The learning system is primarily based on teaching, and teaching through digital resources is referred to as e-learning. As the world progresses towards success day by day, the use of technology, digital devices, and modern techniques is becoming increasingly prevalent. The global shift from traditional paperwork to digital learning is one of the most significant changes in the education sector. However, many factors have created numerous hurdles during the online setup. The Covid-19 pandemic has led to serious problems all over the world, with the education sector being one of the most affected. One of the greatest challenges students face during online education is the lack of digital infrastructure, especially in remote areas of Pakistan. The biggest challenge is connecting students with teachers due to limited internet access. Without proper internet connectivity, both students and teachers cannot access educational materials. In this context, the government plays a crucial role in providing adequate facilities to students, particularly in primary schools. If proper infrastructure is not made available during this pandemic, students will be deprived of a good quality education. Therefore, good infrastructure is essential for effective online education. With the proper resources in place, students will be able to receive a quality education.

Objective: To explore the effect of time exposure to flat screen electronic devices with LED 14 lighting and the Mediterranean diet on macular pigment optical density (MPOD). Methods: MPOD 15 was measured by heterochromatic flicker photometry in 164 eyes (47 of young women 20-31 years 16 and 35 adult women 42-70 years). Exclusion criteria: evidence of macular degeneration and eyes 17 with cataracts. Data on the use of electronic devices and Mediterranean diet adherence were col- 18 lected through a survey. Nonparametric analysis of variance and independent sample t-tests were 19 used to compare subjects. Results: Significant differences (p<0.01) were found in total time of expo- 20 sure to LEDs (hours per day) between both groups (9.31 ± 3.74 young women vs 6.33 ± 3.64 old 21 women). The MPOD values for the young and adult populations were significantly different: 0.38 ± 22 0.16 and 0.47 ± 0.15 (p<0.01), respectively. When comparing both groups for the same time of expo- 23 sure to LEDs, differences were obtained between MPOD values of both populations: For total expo- 24 sures greater than 6 hours per day, the MPOD values were lower in young women than in adult 25 ones (0.37 ± 0.14 vs 0.50 ± 0.14, p<0.01). On the other hand, a significantly higher adherence was 26 found in the old women in comparison with the young women (OW 9.23± 2.50 vs YW 7.70 ± 2.08, 27 p<0.01), with higher MPOD values, (OW (0.52 ± 0.14) vs (YW (0.34 ± 0.18). Conclusions: Higher 28 MPOD values are observed with decreasing exposure time to electronic devices with LED lighting 29 screens and high adherence to the Mediterranean diet.

Background: Mitral regurgitation (MR) is a common valvular disorder linked to high morbidity and mortality. For patients unsuitable for surgery, transcatheter mitral edge-to-edge repair (TEER) with the MitraClip® G4 system offers an alternative. This study aims to evaluate procedural, echocardiographic, functional, and quality of life (QoL) outcomes in patients who underwent TEER with the MitraClip® G4 system, along with possible predictors of New York Heart Associa-tion (NYHA) class I at 30 days and 1 year. Methods: Patients with moderate-to-severe (3+) or se-vere (4+) degenerative MR (DMR) or functional MR (FMR), classified as NYHA class III or IV, who underwent TEER with the MitraClip® G4 system at our center between January 2021 and De-cember 2023 were included. Results: A total of 83 patients [71% FMR, 66% male, median (IQR) age 70 (11) years] underwent TEER, with 100% procedural success. MR ≤2+ was achieved in 100% and 98% of patients at 30 days and 1 year, respectively. NYHA class I or II was achieved in 100% and 96.8% of patients at 30 days and 1 year, respectively. The Kansas City Cardiomyopathy Ques-tionnaire (KCCQ) score improved from 51±20 at baseline to 69±15 at 30 days (p< 0.001) and 70.5±15 at 1 year (p< 0.001). Lower baseline N-terminal pro-brain natriuretic peptide (NT-proBNP) pre-dicted achieving NYHA class I at 30 days (HR: 0.63, 95% CI: 0.41–0.95, p = 0.030), while lower Eu-ropean System for Cardiac Operative Risk Evaluation II (EuroSCORE II) and NT-proBNP pre-dicted it at 1 year [(HR: 0.50, 95% CI: 0.28–0.89, p = 0.019), (HR: 0.67, 95% CI: 0.44–0.99, p = 0.049), respectively]. Conclusions: The MitraClip® G4 system provides significant improvements in MR severity, functional class, and QoL. Lower NT-proBNP and EuroSCORE II were strong predictors of achieving optimal functional status (NYHA class I).

This study examines the feasibility and efficacy of utilizing generative AI technology to create inclusive online dating educational materials, focusing on integrating easy-to-read principles to enhance accessibility while improving efficiency and reducing the cost of material production. As online dating becomes increasingly prevalent, providing easily comprehensible safety education for special populations, such as individuals with disabilities and adolescents, is of paramount importance. This research developed an innovative AI-generated educational framework that combines easy-to-read principles with generative AI technology, aiming to enhance both the accessibility and production efficiency of educational materials. The study compared three AI generation strategies: independent generation by ChatGPT, independent generation by Claude, and Claude utilizing materials generated by ChatGPT. We evaluated 36 educational units through a mixed-methods approach for readability and accessibility. Results indicate that ChatGPT performed optimally in generating easily readable content (average compliance rate of 93.00%), followed by the strategy Claude using ChatGPT-generated materials (91.67%). Statistical analysis revealed significant differences among these strategies (p < 0.05). The research also found that employing AI generation technology significantly reduced material production time and costs, providing educators with a more efficient tool. The findings of this study underscore the significant potential of generative AI technology in creating inclusive educational resources. This not only opens up new avenues for enhancing online safety awareness and educational accessibility for special populations but also provides material developers with more efficient, cost-effective production methods. The empirical evidence presented here for the application of AI in inclusive education is a significant step forward. The study also proposes recommendations for future research and practice, aiming to further improve the accessibility, effectiveness, and production efficiency of online dating education.

Background: Inflammatory Bowel disease (IBD) is one of the worldwide health issues with increasing incidence. Recent data point out that those patients can have a defective immune system, rendering response to vaccinations suboptimal. Since 1990, Hepatitis B Virus (HBV) vaccination has been introduced among the compulsory childhood vaccinations in Oman. Given the questionable immunogenicity of vaccinations in IBD patients, we designed this study to quantify the immune response to scheduled HBV vaccine in IBD patients and compare it with that in a matching control cohort of healthy blood donors at Sultan Qaboos University Hospital (SQUH). Methods: This is a retrospective case-control study that was conducted between the 1st of July 2023 and the 31st of May 2024 at SQUH. Using the hospital information System (HIS), a total of 252 participants were enrolled in our study and divided into two groups. Group (1) included 126 IBD patients and group (2) included 126 healthy controls. Baseline demographics, medical comorbidities and viral serologies before and after vaccination were collected. The primary outcome of the study was to compare the long term immune response to HBV vaccine between the two groups. The secondary outcomes included identifying possible risk factors for suboptimal vaccine response. Results: One hundred and twenty-six participants were included in each group. Durable protective immune response to HBV vaccine was attained in 29 patients (23%) of the IBD group compared to 109 participants (86.5%) of the control group. There was a statistically significant association (p = 0.0156) between prednisolone treatment and low immune response to HBV vaccine. Moreover, esomeprazole usage exhibited a statistically significant association (p < 0.0001) with suboptimal response to HBV vaccine. Meanwhile, there was no statistically significant correlation between low immunogenicity to HBV vaccine and age, sex, type of IBD, comorbidities, and BMI. Conclusions: IBD patients are less immunogenic to HBV vaccination compared to healthy controls. Factors like esomeprazole and/or corticosteroid therapy might be associated with poor immune response. These findings highlight the importance of reassessing the immunogenicity of HBV vaccination and probably other protective vaccinations in all IBD patients as part of their standard of care.

Emotional agility and social intelligence at small to medium-sized enterprises (SMEs) can be an invigorating experience, filled with opportunities for growth, innovation, and collaboration. This research aims to investigate the Omani entrepreneurs’ emotions and intelligence at workplace through self-experiences in SMEs. A sample of 222 Omani entrepreneurs participated in online survey that was designed to attain the objectives of this research. Data was collected using google drive and analyzed using multiple regression path analysis. The results revealed that emotional agility and social intelligence have positive and significant impact on employee thriving at work in Omani SMEs. Further, openness to experience mediates the relationships between entrepreneurs’ emotions and intelligence and sustainable workplace. These results confirm the effective role of openness to experience among Omani entrepreneurs where they should adopt new strategies and techniques to improve their skills and support their SMEs. This research highlighted the role of interpersonal skills including agility and intelligence of entrepreneurs in Arab context.

The elasticity of red blood cells (RBCs) is crucial for their ability to fulfill their role in the blood. Decreased RBC deformability is associated with various pathological conditions. This study explores the application of machine learning to predict the elasticity of RBCs using both image data and detailed physical measurements derived from simulations. We simulated RBC behavior in a microfluidic channel. The simulation results provided the basis for generating data on which we applied machine learning techniques. We analyzed the surface-area-to-volume ratio of RBCs as an indicator of elasticity, employing statistical methods to differentiate between healthy and diseased RBCs. The Kolmogorov–Smirnov test confirmed significant differences between healthy and diseased RBCs, though distinctions among different types of diseased RBCs were less clear. We used decision tree models, including random forests and gradient boosting, to classify RBC elasticity based on predictors derived from simulation data. The comparison of the results with our previous work on deep neural networks shows improved classification accuracy in some scenarios. The study highlights the potential of machine learning to automate and enhance the analysis of RBC elasticity, with implications for clinical diagnostics.

According to current forecasts, global heating is likely to exceed 2,8°C by the end of the century. This makes substantial adaptation measures necessary to secure a broad basis for livelihoods provision and the conservation of biodiversity. While the implementation of top-down and technocratic adaptation efforts is the majority, related adaptation shortcomings of socio-economic and ecological nature are becoming more and more apparent. Community-based adaptation (CBA) with its participatory, inclusive and needs-based bottom-up approach offers a promising and powerful alternative. This article uses a semi-systematic literature review approach to screen the current literature and identify core issues of CBA. Linking communality, locality, multidimensionality, power imbalances, transformative potential, localisation, the triad of adaptation metrics and adaptation with nature to corresponding potential actions for practical implementations provides a more holistic conceptualisation and broadens the horizons for further learnings, research and improved application.

