs. From the healthcare system perspective, moving the time spent in a hospital care consultation to primary care is efficient in terms of the total time devoted per patient. In social terms and in this context, telemedicine is more efficient than usual care. Conclusion: Users’ saving of time in terms of consultation and travel is the main driver of interconsultation between primary and hospital care savings in a semi-urban context. The telemedicine service is also economically favourable for the healthcare system, enabling it to provide a more agile service, which also benefits the healthcare professionals.

In this paper, the preparation methods of porous silicon nitride materials with controllable dielectric constant and pore structure were systematically studied. By using microwave sintering technology, porous silicon nitride materials with high closed pore ratio were prepared by adjusting the content of sintering additives and sintering process parameters, and controlling the grain boundary phase and pore structure and size. The effects of sintering conditions on the total porosity, closed porosity, pore structure and dielectric properties of materials were systematically studied.

Because of the near-term risk of extreme weather events and other adverse consequences from climate change, and, at least in the longer term, global fossil fuel depletion, there is world-wide interest in shifting to noncarbon energy sources, especially renewable energy (RE). Because of possible limitations on conventional renewable energy sources, researchers have looked for ways of overcoming these shortcomings by introducing radically new energy technologies. The largest RE source today is bioenergy, while solar energy and wind energy are regarded as having the largest technical potential. This paper reviews the literature on proposed new technologies for each of these three RE sources: microalgae for bioenergy, photolysis and airborne wind turbines. The main finding is that their proponents have underestimated the difficulties facing their introduction on a very large scale.

Current study aims to evaluate the possibilities to increase part strength by optimizing the FFF process parameters. Five different CAD models of parts with same coupling dimensions but different shape inherited from a recent study were converted into test samples with Ultimaker 2 3D printer. The main measure of success was the sample strength, defined as the load at which the first crack in the stressed area of the part appeared. Three different modifications to the FFF process with verified positive effect on interlayer bonding were applied. First modification included raising the extrusion temperature and disabling printed part cooling. Second modification consisted in reduction of the layer thickness. Third modification combined the effects of the first and the second ones. For four out of five shapes tested applied process modifications resulted in significant strengthening of the part. The shape that exhibited the best results was subject to further research by creating special printing mode. The mode included fine-tuning of three technological parameters on different stages of the part fabrication. As result it was possible to increase the part strength by 108% only by tuning printing parameters of the best shape designed with increasing its weight by 8%.

The bio-oil was largely produced by thermal pyrolysis of Jatropha-derived biomass wastes (denoted as Jatropha bio-oil) using a Pilot Plant with a capacity of 20 kg h-1 at Thailand Institute of Scientific and Technological Research (TISTR), Thailand. Jatropha bio-oil is an unconventional type of bio-oil, which is mostly composed of fatty acids, fatty acid methyl esters, fatty acid amides and derivatives, and consequently it contained large amounts of heteroatoms (oxygen ~ 20 wt.%, nitrogen ~ 5 wt.%, sulfur ~ 1000 ppm.). The heteroatoms, nitrogen especially, are highly poisonous to the metal or sulfide catalysts for upgrading of Jatropha bio-oil. To overcome this technical problem, we reported a stepwise strategy for hydrotreating of 100 wt% Jatropha bio-oil over mesoporous sulfide catalysts of CoMo/γ-Al2O3 and NiMo/γ-Al2O3 to produce drop-in transport fuels, such as gasoline- and diesel-like fuels. This study is very different from our recent work on co-processing of Jatropha bio-oil (ca. 10 wt%) with petroleum distillates to produce a hydrotreated oil as a diesel-like fuel (Chen et al., Catalysts 2018, 8, 59; http://dx.doi.org/10.3390/catal8020059). Jatropha bio-oil was pre-treated through a slurry-type high pressure reactor under severe condition, resulting in a pre-treated Jatropha bio-oil with relatively low amounts of heteroatoms (oxygen < 20 wt.%, nitrogen < 2 wt.%, sulfur < 500 ppm.). The light and middle distillates of pre-hydrotreated Jatropha bio oil was then separated by distillation at temperature below 240 oC, and the temperature of 240-360 oC. Deep hydrotreating of light distillates over sulfide CoMo/γ-Al2O3 catalyst was performed on a batch-type high pressure reactor at 350 oC and 7 MPa of H2 gas for 5 h. The hydrotreated oil was a gasoline-like fuel, which contained 29.5 vol.% of n-paraffins, 14.4 vol.% of iso-paraffins, 4.5 vol.% of olefins, 21.4 vol. % of naphthene compounds and 29.6 wt.% of aromatic compounds, and little amounts of heteroatoms (nearly no oxygen and sulfur, and less than 50 ppm of nitrogen), corresponding to an octane number of 44, and it would be suitable for blending with petro-gasoline. The hydrotreating of middle distillates over sulfide NiMo/γ-Al2O3 catalyst using the same reaction condition produced a hydrotreating oil with diesel-like composition, low amounts of heteroatoms (no oxygen and less than 50 ppm of sulfur and nitrogen), and a cetane number of 60, which would be suitable for use in drop-in diesel fuel.

