This paper presents the PEnsemble 4 model, a sophisticated machine learning framework that integrates IoT-based environmental data to accurately forecast maize yield. With the projected significant growth in global maize demand over the next decade, the inherent risks posed by the crop’s dependence on weather conditions necessitate improved prediction capabilities. The PEnsemble 4 model, developed with high accuracy, incorporates comprehensive datasets encompassing soil attributes, nutrient composition, weather conditions, and UAV-captured vegetation imagery. By employing a combination of Huber and M estimates, the PEnsemble 4 model effectively analyzes temporal patterns in vegetation indices, specifically CIre and NDRE, which serve as reliable indicators of canopy density and plant height. In addition, this research significantly contributes to precision agriculture by offering an efficient and sustainable alternative to conventional farming practices through precise yield predictions. Notably, the PEnsemble 4 model enables earlier estimation, advancing the timeline for yield prediction from the conventional day 100 in the R6 stage to day 79 in the R2 stage. This improvement enhances decision-making processes in farming operations. The remarkable accuracy rate of 91% underscores the importance of adopting a multifaceted data approach that harnesses IoT-derived environmental insights. Additionally, the PEnsemble 4 model extends its benefits beyond yield prediction, facilitating the detection of water and crop stress, as well as disease monitoring in broader agricultural contexts. Ultimately, the PEnsemble 4 model establishes a new standard in maize yield prediction, revolutionizing crop management and protection through the synergistic utilization of IoT and machine learning technologies.

This study aimed to learn disturbance information to effectively control multiple small unmanned surface vehicles (USVs) for marine research purposes at sea. The learned disturbance information was used to investigate the control of multiple USV swarms based on the leading–following formation technique. Numerous studies have already been conducted on swarm control using drones in the air; however, there has been a paucity of studies on swarm control in the sea. Contrary to swarm control in aviation, the fluid density of the sea is high, and the environment is constantly changing; thus, a robot system would be significantly affected by disturbances. This ultimately influences the maintenance of swarm formations and the accomplishment of missions [1,2]. Therefore, it is difficult to control numerous moving objects while maintaining a formation at sea by using the existing aerial drone swarm control technology. To solve this problem, we learned a long short-term memory (LSTM) model with time-series marine environmental data to predict maritime disturbances. Thereafter, the model was applied to a mission-based position control algorithm of each USV constituting the swarm to design a marine unmanned floating vessel swarm control system that can be applied to various marine environments. Specifically, to effectively control numerous small USVs for marine research purposes, ocean currents are learned using the LSTM algorithm, and the predicted ocean currents are used to generate a swarm USV control system for USV formations. In this study, a control system model of several small USVs equipped with two rear thrusters and a front lateral thruster was designed. The LSTM algorithm was learned using the previous ocean current data, and the velocity of the following ocean currents was predicted. The predictions were then used as a system disturbance to determine the thrust of the controller. To measure ocean currents in the sea when each USV moves, the velocity, azimuth, and position (latitude, longitude) data from the GPS mounted on the USV were used to measure the velocity and direction of the hull's movement. Further, the flow rate was measured using a flow rate sensor on a small USV. The USV movement and position were controlled using an artificial neural network-PID (ANN-PID) controller. This study entailed a comparative analysis of the designed USV model results and those generated by the simulator, including the behavior control rule of the USV swarm and the path of the actual USV swarm at sea. It was verified that the effectiveness of the USV mathematical model and behavior control rules. By comparing the movement path of the swarm USV with and without the disturbance learning algorithm and ANN-PID control algorithm applied to the designed simulator, the position error and maintenance performance of the swarm formation were analyzed, and the application results were compared.

The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANN-Artificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%.

The determinants of enterprises providing ICT training in Europe are analyzed in this article. Data are collected from the European Innovation Scoreboard-EIS of the European Commission for 36 European countries in the period 2000-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. Results show that the number of enterprises providing ICT training in Europe is positively associate with “Innovation Index”, “Innovators”, “New Doctorate Graduates”, “Tertiary Education” and negatively associated with “Government Procurement of Advanced Technology Products”, “Human Resources”, and “Marketing or Organisational Innovators”. In adjunct a cluster analysis is performed by using k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of four clusters. Finally, we use eight different machine learning algorithms to predict the value of the enterprises providing ICT training in Europe. We found that the Simple Tree Regression is the best predictor and that the number of enterprises providing ICT training in Europe is expected to growth of the 5,02%.

This study tries to focusing on applying information communication technology for economic importance of Mid Oil Company (MDOC), which is among contemporary oil companies in Iraq. Since ICT forms a significant aspect of achieving organizational economic objectives, most of public and private bodies seek to utilize ICT tool and techniques to improve work efficiencies. The emerging growth in ICT has made it process and service automation possible in managing organizational activities. To determine this effect of ICT on organizations, this study formulated statistical research model at MDOC through using fifteen questionnaires, which were distributed on three axes. The outcome of the questionnaire analysis revealed that there is inadequate comprehensive infrastructure to suitably support ICT within the selected organization management. In addition, it revealed that there are no ideal standards to maintain and sustain internet networks. Based on these revelations, the study presents recommendation for the adoption of ICT with the aim of minimizing cost, enhancing communication and managing infrastructure. Also recommends the need to support IT department within an organization, with essential equipment, in terms of man and machine, for better efficiency to employ the key of ICT Impact in Iraqi governmental oil companies.

Within the Active Living and Well-Being Project (RRP3), funded by the Republic of Slovenia and the European Regional Development Fund Investing in Your Future programme, we aim to develop different approaches and prototypes to provide ICT solutions for the family in order to connect its members, communicate, promote quality family time, active life, a health-friendly lifestyle and well-being, and integrate various sensor and user-based data sources into a smart city ecosystem platform. A mixed methodology, combined qualitative and quantitative approaches, was selected to conduct a study. An online survey with a structured questionnaire as well as semi-structured interviews were performed. Through the analysis of the results we tried to establish a family-centred design approach that would be inclusive as much as possible, creating benefits for all generations in order to develop interactive prototypes that would allow us to further test and verify different use-case scenarios.

The domain of Information and Communication Technology (ICT) education has garnered significant consideration in recent times. However, several challenges are inherent to this area of study, including monetary expense, temporal factors, pedagogical environment, teacher training programs, incentive, syllabus design, and health-related concerns. This paper presents an analysis of the difficulties encountered in the realm of ICT education in Japan, taking into account ten different perspectives.

The evolution towards Industry 4.0 is driving the need for innovative solutions in the area of network management, considering the complex, dynamic and heterogeneous nature of ICT supply chains. To this end, Intent-Based networking (IBN) which is already proven to evolve how network management is driven today, can be implemented as a solution to facilitate the management of large ICT supply chains. In this paper, we first present a comparison of the main architectural components of typical IBN systems and, then, we study the key engineering requirements when integrating IBN with ICT supply chain network systems while considering AI methods. We also propose a general architecture design that enables intent translation of ICT supply chain specifications into lower level policies, to finally show an example of how the access control is performed in a modelled ICT supply chain system.

Background Community infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased rapidly since the emergence of the Omicron strain. During the eighth and ninth pandemic waves—when movement restrictions in the community were eased—the all-case registration system was changed, and the actual status of infection became uncertain. Methods We conducted regular rapid antigen tests (R-RAT) once or twice a week to examine the actual state of coronavirus disease (COVID-19) diagnosis among healthcare employees. Results Overall, 320 (1.42/day) and 299 (1.76/day) employees were infected in the eighth and ninth pandemic waves. During both periods, 59/263 doctors (22.4%), 335/806 nurses (41.6%), 92/194 administrative employees (47.4%), and 129/218 clinical laboratory technicians (59.2%) were infected. In the eighth wave, 56 of 195 employees were infected through close contact; in the ninth wave, 26 of 62 employees were infected. No significant difference was observed in the number of vaccinations between infected and non-infected employees. The positivity rate of R-RAT was 0.41% and 0.45% in the eighth and ninth waves. R-RAT detected infection in 212 and 229 employees during the eighth and ninth waves, respectively; the ratio of R-RAT-detected positive employees to those who reported infection was significantly higher during the ninth wave (odds ratio: 1.67, 95% confidence interval: 1.17–2.37, p

Certain services can help avoid environmental impact in larger contexts. However, there is no commonly agreed bottom-up methodology for calculation of the total net reduction effect of specific digital services. Life Cycle Assessment (LCA) is a common denominator for most methodologies. The most common method is the Attributional LCA (ALCA), and recently the emerging handprint ALCA estimating so-called positive environmental impacts. Moreover, Consequential LCA (CLCA) can be used to capture market effects. The third conceptual approach is Input-Output LCA. The purpose is to propose and test a new method based on some of the existing ones. The existing concepts are compared and a synthesis is made to create a practical but still useful method. The new method is applied to two illustrative cases in the Information and Communication Technology (ICT) domain; the introduction of a 5G enabled drone for pipe inspection and the 5G enabled health consultation. Compared to simplified ALCA, the difference between the absolute score for the baseline system and the target system changes up to 15% when the proposed simplified CLCA (SCLCA) method is used. The results show that SCLCA, when combined with analytical methods for expressing digital ICT services’ own impact, is a fruitful approach which is both practical and feasible.

New hetero-polynuclear coordination complexes based on pentacoordinated Zn(II) metal center with tridentate terpyridine-based ligands and monoanionic gallates functionalized with long alkyl chains containing ferrocene units were designed, synthesized and characterized by spectroscopic and analytical methods. The complexes are mesomorphic, exhibiting columnar hexagonal mesophases at room temperature. The photophysical properties in solution were accurately investigated and the influence of the polarity of the media in solution was evidenced.

The importance of ICTs for dissemination of information to farmers has been verified by extension practitioners, information and communication scholars, policy makers and development agencies. Information related to new seed varieties, production technologies, livestock breeds, vaccines, including weed and pest control, as well as relevant market information is constantly required by smallholder farmers. The identification of specific attributes among smallholder farmers which contributes to their adoption of a proposed ICT-based information source provides an important tool for developing interventions which address the information needs of farmers. Using a literature survey methodology, pertinent studies related to adoption of ICTs, farmers’ information source usage and relevant frameworks were identified, including applicable theories and models in technology adoption and information behaviour. In the proposed framework, the socio-economic characteristics of smallholder farmers were posited as key variables influencing smallholder farmers, within a farming system, to adopt ICT-based information sources. The framework contributes to discern the prospects of adopting ICT-based information sources by individual farmers within a farming system, and may also envisage other related welfare outcomes and market participation pathways among smallholder farmers. The review also addresses the paucity of conceptual discourse, while contributing to a growing pool of research on ICT in African agriculture.

This paper presents the results of a recent study that was conducted with a number of German municipalities/cities. Based on the obtained and briefly presented recommendations emerging from the study, the authors propose the concept of an Urban Data Space (UDS), which facilitates an eco-system for data exchange and added value creation thereby utilizing the various types of data within a smart city/municipality. Looking at an Urban Data Space from within a German context and considering the current situation and developments in German municipalities, this paper proposes a reasonable classification of urban data that allows to relate the various data types to legal aspects and to conduct solid considerations regarding technical implementation designs and decisions. Furthermore, the Urban Data Space is described/analyzed in detail, and relevant stakeholders are identified, as well as corresponding technical artifacts are introduced. The authors propose to setup Urban Data Spaces based on emerging standards from the area of ICT reference architectures for Smart Cities, such as DIN SPEC 91357 “Open Urban Platform” and EIP SCC. Thereby, the paper walks the reader through the construction of an UDS based on the above mentioned architectures and outlines all the goals, recommendations and potentials, which an Urban Data Space can reveal to a municipality/city.

This paper attempts to alter a prevailing assumption that buildings use energy to an understanding that in fact, people use energy. Therefore, to successfully accelerate the transition to a low-carbon society and economy more emphasis should be on motivating people and increasing their awareness by making them energy conscious building users and therefore active players in the energy transition process. In this context, this paper provides insights from the Horizon 2020 MOBISTYLE project. It demonstrates research and development approaches, highlights the main project objectives, and presents findings of an ethnographic (qualitative) study of users’ habits, practices, and needs. The aim of the project is to motivate behavioural change by raising consumer awareness through the provision of attractive personalized information on user’s energy use, indoor environment and health, all enabled by an integrated information and communication technology (ICT) service. In this context, the anthropological people-centred approach is integrated into the MOBISTYLE approach putting users at the centre of the ICT tools development process. The main quantitative objective of the project is a reduction of energy use for at least 16 % prompted by the provision of combined information and feedback systems on energy, indoor environmental quality (IEQ) and health. The most relevant motivational factors and key performance indicators (KPIs) for encouraging a more energy conscious and healthy lifestyle were defined by means of a people-centred approach, adopting anthropological inquiries in different settings. Information about users’ lifestyles and their needs was collected in focus groups with potential users in five case studies, located in different European Union (EU) countries. Behaviour change is achieved through awareness campaigns, which encourage users to be pro-active about their energy consumption and to simultaneously improve health and well-being.