Painting style and creativity are fundamental to art, defining a work’s uniqueness and expression. They embody an artist’s personality, convey emotions, establish identity, and shape audience perception, adding depth and value to the work. Recently, diffusion models have gained popularity in art design, animation, and gaming, especially in original painting creation, poster design, and visual identity development. Traditional creative processes, while demanding unique imagination and creativity, often face challenges such as slow innovation, high reliance on manual efforts, high costs, and limitations in scalability. Consequently, exploring painting-style creative design through deep learning has emerged as a promising trend. In this paper, we introduce a novel network architecture, the Painting-Style Design Assistant Network (PDANet), for style transformation. To support this, we curated the Painting-42 dataset, comprising 4,055 works by 42 renowned Chinese painters. PDANet leverages this dataset to capture the aesthetic intricacies of Chinese painting, offering rich design references. Furthermore, we propose a lightweight Identity-Net for large-scale text-to-image (T2I) models, which aligns internal knowledge with external control signals, thereby enhancing the capabilities of existing T2I models. The trainable Identity-Net feeds image prompts into the U-Net encoder to generate diverse and stable images. Both quantitative and qualitative analyses demonstrate that our approach outperforms current methods, delivering high-quality generated content with wide-ranging applicability.

Here, we report an ultrasoft extra long-lasting reusable hydrogel-based sensor that enables high quality electrophysiological recording with low motion artifacts. The developed sensor can be used and stored in the ambient environment for months before being reused again. The developed sensor is made of a self-adhesive electrical-conductivity-enhanced ultrasoft hydrogel, mounted in an Ecoflex-based frame. Hydrogel’s conductivity was enhanced by incorporating polypyrrole (PPy), resulting in the conductivity of 0.25 S m-1. Young’s modulus of the sensor is only 12.9 kPa and it is stretchable up to 190%. The sensor was successfully used for the electrocardiography (ECG) and electromyography (EMG). Our results indicate that using developed hydrogel-based sensor, the signal-to-noise ratio of recorded electrophysiological signals was improved in comparison to that when medical grade silver/silver chloride (Ag/AgCl) wet gel electrodes were used (33.55 dB in comparison to 22.16 dB). Due to the ultra-softness, high stretchability, and self-adhesion of the developed sensor, it can conform to the skin and therefore, it shows low susceptibility to motion artifacts. Also, the sensor shows no sign of irritation or allergic reaction that usually occurs after long-term wearing medical grade Ag/AgCl wet gel electrodes on the skin. Further, the sensor is fabricated using a low cost and scalable fabrication process.

This paper presents the five-parameter Exponentiated Weibull Weibull (EWW) distribution with Weibull base failure rate parameterization, developed to model the dropout times of students in an online class module. Parameters of the model were estimated using both Maximum Likelihood and Bayesian estimation procedures to determine the most effective estimation method. Simulation results indicate that, across various hazard types and censoring levels, Bayesian estimates are more accurate and precise than Maximum Likelihood estimates. Real-life data analysis of online students module presentation supports these findings, showing significantly lower standard deviations for Bayesian estimates compared to Maximum Likelihood estimates, highlighting the efficiency of Bayesian estimation for the EWW distribution. Additionally, a comparative goodness-of-fit analysis demonstrated that the EWW distribution better fits the student dropout times dataset than Weibull Weibull (WW), Weibull Exponential (WE), and Exponential Weibull (EW) distributions. The median dropout time estimated using the EWW distribution is 24 days, suggesting that instructors should closely monitor student attendance around this period.

Klebsiella pneumoniae, a member of the ESKAPE pathogen group, is a prominent cause of hospital-acquired infections. The WHO recognized carbapenem-resistant K. pneumoniae as a critical-one priority pathogen. These resilient superbugs have the ability to form biofilms and present a significant global threat. In the present study, we isolated and characterized a bacteriophage SAKp02, from hospital sewage, infectious to carbapenem-resistant K. pneumoniae patient isolates. SAKp02 could infect 43 of 72 clinical isolates, indicating a broad host spectrum. Whole genome analysis classified SAKp02 within the family Casjensviridae, with a 59,343 bp genome encoding 82 ORFs. Comparative genomic analysis revealed significant differences between SAKp02 and its closest viruses, indicating a distinct genetic makeup positioning it as a novel phage strain within the lineage. The SAKp02 genome comprises bacteriolytic enzymes, including holin, endolysin, and phage depolymerase, crucial for bacterial lysis and biofilm disruption. It reduced biofilm biomass by over threefold compared to the control and eradicated 99% of viable cells within a 4-hour treatment period. Scanning electron microscopy corroborated the ability of the phage to dismantle biofilm matrices and lyse bacterial cells. Safe and effective treatments are warranted, and hence, the fully characterized lytic phages with therapeutic potential against drug-resistant clinical isolates of bacteria are needed. Our study is the first to report the antibacterial and antibiofilm activity of Casjensviridae phages, and our discovery of a novel K. pneumoniae phage broadens the arsenal against the bacteria.

: Carcinoma-associated fibroblasts (CAFs) are highly accumulated in the tumor surrounding stroma of primary epithelial ovarian cancer (OC). CAFs exert important functions for the vascularization, growth and progression of ovarian tumor cells. However, no attention has been shown to their origin so far. It has been mainly assumed that CAFs in primary OC arise from the activation of resident fibroblasts. Here, we compare CAFs with ovarian location to CAFs found in peritoneal implants from patients with advanced OC. Our findings show that CAFs from primary tumors and peritoneal metastases share the expression of mesothelial-related markers. Therefore, as in peritoneal carcinomatosis, CAFs in primary ovarian carcinomas could be originated via a mesothelia-to-mesenchymal transition (MMT) process. The detection of mesothelial-derived CAFs in tumors confined to the ovary and associated biomarkers could be the key to early detection of peritoneal spread in affected patients.

This article addresses the emergence of a niche for sustainable agricultural production in the province of García Rovira, Colombia. It examines the intervention of the Colombian planning regime, which implements agendas for sustainable territorial development. However, these agendas are not adequately aligned with provincial realities, resulting in a productive decline. From a multi-level perspective, a niche of production linked to the landscape is identified, highlighting sustainable practices and innovation. The study seeks to understand how planning influences the emergence of such niches and what factors boost their transition to sustainability. Through a mixed methodology, growing sectors are highlighted, and the profiles of the producers involved are outlined. The main conclusion is that the planned intervention is inefficient, as the niche of sustainable production emerges without its clear influence. Therefore, it is proposed to re-evaluate planning using alternative analysis frameworks to detect emerging productive dynamics, serving as a basis for future plans.

This paper presents a novel framework for Collaborative Learning Networks (CLNs) in classrooms, aiming to optimize resource utilization and enhance educational services. The study addresses the inefficiencies of traditional education models, particularly the underutilization of computational resources and limited access to specialized software. The proposed framework employs a mix of task-based and random allocation strategies to distribute computational tasks within the CLN, considering each device’s capabilities and task requirements. The findings show significant improvement in resource utilization, facilitated by device-to-device collaboration and task sharing, thus enriching students’ learning experiences. This work contributes to optimizing resource utilization in education, advancing the field of CLNs.

Recent years have witnessed significant advances in reinforcement learning (RL), which has registered remarkable success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games of Go and Poker, robotics, and autonomous driving, involve the participation of more than one single agent, which naturally fall into the realm of multi-agent RL (MARL), a domain with a relatively long history, and has recently re-emerged due to advances in single-agent RL techniques. Although, typically, the communication protocol between agents is manually specified and not altered during training, recently, some papers have shown signs of trying to emerge a communication between agents on the one hand and, on the other hand, to understand what is exchanged between agents. So, there is a growing body of literature on this topic which includes qualitative and quantitative studies and the ones that apply mixed methods. This study presents the scoping review of the methodological strategies undertaken in a total of 16 research articles. The results present the critical appraisal of quantitative methods in terms of validity and reliability and for qualitative methods considering four trustworthiness factors. In the end, relevant insights are further explored with implications and reflections on how they can benefit one's research in the field.

The extent of access to energy of displaced populations in settlements and camps in Africa is largely unknown, given 94% of displaced persons without access to electricity and 81% with a reliance on biomass for cooking. A multitude of contextual factors, such as the location and the characteristics of housing, the legal status, the socio-cultural background and the availability of humanitarian and public services impact the living conditions and the needed energy services. Limitations in accessing energy services have direct, multilayered, and far-reaching implications, including impacts on health, nutrition, education, protection, and livelihood. The objective of this article is to contribute to a more comprehensive understanding of the current state of energy ac-cess in displacement contexts on the African continent by identifying and utilizing existing data. After a screening of the vast and various available information, setting up of a database, consoli-dating the gathered data as well as assessing the quality through a quality assessment method, the currently available information is visualized and discussed. Remarkable differences in the access to electricity for displaced persons across the countries are found. For both electricity and clean cooking, the availability for displaced persons ranges from nearly no access at all up to an access rate of 100%. More strikingly, the results also show that besides South Africa, and the se-lected countries in the Maghreb region, the access to both clean cooking and electricity for dis-placed persons is remarkably low. At the same time, the poor data quality does not allow to draw solid conclusions nor impactful implementation activities. Novel conceptual frameworks and indicators are needed. Future research needs to focus on a more comprehensive understand-ing of how energy is interwoven in the lives of displaced persons, before a set of energy indicators can be derived. It is essential that the concerned persons, the displaced persons themselves are in-cluded in the research in a meaningful way.