The practice of collecting, treating and management of solid waste prior to disposal has become a necessity in developing and modern societies. Over the years, it is known that most wastes that are disposed have a second hand value. However, the construction cost for conventional Material Recovery Facility(s) (MRFs) has been a major barrier for implementation. These technologies require considerable technical expertise, which is often not available in developing nations to successfully operate the MRFs. Covenant University; a private mission institution through her waste to wealth scheme is focused on managing and processing used materials to reusable products. These include Pet bottles, Paper wastes, Food wastes from cafeteria, plastic food packs, nylon, tin cans and others. Specific areas chosen for the Survey include the residential areas for staff and students and the two cafeterias. The waste generated was characterized based on the waste stream so as to quantify the amount of recyclable waste generated and most occurring. The survey involved the use of structured questionnaires, on-site observations and measurements. The study reveals an average amount of recyclable waste generated per day in the institution as 13.46% pet bottles, 4.03% paper, 55.56% food waste, 12.64% plastic, 9.63% nylon and 4.68% tin cans. The study established that adequate waste characterization is a requirement for effective integrated solid waste management which would boost resource recovery, reuse and recycling.

This study presents a critical literature review on the models of users' adoption of blockchain applications in supply chains. This review pertaining to blockchain technology adoption by supply chain stakeholders is significant as it is a pre-requisite for the technical sustainability of blockchain technology in supply chains. Through a critical literature review, the previous studies related to technology adoption models were analyzed to explore practices brought about by blockchain applications for supply chain management. This study examined the suitability of the existing models (e.g., the technology-organization-environment (TOE) framework, task technology fit (TTF), unified theory of acceptance and use of technology (UTAUT)) of technology adoption for blockchain applications in supply chains and came up with a new unified model, namely, TOE-TTF-UTAUT. This review provides implications for a more appropriate research design using mixed methods. When adopting the TOE-TTF-UTAUT model in a study, two phases of research using mixed methods can be performed. The first phase is an exploratory sequential design in which a qualitative approach to explore the TOE and supply chain task constructs is followed by a quantitative approach using a survey and quantitative analyses to investigate the factors affecting blockchain adoption in supply chains. The second phase adopts explanatory sequential design in which the quantitative findings from the first phase are reviewed for follow-up by qualitative interviews to obtain explanations.

The normative and safeguarding role of ethics and law in the development of biomedical science and technology, as well as their importance in promoting the progress of the industry, analyzed the key role of ethics and law in the field of biomedical science and technology, by restricting scientific research behavior, protecting the rights and safety of subjects, providing a solid guarantee for scientific research activities, and promoting the healthy development of biomedical science and technology. At the same time, the positive role of ethics and law in promoting international cooperation and exchange of biomedical science and technology is also discussed, which will inject strong impetus into the global development of biomedical science and technology. In addition, through case analysis, the paper demonstrates the key role of ethical review in the field of biomedical science and technology, as well as the importance of law in maintaining market order, protecting subjects' rights and interests, and fairness and justice. The successful practice of ethics and law in the development of biomedical science and technology is emphasized, which proves that following ethical principles and legal framework is the key factor to promote the progress of biomedical science and technology. This paper explores the important role of ethics and law in the development of biomedical science and technology, and provides valuable reference and guidance for practitioners in the industry. By following ethical principles and legal norms, we will jointly promote the prosperity and development of biomedical science and technology, and contribute to the common progress of human health.