The 2030 global agenda of the United Nations emphasizes peace, human rights, gender equality, partnership, and women's empowerment. It balances the social, economic, and environmental dimensions of sustainable development. The SDG framework was designed to be integrated and indivisible, making the interconnections of 17 Goals and 169 Sustainable Development Goals Targets (SDTs) more complex that need extensive and intensive investigative research. Recent studies have increased on the interrelationships of SDGs, but none of these have focused on integrating Climate Change (CC), Sustainable Forest Management (SFM), and Information and Communication Technology (ICT), also known as CSI Nexus. This study aims to investigate and identify the 169 SDTs linked to CC, SFM, and ICT and assesses the significance of the relationships between these variables. The alignment of SDTs to CSI Nexus was identified through clustering and mapping techniques. The result argued that 56 SDTs are directly connected within CC+SFM+ICT, 16 within CC+SFM, one within SFM+ICT, and 51 within ICT+CC. Our result suggests that CC is significantly associated with SFM; however, ICT has no significant association with CC and SFM. It further asserts that the ICT and SFM have minimal influence on the SDG 2030 framework. The proposed CSI Nexus and SDTs Integration Framework was a science-informed guide for priority-setting, policy coherence, and decision-making supporting the 2030 Sustainable Development Goals. This study does not include interactions, network analysis and visualization, simulations, and modeling between SDG targets.

The specific demands inherent to supply chains built upon large IoT systems, make a must the design of a coordinated framework for cyber resilience provisioning intended to guaranteeing trusted supply chains of ICT systems, built upon distributed, dynamic, potentially insecure and heterogeneous ICT infrastructures. As such, the proposed solution is envisioned to deal with the whole supply chain system components, from the IoT ecosystem to the infrastructure connecting them, addressing security and privacy functionalities related to risks and vulnerabilities management, accountability and mitigation strategies as well as security metrics and evidence-based security assurance. In this paper we present FISHY, as a preliminary designed architecture, designed to orchestrate both existing and beyond state-of-the-art security appliances in composed ICT scenarios and also leveraging capabilities of programmable network and IT infrastructure through seamless orchestration and instantiation of novel security services, both in real-time and proactively. The paper also includes a thorough business analysis to go far beyond the technical benefits of a potential FISHY adoption as well as three real-world use cases where to strongly support the envisioned benefits of a FISHY adoption.

The utility of ICTs for providing market information to rural smallholder farmers is growing rapidly, and access to reliable information and sources is considered crucial for beneficial market interaction. This study explored critical factors contributing to usage of electronic sources for market information search among rural smallholder livestock farmers. Using data collected from 129 respondents through a non-random sampling technique; descriptive and regression analysis was applied to identify key factors responsible for their awareness and use of ICT-based market information sources. Level of education was found to be a driver of awareness of ICT-based sources, and use of these sources was influenced by farmer-specific characteristics such as household size, education, income, membership of cooperatives and herd-size. The key ICT tools used was radio and mobile phones, widely available in the study area. Identified constraints to use of these ICTs include cost and patchy network signals in some areas. Policy interventions to reduce cost of mobile phone services and expansion of base stations; including practical recommendations for improved programming in radio and television offerings, are considered indispensable for greater uptake of e-information sources among smallholder livestock farmers.

Special machinery engineering is of great importance to the manufacturing industry and makes a comparatively large contribution to many economies. Digital transformation is already well advanced in many producing industries, and modern ICT technologies such as agents, service orientation, digital twins and artificial intelligence are being used with increasing success. In addition to improving specific product characteristics such as reliability or flexibility, the adoption of modern ICT technologies to ensure sustainability is being intensively discussed. So far, however, there has been little uptake of these technologies in the special machinery industry; sustainability receives little attention. This article examines in detail the reasons for and impediments to the adoption of modern ICT technologies based on a study among special machinery manufacturers. Observations of existing challenges were gathered during daily work, described in detail, and used to derive conclusions about causal barriers. From this, detailed requirements are derived to promote the adoption of modern ICT technologies in the special machinery engineering sector and, ultimately, to bring sustainability more into focus.

The study explored the contribution of ICT-based information sources to market participation among smallholder livestock farmers. Use of ICTs is considered paramount for providing smallholder farmers with required market information, in order to reduce market asymmetries. A Double Hurdle regression was utilized to analyze data collected from 150 smallholder livestock farmers in the study area. The results show that while use of ICT-based market information sources significantly influenced market participation, the effect of using ICT-based information sources on intensity of market participation was not significant. Other variables shown to influence both market participation and the intensity of market participation were age, additional income and membership of farmer cooperatives. This suggests the need to also consider other associated factors in the application of interventions which utilize ICT-based information sources in achieving planned market interventions.

Green ICT has received significant attention in organizations to reduce global warming since last decade. Several maturity models have been proposed for tracking green ICT practices in organizations. Current literature shows that SMEs around the world try to follow some common strategies such as virtualization, consolidation of devices, energy efficiency and disposal of ICT equipment for greening ICT. The increasing interest for green ICT practices in organizations is not only due to the desire to attain environment-friendly atmosphere but mainly because of sustaining business goals such as cost reduction, competitive advantages and stakeholders’ pressure. Nevertheless, due to the lack of green ICT knowledge, organizations, specially SMEs, tend to ignore those practices. Therefore, this research proposes a framework that provides combination of existing green and sustainable ICT maturity models by mapping them with the strategies the businesses are already following. Out of this framework, a web application has been developed that provides questionnaire for SMEs to identify their present situation of green ICT practices and guidelines for improvement. The results have been analyzed by testing the application in some SMEs of Finland and Bangladesh. Finally, a survey has been conducted to attain SMEs’ perception about the possibility of sustainable development of businesses through this application.

We investigate the human sustainability of ICT and management changes using a French linked employer-employee survey on organizational changes and computerization (COI). We approach the human sustainability of changes through the evolutions of work intensity, skill utilization and the subjective relationship to work. We compare in the private sector and the State civil service the impacts of ICT and management changes on the evolution of these three dimensions of work experience. We find that when ICT and management changes are intense, they are positively associated in the public sector with work intensification and new knowledge. In the private sector ICT and management changes increase the use of skills, but at a rate decreasing with their intensity and without favoring the accumulation of new knowledge. However, their impacts on the subjective relationship to work are much stronger, with public sector employees expressing discouragement as well as the feeling of an increased effort-reward imbalance when private sector employees become more committed. We tested that the self-selection of employees, the specific sources and paths of changes and the implementation of performance pay did not explain this divergence. We identify two partial explanations: one is related with employee turnover in the private sector, the other one with the role of trade unions. These results suggest that the human sustainability of ICT and management changes depends on their intensity and on how their implementation takes into account the institutional context of the organization.

Background and purpose: Chronic kidney disease (CKD) is a common chronic disease usually associated with cardiovascular disease (CVD), and premature death and millions of people are at increased risk for CKD. As this disease is extremely complex, multidisciplinary care (MDC) is needed to provide complete and continuous care. Usually, the nephrology units need coopera-tion from several other Healthcare Professionals (HCPs) such as cardiologists, nutritionists, ob-stetricians, and so forth. All modalities of treatments, peritoneal dialysis (PD) and Hemodialysis (HD) require HCPs and patients to develop a variety of skills to effectively deliver and manage dialysis tasks in the center or at home. Information and Communication Technology (ICT) in-terventions can offer tools that provide HCPs and patients with tools that facilitate the manage-ment of kidney patients in centers or at home. ICT interventions can allow to automate registra-tions, videoconferencing, minimize the geographic burden and resource cost savings. ICT can be the best way to promote cost saving on health spending and ensure the sustainability of the health system and, the environment as well. In the Iberian Peninsula, kidney patients consume about 3% of the total cost of healthcare. The cost of kidney transplants and dialysis is around 1.8 billion euros annually, and 75 % of this amount goes to dialysis treatment. Objective: This study aimed to evaluate and analyze the opinion of Healthcare Professionals (HCP) in Nephrology units about the Intervention of ICT in nephrology care and the Clinical benefits results from the use of ICT in Nephrology Services and dialysis Units in Portugal and Spain. Thus we collected the opinion of Health care professionals concerning the role of ICT intervention in nephrology. Understanding HCPs' feelings and attitudes is essential to understand if such technologies are correctly adjusted to the workflow and really bring huge benefits for the clinical practice of nephrology and also what features need improvement and what should be implemented in the future. ICT intervention has been implemented to promote better healthcare in nephrology units and improve patient outcomes. In the Survey, we intended to evaluate nephrology HCPs' opinions concerning the ICT interventions, in nephrology, represented by several tools that al-low the HCPs to implement solutions such as Remote Patient Monitoring(RPM); Remote Moni-toring of Treatment (RMT); Tele homecare; Telehealth (Tele-nephrology); Home Dialysis; mHealth; mobile App; Web Portal, Telemedicine, and so forth. Key Points: In many countries particularly in the Iberian Peninsula (Portugal and Spain) the incidence of CKD is substantially high. The “treatments” for kidney disease have not improved substantially over the past 50 years, leaving too many kidney patients with a poor quality of life and reduced life expectancy. This situation is associated with staggering aggregate annual costs amounting to €140 billion per year in Europe, more than the annual healthcare costs of cancer or diabetes [1]. The increased daily use of information and communication technologies may lead to the need for healthcare professionals to incorporate technology use competencies into practice.

The Coronavirus outbreak that began in December, 2019 became a worldwide pandemic by March, 2020. The education industry had to adapt to this new change in a speedy and most feasible way by shifting to virtual classes over the internet and other available resources. WhatsApp has turned out to be a boon in academic’s section where in all the teachers have their own subject-wise groups on the said application. This not only helps them to share the necessary information resources but also to have discussion regarding the subject matter. On the other side, this application allows easy access for the students to all the resources shared by the teacher, and they can share their assignments without much difficulty with their subject teachers. Therefore, it has become a primary tool for conducting teaching, learning and evaluation online. The researchers have tried to analyze impact of online classes and the efforts required by the students to learn online with the help of survey conducted with the sample size of 514. The survey questionnaire was grouped into 4 categories namely; Opinion on Information and Communications Technology (ICT) based Teaching, Changes in communication behavior due to ICT using WhatsApp, the main hindrance for integration of ICT (Information Communication Technology) in the teaching-learning process and disadvantages of using ICT for teaching and learning.

Melanoma is a type of highly malignant and metastatic skin cancer. In situ molecular imaging of endogenous levels of the melanoma biomarker tyrosinase (TYR) may decrease the likelihood of mortality. In this study we proposed the weakly fluorescent probe 1-(4-(2-(4-(dicyanomethylene)-4H-chromen-2-yl)vinyl)phenyl)-3-(4-hydroxybenzyl)urea (DCM-HBU), which releases a strong red-shifted fluorescent signal after a TYR-mediated oxidation followed by hydrolysis of the urea linkage. The large Stokes shift of the dye is owed to the recovery of the intramolecular charge transfer (ICT) effect. The resulting probe derivate shows a highly ratiometric fluorescence output. Furthermore, the simultaneous excitation by two near-infrared (NIR) photons of the released DCM-NH2 fluorophore could avoid the usual drawbacks, such as cellular absorption, autofluorescence and light scattering, due to an usually short wavelength of the excitation light on biological systems, resulting in images with deeper tissue penetration. In addition, the probe is useful for the quantitative sensing of TYR activity in vivo, as demonstrated in zebrafish larvae. This new ratiometric two photon NIR fluorescent probe is expected to be useful for the accurate detection of TYR in complex biosystems at greater depths than other one-photon excited fluorescent probes.