Agriculture contributes towards South African economy, but this sector is highly vulnerable to risks imposed by climate change. Smallholder maize farmers are specifically susceptible to climate change impacts. Maize crop plays a crucial role in the country's food security as it is considered a stable food for households and source of feed for livestock. The study aimed to analyze the socio-economic factors influencing smallholder maize farmers’ willingness to adopt climate-smart agriculture. It was conducted in three different areas due to their specific agro-ecological zones. Multipurpose research design was used to gather data, and multistage random sampling to choose the study areas. Subsequently, 209 purposively selected farmers were interviewed face-to-face using structured questionnaires and focus discussion groups. Descriptive statistics and Double-hurdle regression model were used to analyze the data. Descriptive results indicated that 81%, 67%, and 63% farmers were willing to adopt CSA in Ga-Makanye, Gabaza, and Giyani, respectively. Empirical results from the first and second hurdles of the regression analysis showed that farmers’ education, crop diversification, information about CSA positively influenced the decision to adopt CSA while household size and agricultural experience negatively influenced the decision to adopt CSA. It is recommended that the Department of Agriculture, Land Reform, and Rural Development should provide CSA workshops and educational programs to farmers to enhance their knowledge and decision-making processes regarding adaptation strategies.

The global craft beer market is witnessing substantial growth, with a particular spotlight on sour beers. These unique brews are created through lactic fermentation initiated by lactic acid bacteria (LAB). However, the presence of hops, renowned for their antimicrobial properties, can pose a limitation within the realm of sour beer production. This research aims to explore and assess the potential of sour beer as a probiotic beverage. It involves a comparative analysis of the viability of Lacticaseibacillus paracasei subsp. paracasei F19 (F19) and 431 (L431) in a sour beer with an International Bitterness Unit (IBU) value of 26.65, alongside examining the ex-pression of genes such as horA, horB, horC, hitA, bsrA, and recA, which are associated with hop resistance. The study encompasses the development of two formulations of sour beers characterized by both high hop content and a robust probiotic count (8.44 – 8.77 log CFU/mL). The findings suggest that both probiotic strains of F19 and L431, are well-suited to produce sour beers with elevated hop levels, demonstrating excellent stability. Notably, the expression of genes responsible for hops resistance exhibited distinct modulation patterns among the two strains. It appears that a higher concentration of bsrA, as observed in strain L431, may be more effective in mitigating the effects of hop-related stress, potentially surpassing the combined expression of horA and bsrA. Nonetheless, further research is essential to validate this observation in gene expression. F19 and L431 emerge as promising candidates for the development of sour beers with increased hop intensity.

This study investigates the impact of brand lovemark on three customer behavioral outcomes (i.e., green brand loyalty, willingness to pay a deposit, and machine use intention) in coffee shops’ CSR practices. We used a scenario-based experimental design on CSR practices in two coffee shop brands (i.e., Starbucks and Dunkin'). The study demonstrates that consumers with a high level of brand lovemark respond more positively to CSR practices of coffee shops than do customers with a low level of brand lovemark. In addition, the interactions between brand lovemark and gender appear to be important in all three behavioral outcomes. Specifically, it confirms that men and women show different levels of behavior outcomes depending on their level of brand lovemark. Theoretical and managerial implications are also suggested with the direction for future study.

Gas turbine engines are widely used in various industries such as aviation, power generation, and marine propulsion due to their high efficiency and reliability. The combustion chamber of a gas turbine engine design contains a number of elements, including as the chamber's size and form, the fuel injection system, the ignition system, and the cooling system and it plays a critical role in the performance and efficiency of the engine. This research discusses the fabrication of a combustion chamber model for a gas turbine engine. The aim of this research is to develop a combustion chamber that is cost-effective, easily available, and can be fabricated in less time. The research covers the different types of combustion chambers used in gas turbine engines and compares their advantages and disadvantages. It then selects the best type of combustion chamber for the gas turbine engine based on its cost, availability, and fabrication time, Efficiency and high power to fuel ratio. The report also describes the fabrication process involved, including the techniques and materials used, along with safety precautions and environmental protection measures. Lastly, the research suggests future improvements and potential applications for the fabricated combustion chamber model.

As both governments and customers push for sustainable and recyclable textile products, textile companies will have to change their linear business model to a circular one. The aim of the present work is to help these companies take action by providing an update of the state-of-the-art of textile recycling technologies. Extensive desktop research was performed in order to prepare an overview of existing textile recycling technologies, their current state and prognosis, including also facilitating technologies for sorting and disintegration of textile products as well as virtual platforms that connect stakeholders and inform consumers.

Wellness tourism is a growing segment that destinations can rely on to increase tourism flows and revive underdeveloped rural areas. This study elicits tourists' preferences for wellness tourism products and the redevelopment of a wellness destination in a depopulated rural area. The re-search included 595 participants in Central Greece using on-site, face-to-face surveys. The survey data was analyzed using a two-step process. First, conjoint analysis was applied to determine the combination of wellness tourism product attributes that maximize visitors’ utility. In the second step, we elicited visitors' willingness to pay (WTP) for improvements in tourism product attributes using the contingent valuation method. Findings indicate that the combination of attributes that maximizes the preference structure of respondents includes time of visit from September to Oc-tober, duration of visit from 1 to 7 days, wellness tourism as the primary purpose of the visit, and wellness activities that contain both physical activities and training as well as spiritual and emo-tional enhancement. Using binary logistic regression, the analysis indicates that respondents are willing to pay 47.33€ per visit on average further to develop wellness tourism products in the study area. Empirical results confirmed that sustainability issues, quality, and entrepreneurship factors positively impact visitors' WTP for revitalizing wellness products. In contrast, a longer duration of stay in the area and respondents' age negatively impact their WTP. These findings suggest that structuring a customer-driven tourism product will enhance the rural destination's efforts to attract high-yield visitors and advance the rural economy. Furthermore, practical im-plications reveal that Destination Management Organizations will benefit from research results to foster targeted management plans.

This study proposes self-calibration of capacitor mismatch errors for high-resolution pipeline analog-to-digital converters (ADCs). The proposed calibration circuit recursively amplifies the capacitor mismatch error by re-utilizing a multiplying digital-to-analog converter in a pipeline stage without increasing the circuit complexity, and the amplified error voltage is converted into digital code by utilizing the remaining pipeline stages. Error correction is performed by subtracting the digital code from the ADC output during normal operation. A prototype of a 12-bit pipeline ADC is fabricated in a 0.18 µm standard CMOS process. The ADC comprises eight 1.5-bit stages, followed by a 4-bit flash ADC as the final stage; the capacitor mismatch errors in the first two pipeline stages are corrected by utilizing the proposed self-calibration technique. At a sampling rate of 30 MS/s, the measured differential and integral nonlinearities improve from +0.82/-0.75 and +1.12/-1.79 to +0.45/-0.41 and +0.47/-0.91 after calibration, respectively. Further, the measured dynamic performances improve significantly with calibration. For an input frequency of 2.09 MHz, the ADC achieves a spurious-free dynamic range (SFDR) and signal-to-noise and distortion ratios (SNDR) of 69.3dB and 63.9dB before calibration, respectively. After calibration, the SFDR and SNDR increase to 84.1dB and 68.9dB, respectively, and the effective number of bits is approximately 11.1bit. The power consumption of the ADC is 35mW under 1.8V supply, and the resulting figure of merit is 514fJ/conversion step.

Current methods for the hardening step of functional coatings over different materials imply the use of high temperatures, high energy consumption or long periods of time, which have repercussions on the speed and cost of the product. We report here a simple and low cost methodology for the functionalization of low cost stainless steel, which is modular, depending of the functionality pursued: a levelling layer for smooth the surface of the material, an “easy to clean” property, or both of them. The research is based on sol-gel coatings cured under UV light without requiring high thermal hardening processes making it applicable to plastics and other sensible materials and possessing high chemical and thermal stability. The film ensures lower processing costs, and higher rates of hardening if the adequate medium-pressure lamps are employed. This formulation is also well defined for scaling up the process, so it is possible to perform a continuous coating in large areas by employing mild processing conditions (low temperature, atmospheric pressure). In addition, the sol gel solution was fully characterized and studied in order to guarantee a long service life before deposition, with a focus on industrial applications in the domestic sector.

High temperature titanium alloys are widely used in aerospace hot parts, however, the thermal barrier temperature of 600 oC limits its service temperature. In this paper, a two-step hot-dip plating method is proposed to prepare the composite coating containing Ce on the surface of titanium alloy, which can make the oxidation resistance temperature of titanium alloy reach 800 oC The microstructure, phase composition and element distribution of Ce-containing Ti-Al-Si hot-dip coating, Ce-containing Ti-Al-Si pre-oxidation coating and Ce-containing Ti-Al-Si high-temperature oxidation coating were studied by X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS), respectively. The results show that the Ti-Al-Si hot-dip coating containing Ce is mainly composed of (Ti,Ce)(Al,Si)3 alloy phase layer, and the Ti-Al-Si pre-oxidation coating containing Ce is mainly composed of Ti-Al binary system phase layer and dense Al2O3 layer rich in CeO2. Ce in the high temperature oxidation coating of Ti-Al-Si containing Ce is mainly distributed in Ti3Al, TiAl, TiAl3+Ti5Si3 mixed phase layer and Al2O3. The addition of Ce can promote the formation of continuous Al2O3 layer, improve the uniformity of composite coating, prevent the spread of cracks, and improve the high temperature oxidation resistance of Ti-Al-Si coating.