This paper undertakes a comprehensive review to underscore the central role of sustainability in the evaluation and innovation of jet grouting technologies. It meticulously traces the evolution of evaluation methodologies, emphasizing the imperative of sustainable practices throughout history. Traditional evaluation paradigms are examined alongside contemporary trends, with a particular focus on sustainability metrics and visualization techniques. Through an examination of innovative jet grouting technologies, this paper illustrates how sustainability principles have driven advancements aimed at improving the efficiency and environmental impact of jet grouting methods. Central to this review is an assessment of sustainability across multiple dimensions, including method applicability, installation and operational compatibility, and the performance of the resulting jet grouted piles. By emphasizing sustainability considerations, the paper highlights the intrinsic link between environmental integrity and technological innovation in the field of jet grouting. In addition, it discusses analytical evaluation methods designed to proactively address sustainability concerns prior to construction, thereby promoting a more environmentally responsible approach. Finally, this paper presents a pioneering evaluation framework that integrates real-time monitoring and visualization tools, allowing stakeholders to track sustainability milestones throughout the construction process. By emphasizing sustainability as a guiding principle, this review advocates for a paradigm shift toward more ecologically sound and resilient jet grouting practices.

Agriculture is an industry that heavily relies on the environment. The increasing frequency of ex-treme disasters attributable to climate change has adversely affected agricultural land and dis-rupted the stability of the supply of agricultural products. Therefore, we implemented a research program focused on current strategies for adapting to agricultural meteorological disasters. The primary goal was to actively promote disaster prevention information and techniques through information platforms and applications and to provide refined forecasting and an early warning system to enhance preparedness for and recovery from agricultural disasters. This initiative can transform passive mitigation into dynamic action by disseminating crucial information to farmers. We integrated meteorological data and crop characteristics to develop disaster prevention strate-gies for the predisaster, during-disaster, and postdisaster stages to empower farmers to implement autonomous disaster prevention, ensuring their profitability and minimizing the impact of disas-ters. This paper presents an agricultural disaster prevention system involving cross-disciplinary collaboration to establish an early warning system for crop disasters. However, the effectiveness of the early warning system relies on the availability of complete meteorological and crop infor-mation, necessitating high-density agricultural meteorological stations, refined weather forecast services, historical crop damage data, and ongoing research and development on disaster preven-tion technology. In the system, a diversified social media interface is used to provide local farmers with weather forecast information. When impending disasters are identified, the platform acti-vates disaster prevention measures to reduce agricultural losses. This article paper introduces Taiwan’s agricultural disaster prevention system as a complete disaster prevention strategy.

(1) Background: This paper details the development process of two assistive technology products (ATs) implemented in the PAID project, aiming to promote the social, educational, and labor inclusion of people with disabilities across 10 municipalities of Antioquia, Colombia. (2) Methods: Applying Design Thinking (DT) methodology, including stages of empathizing, defining, ideating, prototyping, and testing, alongside a demographic study where specific needs of people with disabilities (PwDs) were identified. (3) Results: As a result, the construction process of two specific cases of assistive technology products (ATs) is detailed, including finite element simulation, mechanical testing, and delivery to end-users. Additionally, workshops for assistive product fabrication conducted in select municipalities of the project are highlighted. (4) Conclusions: the information gathered guided the development of the ATs, focusing on their features on accessibility and ease of replication. The primary objective is to facilitate the participation of PwDs in educational environments, thus promoting inclusion and accessibility. This article describes the results of two of these ATs; however, it is worth noting that this process was performed for 112 ATs delivered through the duration of the project.