Target 9.c of the 2015 United Nations (UN) sustainable development goals (SDGs) specifically addresses increasing access to information and communication technology (ICT) resources, and striving for universal access to the internet by 2020. The present study seeks to evaluate the effectiveness of the youth related national strategies implemented in this regard by a select number of countries in the Middle East region. The study does so, by relying on a spatial bivariate copula regression analysis of data on youth respondents from five countries, extracted from the 2018 Program for international students’ assessment (PISA). Focusing specifically on evaluating the availability of ICT resources to the youth population, and also identifying the impact of ICT resources on youth subjective well-being in the region, we find that except for the UAE and Qatar that have above OECD average youth performance on the ICT resource index, youth from the remaining countries reported below OECD level average access to ICT resources. The within region cross-country comparative analysis of ICT resources availability to the youth population at home, also highlighted significant heterogeneity across the five countries, post 2015 SDG adoption by UN country members. Furthermore, looking at the impact of ICT resources on youth well-being, controlling for not only cross-country spatial correlations, and factors such as home educational resources, cultural possessions at home, parental occupation status, youth expected occupation status, economic and socio-cultural status, age, gender, and grade level in school; we found that every standard deviation increase in ICT resources to the youth population in the region raises their self-expressed sense of belonging in school by 1.88% standard deviations. Given the empowering nature of ICT resources to youth, and the potential of both to support national as well as regional economic development initiatives, a concerted effort to ease ICT resources diffusion by member countries in the middle east region could assist not only each country in its own development path, but also the region as a whole to live up to its growth potential by the 2030.

The aim of this paper is to analyze the real impact of ICT skill mismatch on SME’s sustainable competitiveness in presence of minimum wage guaranteed. As part of public policies – the minimum wage need to maintain a balance between increasing employment and not being a burden for the companies, leading them to bankruptcies, especially in times of disruptive change in which economy have to be more resilient. The rapid progress in information and communication technologies has dramatically redefined the rising unemployment as a result of skills mismatch. This paper aims to understand, on one side if, there is a match between the supply demand of ICT skills and how increasingly powerful digital technologies affect skills, jobs, and the demand for human labour. On the other, if increasing productivity and a fair minimum wage could be an integrated approach in stimulating SME’s in increasing sustainable competitiveness.

The lack of application of management models that allow strategies to be converted into action and then measure their results in order to apply improvement actions to meet the objectives in small and medium-sized companies (SMEs); they generate problems in their management causing the closure of their operations unexpectedly; To mitigate the risks of closure and bankruptcy with the support of ICT, an alternative was presented considering that risk management is important in decision making at a strategic, tactical and operational level. The objective is to design a prototype to mitigate risks and prevent threats to avoid the closure of this type of company. Through the analysis of related articles, applying sequences of methodological steps; It was determined that the proposed results are aimed at how to identify and mitigate the risks and threats that cause their bankruptcy and closure. Prototypes resulted that allow mitigating risks, preventing threats and minimizing vulnerabilities in the management of SMEs. It was concluded that the proposed prototype to detect threats and vulnerabilities provides an optimal security model for small and medium-sized companies; As a result of the simulations, a security percentage of 77.92% was established, which means that the greater the number of risks and threats, the greater the probability that a small and medium-sized company will close.

Nowadays, emerging technologies have changed the places of work through computers and ICT tools, which have revolutionized teaching and learning environments in different ways. In spite of the fact that computers as ICT tools have become part and progressively instrument for teachers and instructors used in teaching and learning, but most educators can't incorporate them into their teaching and learning process, which results in students being ill-equipped or lacking some necessary skills in the world of work, which leads to low performance and poor handling of tools whose lead to low production. To tackle this issue, it is essential to develop the technical and vocational education and training (TVET) system by determining the quality of technical and vocational education (TVE) teachers. In this paper, the literature concerning the competence required by TVET teachers towards computer-related instructional tech-nology for classroom teaching and learning was examined through the technological pedagogical content knowledge (TPACK) model. Sixty (60) questionnaires were ad-ministered to TVE teachers within six technical colleges of education in north-eastern Nigeria. The data was quantitatively analyzed using traditional linear models, namely multilinear regression (MLR) and artificial intelligence (AI) models, namely artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS), which were developed using MATLAB 9.3 (R2019a), while the classical linear MLR model was developed using SPSS software. The results from our classical study indicated that TVE teachers are competent in computer and some instructional technology usage and show a high correlation between competence and teaching experience and a lower correlation between competence and gender. The goodness of fit shows a good fit of the model. Future studies should examine the application of other linear and non-linear AI techniques.

The COVID-19 pandemic crisis has brought about unprecedented economic and social consequences worldwide. The implementation of isolation measures, including national and international travel restrictions, significantly affected contact-intensive sectors such as tourism. During this lockdown period, Information and Communication Technology (ICT) was crucial in maintaining connectivity and enabling remote activities. Governments across the world implemented discretionary measures to mitigate the crisis's adverse effects on economic activity. This paper aims to analyze whether the level of ICT adoption and the importance of tourism influence the fiscal policy efforts pursued by governments. Based on the results of a linear regression analysis for 154 countries, the findings suggest that in countries with higher international tourism receipts, the governments had to promote higher fiscal stimulus. At the same time, ICT development diminished the efforts of the fiscal policy response to the crisis since it facilitated economic resilience. The findings of this study can contribute to understanding how governments responded to the pandemic crisis and the factors that influenced their fiscal policy decisions.

This study aimed to explore what factors affect teachers’ acceptance and instructional use of ICT in Chinese higher vocational colleges. Grounded in the modified UTAUT model, the current study investigated the direct and indirect effects of teachers’ performance expectancy, effort expectancy, external conditions, and behavioral intentions on using ICT in teaching. A total of 6087 teachers from 219 vocational colleges in 28 provinces in China participated in a large-scale survey. Structural equation modeling revealed that the teachers’ psychological perceptions (including performance expectancy, effort expectancy, and intention to use ICT technology) and the external support conditions (including professional development support, infrastructures, the climate of organizational reform and innovation, and teacher performance assessment mechanisms) significantly directly affect the use of ICT in Chinese higher vocational college teachers’ teaching practice. Moreover, this study confirmed the mediating role of teachers’ intention to use ICT in teaching in the relationship between teachers’ psychological perceptions and ICT instructional usage behavior. However, there were differences in the significance of these variables in the chain effect of teachers’ intention to use ICT. These findings expand our understanding of the factors influencing ICT use in teaching among VET teachers in China and thus provide practical implications for higher vocational college managers to promote teachers’ ICT teaching behaviors.

This study identified, analysed, and prioritised significant factors for standardising the Korean smart city project evaluation system. We analysed the efficiency and productivity of companies currently providing smart city services to consider both policy and practical aspects. The prioritisation of smart city planning reflects the latest trends in South Korea, where urban planning is moving towards smart city planning. Furthermore, the capacity building of public-private/private-private partnerships indicate the importance of business scalability. This indicates that smart city services are only stabilised when the private sector is involved and leads the project, rather than focusing on public development. The feasibility of building intelligent facilities indicates that smart city projects should be implemented after securing cost-benefit feasibility. The results were used as the basis for building an evaluation system, showing that in smart city convergence alliances, small- and medium-sized enterprises achieved the highest efficiency by reducing inputs to 81% and 86%, under the assumptions of constant and variable returns to scales, respectively. As the operational aspect is more problematic than the technical aspect, policy alternatives are necessary for smooth business progress, including increased flexibility of laws and institutions and the activation of policies that temporarily relieve regulations to demonstrate smart city projects.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

The objective of this paper is to investigate the debonding behavior of the interface between continuously and discontinuously fiber reinforced thermoplastics using the climbing drum peel test. The study emphasizes the importance of considering different climatic boundary conditions due to the properties of thermoplastics. Specimens with varying moisture contents are prepared and tested. It is observed that an increase in moisture content initially results in a higher fracture surface energy being required to separate the two materials, but a further increase results in a decrease of the required energy. The study presents an explanatory model of increasing plasticization of the polymer due to increased polymer chain mobility, which results in more deformation energy being required to propagate the crack. The experiment is also modeled numerically for the first time with cohesive surfaces, which successfully reproduces the force-displacement curve in the experiment.

This study presents the comparison of heat transfer capacity and pressure drop characteristics between a basic fin-tube heat exchanger and a modified heat exchanger with the structural change of branch tubes and coiled turbulators. All experiments were carried out using an air-enthalpy type calorimeter based on the method described in ASHRAE standards, under heat exchanger experimental conditions. 14 different kinds of heat exchangers were used for the experiment. Cooling and heating capacities of the turbulator heat exchanger were excellent, compared to the basic one. As the insertion ratio of the coiled turbulator and the number of row increased, the heat transfer performance increased. However, the capacity per unit area was more effective in 4 rows than 6 rows, and the cooling performance of the 6 row turbulator heat exchanger (100% turbulator insert ratio) was down to about 6% than that of 4 row one. As the water flow rate and the turbulator insertion ratio increased, the pressure drop of the water side increased. This trend was more pronounced in 6 rows. In the cooling condition, the pressure drop on the air side was slightly increased due to the generation of condensed water, but was insignificant under the heating condition. The power consumption of the pump was more affected by the water flow rate than the coiled turbulator. The equivalent hydraulic diameter of a tube by the turbulator was reduced and then the heat transfer performance was improved. Thus, the tube diameter was smaller, the heat flux was better.

Hybrid forecasting methods have emerged as a solution surpassing the limitations of both statistical and deep learning approaches. While the first emphasize the significance of variables, they often produce worse forecasting results when compared to newer techniques. In contrast, deep learning models remain enigmatic "black boxes" in terms of interpretability, although achieving better results in forecasting. This article introduces the Comprehensive Cross-Correlation and Lagged Linear Regression Deep Learning (CCLR-DL) framework, designed to harness the best of both approaches, enhancing forecasting accuracy while retaining model interpretability through a feature selection process. CCLR-DL blens cross-correlation analysis, lagged multiple linear regression and granger's causality procedures with deep learning architectures based on LSTM. In a practical demonstration, CCLR-DL was applied to a real database of clinical visits associated to diagnoses in Catalonia, Spain (tracking a population of 6.3 million patients during 10 years). Predicting visits enables the healthcare managers to be ready for future demand shifts. Results demonstrate a consistent and substantial improvement over standalone statistical and deep learning methods when predicting healthcare demand. This hybrid approach not only showcases its efficacy but also offers a promising solution to the challenge of balancing predictive accuracy with model explicability. In this context, this work aims to design and validate a method for feature selection and forecasting of multivariate high dimensional time series datasets not only to improve prediction accuracy but also to model transparency by identifying a subset of variables that improve predictions and G-cause the target variable.

The antimicrobial peptide LRGG (LLRLLRRGGRRLLRLL-NH2) was designed and chemically synthesized in a study conducted by Jia et al. Gram-negative bacteria were found to be sensitive to LRGG and exhibited a high therapeutic index. Genetic engineering methods were used to create the prokaryotic fusion expression vector pQE-GFP-LRGG, and the resulting corresponding fusion protein GFP-LRGG was subsequently expressed and purified. The precursor GFP was then removed by TEV proteolysis, and pure LRGG was obtained after another round of purification and endotoxin removal. The prokaryotic-expressed antimicrobial peptide LRGG displays a broad-spectrum antibacterial effect on gram-negative bacteria and can eliminate 99.99% of E. coli within 100 minutes at the minimal MIC concentration. Compared to the chemically synthesized LRGG, the prokaryotic-expressed LRGG exhibits similar temperature, pH, salt ion, serum stability, and cell selectivity. Furthermore, prokaryotic-expressed LRGG showed excellent therapeutic effects in both the infection model of cell selectivity and no embryotoxicity in a Galleria mellonella infection model. The mechanism by which LRGG causes bacterial death was found to be disruption of Gram-negative cell membrane.

Exosomes, natural nanovesicles that contain a cargo of biologically active molecules such as lipids, proteins, and nucleic acids, are released from cells to the extracellular environment. They then act as autocrine, paracrine, or endocrine mediators of communication between cells by delivering their cargo into recipient cells and causing downstream effects. Exosomes are greatly enriched in miRNAs, which are small non-coding RNAs that act as cytoplasmic posttranscriptional repression agents, modulating the translation of mRNAs into proteins, as well as nuclear transcriptional gene activators. Neuronal exosomal miRNAs have important physiologic functions in the Central Nervous System (CNS), including cell-to-cell communication, synaptic plasticity, and neurogenesis, as well as modulating stress and inflammatory responses. Stress-induced changes of exosomal functions include effects on neurogenesis and neuroinflammation, which can lead to the appearance of various neuropsychiatric disorders, such as schizophrenia, major depression, bipolar disorder, and Alzheimer's and Huntington’s's diseases. The current knowledge regarding the roles of exosomes in the pathophysiology of common mental disorders is discussed in this review.