Type 2 diabetes mellitus may be complicated with chronic complications including diabetic neuropathy (DN). Timely diagnosis is crucial in treatment and maybe reversal of this complication. C reactive protein to albumin ratio (CAR) is considered as a marker of inflammation in various diseases that characterized with acute or chronic inflammation. Since diabetic neuropathy and type 2 diabetes mellitus are also associated with chronic, low grade inflammation, we aimed to study CAR levels of type 2 diabetic subjects with diabetic neuropathy and to compare to those in patients without diabetic neuropathy. Type 2 diabetic patients presented to our institutional outpatient clinics were divided into two according to the presence of DN. Subjects with DN were listed as DN group and others were as non-DN group. Characteristics and laboratory data, including CAR, in DN and non-DN groups were compared. Median CAR of the DN and non-DN groups were 2,19 (0,2-49)% and 0,56 (0,02-5,8)%, respectively (p&lt;0.001). CAR was significantly and positively correlated with age (r=0.15, p&lt;0.001), weight (r=0.19, p=0.01), BMI (r=0.11, p=0.03), waist circumference (r=0.10, p=0.046), fasting plasma glucose (r=0.14, p=0.004), serum creatinine (r=0.25, p&lt;0.001), triglyceride (r=0.17, p&lt;0.001), and LDL-cholesterol (r=0.13, p=0.001) levels. Moreover, CAR was inversely correlated with eGFR levels (r=-0.16, p&lt;0.001). The sensitivity and specificity of CAR (when higher than 1,02%) in predicting diabetic neuropathy were 78% and 73%, respectively (AUC: 0.84, p&lt;0.001, 95% CI: 0,82-0,87). Moreover, high CAR level was an independent risk factor of diabetic neuropathy (p&lt;0.001, OR: 1.34, 95% CI: 0.48-1.62). In conclusion, elevated CAR levels could be considered as a marker of diabetic neuropathy.

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

Bacterial transformation is the essential tool for introducing foreign DNA into bacterial cells in a host of recombinant technology applications useful for biomanufacturing and drug production. Thus far, chemically competent cells remain an important enabling technology for bacterial transformation given its facile transformation approach. However, many parameters affect transformation efficiency, and there is relatively little documentation of their cross-interacting effect in the literature. This work explores the roles played by incubation time on ice, competent cell concentration, and plasmid-to-cell ratio on transformation efficiency in Escherichia coli DH5α. Results revealed that increases in incubation time improve transformation efficiency, but 2 minutes incubation still yield appreciable efficiency. On the other hand, low concentration competent cells (10⁶ CFU/mL) yielded significant improvement in transformation efficiency compared to high concentration competent cells (10⁸ CFU/mL). In terms of plasmid-to-cell ratio, higher ratio increases transformation efficiency. Overall, bacterial transformation is incompletely understood particularly in the area of cross-interacting parameters. Experiments reported here revealed the possibility of short duration transformation where lower competent cell concentration and higher plasmid-to-cell ratio could improve transformation.

Antibiotics are the most magnificent discovery of 20th century that have saved millions of lives from infectious diseases. Microbes have developed acquired antimicrobial resistance (AMR) to many drugs due to high selection pressure from increasing use and misuse of antibiotics over the years. The transmission and acquisition of AMR occur primarily via human–human interface both within and outside of the healthcare facilities. A huge number of interdependent factors related to healthcare and agriculture govern the development of AMR through various drug resistance mechanisms. The emergence and spread of AMR from the unrestricted use of antimicrobials in livestock feed has been a major contributing factor. The prevalence of AMR bacteria has attained its incongruous level worldwide and threatening global public health as silent pandemic, necessitating urgent intervention. Therapeutic options of AMR bacterial infections are limited resulting in significant morbidity and mortality with high financial impact. The paucity in discovery and supply of new novel antimicrobials to treat life-threatening AMR infections stands in sharp contrast to demand. Immediate interventions to contain AMR include surveillance and monitoring, minimizing over the counter antibiotics and antibiotics in food animals, access to quality and affordable medicines, vaccines and diagnostics, and enforcement of legislation. An orchestral collaborative action within and between multiple national and international organizations are required urgently, otherwise, a post-antibiotic era can be a real possibility than an apocalyptic fantasy for the 21st century. This narrative review highlights on the basis, mechanisms and factors in microbial resistance and key strategies to combat antimicrobial resistance.

Food demand and food supply have been heavily affected by Covid-19 pandemic. To understand changes in households’ behavior related to the pandemic, we investigate the willingness to pay for local organic apples pre- and during Covid-19. Besides, we assess whether the changes occurred within the family, estimating also separate models for the two members of the couple. Our findings show that respondents show a positive price premium for local organic apples whose consumption helps reducing the environmental costs associated with food production. The median estimated values during the pandemic range from 34% to 250%. Overall, respondents show a positive mean willingness to pay which increase with the pandemic. The socio-economic variables are the most important in explaining the willingness to pay, while the behavioral variables have more heterogeneous results even if the lifestyle and the request for information through the label are important variables. The pandemic tends to narrow the gaps in preferences between members of the couple. In conclusion, the local and organic dimension is embodied in the short chain in which knowledge and trust in the producer are crucial elements in the consumer's choices.

Drought stress is a major production constraint in crops globally. Crop wild relatives are important source of resistance and tolerance for both biotic and abiotic stresses, respectively. A breeding program was initiated to introgress drought tolerance in sunflower through hybridization between the wild species Helianthus argophyllus and the cultigen pool of H. annuus. Selection was carried out in the F2 to F5 segregating populations for high cuticular waxes, smaller leaf area, single heading and high oil content. The selected F5 breeding lines were compared with non-adapted elite sunflower germplasm in a replicated randomized complete block research project using different water treatments comparing fully irrigated (T0), with 75 (T1), 50 (T2) and 25% (T3) irrigation treatments. The comparison between the two types of germplasm showed that drought tolerant breeding lines had comparatively lesser decreases in leaf area, shoot weight and root shoot ratio 10 under the various drought treatments. Leaf area of the drought selected F5 lines were smaller than that of the elite germplasm under controlled irrigated treatments, but they maintained their leaf area under the drought treatments. Several drought resistant promising lines D-2, D-5, and D-27 were identified and showed high leaf area, great root length and increase root to shoot ratio under the highest stressed treatments (T3). Some of the lines could be directly used for the development of drought tolerant hybrids. Combining ability test indicated D-27 (F7) as good general combiner for seed yield plant−1 and oil contents when mated with male line RSIN.82. These hybrids could help to minimize seed yield losses due to water stress and to achieve profitable cultivation of sunflower in 18 arid regions of Pakistan.

In the context of Covid-19 virus containment, there is a lack of acceptance of preventive measures in the population. The present work investigated which factors influence the belief in of scientific propositions compared belief in conspiracy theories. The focus here was on the determinants of conspiracy beliefs in the context of Covid-19 related media content. Using an online questionnaire (N = 175), results indicate that scientific compared to conspiracy theoretical media content led to higher acceptance. Furthermore, Need for Cognition (NFC-K), a conspiracy theoretical worldview (CMQ), and openness to experience (NEO-FFI) were positively associated with conspiracy beliefs derived from Facebook postings. In addition, a conspiracy theoretical worldview was negatively associated with belief in scientific media content. Furthermore, agreeableness was unrelated to conspiracy beliefs, although it was positively associated with conspiracy theoretical worldview. The results imply promising persuasion strategies for reducing conspiracy theoretical beliefs and to increase the acceptance of preventive measures.

Enteropathogens, namely Salmonella and Campylobacter, are a concern in global public health and have been attributed in numerous risk assessments to a poultry source. During the last decade a large body of research addressing this problem has been published. The literature reviewed contains review articles on certain aspects of poultry production chain, however in the past decade there hasn’t been a review on the through production chain, farm to fork, production of poultry. This review, a pool of 514 articles were selected for relevance via a systematic screening process (from >7500 original search articles). These studies identified a diversity of management and intervention strategies for the elimination or reduction of enteropathogens in poultry production. Many studies were laboratory or limited field trials with implementation in true commercial operations being problematic. Entities considering using commercial anti-enteropathogen products and interventions are advised to perform an internal validation and fit for purpose trial as Salmonella and Campylobacter serovars and biovars may have regional diversity. Future research should focus on non-chemical application within the processing plant and how synergistic through chain intervention may contribute to reducing the overall carcass burden of enteropathogen, coupled with increased consumer education on safe handling and cooking of poultry.

Extensive in-situ resource utilisation (ISRU) will be essential to enable long-duration stays on Luna and Mars and reduce reliance on resupply from Earth. Early development of ISRU technologies has focused on standalone capabilities for specific targets related to life support and ascent propellant. An unexplored opportunity remains for greatly expanding the scope of materials that can be supplied by ISRU, and for integrating various technology platforms into a larger system. Recent advances in power-to-X technology aimed at decarbonising the global economy have made it possible to drive key chemical processes using electricity with small-scale, modular reactor. This paper proposes a vision for an integrated system of ISRU processes based on power-to-X technology to produce oxygen, hydrogen, water, methane, polymers, metal alloys, and synthetic fertilisers, using Martian regolith, atmosphere, and ice. A ‘building block’ strategy is adopted to convert raw materials into versatile intermediaries, which can then be combined to form essential products. A wider range of raw materials are available on Mars compared to Luna, suggesting greater opportunity for ISRU deployment to compensate for the greater time and cost requirements for a Mars resupply mission.

Current commitments by European governments seek to improve energy consumption as a means to reduce carbon emissions from building stock by 2050. Within such context, retrieving reliable three-dimensional contours from point clouds becomes an important step in developing facade retrofitting solutions since facade retrofitting projects often make use of as-built 3D models to help reduce inaccuracies by narrowing interpretation and measurement errors. This work aims to provide a method that uses topology-based parametric modelling for reconstructing building envelopes from point clouds. Through a semi-automated process that gives permanent visual feedback, the user adjusts parameters to custom standards of acceptability. A solution under the form of a Grasshopper definition delivers building envelope 3D contours in various file formats as a means for increasing interoperability. The main contributions of this work consist of a parametric reconstruction workflow capable of solving building topology for retrieving 3D contours, a strategy to bypass point cloud occlusion, and a strategy for converting those contours into an IFC model directly from the parametric modelling environment.

Autonomous systems require identifying the environment and it has a long way to go before putting it safely into practice. In autonomous driving systems, the detection of obstacles and traffic lights are of importance as well as lane tracking. In this study, an autonomous driving system is developed and tested in the experimental environment designed for this purpose. In this system, a model vehicle having a camera is used to trace the lanes and avoid obstacles to experimentally study autonomous driving behavior. Convolutional Neural Network models were trained for Lane tracking. For the vehicle to avoid obstacles, corner detection, optical flow, focus of expansion, time to collision, balance calculation, and decision mechanism were created, respectively.