Digital transformation systems generate a substantial volume of data, creating opportunities for potential innovation, particularly those driven by artificial intelligence. This study focuses on the intricate relationship between artificial intelligence and innovation as foundational elements in the digital transformation framework for sustained growth and operational excellence. This study provides a holistic perspective on the cultivation and pillars of AI-powered innovation, highlighting their pivotal role in revolutionizing industries, including healthcare, education, finance, manufacturing, transportation, and agriculture. The work emphasizes the key pillars essential for fostering AI-powered innovation, including monitoring performance measurement to use the power of the present, continuous learning and innovation, data analytics and insights, predictive analytics, and innovative product development. This study investigates how these pillars serve as the foundation for groundbreaking advancements, driving efficiency, enhancing decision-making processes, and fostering creativity within organizations. This study explores the significance of continuous learning, interdisciplinary collaboration, and industry partnerships in nurturing a thriving AI-powered innovation ecosystem. By understanding and harnessing these fundamental elements, businesses can navigate the complexities of the digital age, fostering innovation that not only optimizes processes but also enhances the overall human experience, ushering in a new era of technological excellence and societal progress.

The development of new medical monitoring applications requires precise modeling of the human body effects as well as simulating and emulating realistic scenarios and conditions. The first aim of this paper is to develop realistic and adjustable human body 3D emulation platforms which could be used for evaluating emerging microwave-based medical monitoring/sensing applications such as the detection of brain tumors, strokes, breast cancers as well as for capsule endoscopy studies. The new phantom recipes are developed for microwave ranges for the realistic shaped phantom molds. The second aim is to validate the feasibility and reliability of the phantoms for practical scenarios with electromagnetic simulations using tissue layer models and biomedical antennas. The third aim is to investigate the impact of the water temperature in the phantom cooking phase on the dielectric properties of the stabilized phantom. The evaluations show that the dielectric properties of the developed phantoms correspond closely to those of real human tissue. The error in dielectric properties varies between 0.5-8%. In the practical scenario simulations, the differences obtained with phantoms-based simulations in S21 parameters are 0.1-13dB. However, the differences are smaller in the frequency ranges targeted for medical applications.

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.

Post-harvest handling and ripening techniques have an impact on peach quality and shelf life, which has a big impact on consumer satisfaction and market competitiveness. This review paper examines recent advancements in ripening techniques and post-harvest technologies with the goal of improving peach fruit quality and sustainability. The factors impacting fruit quality after harvest and the physiological changes that occur throughout peach ripening are fully explained. For maintaining peach freshness and reducing losses, novel handling methods like modified atmosphere packaging (MAP) and controlled atmosphere storage (CAS) have been investigated. The study explores the possibilities of nanotechnology applications and low-temperature storage for prolonging shelf life while maintaining texture, flavor, and aroma. Examining the effectiveness and waste reduction potential of automation and mechanization in post-harvest activities. The paper also discusses ethylene-based and non-ethylene-based ripening agents, as well as innovative techniques including gene editing and RNAi technology for controlled and delayed ripening. Analyses are done on how these technologies affect the sensory qualities and nutrient profiles of peaches. The study emphasizes the significance of sustainable practices in the peach industry by focusing on waste reduction, resource efficiency, and circular economy integration. Post-harvest technologies' potential environmental consequences have been taken into consideration and the paper encourages more study and cooperation to increase sustainability.

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.

In this study, sodium alginate (SA) was oxidized with potassium periodate to produce an alginate-based tanning agent. Using OSA as a biodegradable tanning agent and a nano-hydroxyapatite (nano-HAp) low concentration suspension to give flame retardancy to leather, eco-design concepts were applied to establish a chrome-, aldehyde-, and phenol-free tanning process. Micro-DSC, 1H NMR, attenuated total reflection mode Fourier transform infrared spectroscopy (FTIR-ATR), and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS) were used to investigate the complex matrix collagen-OSA-nano-HAp. Micro-differential scanning calorimetry (micro-DSC) was used to assess OSA's ability to interact with collagen and stabilize the collagen-OSA matrix, while 1H unilateral nuclear magnetic resonance (NMR) was used to investigate the aqueous environment and limitations around collagen molecules caused by their association with OSA and nano-HAp. Industrial standard tests were used to assess mechanical properties and fire resistance of the new leather prototype. The findings reported here indicate that both OSA and nano-HAp are suitable alternatives for cleaner tanning technologies and more sustainable leather.

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&lt;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.