The emergence of the coronavirus 19 (COVID-19) has posed a major challenge to healthcare systems worldwide, especially as COVID-19 mutations complicate the development of vaccines and antiviral drugs. Therefore, the search for natural products with broad anti-COVID-19 capabilities is an important option for the prevention and treatment of infectious diseases. Lectins, which are widely recognized as antiviral agents, could contribute to the development of anti-COVID-19 drugs. In this study, we evaluated the binding ability of a total of six lectins, including MVL from Microcystis viridis NIES-102, to the spike protein RBD of the original (wild) COVID-19 and it’s three mutants: alpha, delta, and omicron. As a result, two lectins, MVL from Microcystis viridis NIES-102 and jacalin from Artocarpus altilis, showed distinct binding ability to the RBDs of the four COVID-19 strains. The other lectins (DB1, ConA, PHA-M and CSL3) did not show any binding ability. Although the glycan specificities of the two lectins, MVL and Jacalin, were different, they showed the same affinity for the RBDs of the four COVID-19 strains, i.e., alpha > delta > original > omicron. The verification of glycan-specific inhibition revealed that jacalin binds to RBDs by glycan-specific recognition, whereas MVL binds to RBDs by protein-protein interactions in addition to glycan-specific recognition.

We hypothesize that the first ancestral "ante-cell" molecular structures, i.e., first RNAs and peptides which gradually transformed into real cells once the Earth had cooled sufficiently for organic molecules to appear there, have leaved traces in RNAs and genes of present cells. We propose a circular RNA which could have been one of these ancestral structures whose vestigial pentameric subsequences would mark the evolution from this key moment when the ante-cells have begun to join the living organisms. In particular, we propose that in present RNAs (ribosomal or messenger) playing an important role in the metabolism of current cells, we look for traces of the proposed primitive structure in the form of pentamers (or longer fragments) belonging to their nucleotide sequence. The result obtained can be summarized in the existence of a gradient of occurrence of such pentamers, with a high frequency for the most vital functions (protein synthesis, nucleic synthesis, cell respiration, etc.). This gradient is also visible between organisms, from the oldest (Archaea) to the most recent (Eukaryotes) in evolution of species.

The conservation status of monarch butterflies in North America is a topic of intense scrutiny and debate. It is clear that winter colonies in Mexico are declining, yet some recent studies suggest that summer breeding populations are relatively stable and similar to historical abundances. One possible explanation for these discordant patterns is that fall migration success has been recently disrupted. Here, we use a relatively unexplored citizen-scientist dataset on the size of monarch “roosts,” which are resting aggregations on vegetation, to infer changes in monarch abundance along the fall migration route over the last 17 years. We found that the timing of migration remained relatively unchanged while the flyway has generally become warmer and greener. Warmer and greener conditions were associated with larger roosts, yet we found steady, dramatic declines in roost sizes through time that were independent of climate and landscape factors. Roost sizes have declined as much as 80%, with losses increasing from north to south along the migration route. These findings suggest that failure during the fall migration could explain the apparent drop in monarch numbers from summer breeding to overwintering populations. This in turn suggests that conservation efforts that support fall migration success are most needed, such as limiting the planting of non-native milkweeds that enhance parasite loads and perhaps dampen migration success. Overall, it appears the fall migration of monarch butterflies is under imminent threat, even if the species’ overall survival is not.

Simple summary This reassessment of the findings from our Phase I/II study seeks to evaluate the effectiveness of SBRT for treating local intermediate-high risk prostate cancer in the absence of androgen-deprivation therapy due to patient’s refusal, with a median follow-up of 6.5 years. Our primary focus is on analysing the treated areas compared to recurrence patterns in the seven patients who experienced local relapse. Additionally, we provide updated data on late toxicities of grade 2 or higher, both genitourinary and gastrointestinal. Abstract Objectives: We investigated spatial patterns between primary and recurrent tumor sites and assessed long-term toxicity after dose escalation stereotactic body radiation therapy (SBRT) to the dominant intraprostatic nodule (DIN). Materials and methods: In 33 patients with intermediate-high risk prostate cancer (PCa), doses up to 50 Gy were administered to the DIN. Recurrence sites were determined and compared to the original tumor development sites through multiparametric MRI and 68Ga-labelled prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (68Ga-PSMA-PET/CT) images. Overlap rates, categorized as 75% or higher for full overlap, and 25-74% for partial overlap, were assessed. Long-term toxicity is reported. Results: All patients completed treatment, with only one receiving concomitant androgen deprivation therapy (ADT). Recurrences were diagnosed after a median of 33 months (range: 17-76 months), affecting 13 out of 33 patients (39.4%). Intraprostatic recurrences occurred in 7 patients (21%), with ≥ 75% overlap in two, a partial overlap in another two, and no overlap in the remaining three patient. Notably, 5 patients with intra-prostatic recurrences had synchronous bone and/or lymph node metastases, while six patients had isolated bone or lymph node metastasis without intraprostatic recurrences. Extended follow-up revealed grade 2 or higher late GU and GI toxicity in 18% (n=6) and 6% (n=2) of the patients. Conclusions: Among patients with intermediate-high risk PCa undergoing focal dose-escalated SBRT without ADT, DIN recurrences were infrequent. When present, these recurrences were typically located at the original site or adjacent to the initial tumor. Conversely, relapses beyond the DIN and in extra-prostatic (metastatic) sites were prevalent, underscoring the significance of systemic ADT in managing this patient population. Advances in knowledge: focal dose escalated prostate SBRT prevented recurrences in the dominant nodule, however extra-prostatic recurrence sites were frequent.

Background/Aim: Stool gluten immunogenic peptides (GIP) determination is now considered a valuable tool for detecting dietary lapses in treated celiac disease (CeD) patients. Our study aims to explore the diagnostic performance of a qualitative lateral flow immunoassay point-of-care test (LFIA/PoCT) compared with a qualitative enzyme-linked immunosorbent assay (ELISA) for detection of stool GIP. Methods: The study is a post hoc analysis of stool samples collected in the real-life conditions from a cohort of gluten-free diet-treated CeD patients. Stool GIP was measured in µg/g of stool using an ELISA kit (iVYLISA GIP S®, Biomedal SL). For the qualitative evaluation of stool GIP, a LFIA/PoCT test (GlutenDetect®; Biomedal S.L) was employed, which reported results as positive or negative. The LFIA/PoCT performance was evaluated against ELISA, considered as the gold standard. GIP concentrations

Based on a constant volume combustion chamber, the initial ambient pressure effect on combustion performance and flame propagation of the active and passive pre-chamber ignition systems were studied. Compared with the passive pre-chamber, the active pre-chamber can significantly expand the lean combustion limit, enhance the ignition and combustion performance, and speed up the combustion of the main combustion chamber. At slightly lean combustion conditions, the heat release performance has a positive correlation with the initial ambient pressure. As the premixed λ increases, the heat release performance and the initial ambient pressure begin to become negatively correlated. Ignition delay can be minimized by controlling the excess air coefficient in the pre-chamber close to the stoichiometric ratio. The high ambient pressure in the constant volume chamber greatly reduces the mixture entrainment ability of the jet flame at lean combustion conditions, thereby reducing the combustion speed and peak heat release rate.

The Lower Mekong Basin has had extensive hydropower dam development, which changes hydrologic conditions and threatens the exceptional aquatic biodiver-sity. This study quantifies the degree of hydrologic change between pre-impact (1965-1968) and post-impact (2018-2021) peak hydropower development in two major tributaries of the Lower Mekong Basin, the Sekong River with the fewest dams and the Sesan River with the most dams. Both rivers historically supported migratory fishes. We use daily pre- and post-impact data and the Indicators of Hydrologic Alteration framework to evaluate streamflow changes from dam development. We found signifi-cant changes in low and high magnitude flows in the pre- and post-impact periods of dam development. For the Sekong River, minimum flow had large fluctuations that ranged 290% to 412% more than the pre-impact period, while the Sesan River ranged 120% to 160% more than pre-impact. Dry season flows increased by 200±63% on av-erage in the Sekong River, which is caused by releases from upstream dams. Mean-while, Sesan River dry season flows increased by 100±55% on average. This study in-dicates that seasonal flow changes and extreme flow events occurred more frequently in the two basins following dam construction, which may threaten the ecosystem func-tions.

The article presents an accessible route into the field of neuroscience through ardEEG device. This device allows convert Arduino UNO R4 WIFI into a brain-computer interface, making it easy to measure EEG, EMG and ECG signals with 8 channels. Over the past decade, the proliferation of artificial intelligence has significantly impacted various industries, including neurobiology. The integration of machine learning techniques has opened avenues for practical applications of EEG signals across technology sectors. This surge in interest has led to the widespread popularity of low-cost brain-computer interface devices capable of recording EEG signals using non-invasive electrodes. ardEEG device demonstrates satisfactory noise levels and accuracy for use in applied tasks. Moreover, it successfully detects alpha brain waves, showcasing its effectiveness in capturing essential neurological signals

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual energy imaging remains relatively untapped, possibly due to its intricate workflow and intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is neces-sary for an appropriate clinical use. The aims of this paper are to review physical and technical basis of DECT acquisition and analysis, to discuss advantages and limitations of DECT in dif-ferent clinical scenarios, to review technical constraints in material labeling and quantification, and to evaluate cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radioge-nomics

Lap joints were friction stir welded in AA 7075-T6 at 1320 rpm and using two welding speeds: 70 mm/min and 120 mm/min. The temperature profiles of the weld zone were registered during the process; furthermore, the microhardness, tensile strength, and microstructure of the joints produced were examined. This study brings new insights into the thermomechanical behavior of the material during the process. The peak temperature obtained with the lower welding speed (70 mm/min) is 10% higher than that obtained with the higher speed (120 mm/min). Moreover, a 5% increase in microhardness and a 6% increase in tensile strength were were observed increasing the welding speed. Addition-ally, the microstructure examination demonstrated that, by decreasing the welding speed, the larger interaction between the tool and the material results in a deeper stir zone due to the increased heat diffusion downwards to the material. This heat flow affects the thermal profile and influences the resulting mechanical properties of the welded joints.

The increasing emergence of multidrug resistant (MDR) pathogens causes difficult-to-treat infections, with long-term hospitalizations and high incidence of death, thus representing a global public health problem. To manage MDR bacteria bugs, new antimicrobial strategies are necessary, and their introduction in practice is a daily challenge for scientists in the field. An extensively studied approach to treat MDR infections consists in inducing high levels of reactive oxygen species (ROS) by several methods. Although further clinical investigations are mandatory on the possible toxic effects of ROS to mammalian cells, clinical evaluations are extremely promising, and their topical use to treat infected wounds and ulcers, also in presence of biofilm, is already clinically approved. Biochar (BC) is a carbonaceous material obtained by pyrolysis of different vegetable and animal biomass feedstocks, at 200−1000 °C in limited presence of O2. Recently, it has been demonstrated that BC capability of removing organic and inorganic xenobiotics is mainly due to the presence of persistent free radicals (PFRs), which can activate oxygen, H2O2 or persulfate in the presence or not of transition metals by electron transfer thus generating ROS, which in turn degrade pollutants by advanced oxidation processes (AOPs). In this context, the antibacterial effects of BC containing PFRs have been demonstrated by some authors against Escherichia coli and Staphylococcus aureus, thus giving birth to our idea of the possible use of BC-derived PFRs as a novel method capable of inducing ROS generation for antimicrobial oxidative therapy. Here, the general aspects concerning ROS physiological and pathological production and regulation, and the mechanism by which they could exert antimicrobial effects have been reviewed. The methods currently adopted to induce ROS production for antimicrobial oxidative therapy have been discussed. Finally, for the first time, BC-related PFRs have been proposed as a new source of ROS for antimicrobial therapy via AOPs.

Green investments help to create less harmful alternatives and adequate funds that contribute to economic growth, sustainable development, and social well-being. The applied methods are empirical and analytical based on the study of literature, multi-criteria modelling, determination of weights, and ranking of criteria in deciding green investments mapping of indicators, and monitoring of progress towards green growth through official OECD data. The analysis uses official sources on indicators related to the green economy and the environment. Multi-criteria decision-models (MCDM) were used to select adequate green investments, where instead of indicators from the official OECD-database, investors use the areas in which the indicators are distributed. According to the findings of AHP, half of the investments in the green economy come from public sources (0.51), and the other half are private (0.25), and institutional investors (0.24). While, BWM reveals that the best criterion for the decision to invest in the green economy is the environmental and resource productivity of the economy, and the worst is the base of natural assets. This paper aims to enable decision-makers to use these results as weights for the overall assessment of green investments in ESG and to simplify the decision-making approach in future analyses.