The study is an attempt to enquire into the preference of undergraduate students, after a considerable and over a year-long experience with Online Teaching and Learning (OTL), under the emergency preventive measure of switching from the traditional face-to-face classes to online. The study followed an exploratory approach, with a quantitative survey followed by a qualitative one, and a convenient sampling method to collect responses from a substantial sample size. The study is positioned after more than a year of remote classes by the undergraduate student, and hence represents highly experienced reflections and preferences from these students, as compared to other studies conducted last year. The study has profound implications in considering, and questioning, the importance of on-campus classes, and significance of the physical presence of a tutor in the class, and its effect on the learning experience of undergraduate students.

The wide adoption of the recently coined fog and edge computing paradigms alongside conventional cloud computing creates a novel scenario, known as the cloud continuum, where services may benefit from the overall set of resources to optimize their execution. To operate successfully, such a cloud continuum scenario demands for novel management strategies, enabling a coordinated and efficient management of the entire set of resources, from the edge up to the cloud, designed in particular to address key edge characteristics, such as mobility, heterogeneity and volatility. The design of such a management framework poses many research challenges and has already promoted many initiatives worldwide at different levels. In this paper we present the results of one of these experiences driven by an EU H2020 project, focusing on the lessons learnt from a real deployment of the proposed management solution in three different industrial scenarios. We think that such a description may help understand the benefits brought in by a holistic cloud continuum management and also may help other initiatives in their design and development processes.

RNA editing involves the insertion, deletion or substitution of single nucleotides within a RNA molecule, without altering the DNA sequence. Adenosine to inosine (A-to-I) editing consists of an RNA modification where single adenosines along the RNA sequence are converted into inosines. Such a biochemical transformation is catalyzed by enzymes belonging to the family of adenosine deaminases acting on RNA (ADARs) and occurs either co- or post-transcriptionally. Initially, the A-to-I RNA editing phenomenon was discovered and studied in messenger RNAs (mRNAs), where it can influence RNA splicing and cause the recoding of codon sequences. The employment of more powerful, high-throughput detection methods has recently revealed that A-to-I editing widely occurs in non-coding RNAs, including microRNAs (miRNAs). MiRNAs are a class of small regulatory non-coding RNAs (ncRNAs) acting as translation inhibitors, known to exert relevant roles in controlling cell cycle, proliferation, and cancer development. Indeed, a growing number of recent researches have evidenced the importance of miRNA editing in cancer biology by exploiting various detection and validation methods. Herein, we briefly overview early and currently available A-to-I miRNA editing detection and validation methods and discuss the significance of A-to-I miRNA editing in human cancer.

Stakeholder input into the decision-making process when developing public health programs and policies is crucial. This article presents an innovative approach, involving online participation with a wide group of stakeholders located in different geographic locations, for policy consensus by research methodology. The results of the project have been used to propose assumptions regarding a strategy for preventing blood-borne diseases in Poland. The research was conducted iteratively using a multi-stage qualitative methodology to explore risk assessment involving blood-borne infections. The final output of the entire project is a list of key problems/challenges and solutions associated with medical and nonmedical services that are connected to the breakage of tissue continuity. Qualitative research is rare in risk assessment as priority is usually given to statistical data and end-points (quantitative studies ). Statistical data on health risk allows to assess the health implications, while the methodology applied also allowed diagnosis of the processes leading to these effects. In addition to policy preparation for blood-borne illnesses, the methodology employed in the study can also be used to successfully explore other areas of public health policy decisions.

This short note proposes a national Geographic Information System (GIS) - based health infrastructure to deal with epidemics and pandemics. Currently, there is no pan-India health infrastructure available that can compile, update, and report the spread of epidemic diseases. It not only curtails the opportunity of finding the real-time data on the spatial distribution of a disease but prevents one to inquire into the causes of the disease through epidemiological analysis. The proposed infrastructure in this study is a pan-India one and can broadly be divided into two parts, hotspot mapping and accessibility to services. In the first part, hospitals are proposed to act as nodes of data collection, sending data to a national GIS portal. This portal shall have the capabilities of plotting the data using map rendering services such as Google and Bing Maps. This way, hotspots can be visualized in no time, benefitting the government and common citizenry alike. The second part deals with the accessibility of citizenry to a wide range of services, i.e., healthcare services, grocery outlets, emergency services, baby food, and many other essential services of the day to day life. In order to implement this, we propose that the government need to enforce a mandatory submission of locational coordinates of all Goods and Services Tax (GST) enrolled service providers. Once the coordinates are submitted, the government can effectively control the opening and closing of services and inform the citizenry at the same time. The proposed infrastructure is going to help deal with the extraordinary situations during epidemic and pandemics similar to what the world is currently facing in the form of Corona Virus Disease 2019 (COVID-19). Furthermore, the infrastructure can be scaled up or down as per the spread of a disease. The health-GIS platform proposed in this concept paper, shall help India in controlling and managing the epidemic more efficiently.

Despite great strides being achieved in improving cancer patients’ outcomes through better therapies and combinatorial treatment, several hurdles still remain due to therapy resistance, cancer recurrence and metastasis. Drug resistance, culminating in relapse and metastatic disease continue to be associated with fatal disease. Cancer stem cells (CSCs) are a subpopulation of cancer cells known to be resistant to therapy and cause metastasis. Whilst the debate on whether CSCs are the origins of the primary tumor rages on, CSCs have been further characterised in many cancers with data illustrating that CSCs display great abilities to self-renew, withstand therapies due to enhanced epithelial to mesenchymal (EMT) properties, enhanced expression of ABC membrane transporters, activation of several survival signaling pathways and increased immune evasion DNA repair mechanisms. CSCs also display great heterogeneity with the consequential lack of specific CSC markers presenting a great challenge to their targeting. In this updated review we re-visit CSCs within the tumor microenvironment (TME) and present novel treatment strategies targeting CSCs. These promising strategies include targeting CSCs-specific properties using small molecule inhibitors, immunotherapy, microRNA mediated inhibitors, epigenetic methods as well as targeting CSC niche-microenvironmental factors and differentiation. Lastly, we present recent clinical trials undertaken to try to turn the tide against cancer by targeting CSC-associated drug resistance and metastasis.

Sharing the same raw material, recycling and composting are in direct conflict with incineration of municipal solid waste in combined heath and power plants. Indeed, waste-to-energy plants in regions with high recycling rates import urban waste from other countries to use otherwise unused capacity, and raise revenues. Using the case of Italy’s second largest and economically most developed region, I discuss the economic viability of municipal solid waste incineration to produce electricity and heath in the context of the increasing role of electricity production from renewable energy sources as well as of the emerging mass-scale uptake of bioplastics. Four lessons and three guidelines aimed to local authorities and policy makers emerge from the present study.

This paper aims to investigate the criteria of behaviour of certain type of third order neutral generalized difference equations with distributed delay. With the technique of generalized Riccati transformation and Philos-type method, some oscillation criteria are obtained to ensure convergence and oscillatory solution of suitable example is listed to illustrate the main result.

Sensory evaluation has been widely applied in assessing the quality of many consumer products that directly serve human needs such as food, beverages, clothing, etc. This paper first examined the inherent deficiencies in this approach, due mainly to the essentially subjective nature of human sensory preference. It then argued that instinctively designating certain materials attributes as sensory perceptions is unnecessary; considering every scientific concept is in essence the processed results of our sensory organs/brains, i.e., all quantities were initially human perceptions. Scientific advances have inevitably generated gradual transformation of such human perceptions as warmth and heaviness into objective parameters measurable in physical quantities like temperature and kilograms. Then using existing successful examples, it demonstrated firmly how the sensory attributes can be assessed by more reliable instrumental methods, and envisioned the key steps to turning a perception into scientifically measurable parameter(s).

Pain is a major problem in sick newborn infants, especially for those needing intensive care. Pharmacological pain relief is the most commonly used but may be ineffective, have side effects, including long-term neurodevelopmental sequelae. The effectiveness and safety of alternative analgesic methods are ambiguous. The objective is to review the effectiveness and safety of non-pharmacological methods of pain relief in newborn infants and to identify those that are the most effective. PubMed and Google Scholar were searched using the terms: ‘infant’, ‘premature’, ‘pain’, ‘acupuncture’, ‘skin to skin contact’, ‘sucrose’ ‘massage’, ‘musical therapy’ and ‘breastfeeding’. We included 24 studies assessing different methods of non-pharmacological analgesic techniques. Most resulted in some degree of analgesia but many were ineffective and some were even detrimental. Sucrose, for example, was often ineffective but more effective than music therapy, massage, breast milk (for extremely premature infants) or non-invasive electrical stimulation acupuncture. There were also conflicting results for acupuncture, skin to skin care and musical therapy. Most non-pharmacological methods of analgesia provide some modicum of relief for preterm infants but none are completely effective and there is no clearly superior method. Study is also required to assess potential long-term consequences of any of these methods.

Glaucoma is a disease associated with retina of eye. Presently, millions of human being is suffering from this disease. Early detection of these diseases can save the people from blindness. Therefore, various methods have been developed for its detection. In this paper, we have studied the reported methods and summarized their performance in terms of accuracy of detection.

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

Revitalization of open water bodies into recreational areas are becoming widely popular in many parts of Sri Lanka. Understanding community perception and expectation on recreational development have important policy and cost-effectiveness implications. This paper explores the public perspectives on development, conservation and value of the open water recreational development at Diyatha Uyana and surrounding area. Contingent Valuation Method has been applied to estimate peoples’ Willingness To Pay for recreational spaces in the selected area. A total of 300 residents from different socioeconomic backgrounds were selected randomly for the study. Enjoying peace and relaxation, taking children to play and breath clean air were mentioned as most important aspects of open water body areas. More frequent visits occur to enjoy peace and relaxation, breath clean air and enjoy the natural landscape. Almost all the participants were agreed upon conserving open water body areas in urban settings. Willingness to pay was significantly associated with income and occupation status. It yielded a monthly average payment of Rs.446.93 per household for another five years’ time. The limited budget was the main reason for not willing to pay. This paper is significant as there is no contingent valuation method study has been carried on water body development in Sri Lanka.