Mobile payment has become increasingly popular due to the widespread use of smartphones and their applications. However, its adoption in African countries has been limited, despite its potential to simplify our lives. This study aims to enhance our understanding of the factors that affect the acceptance of mobile payment in Nigeria. To achieve this, the paper explores the impact of "network externalities" in addition to traditional technology acceptance factors. The study hypothesizes that the key drivers of mobile payment acceptance are performance expectancy, effort expectancy, social influence, trust, and network externality. The research findings suggest that while traditional drivers still play a role in customers' willingness to adopt mobile payment, network externalities have the strongest impact. Although the results did not support the influence of effort expectancy, the paper provides recommendations for future research.

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.

Silicon-based microchannel technology offers unmatched performances for cooling high energy physics silicon-pixels detectors. Although Si-Si direct bonding, used for the fabrication of cooling plates, meets the stringent requirements of this application, in particular high-pressure resistance (~200 bar), it is reported to be a challenging and expensive process. In this work, we have evaluated two alternative bonding methods towards a more cost-effective fabrication process: Si-Glass-Si anodic bonding (AB) with a thin-film glass and Au-Au thermocompression (TC). The bonding strength of the two methods were evaluated with destructive pressure burst tests (0 - 690 bar) on test structures, each made of a 1×2 cm² silicon die etched with a tank and an inlet channel and sealed with a plain silicon die using AB or TC bonding. The pressure resistance of the structures was measured to be higher for the TC sealed samples (max. 690 bar) than for the AB ones (max. 530 bar) but less reproducible. The failure analysis indicates that the AB structure resistance is limited by the adhesion force of the deposited layers. Nevertheless, both the TC and AB methods provided sufficient bond quality to hold the high pressure required for the high energy physics pixel detectors cooling application.

Commonly employed methods for reversibly disrupting gene expression, such as those based on RNAi or CRISPRi, are rarely capable of achieving >80-90% downregulation, making them unsuitable for targeting genes that require more complete disruption to elicit a phenotype. Genetic deletion, on the other hand, while enabling complete disruption of target genes, often produces undesirable irreversible consequences such as cytotoxicity or cell death. Here we describe the design, development and detailed characterization of a dual-function "TRE-Lox" system for effecting either (a) doxycycline (Dox)-mediated downregulation or (b) genetic deletion of cathepsin D (CatD), based on targeted insertion of a tetracycline-response element (TRE) and two LoxP sites into the 5' end of the endogenous gene (CTSD). Using an optimized reverse-tetracycline transrepressor (rtTR) variant fused with the Krüppel-associated box (KRAB) domain, we show that CatD expression can be disrupted by as much as 98% in mouse embryonic fibroblasts (MEFs). This system is highly sensitive to Dox (IC50 = 1.46 ng/mL) and results in rapid (t1/2 = 0.57 d) and titratable downregulation of CatD. Notably, even near-total disruption of CatD expression was completely reversed by withdrawal of Dox. As expected, transient expression of Cre recombinase results in complete deletion of the CTSD gene. The dual functionality of this novel system will facilitate future studies of the involvement of CatD in various diseases, particularly those attributable to partial loss of CatD function. In addition, the TRE-Lox approach should be applicable to the regulation of other target genes requiring more complete disruption than can be achieved by traditional methods.

In recent years, the rise of advanced artificial intelligence technologies has had a profound impact on many fields, including education and research. One such technology is ChatGPT, a powerful large language model developed by OpenAI. This technology offers exciting opportunities for students and educators, including personalized feedback, increased accessibility, interactive conversations, lesson preparation, evaluation, and new ways to teach complex concepts. However, ChatGPT poses different threats to the traditional education and research system, including the possibility of cheating on online exams, human-like text generation, diminished critical thinking skills, and difficulties in evaluating information generated by ChatGPT. This study explores potential opportunities and threats that ChatGPT poses to overall education from the perspective of students and educators. Furthermore, for programming learning, we explore how ChatGPT helps students improve their programming skills. To demonstrate this, we conducted different coding-related experiments with ChatGPT, including code generation from problem descriptions, pseudocode generation of algorithms from texts, and code correction. We also verified the generated codes with an online judge system to evaluate their accuracy.