Ever since Varela and Maturana proposed the concept of autopoiesis as the minimal requirement for life, there has been a focus on cellular systems that erect topological boundaries to separate themselves from their surrounding environment. Here we reconsider whether the existence of such a spatial boundary is strictly necessary for self-producing entities. This work presents a novel computational model of a minimal autopoietic system inspired by dendrites and molecular dynamics simulations in three-dimensional space. A series of simulation experiments where the metabolic pathways of a particular autocatalytic set are successively inhibited until autocatalytic entities that could be considered autopoietic are produced. These entities maintain their distinctness in an environment containing multiple identical instances of the entities without the existence of a topological boundary. This gives rise to the concept of a metabolic boundary which manifests as emergent self-selection criteria for the processes of self-production without any need for unique identifiers. However, the adoption of such a boundary comes at a cost, as these autopoietic entities are less suited to their simulated environment than their autocatalytic counterparts. Finally, this work showcases a generalized metabolism-centered approach to the study of autopoiesis that can be applied to both physical and abstract systems alike.

Solar energy has emerged as a promising alternative to traditional fossil fuels due to its abundant availability and sustainability. Solar cells, the fundamental units of solar energy conversion, have undergone significant advancements in fabrication techniques to enhance their efficiency, durability, and cost-effectiveness. This review aims to provide a comprehensive overview of various methods employed in the preparation of solar cells, including thin-film, crystalline silicon, organic, and perovskite-based technologies. By analyzing recent research developments, challenges, and future prospects, this article sheds light on the evolving landscape of solar cell fabrication, contributing to the ongoing efforts in achieving widespread adoption of solar energy.

Methodologies for future-oriented research are mutually beneficial to highlight different methodological perspectives and proposals for extending higher education didactics towards sustainability. This study explores how different augmented reality applications can enable new ways of teaching and learning. It systematically investigates how student teachers (n=18) in higher education experienced ongoing realities while designing learning activities for a hybrid conference and interconnecting sustainability knowings via didactic modelling and design thinking. This qualitative study aims to develop a conceptual hybrid framework concerning the implications of student teachers incorporating the design thinking and inner transition into their professional work with future-oriented methodologies on didactic modelling for sustainability commitment. With a qualitative approach data was collected during and after a hackathon-like workshop through student teachers’ reflections, post-workshop surveys, and observation field notes. The thematic analysis shed light on transgressive learning and a transition in sustainability mindset through activation of inner dimensions. Findings reinforcing sustainability commitment evolved around the following categories: being authentic (intra-personal competence), collaborating co-creatively (inter-personal competence), thinking long-term-oriented (futures-thinking competence on implementing didactics understanding), relating with creative confidence (values-thinking competence as embodied engagement), and acting based on perseverant professional knowledge driven change (bridging didactics) by connecting theory-loaded empiricism and empirically loaded theory. The results highlight some of the key features of future-oriented methodologies – and approaches to future-oriented methodologies feature collaboration, boundary crossing and exploration – and show the conditions that can support or hinder methodological development and innovation.

The thermal surface properties of graphenes and carbon materials are of crucial importance in chemistry of materials, chemical engineering, and many industrial processes. (1) Background: The determination of these surface properties is carried out using inverse gas chromatography at infinite dilution which leads to the retention volume of organic solvents adsorbed on solid surfaces. This experimental and fundamental parameter actually reflects the surface thermodynamic interactions between injected probes and solid substrates. (2) Methods: The London dispersion equation and the Hamieh thermal model were used to quantify the London dispersive and polar surface energy of graphenes and carbon fibers as well their Lewis acid-base constants by introducing the coupling amphoteric constant of materials. (3) Results: The London dispersive and polar acid-base surface energies, the free energy of adsorption, the polar enthalpy and entropy, and the Lewis acid-base constants of graphenes and carbon materials were determined. (4) Conclusions: it was showed that graphene exhibited the highest values of London dispersive surface energy, polar surface energy, and Lewis’s acid-base constants. These highest characteristics of graphene justify its great potentiality and uses in many industrial applications.

Uterine tube extracellular matrix is a key component that regulates tubal tissue physiology, and it has a region-specific structural distribution, which are directly associated to their functions. Considering this, application of biological matrices in culture systems is an interesting strategy to develop biomimetic tubal microenvironments and enhance their complexity. However, there are no established protocols to produce tubal biological matrices that consider the organ morphophysiology for such applications. Therefore, this study aimed to establish region-specific protocols to obtain decellularized scaffolds derived from porcine infundibulum, ampulla, and isthmus to provide suitable sources of biomaterials for tissue-engineering approaches. Porcine uterine tubes were decellularized in solutions of 0.1% SDS and 0.5% Triton X-100. Decellularization efficiency was evaluated by DAPI staining and DNA quantification. We analyzed ECM composition and structure by optical and scanning electronic microscopy, FTIR and Raman spectroscopy. DNA and DAPI assays validated the decellularization, presenting significative reduction of cellular content. Structural and spectroscopy analyses revealed that produced scaffolds remained well structured and with ECM composition preserved. YS and HEK293 cells were used to attest cytocompatibility, allowing cell survival and successful interaction with the scaffolds. These results suggest that such matrices are applicable for future biotechnological approaches in the reproductive field.

Numerous study reports on chitosan hydrogels in different forms such as films, porous structures, nanoparticles, and microspheres for biomedical applications, however, this study concentrates on their modifications with different crosslinking agents and observing their effects on drug loading and releasing capacities. Linear chitosan along with crosslinked by two major cross-linkers, i.e., genipin and disulfide have been used to formulate three different hydrogel systems. The cross-linking process is heavily impacted by the temperature and the pH conditions. Three different drugs, i.e., thymoquinone, gefitinib, and erlotinib are loaded in phosphate buffer solutions and infused with three different hydrogel systems, thus, a total of nine combinations are studied and analyzed for drug loading and releasing capabilities with Ultraviolet–visible (UV-Vis) spectroscopy. This study finds thymoquinone shows the lowest loading efficacy compared to two other drugs in all three systems. Gefitinib shows stable loading and releasing regardless of crosslinking systems and genipin crosslinked system shows stable loading and releasing with all three drug molecules. These experimental results agree well with the findings of our previously published results conducted with molecular dynamics simulations.

Mushroom cultivation vastly improves the yield of mushrooms under optimized, controlled conditions, but may be susceptible to opportunistic colonization by pest species that can establish themselves, as well as the pathogens and pests they may transmit. Here we describe our investigation into the bacterial communities of adult Lycoriella ingenua (Diptera: Sciaridae) and Megaselia halterata (Diptera: Phoridae) collected from button mushroom (Agaricus bisporus) production houses in Pennsylvania. We collected adult flies and sequenced the hypervariable v4 region of the bacterial 16S rRNA using the Illumina MiSeq. The most abundant bacterial genus detected in both species was Wolbachia, but phylogenetic analysis revealed that the infections are from different clades. Future studies include the characterization of Wolbachia infections on fly behavior and biology, comparison of microbial diversity of fly species colonizing wild mushrooms, and other microbiota that may contribute to the success of certain pest fly species.

The increasing demand for water in agriculture and the need for more efficient irrigation systems has led to the development of smart irrigation systems based on the Internet of Things. In this system, an Arduino microcontroller is used to control and monitor the watering of crops. The system is equipped with sensors that measure soil moisture which are used to optimize the irrigation process. The data collected by the sensors is transmitted to the Arduino, which then adjusts the watering schedule based on the information received. The use of IoT in smart irrigation systems provides several benefits, including reduced water waste, increased crop yields, and improved plant health. The implementation of this system using an Arduino platform is relatively simple, cost-effective, and can be easily integrated into existing irrigation systems. Overall, the use of IoT in smart irrigation using an Arduino platform has the potential to revolutionize the way we manage water resources in agriculture.

A predictive approach to the phase behavior of four-component poly-mer-water-surfactant-electrolyte systems is formulated, by viewing the four-component system as a binary polymer-pseudosolvent system, with the pseudosolvent representing water, surfactant, and the electrolyte. The phase stability of this binary system is examined using the framework of the lattice fluid model of Sanchez and Lacombe. In the lattice fluid model, a pure component is represented by three equation of state parameters, the hard-core volume of a lattice site ( ), the number of lattice sites occupied by the component (r) and its characteristic energy ( ). We in-troduce the extra thermodynamic postulate that r and for the pseudosolvent are the same as for water and all surfactant-electrolyte composition dependent characteristics of the pseudosolvent can be represented solely through its characteristic energy parameter. The key implication of the postulate is that the phase behavior of polymer-pseudosolvent systems will be identical for all pseudosolvents with equal values of the characteristic energy, despite their varying real compo-sitions. Based on the pseudosolvent model, illustrative phase diagrams have been computed for several four-component systems containing alkyl sulfonate/sulfate surfactants, electrolytes and anionic or nonionic polymers. The pseudosolvent model is shown to describe all important trends in experimentally observed phase behavior, pertaining to polymer and surfactant molecular characteristics. Most importantly, the pseudosolvent model allows one to construct a priori phase diagrams for any polymer-surfactant-electrolyte system, knowing just one experimental com-position data for a system at the phase boundary, using available thermodynamic data on sur-factants and electrolytes and without requiring any information on the polymer.

Adeno-associated viral (AAV) vectors can be used for gene delivery. AAV.CAP-Mac was recently developed; it can cross the blood-brain barrier and transduce cells throughout the CNS. However, some brain regions were not transduced in adult rhesus monkeys. Additionally, AAV vectors can only package 5 kb of DNA. Also, AAV vectors may be genotoxic and cytotoxic, especially at high doses. Finally, AAV vectors are very expensive to produce at sufficiently high titers for treatment. Off-the-shelf cell-based delivery systems wherein the cells can infiltrate the target tissue and be hyper-motile would be ideal. Also, mRNA-based gene editing would be a transient treatment, and thus be much safer.

This paper addresses the capability to alter the wettability characteristics of poly(vinyl alcohol) (PVA) polymer films doped with glycerol. Films of PVA and glycerol-choline chloride (GCC) blends have been prepared by solution casting method with different glycerol dopants ranging from 0% to 10% (wt %). The results show that as the dopant content increases from 0% to 10%, the wettability increases and hence increases the surface energy of the solid film. The wettability changes are observed by identifying the contact angle of 10 µL deionized water droplet which altered from 55o to 28o as dopant content changed from 0% to 10% per PVA solution weight. The results show that the roughness of film surfaces increases as the content of dopant (GCC) increases in the film which indicates that roughness has a strong influence on the wettability of the casted films.

Objective: To determine the effect of sandblasting before and after sintering on the surface roughness of zirconia and the micro-tensile bond strength of a pressable veneering ceramic to zirconia. Methods: Pre-sintered zirconia blocks (IPS e.max ZirCAD, Ivoclar Vivadent) were divided into a control group (CTR, no surface treatment) and four test groups of three specimens each: Pre-S-30, Pre-S-50, Pre-S-110 were sandblasted with 30µm SiO2, 50µm Al2O3 and 110µm Al2O3 particles respectively, before sintering, Post-S-30 was sandblasted with 30µm SiO2 after sintering. For each treatment, the surface roughness was measured (Ra, Perthometer M4P, Mahr Perthen). After sintering the zirconia blocks, a liner and a pressable ceramic (IPS e.max ZirPress, Ivoclar Vivadent) were fired. Sixteen micro-bars were obtained from each block and submitted to the micro-tensile bond strength (µTBS) test. Data were analyzed with one-way ANOVA. Any correlation between Ra and µTBS was evaluated (Sperman test). Results: Sandblasting before sintering with 110µm Al2O3 (Ra=3.44±0.44µm), 50µm Al2O3 (Ra=2.32±0.46µm), and 30µm SiO2 (Ra=1.22±0.22µm) resulted in significantly higher roughness than sandblasting after sintering with 30µm SiO2 (Ra=0.46±0.11µm). The highest µTBS was measured when the sintered zirconia was sandblasted with 30μm SiO2 (26.79±14.80 MPa), which was significantly different from that of specimens that were sandblasted before sintering (Pre-S-30=20.90±11.70; Pre-S-50=21.27±15.19; Pre-S-110=23.99±16.83) or were not treated (CTR=17.44±14.03). Conclusions: Sandblasting zirconia before sintering enhances the surface roughness proportionally to the particle size of the sand used. Sandblasting with 30µm SiO2 after sintering appeared to improve bonding between the veneering ceramic and zirconia. Clinical Significance: Sandblasting with 30µm SiO2 after sintering may improve bonding between veneering ceramics and zirconia, thus reducing ceramic fractures/chippings.