Addressing non-unions involves stabilizing the affected area through osteosynthesis and improving bone biology using bone grafts. However, there is no consensus on the optimal treatment method. This study aims to compare outcomes of non-union revision using conventional treatment methods (metal hardware ± graft) versus osteosynthesis with the human, allogeneic cortical bone screw (Shark Screw®). Thirty-four patients underwent conventional treatment, while 28 cases received Shark Screws®. Patient demographics, bone healing, time to bone healing, and complications were assessed. Results revealed a healing rate of 96.4% for the Shark Screw® group, compared to 82.3% for the conventionally treated group. The Shark Screw® group exhibited a tendency for faster bone healing (9.4±3.2 vs. 12.9±8.5 weeks, p=0.05061). Hardware irritations led to six metal removals in the conventional group versus two in the Shark Screw® group. The Shark Screw® emerges as a promising option for personalized non-union treatment in the foot, ankle, and select lower leg cases, facilitating effective osteosynthesis and grafting within a single construct, promoting high union rates, low complications, and a rapid healing process.

Electrifying off-grid and isolated islands in the Philippines remains one of the challenges that hinders community development. One of the solutions seen to ensure energy security, expand energy access and promote a low carbon future in this isolated islands is the use of renewable energy sources. This study wishes to determine the nearshore wave energy resource during monsoon seasons in Cuyo Island using a 40-year wave hindcast and 9-year on-site wind speed data to develop high resolution wave energy model using SWAN wave model, and assessed its annual energy production through matching with wave energy devices. Results shows that average significant wave height (Hs), peak period (Tp) and wave power density (Pd) during northeast monsoon are Hs = 1.35 m, Tp = 4.79 s and Pd = 4.05 kW/m respectively, while southwest monsoon which is sheltered by the mainland resulted to a lesser outcome, Hs = 0.52 m, Tp = 3.37 s and Pd = 0.34 kW/m. While the simulated model was observed to overestimate the wave energy resource (Bias = 0.398, RMSE = 0.54 and SI = 1.34), it has a strong relationship with the observed values (average r = 0.9). Its annual energy production is highest at Station 5, with AEPWaveBouy = 43.761 MWh, AEP-Pelamis = 216.786 MWh and AEPWave Dragon = 2462.66 MWh. At present, the minimum requirement for a wave energy development to be feasible is 5 kW/m, which in this case, Cuyo Island falls short, but with the continuous evolution of wave energy converters, applications on milder re-sources will soon materialized.

This article presents a unique set of voltage and current data from a public building and acquired using a hybrid measurement solution that combines Python and Grafana. The transversal purpose consists of contributing to the community with a vision of the quality of the supply more oriented to the monitoring of the state of the network, providing a more realistic vision, which allows a better understanding, and the adoption of the best decisions to achieve the efficient energy management and thus optimize the operation and maintenance of power systems. The work focuses on higher order statistical estimators that, combined with exploratory data analysis techniques, improve the characterization of the shape of the stress signal. These techniques and data, together with the acquisition and monitoring system, present a unique combination in the line of low-cost measurement solutions. It also incorporates the underlying benefit of the contribution to industrial benchmarking. The paper also includes a computational comparison between Python and LabVIEW to elicit the performance of the measurement solution.

Computation of Common Middle Point seismic sections and their subsequent time migration and diffraction imaging provides very important knowledge about the internal structure of 3D heterogeneous geological media and are key elements for successive geological interpretation. Full-scale numerical simulation, that computes all single shot seismograms, provides a full understanding of how the features of the image reflect the properties of the subsurface prototype. Unfortunately, this kind of simulations of 3D seismic surveys for realistic geological media needs huge computer resources, especially for simulation of seismic waves’ propagation through multiscale media like cavernous fractured reservoirs. In order to significantly reduce the query of computer resources we propose to model these 3D seismic cubes directly rather than the shot-by-shot simulation with subsequent CMP stacking. To do that we modify the well known "exploding reflectors principle" for 3D heterogeneous multiscale media by use of the finite-difference technique on the base of grids locally refined in time and space. To be able to simulate realistic models and acquisition we develop scalable parallel software, which needs reasonable computational costs. Numerical results for simulation of Common Middle Points sections and their time migration are presented and discussed.

This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power system based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid currents synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage control based on ISMC theory is proposed in order to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid currents synchronization. Numerical simulations are performed in Matlab/SimulinkTM environment in order to evaluate the proposed control strategy. In comparison with conventional control scheme, the developed control strategy provides an accurate MPP tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under climatic conditions variations. Moreover, the transfer of the extracted power into the grid is achieved with high quality.

Rapid development and deployment of vaccines greatly reduced mortality and morbidity during the COVID-19 pandemic. The most widely used COVID-19 vaccines approved by national regulatory authorities require intramuscular administration. SARS-CoV-2 initially infects the upper respiratory tract where the infection can be eliminated with little or no symptoms by an effective immune response. Failure to eliminate SARS-CoV-2 in the upper respiratory tract results in lower respiratory tract infections that can lead to severe disease and death. Presently used intramuscularly administered COVID-19 vaccines are effective in reducing severe disease and mortality but are not entirely able to prevent asymptomatic and mild infections as well as person to person transmission of the virus. Individual and population differences also influence susceptibility to infection and the propensity to develop severe disease. This article provides a perspective on the nature and the mode of delivery COVID-19 vaccines that can optimize protective immunity in the upper respiratory tract to reduce infections and virus transmission as well as severe disease.

Due to the convenience of implementing without additional transmitter, radar communication integrated systems using conventional communication signals have become an effective means of monitoring unmanned aerial vehicles and other aircraft. However, the non-ideal radar signal form causes the strong signal to cover the weak signal, and the clutter suppression is required to expose the target. As the target signal is extremely low, and the performance of conventional clutter suppression methods is limited, the residual clutter remains after the time-varying clutter is suppressed, which leads to many false alarm points on the processed RD spectrum. The two-dimensional distribution of these false alarms in range-Doppler is very similar to the target and difficult to be distinguished, which seriously affects the target detection and tracking. To reduce false alarm points and improve the performance of target detection, the difference of spatial-temporal stationarity between target signal and clutter in a short time is discussed in this paper, a radar false alarm suppression method based on target spatial-temporal stationarity is proposed by using the difference of stationarity between target signal and false alarm points in range, Doppler, energy and azimuth. In this algorithm, to ensure the short-time stationarity of the target, the RD spectrum of sub-frames with short time interval is obtained by using the sliding matching filtering method and extract the peak points. Then, the Mahalanobis distance between the peak points of each sub-frame is used to eliminate false alarm points. Finally, false alarm points are further eliminated through the target tracking and retain the real target information, so as to improve the radar target detection performance. The simulation experiments show that this method can eliminate more than 90% false alarms points while maintaining the detection performance of the target. The processing of actual data in the field experiment shows that the after suppression false alarm by this algorithm can obtain more ideal target detection results, and realize the tracking of the UAV and other aircraft track.

In recent times, the application areas of unmanned aerial vehicles (UAVs) are expanding, and autonomous functions are becoming increasingly prominent, eliminating the need for remote pilot control. Certain applications require the drone to use a docking station autonomously, even for wireless charging. This involves performing autonomous takeoff and landing, where high preci-sion is demanded. These maneuvers can be significantly influenced by environmental factors. The effectiveness of the precision landing function of the DJI Mavic 2 Pro UAV in strong winds is in-vestigated in this article based on experimental measurements conducted outdoors. New findings on the precision landing capabilities of the DJI Mavic 2 Pro UAV are presented in this paper, par-ticularly under windy conditions. The efficiency of precision landing is compared in cases when the precision landing function is enabled versus when it is disabled. It is investigated whether there is a statistically significant difference between the two landing modes in strong winds and it is examined whether the DJI Mavic 2 Pro can perform precision landing on a surface of a specific size in windy conditions. This helps to predict the suitability of the DJI Mavic 2 Pro for precise landing and wireless charging at a docking station in strong winds and high gusts.

Fusing data from many sources helps to achieve higher results of analysis. In this work, we present a new algorithm to fuse data from multiple cameras with data from multiple lidars. This algorithm was developed to increase the sensitivity and specificity of autonomous vehicle perception systems, where the most accurate sensors measuring the vehicle’s surroundings are cameras and lidar devices. Perception systems based on data from one type of sensor do not use complete information and have lower quality. The camera provides two-dimensional images; lidar produces three-dimensional point clouds. We developed a method for matching pixels on a pair of stereoscopic images using dynamic programming inspired by an algorithm to match sequences of amino acids used in bioinformatics. We improve the quality of the basic algorithm using additional data from edge detectors. We also improve the algorithm performance by reducing the size of matched pixels determined by available car speeds. We perform point cloud densification in the final step of our method, fusing lidar output data with stereovision output. We implemented our algorithm in C++ with Python API, and we provided the open-source library named Stereo PCD. This library very efficiently fuses data from multiple cameras and multiple lidars. In the article, we present the results of our approach to benchmark databases in terms of quality and performance. We compare our algorithm with other popular methods.

Toll plaza optimization is essential for improving traffic flow and easing congestion on road networks. This study aims to suggest and assess potential optimization solutions for the Peshawar toll plaza, considering variables like traffic volume, toll-collecting effectiveness, and customer facilitation. Different resources are used for data collection, like the National Highway Authority of Pakistan. Physical data is collected from the established Toll Plaza of Peshawar, along with the development of each line. The goal of this study is to suggest and assess potential optimization solutions for the Peshawar toll plaza, considering variables like traffic volume, toll-collecting effectiveness, and customer happiness. The analysis of present traffic patterns, the detection of bottlenecks, and the creation of plans to ease congestion and enhance overall traffic flow are all part of the optimization process. The approaches used in this study include data analysis, simulation, and traffic modeling. PTV VISSIM is software for transportation planning, design, and analysis. The simulations consider various conditions, such as variable traffic volumes, toll collection methods, and lane configurations. When comparing the different optimization strategies, performance indicators like trip time, latency, and queue length are utilized to determine which approach is practical. Waiting time Vs. Existing each lane, etc, is explained. In the end, comparing queue lengths and throughput across different lane scenarios shows that maximizing throughput with existing lanes yields up to 45% improvement with E-tag lanes, 40% with existing E-tag lanes, 38% with E-tag plus additional toll and cash lanes, 32% with three cash lanes, and 28% with two E-tag lanes. Failure to regularly monitor and adjust the existing lane pattern scenario based on traffic patterns can lead to queues being 20% longer. Without proactive evaluation and optimization, there is a potential 63% opportunity for queue length improvement

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles has been discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we have compared the key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For the energy storage systems employing ultra capacitors, we have presented the characteristics such as cell voltage, cycle life, power density and energy density. Furthermore, we have discussed and evaluated the interconnection topologies for the existing energy storage systems. We have also discussed the hybrid battery-flywheel energy storage system as well as the mathematical modeling of the battery-ultracapacitor energy storage system. Toward the end, we have discussed energy efficient powertrain for hybrid electric vehicles.