Background and Purpose: Open-source Artificial intelligence (AI) applications are fast transforming access to information and allow students to prepare assignments and offer quite accurate responses to a wide range of exam questions which are routinely used in assessments of students across the board including undergraduate dental students. This study aims to evaluate the performance ChatGPT, an AI-based application, on a wide range of dental assessments and discusses the implications for undergraduate dental education. Methods: This was an exploratory study investigating the accuracy of ChatGPT to attempt a range of recognized assessments in undergraduate dental curricula. ChatGPT was used to attempt ten items based on each of the five commonly used question formats including single-best answer (SBA) multiple-choice questions (MCQs); short answer questions (SAQs); short essay questions (SEQs); True/False questions and fill in the blanks items. In addition, ChatGPT was used to generate reflective reports based on multisource feedback (MSF); research methodology; critical appraisal of the literature. Results: ChatGPT application provided accurate responses to majority of knowledge-based assessments based on MCQs, SAQs, SEQs, Tue/False and fill in the blanks items. However, it was only able to answer text-based questions and did not allow processing of questions based on images. Responses generated to written assignments were also of good quality apart from those for critical appraisal of literature. Word count was the key limitation observed in outputs by ChatGPT as it was only able to produce reports limited to approximately 650 words. Conclusion: Notwithstanding their current limitations, AI-based applications have the potential to revolutionize virtual learning. Instead of treating it as a threat, dental educators need to adapt teaching and assessments in dental education to the benefits of the learners whilst mitigating against dishonest use of AI-based applications.

With the rise of powerful computational technologies, healthcare systems are going through a paradigm shift to the era of healthcare 5.0, also known as" smart healthcare". This new-age healthcare system not only enhances the life of patients but also aims to reduce healthcare costs significantly. People's health data collected through various means, including various Internet of Things (IoT) devices, is too sensitive to be regulated by particular organisations owing to increasing privacy and security threats. The sheer size of data makes it difficult for centralised bodies to regulate, due to which third-party involvement is introduced, which again poses threats to the privacy of the data holder. Motivated by the abovementioned gaps, we propose a decentralised approach using Ethereum blockchain technology and Oasis protocol. The patient-driven solution approach effectively solves the privacy problem by providing complete control of data to the owner. Along with this, byproducts such as fine-grained access control and on-chain data processing capabilities are also obtained.

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.

Global demand for sleep-tracking wearables, or consumer sleep technologies (CSTs), is steadily increasing. CST marketing campaigns often feature a scientific component, but the scientific relevancy and monetary value of CST features within the sleep research community remains unquantified. Sleep medicine experts were recruited through social media and nonprobability sampling techniques to complete a survey identifying sleep metrics and device features that are most desirable to the scientific community. A hypothetical purchase task (HPT) estimated economic valuation for devices with different features by price. Forty-six (N=46) respondents with an average of 10±6 years’ experience conducting research in real-world settings completed the online survey. Total sleep time was ranked as the most important measure of sleep followed by objective sleep quality while sleep architecture/depth and diagnostic information were ranked as least important. Experts preferred wrist-worn devices that could reliably determine sleep episodes as short as 20 minutes. Economic value was greater for hypothetical devices with longer battery life. These data set a precedent to determine how scientific relevance of a product impacts the potential market value of a CST device. This is the first known attempt to establish consensus opinion or economic valuation for scientifically-desirable CST features and metrics using expert elicitation.

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.

The last half of the 20th century was characterized by the most impactful ecosystem changes throughout regulations and guidelines minimalizing environmental harms. Many of them emphasize the importance of enterprise sustainability for renewable energy policy. When dealing with numerous alternatives for the implementation of renewables-based policy, decision-makers need to analyze their impacts on environmental, economic, and social dimensions from a long-term perspective. The aim of this paper is to highlight a challenge to apply the multi-criteria sustainability decision-making framework (MDCA) to mainstream energy policy. The integrative framework covers an approach for the needs of analyzing factors influencing the energy technology selection. In this study, the MDCA-approach combines lifecycle-based methods, Analytical Hierarchy Process, PESTEL (Political, Economic, Social, Technological, Environment and Legal). To demonstrate the applicability and usability of the method three photovoltaic technologies are assessed. The results showed that string ribbon technology is the most sustainable along its life cycle, with a 0.503 sustainability score. The study highlighted the need to embody robust methodologies assessing sustainability-oriented technologies, not used anymore for supporting energy policies. This challenge regarding example evidence can give energy decision-makers a tool to realize their energy policy and in consequence, enhance enterprise sustainability.