Yeasts are gaining increasing attention for their potential health benefits as probiotics in recent years. Researchers are actively searching for new yeast strains with probiotic properties (i.e, Debaryomyces hansenii; Kluyveromyces marxianus; Yarrowia lipolytica; Pichia hudriavzevii; Torulaspora delbrueckii) from various sources, including traditional fermented foods, the human gut, and the environment. This exploration is expanding the pool of potential probiotic yeasts beyond the well-studied Saccharomyces boulardii. Research suggests that specific yeast strains possess properties that could be beneficial for managing conditions like inflammatory bowel disease, irritable bowel syndrome, skin disorders and allergy. Additionally, probiotic yeasts may compete with pathogenic bacteria for adhesion sites and nutrients, thereby inhibiting their growth and colonization. They might also produce antimicrobial compounds that di-rectly eliminate harmful bacteria. To achieve these goals, the approach that uses probiotics for human health is changing. Next-generation yeast probiotics are emerging as a powerful new approach in the field of live biotherapeutics. By using genetic engineering, scientists are able to give these tools specialized capabilities. However, most research on these probiotic yeasts is still in its early stages, and more clinical trials are needed to confirm their efficacy and safety for various health condi-tions. This review could provide a brief overview of the situation in this field.

Introduction: A plethora of biological molecules regulate chondrogenesis in the epiphyseal growth plate. Disruptions of quantity and function of these molecules can manifest clinically as stature abnormalities of various etiologies. Traditionally, the growth hormone/insulin-like growth factor 1 (IGF1) axis represents the etiological center of final stature attainment. Of note, little is known about the molecular events that dominate the growth of the craniofacial complex and its correlation with somatic stature. Aim: Given the paucity of the relevant data, this review discusses available information regarding potential applications of lateral cephalometric radiography as a potential clinical indicator of genetic short stature in children. Materials and Methods: A literature search was conducted in the PubMed electronic database using the key words: cephalometric analysis and short stature; cephalometric analysis and achondroplasia; cephalometric analysis and hypochondroplasia; cephalometric analysis and skeletal abnormalities; cephalometr* and SHOX; cephalometr* and CNP; cephalometr* and ACAN; cephalometr* and CNVs; cephalometr* and IHH; cephalometr* and FGFR3; cephalometr* and Noonan syndrome; cephalometr* and “Turner syndrome”; cephalometr* and achondroplasia. Results: In individuals with genetic syndromes causing short stature, linear growth of the craniofacial complex is confined, following the pattern of somatic short stature regardless of its etiology. The angular cephalometric measurements differ from the average height normal individuals and are suggestive of a posterior placement of the jaws and a vertical growth pattern of the face. Conclusion: The greater part of the existing literature regarding cephalometric measurements in short statured children with genetic syndromes provides qualitative data. Furthermore, cephalometric data for individuals affected with specific rare genetic conditions causing short stature, should be the focus of future studies. These quantitative data are required to potentially establish cut-off values to refer for genetic testing based on craniofacial phenotypes.

Weather-related risks in aviation are one of the main causes of accidents worldwide. This article aims to analyze aviation risks resulting from adverse weather conditions, using the case study of the Pucallpa accident that occurred on August 23, 2005, in eastern Peru. In this analysis, we have determined the relationship between meteorological information and aviation risks, presented a matrix of risks associated with the most predominant meteorological variables at Pucallpa airport, and drawn up three maps of meteorological risks indicating the month of the year in which their incidence is most relevant. Finally, we conclude that it is essential to emphasize the importance of considering the prevailing weather conditions at Pucallpa airport to help mitigate the potential risks that may occur during different phases of the flight.

We are going to demonstrate the origin of dark energy, using a Hardwire similarity, a test that is carried out in terrestrial seismic with vibroseis in the search for gas and oil. In the first instance, we are going to analyse the mathematical function of Dirac's delta and compare it with the detonation of an explosive that is carried out in the search for gas and oil. Let's understand that in both cases a frequency spectrum is produced. We will also explain the meaning of a non-causal, zero-phase system; a causal system, of minimum phase, in order to determine the mathematical behaviour that corresponds to the Big Bang. Next, following the line of seismic, we will analyse a Hardwire Similarity to demonstrate that a vibroseis source, which generates a sweep, produces, in addition to the ideal sweep of fundamental frequencies, spurious harmonic frequencies and additional noise. We will show that this additional energy generated by the spurious harmonic frequencies and additional noise adds to the energy of the fundamental frequency sweep in analogy as dark energy does.

Abstract: Steamed ginseng water (SGW), the by-product generated from the heated processing of red ginseng, with high content of active substances, better skincare activities, and large amount output ineffective utilization, resulted in environmental pollution and resource waste. In current study, UHPLC-Q-Exactive-MS/MS liquid chromatography-mass spectrometry and multivariate statistical analysis were conducted to characterize the compositional features of the repeated thermal-treated SGW. The total sugar content, total sugar content, total reducing sugar content, total non-reducing sugar content, DPPH, ABTS+, Fe3+ reducing capacity, and the hydroxyl radical scavenging abilities were employed to evaluate the gross contents variation connect with anti-oxidant activities during heat processes. The result revealed the SGW content and antioxidant activity were highly correlated, the 7th SGW sample showed the highest content and the strongest ability on anti-aging capacities. 38 significant common differential markers were screened, by the four compared SGW groups (1- and 3-, 1- and 5-, 1- and 7-, and 1- and 9) through OPLS-DA analysis. The current study showed that the thermal proceeding times could be a vital index value during the recycling operation quality control of SGW, which has a huge potential in anti-aging cosmetic raw materials, In the meanwhile, our results provided a green, sustainable, low-cost thinking of rational application on ginseng resource.

Areas covered with vegetation play a key role for life on Earth and should be inventoried in a clear and complete manner in order to improve the process of its protection and development. Data showing the amount of greenery in areas most deformed by humans, i.e. urbanized areas, are particularly important. Local governments need to know how to invest theirs limited sources in the quality of life of residents by supplementing the urban fabric with additional vegetation. The article presents a proposal for how to calculate the degree of greenness of cities based on remote sensing data. Additionally, a novel method was proposed to help in planning the development of areas covered with vegetation, taking into account the spatial distribution of the local population. The result was a comprehensive method presenting the actual natural situation in a specific city.

Given the many approaches to and definitions of gender responsive monitoring and evaluation (M&E) for health programs and interventions there is a lack of clarity on how to operationalize it including what to measure and how to measure it. We conducted a scoping review to understand what makes M&E gender responsive. We included 31 studies and conducted two rounds of extraction to delineate ways in which gender was integrated into M&E. Twelve articles described the use of theory to guide M&E though most were not related to gender. Twelve articles employed a gender score in data collection, most of which measured Likert scale responses related to gender equity. Even though most studies did not use a specific gender framework, most incorporated gender domains in their analysis. Seven studies used participatory methods in the design and implementation of M&E. Most studies conducted M&E on programs or interventions that were designed to be gender intentional and related to gender issues. Gender responsive M&E intentionally integrates gender into the M&E process, regardless of how gender-intentional the program or intervention is. Gender dimensions can be identified through gender theories, models, scores, and frameworks to inform tool development, data collection, analysis, and stakeholder engagement processes.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

The impact of the presence of Microplastics (Mp's) has become popular due to its presence in all environments, however, its transportation, accommodation and destination is still unknown. This study developed a laboratory-scale experiment, using eco-technologies for the treatment of domestic wastewater and reused for agriculture. A Constructed Wetland System of horizontal subsurface flow conditioned with substrate gravel and with two types of ornamental plants Hippeastrum Hybridum Hort and Heliconia Bihai Marginata, obtained an average 90% efficiency in the removal of pollutants COD, TDS, NH4, NT, PO4 , NO2 and PT; directing water through a drip irrigation system for irrigation of the Phaseolus vulgaris crop, selected for its nutritional importance (36% of daily protein intake), grown in two Growth Beds; The crop irrigated with treated water presented a greater relationship between growth and number of pods; finally identify the presence of Mp's through Fourier transform infrared spectroscopy (FTIR) analysis in the different types of water (domestic waste, treated waste and well) and determine the quality of the fruit for consumption with safety tests. Escherichia coli and Salmonella.

Urban ecology is a factor that significantly affects the urban landscape. Proper management and sustainable planning of ecosystems in cities can help urban landscapes to increase biodiversity and contribute to the efficient use of natural resources. In this framework, the integration of green spaces and ecosystem services can improve the quality of urban landscapes by increasing the health and resilience of urban ecosystems. This paper, which examines the effects of ecological factors on urban landscape in Antalya-Muratpaşa, presents a detailed analysis using various data sets. Within the scope of the research, the number of vehicles, carbon emissions by years, the ratio of green areas to population, CORINE data and land surface temperatures were analyzed. In addition, the change in land use from 1990 to 2018 and the land surface temperature forecast for 2040 and 2041 shed light on the evolutionary processes in the city. In an effort to understand the ecological status of Antalya-Muratpaşa, the paper highlights the potential impacts on the sustainability of the urban landscape. In particular, predicting the possible impacts of future land use on the urban landscape with population growth offers a strategic approach in planning processes. This study can be an important resource for urban planners, researchers and local governments because the data in the Antalya-Muratpaşa case provides a comprehensive overview that can guide those who want to consider sustainability and environmental factors in urban landscape planning. In line with this perspective, it is recommended to encourage green roof and green facade practices, rainwater harvesting, gray water recycling, etc. in new constructions.

The event camera generates an event stream based on changes in brightness, retaining only the characteristics of moving objects, addresses the high power consumption associated with using high-frame-rate cameras for high-speed eye tracking tasks. However, the asynchronous incremental nature of event camera output has not been fully utilized, and there are also issues related to missing event datasets. Combining the temporal information encoding and state-preserving properties of spiking neural network (SNN) with event camera, a near-range eye tracking algorithm is proposed as well as a novel event-based dataset for validation and evaluation. According to experimental results, the proposed solution outperforms artificial neural network (ANN) algorithms, while computational time remains only 12.5\% of that of traditional SNN algorithms. Furthermore, the proposed algorithm allows for self-adjustment of time resolution, with a maximum achievable resolution of 0.081ms, enhancing tracking stability while maintaining accuracy.

We aimed to directly compare the cost-effectiveness of the NELSON and NLST screening protocols, two trials influencing lung cancer screening implementation internationally. A decision-analytic model analyzing the cost-effectiveness of the NELSON protocols was manipulated to reflect the protocols of the NLST, while maintaining features specific to the Hungarian healthcare setting. In the NELSON protocol, there are three possible outcomes to the initial round of screening: positive, negative, or indeterminate, indicating an uncertain degree of suspicion for lung cancer. This pro-tocol differs from the NLST protocol, in which the only possible screening outcomes are positive or negative, with no indeterminate option. The NLST pathway for smokers aged 55-74 resulted in a 43 € increase in total average lifetime costs compared to the Hungarian screening pathway and re-sulted in a lifetime gain of 0.006 QALYs. The incremental costs and QALYs yield an ICER of 7875 €/QALY. Our results demonstrate that assigning any suspicious LDCT screen as a positive result (NLST protocol) rather than indeterminate (NELSON protocol) can yield a slight QALY gain that is worth the additional use of resources according to Hungary’s willingness to pay threshold. Our study provides insight on the cost-effectiveness, advantages, and disadvantages of various LDCT screening protocols for lung cancer and can assist other countries as they implement their screening programs.

Membranes are a selective barrier that allows certain species (molecules and ions) to pass through while blocking others. Some rely on size exclusion, where larger molecules get stuck while smaller ones permeate through. Others use differences in charge or polarity to attract and repel specific species. Membranes can be used to purify air and water by allowing only air and water molecules to pass through but preventing contaminants such as microorganisms and particles or to separate target gas or vapor, such as H2, CO₂, from other gases. The higher the flux and selectivity, the better a material is for membranes. The desirable performance can be tuned through material type (polymers, ceramics, and biobased materials), microstructure (porosity and tortuosity), and surface chemistry. Most membranes are made from plastic from petroleum-based resources, which contribute to global climate change and plastic pollution. Cellulose can be an alternative sustainable resource to make renewable membranes. Cellulose exists in plant cell walls as natural fibers, which can be broken down into smaller components such as cellulose fibrils, nanofibrils, nanocrystals, and cellulose macromolecules through mechanical and chemical processing. Membranes made from reassembling these particles and molecules have variable pore architecture, porosity, and separation properties and therefore have a wide range of applications in nano-, micro-, and ultrafiltration or forward osmosis. Despite their advantages, cellulose membranes face some challenges. Improving the selectivity of membranes for specific molecules often comes at the expense of permeability. The stability of cellulose membranes in harsh environments or under continuous operation needs further improvement. Research is ongoing to address these challenges and develop advanced cellulose membranes with enhanced performance. This article reviews the microstructure, fabrication methods, and potential applications of cellulose membranes, providing some critical insights into processing-structure-property relationships for current state-of-the-art cellulosic membranes that could be used to rationally improve their performance.