A novel technique suitable for propulsion of small unmanned aerial vehicles (UAV) is discussed in this paper. This approach utilizes the rotational energy of airborne gyro rotors and converts it into translational propulsion for the vehicle. The energy conversion is achieved by generating precisely directed centrifugal force pulses through short-duration rotor unbalances. The accurate control of the timing and magnitude of these unbalances is crucial for successful propulsion generation. Our first-order theory of controlled unbalance propulsion (CUP) predicts the potential for achieving high translational accelerations and vehicle velocities up to orbital levels. Power saving levitation of UAVs can be attained. In this paper, we provide traceable evidence that pulsed centrifugal propulsion is based on well-established laws of physics and can be realized using state-of-the-art technologies.

In-wheel motor vehicles are gaining attention as a new type of electric vehicle due to their efficient power units located inside each wheel hub. However, they are more susceptible to wheel resonance due to the increase in unsprung mass caused by the motor's weight. This can result in decreased both the ride comfort and driving stability. To resolve this issue, this study aims to apply an optimal switching controller with a semi-active n actuator; magnetorheological (MR) damper. For the implementation of the optimal switching controller, a road type classification is also carried out. An acceleration sensor is used for road type classification, and control logics include a ride comfort controller; the linear quadratic regulator (LQR _Paved Road) and a wheel motion controller (LQR_Off Road) for improved driving stability. For paved roads, the LQR_Paved Road control input is applied to the MR damper. However, if a road type prone to wheel resonance is detected, the control logic switches to the LQR_Off Road. During the transition, a weighted average of both LQR_ Paved Road and LQR_Off Road control input is applied to the actuator. Computer simulations are undertaken to evaluate vibration control performance, including the ride comfort and driving stability at various road profiles.

This work aims to study and analyze a hybrid power system for electric vehicles consisting of a dual low and high-rate lithium battery block and a fuel cell. In this configuration, the high-rate lithium battery powers the electric vehicle in high power demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads and the fuel cell supplies energy at intermediate power demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency since every power unit operates optimally depending on driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cell shows an efficiency improvement of 31.4% for the hybrid dual battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study bases on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell and a high rate lithium battery produces a 29 % power gain.

The automotive industry is continuously developing to meet the needs of users in terms of efficiency and convenience. The Thailand government has set a policy for Thailand to be a hub for the production of electric vehicles and key components in the region, with a target to produce electric and zero-emission vehicles by 2030. This article is an example of communication in an electric vehicle system. The CAN Bus system is a communication system in electric vehicles that can receive and send communication data via CAN-Hight/Low lines designed for vehicles. CAN Bus is a standard communication system supported by global organizations and used in modern automotive systems. The design of the communication system in electric vehicles uses MRS Developers Studio software to help write programs to receive and send data and prioritize the importance of the received data. The system consists of communication examples studied, such as pressing the start button, turning on/off the headlights, turning on/off the turn signal, turning on/off the brake light, turning on/off the emergency light, sending the horn signal, sending the signal to shift forward/backward, and tuning the motor gear system. From the communication examples mentioned, the communication will be a prototype transport set for small electric vehicles under the scope of the lithium battery energy storage system, NMC type, size 72 V 25 Ah, to test the use, efficiency, and stability in CAN Bus communication up to 1000 times.

This paper presents a novel real time control strategy on four-wheel independent steering system for electric vehicle with stepper motors using neural networks combined with fuzzy logic. The control of the four wheels is based on a variation of Hopfield Neural Network (VHNN) method, in which the input is the error of each steering motor and the output is processed by a hyperbolic tangent function (HTF) feeding the fuzzy logic controller (FLC), which ultimately drives the stepper motor. The whole system is made up of the four aforementioned blocks where they work in sync and inseparable from each other with the common goal of driving all the steering stepper motors at the same time. Simulation results demonstrate that the proposed control method has strong robustness and practicability under different angles and speeds.

The use of unmanned aerial aircrafts (UAVs) is governed by strict regulatory frameworks that prioritize safety. To guarantee safety, it is necessary to acquire and maintain situational awareness (SA) throughout the operation. Existing Canadian regulations require pilots to operate their aircrafts in visual line-of-sight. Therefore, the task of acquiring and maintaining SA primary falls to the pilots. However, the development of aerial transport is entering a new era with the adoption of a highly dynamic and complex system known as advanced air mobility (AAM), which involves UAV operating autonomously beyond visual line-of-sight. SA must therefore be acquired and maintained primarily by each UAV through specific technologies and procedures. In this paper, we review these technologies and procedures in order to decompose the SA of the UAV in the AAM. We then use the system modeling language to provide a high-level structural and behavioral representation of the AAM as a system having UAV as its main entity. In a case study, we analyze one of the flagships UAVs of our industrial partner. Results show that this UAV doesn’t have all the technologies and methodologies necessary to achieve all the identified SA goals identified for the safety of the AAM. This work is a theoretical framework intended to contribute to the realization of the AAM, and we also expect to impact the future design and utilization of UAVs.

This paper develops feasible control strategies and associated system responses to bring an autonomous front-axle bicycle robot from specified initial conditions to final conditions such that a specific performance index is minimized. To solve the problem, the following approach is used: The feasible controls derived from the normal equations of optimality are substituted into the state and the costate systems and form a combined control-free state-costate system which is vectorized to enable and ease the application of a numerical method. A computer program written in Matlab computer programming language, codes a fourth-order Runge-Kutta numerical method and then solve the combined state-costate system of ordinary differential equations. The obtained results are the feasible bicycle robot trajectory, the feasible state functions, the feasible costate functions and the feasible control functions. Associated Computational Simulations are designed and provided to persuade on the effectiveness and the reliability of the approach.

This paper describes research on a unique propulsion system design for a low-speed Biomimetic Unmanned Underwater Vehicle (BUUV). It is biomimetic in the sense that it mimics the movement of aquatic organisms. The undulating propulsion system has numerous advantages over the rotary impeller and is becoming more popular in underwater robotics. The analysis of an artificial seal’s propulsion system with two tail fins is described here. The contrast between the previous undulating propulsion system and the new one is detailed using mathematical analysis and experimental data. The experimental comparison was carried out on a laboratory test stand equipped with specialist sensor equipment to determine the energy efficiency of various types of propulsion systems. Due to a patent procedure, the innovative propulsion system presented in this work has never been published previously. The fins have extra joints, which is the subject of patent claims. The extra joint is intended to improve energy efficiency and reduce fatigue wear on the fins.

Vehicle routing is a critical factor in municipal solid waste (MSW) collection planning and operations. Poor routing can introduce inefficiencies and cause targeted levels of services or performance to be missed irrespective of the level of resource application. Trial and error approaches have been proven to be not the best in the planning and prediction of expected performance. This study explores various Geographic Information System (GIS) tools and analysis techniques, and how they can be applied to optimizing vehicle routes in light of challenging site conditions. Using Adentan West residential area, suburb of Accra Ghana as a case study, current performance of the trial and error method was measured and a GIS computer model was used to evaluate various optimization scenarios to determine the level of savings that can be made. Field measurements were taking with Global Positioning System (GPS) devices for waste collection activities in areas with varying characteristics and conditions, and data analysed for one selected vehicle operating four days per week. It was found that, for a scenario where only the bin collection order was optimized while route selection was restricted by the ArcGIS Network Analyst, 2.6% of travel distance and 2.21% of travel time were saved. For the second scenario where only the route selection was optimized while order of bin collection was restricted, 4.1% and 1.5% of travel distance and time respectively were saved. For a third scenario where both the order of collection and route selection were together optimized, 10.9% and 3.7% of travel distance and time respectively were saved. Lastly, by regrouping all the bins for daily collection, 4.5% and 1.2% of travel distance and time respectively were saved. The results demonstrated that there is always room for optimization of solid waste collection routing irrespective of site constraints and other challenges that the nature of bin distribution pose to drivers. In developing countries like Ghana, where there is high demand for services in the face of limited road network access, application of GIS in optimization of routes will guide providers in planning and subsequently make more savings in fuel consumption, vehicle maintenance and cost of man-hours.

Human detection from Unmanned Aerial Vehicles (UAV) is gaining popularity in the field of disaster management, crowd counting, people monitoring. Real time human detection from UAV is a challenging task, because of many constraints involved. This study proposes a system for real time detection of humans on videos captured from UAVs addressing three of these constraints namely, flying height, computation time and scale of viewing. The proposed method integrated an android application with a binary classifier based on Haar-features to automatically detect human / non-human class from UAV images. The video frames were parsed and detected humans from image frames were geo-localized and visualized on Google Earth. The performance was evaluated for geo-localization accuracy, computation time and detection accuracy, considering human coverage – pixel size relationship for various heights and scale factor. Based on flying height - human size relationship and tradeoff between detection accuracy vs computation time, the study came up with optimal parameters for OpenCV’s cv2.cascadeClassifier. detectMultiScale function. This paper establishes a strong ground for further research relating to real time human detection from UAV.

Over the past few decades, aircraft Ground Handling Operations (GHO) have been investigated by numerous researchers. Some aspects of GHO have been more focused on than others due to their importance in the GH processes. For instance, GHO performance has been tackled from different perspectives while workers and vehicles allocation suffer from the lack of research in the area. This paper is a literary review of the research that has been conducted in different areas of GHO. It sheds light on GHO performance, resource allocation and scheduling, operations scheduling, vehicle routing, and workers and vehicles allocation.