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.

Livestock production systems generate nuisance odor and gaseous emissions affecting local communities and regional air quality. Also, there are concerns about the occupational health and safety of farm workers. Proven mitigation technologies that are consistent with the socio-economic challenges of animal farming are needed. We have been scaling up the photocatalytic treatment of emissions from lab-scale, aiming at farm-scale readiness. In this paper, we present the design, testing, and commissioning of a mobile laboratory for on-farm research and demonstration of performance in real farm conditions. The mobile lab is capable of treating up to 1.2 m3·s-1 of air with TiO2-based photocatalysis and adjustable UV-A dose based on LED lamps. We summarize the main technical requirements, constraints, approach, and performance metrics for the mobile laboratory, such as the effectiveness (measured as the percent reduction) and cost of photocatalytic treatment of air. The commissioning of all systems with standard gases resulted in ~9% and 34% reduction of NH3 and butan-1-ol, respectively. We demonstrated that as the percent reduction of standard gases increased with increased light intensity and treatment time. These results show that the mobile laboratory was ready for on-farm deployment and evaluating the effectiveness of UV treatment.

The efficiency of producing embryos using in vitro technologies in livestock species rarely exceeds the 30 to 40% threshold, indicating that the proportion of oocytes that fail to develop after in vitro fertilization and culture is considerably large. Considering that the intrinsic quality of the oocyte is one of the main factors affecting blastocyst yield, the precise identification of non-invasive cellular or molecular markers that predict oocyte competence is of major interest to research and practical applications. The aim of this review was to explore the current literature on different non-invasive markers associated with oocyte quality in the bovine model. Apart from some controversial findings, the presence of cycle-related structures in ovaries, a follicle size between 6 and 10 mm, large number of surrounding cumulus cells, slightly expanded investment without dark areas, large oocyte diameter (>120 microns), dark cytoplasm, and the presence of a round and smooth first polar body have been associated to better competence. In addition, the combination of oocyte and zygote selection by BCB test and spindle imaging have the potential to further optimize the identification of oocytes with better developmental competence for in vitro-derived technologies in livestock species.

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.

With the continuous emergence and application of new technologies, the construction of smart cities has entered the practical promotion period. Since 2012, the pilot construction of smart city has been promoted by the government in China. On the basis of these practical experiences, this paper presents an overview of the latest technologies and applications for smart city construction in China and demonstrates that smart city strategy needs to be implemented according to local conditions, adhering to the people-oriented concept and using scientific and effective top-level design and planning. The construction of smart city is comprehensive system engineering, including the integration of geographic information sharing service platform, full-cycle management and control system of urban planning, construction and social management, as well as intelligent business information management system of gardening, water conservancy, environmental protection and other industries and departments. The information system (GIS), satellite remote sensing (SRS), global navigation satellite system (GNSS), Internet of things, mobile applications, cloud computing, visualization technology ware used to promote urban construction and sustainable development, and to meet the needs of future smart city development. Results show that centralized management is very important for the construction of smart city. The government plays a major role in the construction of smart city, which will be conducive to the development of new technologies and the effective use of smart city construction resources.

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.