Aflatoxin being a serious threat to public health and international trade, necessi-tates a comprehensive understanding and calculated response with effective inter-vention strategies. This review methodically looks at several aspects of aflatoxin, starting with how it affects international trade laws through feed and feed ingre-dient regulations. Aflatoxin contamination poses serious challenges to world health and the economy, especially in areas that are already at risk. Examining the varia-bles affecting aflatoxin toxicity, the paper clarifies aflatoxin toxicity's complex me-tabolism and the resulting health effects of exposure. The serious repercussions of aflatoxicosis outbreaks and their connections to illnesses like Aspergillosis and cancer are highlighted by a detailed exploration of prospective decontamination techniques as well as strategies for detecting and capturing aflatoxin. A thorough knowledge of the factors that contribute to aflatoxin contamination demonstrates the intricate interactions between environmental variables, farming methods, stor-age circumstances, and different physical, biological, and nutritional components. Strong detection strategies are required due to aflatoxins’ significant effects on an-imal and human health. The paper describes complete preventative tactics that en-compass manipulation in management strategies. global trade and public health from this pervasive threat.

Traditional photodynamic therapy (PDT), a clinical cancer therapeutic approach using light in killing cancer cells, is often limited by insufficient light penetration, inefficient photosensitizer energy transfer, and inadequate oxygen in hypoxic tumors. Employing X-ray to activate photosensitizer in PDT can potentially overcome these limitations. Here, we compared protocols to synthesize a novel nano-photosensitizer composed of a europium-doped yttrium oxide core with a silica shell (Y₂O₃:Eu@SiO₂) which can be utilized in such therapeutic method, i.e., X-ray activated PDT (XPDT). Transmission electron microscopy (TEM) and dihydroethidium (DHE) were utilized to evaluate the effects of various synthesis conditions on the characteristics of Y₂O₃:Eu@SiO₂ and their ability to generate reactive oxygen species (ROS). The in vivo tumor suppression effects of the Y₂O₃:Eu@SiO₂ were assessed by ¹⁸F-fluorothymidine position emission tomography (¹⁸F-FLT PET) in human ovarian cancer xenografts using radiation sensitive CAOV3 and radiation resistant SKOV3 cell lines. Our data revealed a positive correlation between nanoparticle condensation time and core size as well as a negative correlation between urea concentrations and core size. Addition of cetyltrimethylammonium bromide (CTAB) during core synthesis enhanced particle dispersion. Two silica coating conditions showed the greatest efficiency in the enhancement of ROS generation. Furthermore, our in vivo study revealed suppression of tumor growth by Y₂O₃:Eu@SiO₂ administration when compared to non-treated control. Silica shell provides flexibility to conjugate moieties that specifically target to cancers. This nano-photosensitizer demonstrates the significant promise for overcoming limitations of conventional PDT and combating various cancers in clinical applications.

The aquifer delineation using a hydrogeophysical survey was carried out in De Aar, a small town in the eastern part of the Karoo supergroup, Northern Cape, South Africa. In this re-gion, the current approach for estimating recharge, water allocation plans, and water monitoring does not consider the existence of different types of aquifers. Instead, it assumes there is one aquifer system and therefore the area might have one value of recharge. This study aimed to delineate aquifers into unconfined and confined aquifers for estimating recharge and demonstrate the use of geophysics techniques in delineating aquifer systems. Six VES stations and seven profile lines were measured using a Wenner array configuration and ground magnetotelluric method, respectively. VES data was processed using IPI2win software while electric potential difference curve was in-terpreted together with lithological data. Four significant layers of low (0.9-8.1 Ωm), moderate (22.4-125 Ωm), and high 68-177 Ωm) resistivity values were delineated suggestive of the different lithological formations. The subsurface profile mapping using ground magentotelluric methods did not suggest groundwater accumulations below 50 m, instead supported shallow groundwater potentials boreholes. These results have provided a double layer aquifer system thereby suggesting that recharge estimation need to be carried out in two different aquifer systems to enhance water allocation plans, and water monitoring in groundwater-dependent areas similar to prevailing conditions in the current study area.

Design plays a critical role and creates a positive user experience, establishing a solid brand identity and staying competitive in the digital world. This research investigates the impact of user data collecting and analysis in improving user experience. The Data-driven User interface design can create an optimized and relevant UI with individual preferences, which leads to increasing user engagement and usability. The proposal explores methodologies to implement data collection and user research for tailoring digital products.

Hydrogels have gained significant attention as vehicles for transdermal delivery systems. These polymeric-structured substances have been implemented in pharmaceutical and cosmetic applications. Many factors are employed in their preparation. Light, pH, temperature and specific molecules ligands are commonly used in the production of hydrogels. The Transdermal delivery system (TDD) is a widely used route, used to deliver actives/drugs via the skin. Hydrogels as a TDD have been shown to be efficient in enhancing the efficacy in delivering the actives and drugs. The aim of this review is to discuss the hydrogels application in both dermatological therapeutic and cosmetic applications, covering the types, and properties of hydrogel polymer networks. Furthermore, this review presents one of the most extensively used polymers (Hyaluronic acid HA) in this field and discusses the properties, preparation methods and applications of HA hydrogel patches as a delivery system, including methods of loading the actives and the releasing of these actives from them.

One important goal of research on heterogeneous catalysis for Fischer Tropsch synthesis (FTS) is to understand the connection linking catalyst morphology and its activity. Development of these effective catalysts highlights the potential for understanding the effectiveness of promoted supported catalysts and revealing their complex and dynamic effects in FTS. The metal-support interaction (MSI) is influenced by the physicochemical and textural features provided by the modified support and can directly influence the sizes of active metal crystallites, reactants and/or products mass transfer, dispersion, mechanical strength, stability and consequently the adsorption-desorption characteristics of the catalyst. Herein, this article explores the general strategies for modifying silica supports (achieved through doping, coating, or promoting the support or support precursor) and how these strategies can be manipulated to further alter catalyst performance and product selectivity by enhancing the amount of active metal species and improving the intrinsic turnover frequency (TOF). Furthermore, the review emphasises a new strategy (the inverse model of the silica support modification) aiming at overcoming the challenges posed by active metal coating or coverage, as well as pore blockages by promoters that occur during conventional preparation of promoted silica supported FT catalysts.

Researchers have explored primary colour-geometric shape associations since Kandinsky's correspondence theory. However, there is a gap in the literature regarding interior colour applications on surface shapes. To address this gap, an online study was employed to gather data with one hundred participants who were asked to choose their preferred colours for shapes on bedroom walls with follow-up questions on the colour-shape semantic associations, their preference of colours and shapes on bedroom walls independently in addition to their favourite colour, their favourite shape, and colour-shape pairs without interior context. The results revealed that colour-shape preferences in interiors differ from those found in psychology studies, other colour applications on bedroom walls, and other preferences, indicating that colour preference is context-dependent. Interestingly, the most popular colour for surface shapes on bedroom walls is purple, followed by brown and blue. The study contributes to the existing literature by providing colour charts for bedroom applications for professionals in the industry, their clients/users, and future studies.

Recently several papers have been published on the Liénard equation x'' +L x+m x^3+n x^5=0, where the authors studied their explicit solutions and their applications. Here we describe the complete dynamics of these differential equations in the Poincar\'e disc. The Poincar\'e disc is the closed disc centered at the origin of coordinates of radius one, the whole plane R^2 is identified with the interior of this disc, and its boundary, the circle $\sss^1$ is identified with the infinity of R^2.

The introduction of the Industrial Internet of Things (IIoT) has led to major changes in the industry. Thanks to machine data, business process management methods and techniques could also be applied to them. However, one data source has so far remained untouched: The network data of the machines. In the business environment, process mining, for example, has already been carried out based on network data, but the IIoT, with its particular protocols such as OPC UA, has yet to be investigated. With the help of design science research and on the shoulders of CRISP-DM, we first develop a framework for process mining in the IIoT in this paper. We then apply the framework to real-world IIoT network traffic data and evaluate the outcome and performance of our approach in detail. We find tremendous potential in network traffic data but also limitations. Among other things, due to the dependence on process experts and the existence of case IDs.

Literature indicates scarcity of cross-national research on the association between physical fighting and bullying victimisation among adolescents, and the moderating role of perceived social support and education spending on this association. Using multilevel binary logistic regression, this study examined the association of physical fighting with traditional bullying and cyberbullying victimisation, with public education spending and perceived social support from families and teachers as moderators. Country-level data were combined with 2017/18 Health Behaviour in School-aged Children (HBSC) survey data from 162,792 adolescents (11-, 13- and 15-year-olds) in 27 European countries. Results showed that physical fighting was positively and significantly associated with cyberbullying and traditional bullying victimisation. These results signify that physical fighting is a robust predictor of bullying victimisation. The findings demonstrate that perceived social support and education spending buffered the association of physical fighting with traditional bullying and cyberbullying victimisation. The findings imply that social support not only prevents adolescents from engaging in physical fights, but also reduces the risk of bullying victimisation. Accordingly, to deter adolescents from engaging in physical violence and reduce the risk of bullying victimisation, there is need to fully comprehend the influence of physical fighting on bullying victimisation, and the moderating role of social support.

Background: Alzheimer's Disease (AD) is a progressive and incurable condition that prompts the exploration of interventions to slow its advancement and enhance the quality of life. The cortical brain waves could have a role in the process of executive function deterioration, increasing dementia symptoms. Objective: To interrogate the effects of physical exercise, and non-invasive brain stimulation, both in electrophysiological behavior of the brain, the executive functions, and dementia symptoms in older adults with AD. Methods: One hundred and sixteen older adults were grouped (n=22 each): GAE (AD, PMED+NIBS), GCP (AD, PMED), GCN (AD, NIBS), GCS (control, no intervention). Binaural beats were used as a non-invasive brain stimulation, physical exercise, or both, were applied during 16 weeks. Pre/post measurements included Alpha Band, and SMR Rhythms, executive functions, and dementia symptoms. Results: GCS showed no significant changes (p>0.05). GCN and GCS slightly enhanced inhibitory control (p>0.05) and working memory (p>0.05). In contrast, GCP and GAE improved executive function (p

Metabolites present in the hemolymph of honey bees play a crucial role in modulating the metamorphic process within the species. However, the precise alterations in metabolite composition, along with the associated variances and regulatory pathways implicated during the larvae-to-pupae metamorphosis of honey bees, remain incompletely elucidated. In this investigation, we gathered hemolymph samples from honey bee larvae at three distinct physiological stages-feeding, prepupal, and pupae and subjected them to metabolite analysis utilizing the liquid chromatography-mass spectrometry (LC-MS) technique. Employing principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), we identified significant differential metabolites and conducted a metabolic pathway analysis on those differentially up-regulated during the prepupal and pupae stages. Notably, metabolites up-regulated in the hemolymph of prepupal stage larvae primarily governed glucose metabolism and fat digestion and absorption, while those in pupae stage larvae were involved in regulating chitin and lipopolysaccharide precursor formation, as well as the biosynthesis of phenylalanine, tyrosine, and tryptophan. These findings bear significant implications for advancing our comprehension of the metamorphic processes in honey bees.

In an era marked by digitization and automation, extracting relevant information from business documents, like electricity invoices, remains a major challenge. To address this, we need to use machine-learning techniques to automate the process, reduce manual labor, and minimize errors. This work introduces a new method for extracting key values from this type of invoice, including customer personal data, bill breakdown, electricity consumption, or marketer data. We evaluate several machine learning techniques, such as Naive Bayes, Logistic Regression, Random Forests, or Support Vector Machines. Our approach uses a bag-of-words strategy and custom-designed features specifically tailored for electricity data. We tested the method on the IDSEM dataset, which includes 75.000 electricity invoices with eighty-six different fields. The method converts PDF invoices into text and processes each word separately using a context of eleven words. The results of our experiments indicate that Support Vector Machines and Random Forests perform exceptionally well in capturing numerous values with high precision. The study also explores the advantages of our custom features and evaluates the performance of the model on unseen documents. The precision obtained with Support Vector Machines is 91,86%, peaking at 98,47% for one document template. These results demonstrate the effectiveness of our method in accurately extracting key values from invoices.

Rotorcrafts operate HUMS for fault diagnosis, but the capabilities of HUMS analysts are important due to the complex mechanical configuration of rotorcraft and the difficulty of analysis. Accordingly, an advanced algorithm is needed to identify faults, and flight data can be used to develop the algorithm. However, flight data contains abnormal or missing data due to problems such as sensor defects, which can be a major problem in algorithm development. Therefore, in this paper, we study a gap filling method using MLP to obtain normal data when there are problems such as abnormal or missing data in rotorcraft flight data. Existing methods typically fill the gap through interpolation or curve fitting using the before and after values of missing data. However, in this study, normal values were estimated using the values of other parameters at the moment of missing or abnormal data occurred. As a result of evaluating the performance of the trained MLP using normal data, it was confirmed that the output of the model well estimates the changing trend of the target. And when abnormal data was applied to the trained model, it was confirmed that point outliers were eliminated and appropriate values were found in the case of missing data.

With a view to understand and resolve the complexity of the food matrix, ohmic technologies alone or in combination were extensively employed. In this sense, the newest developments and advances of proteomics, metabolomics, lipidomics whith their unique benefits could simplify and understand the link between physiological and pathological activities in biology, physiology, pathology, and food science and processing. This review aims to briefly introduce the basis of proteomics, metabolomics, lipidomics, then expansively review their impact on the assessment of meat quality and safety. Here, also, we discuss the application of proteomics, metabolomics, lipidomics for the authentication and adulteration of meat and meat derivatives from different sources, and provides some perspectives regarding the use of emerging techniques such as rapid mass spectrometry (MS) and non-invasive measurements for the analysis of meat quality and safety. This paper summarizes all significant investigation in these matters, and underlines the advances in analytical chemistry technologies and meat science areas. By emphasizing the requirement for additional examinations, this paper attempts a comprehensive knowledge of “foodomics” and their potential to improve their employment in meat science.

Repetitive elements, often referred to as selfish genes, pose significant challenges to genome assembly and read mapping in bioinformatics. These elements can replicate within the genome without providing functional benefits to the host organism, leading to complexities in accurate genome analysis. This study presents a simulation-based approach to illustrate the impact of repetitive elements on read mapping accuracy. By comparing genome sequences with and without repetitive elements, we demonstrate how these selfish genes create ambiguities and errors in read alignment. The findings underscore the importance of developing advanced bioinformatics tools aligned with artificial intelligence to mitigate the effects of repetitive sequences and improve the reliability of genomic analyses.

Bi1-xSbx crystal is one of the best n-type thermoelectric materials below 200 K, but its weak mechanical strength hinders practical applications for deep refrigeration. Herein, we adopted the mechanical enhancement method of hot extrusion to investigate the comprehensive mechanical and thermoelectric properties of Bi0.905Sb0.095. It revealed that reducing the grain size of the matrix and increasing the extrusion ratio can improve the gain size uniformity and mechanical properties. While the thermoelectric performance depends on the texture, grain size, and local composition. The extruded sample prepared by ingot with the high extrusion ratio of 9:1 generated a high texture degree of (001) plane and small grain sizes between ~4-40 mm, which resulted in the high bending strength of Bi1-xSbx ~130 Mpa and a high-power factor of ~ 68 μW·cm-1·K-2@173 K, as well as the relative high figure of merit of 0.25@173K. This work highlights the importance of the uniform distribution of the grain size and the compositions for Bi1-xSbx, as well as the required universal key parameter for the hot-extrusion method.

In this work, an improved collocation method based on the Bernoulli polynomials is presented to solve the Volterra integral equation (VIE) of the second kind. The main idea of the proposed method is to improve the results of the classic Bernoulli collocation method (BCM) by dividing the interval into some sub-intervals and considering the collocation points on each of them. Here, the zeros of the shifted Chebyshev polynomials (SCPs) are considered as collocation points. Then, BCM is applied step by step from the first sub-interval to the last one. By this process, a system of algebraic equations is attained for each sub-interval that could be easily solved. Convergence of the scheme is analyzed. For the purpose of demonstrating the validity, applicability, and efficiency of the suggested scheme several numerical examples are provided. Numerical results illustrate that the accuracy of the improved Bernoulli collocation method (IBCM) is more than BCM.

The aim of this prospective, randomized, clinical study was to evaluate the use of the pleth variability index (PVi) to guide the rate of intra-operative fluid therapy as compared with a traditional fixed fluid rate approach in ASA 1-2 dogs undergoing surgery. Twenty-seven dogs meet the inclusion criteria and were randomly assigned to conventional fluid management group (CFM, n = 12) or PVi-guided group (PVi, n = 15). The CFM group received a fixed rate of 5 ml kg-1 h-1 of crystalloid solution, while in the PVi group the rate was continuously adjusted based on PVi: PVi < 14% = 3 ml kg-1 h-1; 14% ≤ PVi ≥ 20% = ml kg-1 h-1; PVi > 20% = 15 ml kg-1 h-1. Hypotension (MAP < 65 mmHg) was managed in CFM with maximum two fluid boluses (5 ml kg-1 in 10 minutes) and in case of no response dobutamine (1-3 mcg kg-1 min-1) was administered. In the PVi group treatment of hypotension was similar except when PVi > 14% when dobutamine was directly initiated. The total fluid amount was significantly lower in PVI group (0.056 ± 0.027 ml kg-1 min-1) vs. CFM group (0.132 ± 0.115 ml kg-1 min-1), and hypotension incidence was lower (p = 0.023) in PVi group (0%) vs. CFM group (41%). Mean arterial pressure (MAP) was significantly higher during surgery in the PVi group. Dobutamine was never administered in both groups. Preliminary data suggest that PVi may be considered a potential target to guide fluid therapy in dogs; larger studies are needed, especially in cases of cardiovascular instability.

The deaf-mute and individuals with hearing disabilities who communicate through sign language should not be overlooked or excluded. It is a social responsibility to strive for an inclusive world without inequality. Advances in technology offer various solutions to address the communication gap, one of which is the use of computer-based sign language recognition systems. This project proposes a Malaysian Sign Language recognition model utilizing MobileNetV1, a convolutional neural network-based algorithm, to interpret sign language in real-time settings through a website application using Streamlit. The outcome of the model test shows that it has achieved a recognition rate of 96 percent. Although the proposed model has demonstrated the ability to recognize sign language, it is suggested that further improvement can be achieved by enhancing the quality and diversity of the dataset. The implementation of a more comprehensive dataset would lead to improved performance and increased accuracy of the model. This project underscores the importance of considering and accommodating the needs of the deaf-mute and individuals with hearing disabilities and highlights the potential of technology to bridge communication barriers and achieve a more inclusive society.

This study presents an in-depth analysis of land use and land cover change on the Kerch Peninsula over a period spanning three decades. Utilizing convolutional neural networks alongside satellite imagery analysis, we have mapped and quantified the changes in land use and cover, revealing significant trends and transformations within the peninsula's landscape. The research aims to elucidate the interplay between anthropogenic activities, climatic variations, and policy interventions in shaping land cover dynamics, thereby providing insights into the environmental and socio-economic impacts of these changes. Our findings indicate a marked increase in urban expansion at the expense of natural ecosystems, including forests and wetlands, underscoring the urgent need for sustainable land management strategies. The study highlights the role of agricultural intensification and expansion in altering the peninsula's ecological balance and emphasizes the critical importance of integrating change analysis and prediction. By leveraging advanced remote sensing and GIS technologies, our analysis not only enhances the understanding of the complex dynamics driving land use and land cover change but also showcases the potential of predictive modeling in forecasting future land cover scenarios. The implications of this study extend beyond the Kerch Peninsula, offering valuable lessons for managing land use changes and conserving natural landscapes in similar regions globally.

Visible light communication (VLC) has attracted much attention in recent years among industrial and academic researchers. The large scale use of energy efficient light emitting diodes (LEDs) in lighting applications offers a unique opportunity to use license free visible light as the carrier in wireless communications. It has many potentials to complement radio frequency (RF) based communication systems. Researchers working on VLC have mainly concentrated on improving the communication speeds to match with Wi-Fi though the latest generation Wi-Fi standards offer significantly higher capacity at longer communication distances. Thus, market penetration is challenging for VLC as Wi-Fi is already quite mature and ubiquitous. Commercialization of VLC can only be successful if VLC can offer applications where VLC is more advantageous over the existing RF-based solutions. Once VLC enters the market through specific applications and becomes more mature in the process, the ecosystem may gradually adopt VLC in broader applications. In this article, the state of the art of the three promising VLC applications, their issues, and possible solutions have been discussed.

Hydrogen gas (H2) has attracted attention as a next-generation clean energy source. Its efficient and safe preparation and utilization are crucial in both industry and organic chemistry. In this study, a Pt/CB-catalyzed MW-mediated continuous-flow hydrogenation reaction was developed using methylcyclohexane (MCH) as the reducing agent (hydrogen carrier). Alkynes, alkenes, nitro groups, benzyl esters, and aromatic chlorides were chemoselectively hydrogenated using Pt/CB under MW-assisted continuous-flow conditions. This methodology represents a safe and energy-efficient hydrogenation process, as it eliminates the need for an external hydrogen gas supply or heating jackets as a heat medium. Further application of MW-mediated continuous-flow hydrogenation reactions is a viable method for the efficient generation and utilization of sustainable energy.

The principal function of science education is to introduce students to core scientific concepts and practices; nevertheless, it is now impossible, in such a complex world, to neglect the ethical issues involved. Placing school science in a broader context motivates students and equips them with valuable critical skills. A meaningful example was from palm oil production and pervasive use worldwide: plantations result in major deforestation occurring in species-rich tropical regions, making the palm oil issue global in scope and highly critical for several aspects related to sustainability. This paper reports a sequence of didactic activities starting from palm oil chemistry, gradually extended initially by a multidisciplinary approach, then by interdisciplinary-systemic maps and, ultimately, through a holistic vision - involving anthropological and cultural considerations about indigenous people of deforested territories. This progressive broadening corresponds to an ever-greater penetration into the personal sphere, a condition for a real ethical consciousness. The increased students’ awareness was tested by qualitative considerations, supporting the teaching dimension more than the learning one. Contrary to disciplinary contents, the emergence of moral feelings cannot be measured but only perceived. Therefore, chemistry provides key concepts essential for global competences development in order to deal with sustainability issues with an increased ethical awareness.

Oral squamous cell carcinoma (OSCC) is a highly prevalent and aggressive malignancy, with mortality rates that reach 60%, mainly due to an excessive diagnostic delay. MiRNAs, a class of crucial epigenetic gene-expression regulators, have emerged as potential diagnostic biomarkers, with >200 molecules reported to be dysregulated in OSCC. We had previously established an in silico methodology for the identification of the most disease-specific molecules by bridging genetics and epigenetics. Here, we identified the stage-specific miRNAs that govern the asymptomatic early stages of oral tumorigenesis by exploiting the reverse interplay between miRNA-levels and their target-genes’ expression. Incorporating gene expression data from our group’s experimental hamster model of sequential oral oncogenesis, we bioinformatically detected the miRNAs that simultaneously target/regulate >75% of the genes that are characteristically upregulated or downregulated in the consecutive stages of hyperplasia, dysplasia and early-invasion OSCC, while exhibiting the opposite expressional dysregulation in OSCC-derived tissue and/or saliva specimens. We found that all stages share the downregulation of miR-34a-5p, miR124-3p, and miR-125b-5p, while miR-1-3p is underexpressed in dysplasia and early-invasion. Malignant early-invasion stage is distinguished by the downregulation of miR-147a and the overexpression of miR-155-5p, miR-423-3p and miR-34a-5p. The identification of stage-specific miRNA molecules may facilitate their utilization as biomarkers for presymptomatic OSCC diagnosis.

Whey protein was pretreated with multi-frequency ultrasound in mono, dual, and tri-frequency modes. The effect of multi-frequency ultrasound pretreatment on the hardness, chemical forces, and microstructure of acid-induced whey protein gel was investigated. Whey protein gels pretreated with dual and tri-frequency ultrasound showed higher hardness (p3.35 mm) in those samples were resisted to gastric digestion. Moreover, the tri-frequency ultrasound pretreatment of whey protein gel released the least free amino group during gastric digestion. In contrast, whey protein gel with the mono-frequency ultrasound pretreatment released the highest amount of free amino acid group during intestinal digestion. Findings from this study suggested that gel hardness and network density could modulate the digestion behaviors of protein gels.