The definition of a Smart-complex of educational discipline and its technology is given. Attention is focused on the form of the Smart-complex and constructive elements: the creative educational environment, the author's environment, the non-verbal environment, the encyclopedia, the creative / self-realization environment, the monitoring / self-evaluation environment.A feature of the Smart-complex of the academic discipline is the integration into it of the structural equalization block. Constructive alignment (alignment) is based on the design of the student's own learning participation in educational projects. Alignment refers to creating an appropriate learning environment and involves selecting the most appropriate training activities and evaluating each learning outcome. If the result of the training is to develop analytical skills, then for the assessment it is necessary to build questions and scenarios for their development.Two main components of the structural alignment are considered: 1) the first component is based on cognitive psychology and constructivist theory, recognizes the importance of linking new material with the concepts and experiences of students and extrapolation to possible future scenarios in the process of mission activity - they comprehend what they are doing during training; 2) the second component is based on the declaration by the teacher of the correspondence between the planned educational activities and the results of the training of students. This makes planning of educational activities and development of self-assessment criteria for organizing feedback. It is necessary to take into account the impact of Smart-complexes of educational disciplines on three think-tank training networks: 1) effective networks (why learn) - several ways of presenting to give students different ways of obtaining information and knowledge; 2) recognition networks (learning outcomes) - several ways of expressing them to provide them with an alternative for demonstrating what they know; 3) strategic exercises (how to learn) - several ways to increase the motivation for learning to attract their attention to both their own learning project and its technical and historical decision. Smart-complexes of educational disciplines should be: 1) scientific; 2) with user-friendly interface; 3) have a connection with LMS; 4) structured; 5) with visual material; 6) working in Off-line mode; 7) used on various devices in an educational institution, as well as at home.

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.

Background: in this paper, a new physical penetration technology for transdermal administration with traditional Chinese medicine (TCM) characteristics - Fu’s cupping therapy (FCT) - was established and studied by in-vitro and in-vivo experiments; the penetration effect and mechanism of FCT physical penetration technology (FCT-PPT) was preliminarily discussed. Method: Indomethacin (IM) as a model drug，by transdermal in vitro tests the establishment of the high，medium and low reference were finished as the chemical permeation system；chemical penetration enhancers and iontophoresis as a reference，the percutaneous penetration effect of FCT for IM patch was evaluated with 7 species diffusion kinetics model and in vitro drug distribution；naproxen as an internal standard，using UPLC-MS/MS technology，the IM quantitative analysis method in vivo was established，and pharmacokinetic parameters (AUC0-t，AUC0-∞，AUMC0-t，AUMC0-∞, Cmax and MRT) as indicators were used evaluate to FCT penetration role in vivo；in the same time，the group used 3K factorial design to study joint synergistic penetration effect on FCT and chemical penetration enhancers (CPEs)；by SEM and TEM，the skin micro and ultrastructural changes of the stratum corneum (SC) surface were observed, to explore pay tank penetration mechanism. Results: In vitro and in-vivo skin permeation experiments revealed that both the total cumulative percutaneous amount and in-vivo percutaneous absorption amount (AUC and AUMC) of indomethacin that permeated SD mouse skin using FCT techniques were greater than the amount observed using CPE and iontophoresis: Firstly, in contrast to the control group, the indomethacin percutaneous rate (PR) of the FCT lower group (FCTL) was 35.52%, and the enhancement ratio (ER) at 9h was 1.76X, which was roughly equivalent to the penetration enhancing effect of the CPEs and iontophoresis; secondly, the indomethacin PR of the FCT middle (FCTM) group and the FCT high intensity group (FCTH) were respectively 47.36% and 54.58%, ER at 9h were separately 3.58X and 8.39X; thirdly, pharmacokinetic studies showed that in-vivo indomethacin percutaneous absorption of the FCTs was higher than that of the control group, that of the FCTM group was slightly higher than that of the CPEs group, and that of the FCTM group was significantly higher than that of the others. Meanwhile, the variance analysis indicated that the combination of the FCT penetration enhancement method and the CPE method had beneficial effects in penetration enhancing of the skin: the significance level of the CPE method was 0.0004, which was apparently lower than the 0.001, meaning the difference was markedly significant; the significance level of the FCT was under 0.0001, its difference markedly significant; and the significance level of factor interaction A×B was lower than 0.0001, indicating that its difference of the synergism was markedly significant. Moreover, SEM and TEM images showed that the SC surfaces of SD rats treaded with FCT-PPT was damaged, and hard to observe the complete surface structure with its SC pores growing bigger and its special “brick structure” becoming looser, indicating that it broke the barrier function of skin, which revealed potentially a major route of skin penetration. Conclusion: FCT, as percutaneous penetration new technologies, has penetration effects significantly, with Chinese characteristics and highly clinical value, worth promoting development.