The enormous growth in the penetration of electric vehicles (EVs), has laid the path to advancements in the charging infrastructure. Connectivity between charging stations is an essential prerequisite for future EV adoption to alleviate users’ “range anxiety”. The existing charging stations fail to adopt power provision allocation and scheduling management. To improve the existing charging infrastructure data based on real-time information and availability of reserves at charging stations could be uploaded to the users to help them locate the nearest charging station for an EV. This research article focuses on an a interactive user application developed through SQL and PHP platform to allocate the charging slots based on estimated battery parameters, which uses data communication with charging stations to receive the slot availability information. The proposed server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on road due to battery drain out. The proposed model is implemented using a low-cost microcontroller and the system etiquette tested.

This paper examines some of the largely neglected areas of opportunity to utilize skeletal space structure systems in support of modular, industrialized, economical, sustainable and digital future of the construction industry. In this context, the feasibility of future use of skeletal space structures is studied for a few classes of engineering structures, namely, residential apartment buildings, and offshore platforms, along with their suitability for reconstruction, renovation, modernization and retrofit of damaged buildings and urban areas of cultural heritage significance. Finally, the particulars of lean project management of space structures are discussed with emphasis on engineering and economic factors, production management, environmental aspects, quality management, and reliability, maintainability and sustainability considerations. This article concludes that skeletal space structures can fulfil many of the essential construction requirements of modern societies, especially those facing environmental challenges, all while allowing for design flexibility and mass customization.

In this paper, we study the performance of various deep reinforcement learning algorithms to enhance the energy management system of a microgrid. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a set of thermostatically controlled loads, a set of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate among the different flexible sources by defining the priority resources, direct demand control signals, and electricity prices. Seven deep reinforcement learning algorithms were implemented and are empirically compared in this paper. The numerical results show that the deep reinforcement learning algorithms differ widely in their ability to converge to optimal policies. By adding an experience replay and a semi-deterministic training phase to the well-known asynchronous advantage actor-critic algorithm, we achieved the highest model performance as well as convergence to near-optimal policies.

The consumption of contaminated water contributes to the global burden of diarrhea and other water-borne diseases, especially among young children. While the decentralized solar water disinfection treatment system remains a viable option to have safe drinking water, our understanding of the effects of household water treatment before use on willingness to accept and adopt a decentralized solar water disinfection treatment system is limited. In this study, a complementary log-log regression analysis of the compositional and contextual factors that systematically vary with willingness to accept and adopt a decentralized solar water disinfection treatment system in the Sawla-Tuna-Kalba (STK) district of Ghana was carried out. Based on our findings, a greater proportion of households’ (97%) are willing to accept and adopt a decentralized solar water disinfection treatment system. Compositional and contextual factors such as age, marital status, education, religion, and geographical location significantly contribute to households’ willingness to accept and adopt a decentralized solar water disinfection treatment system in the STK district of Ghana. Households that treat their water before use (66%, P&lt;0.05) are more likely to accept and adopt a solar water disinfection treatment system compared to those that do not treat their water before use. The findings therefore suggest that scaling up solar water disinfection systems in the STK district is sacrosanct, and highlight the necessity to analyze compositional and contextual factors influencing willingness to accept and adopt solar water disinfection systems. Our findings will inform policies and programs aimed at implementing solar water disinfection systems in the study area to improve the health of communities that must rely on poor quality drinking water sources.

In Europe, non-residential building stock built before building energy codes consumes more energy and resources than new buildings. Existing educational buildings comprise 17% of this outdated stock. These buildings can be retrofitted to create a conducive learning environment that can improve students’ comfort. Facade renovation has become the first choice for elevating the building performance of the education stock because it is less expensive than other alternatives. This study develops a methodology to optimize facade renovation solutions including: 1) preparation, 2) simulations of the simplified model using local shading, and 3) modelling realistic optimized facade design. This study evaluates visual comfort by considering multiple-dimensional metrics such as useful daylight illuminance (UDI), annual sunlight exposure (ASE), illuminance uniformity and the daylighting factor. The methodology was first applied to improve the facade proposal “Roof to Façade” in the project Waste-based Intelligent Solar Control Devices for Envelope Refurbishment (WiSeR) and simulations with the software DesignBuilder to design tile system facades. The results illustrate that implementing these solutions could efficiently improve indoor visual comfort by considering multiple daylight metrics. Moreover, for a constant gaps surface, the facade distribution with staggered gaps performs better in terms of the daylighting factor, solar gains and uniformity than more continuously connected gaps.

In an era of relentless technological change, accelerating the pace of innovation has become a critical imperative for organizations seeking to maintain a competitive edge and drive meaningful societal progress. Yet the complex, multifaceted innovation process - from ideation to commercialization - is often plagued by bottlenecks and challenges that can significantly delay the time-to-market for groundbreaking new products, services, and business models. This pioneering article represents an outstanding contribution to the burgeoning field of innovationology, offering a comprehensive, evidence-based playbook for shortening the innovation lifecycle. Drawing on an extensive review of over 180 cutting-edge academic sources, the paper maps the key stages of the innovation process - idea generation, concept development, prototyping, testing, and launch - and illuminates cutting-edge strategies that innovators can deploy to overcome common barriers and drive transformative innovations to market more quickly. From advanced idea generation techniques like design thinking and AI-powered creativity to innovative approaches to rapid prototyping, virtual experimentation, and data-driven commercialization, this seminal work equips scholars, practitioners, and policymakers with a transformative, globally-relevant toolkit for accelerating the innovation lifecycle. By synthesizing insights from a diverse array of industries and disciplines, the article establishes a new benchmark for innovationology research and empowers organizations to cultivate the conditions needed to translate visionary ideas into game-changing realities with unprecedented speed and efficiency. As the world grapples with ever-more complex, interconnected challenges, the ability to rapidly develop and scale breakthrough innovations has never been more crucial. This paradigm-shifting contribution to the field of innovationology represents a vital resource for driving the bold, disruptive changes needed to shape a more sustainable, equitable future.

Optical wireless video transmission technology combines the advantages of high data rates, enhanced security, large bandwidth capacity, and strong anti-interference capabilities inherent in optical communication, establishing it as a pivotal technology in contemporary data transmission networks. However, video data comprises a large volume of image information, resulting in substantial data flow with significant redundant bits. To address this, we propose an adaptive block sampling compressive sensing algorithm that overcomes the limitations of sampling inflexibility in traditional compressive sensing, which often leads to either redundant or insufficient local sampling. This method significantly reduces the presence of redundant bits in video images. First, the sampling mechanism of the block-based compressive sensing algorithm was optimized. Subsequently, a wireless optical video transmission experimental system was developed using a Field-Programmable Gate Array chip. Finally, experiments were conducted to evaluate the transmission of video optical signals. The results demonstrate that the proposed algorithm improves the Peak Signal-to-Noise Ratio by over 3 dB compared to other algorithms, with an enhancement exceeding 1.5 dB even in field tests, thereby significantly optimizing video transmission quality. This research contributes essential technical insights for the enhancement of wireless optical video transmission performance.

Breast cancer in patients with prior breast augmentation poses unique challenges for detection, diagnosis, and management. Mastectomy rates are increasing, and patients with prior augmen-tation often have a lower body mass index, making autologous techniques unsuitable. This study aims to assess the best reconstructive option in patients with a history of subglandular or dual plane breast augmentation. Materials and methods: a prospective analysis was conducted on pa-tients who underwent breast reconstruction after mastectomy. Patients with subglandular or dual plane breast augmentation were included. Patients were divided into submuscular breast recon-struction (group 2) or prepectoral breast reconstruction (group 1) groups. Demographic and sur-gical data were collected. Results: A total of 47 patients were included, with 23 in Group 1 and 24 in the Group 2. Complications occurred in 11 patients (23.4%), with significant differences be-tween groups. The most common complication was seroma formation. Implant loss occurred in 4.3% of cases in the Group 1, while no implant loss was observed in the Group 2. Patient-reported satisfaction scores were similar between groups at 12 months postoperatively. Conclusions: sub-pectoral breast reconstruction with a tissue expander seems a safer and effective technique for pa-tients with prior breast augmentation. It resulted in fewer complications. This approach should be considered as an option for breast reconstruction after mastectomy in this cohort of patients.

The energy transition towards Net Zero Emission by 2060 hinges on the renewable energy power plants in Indonesia. Good practices in several countries suggest a peer-to-peer (P2P) energy trading system using blockchain technology, supported by renewable energy (solar panels), an innovation to provide equal access to sustainable electricity while reducing the impact of climate change. The P2P energy trading concept has a higher social potential than the conventional electricity buying and selling approach, such as that of PLN (the grid management concept), but does not have a sharing element. This model implements a solar-powered mini-grid system and produces a Smart Contract that facilitates electricity network users to buy, sell, and trade electricity in rural areas via smartphones. This study aims to analyze the stakeholders' perceptions of the peer-to-peer (P2P) energy trading model using blockchain technology in Gumelar District, Banyumas Regency, Central Java Province, Indonesia. The stakeholders include households, the Ministry of Energy and Mineral Resources (ESDM), the State Electricity Company (PLN), the Institute for Essential Services Reform (IESR), Awina Company, and IPB University. The strength factors of this model are the freedom to generate and sell electricity (0.1) and transparency in electricity usage and sales by disclosing the amount, duration, and price of electricity (0.1). Regarding weakness factors, this model is primarily suitable for the lower middle class residing in rural or remote areas (0.02). Additionally, the intermittent electricity production to meet the substantial demand is a weakness (0.03). The opportunity factor for the model is the increase in public awareness and cooperation in using environmentally friendly, pollution-free electricity (0.12). Furthermore, there is an opportunity for additional income (0.12) and new business investment (0.12). Regarding threat factors, the model faces significant threats from the implementation aspect involving multiple parties (0.04). There is a potential threat in the form of losses for state utilities such as PLN or individuals who have already established electricity infrastructure if this program is implemented on a large scale (0.04). This model is located at the coordinate point (-0.40; 0.31), placing it in quadrant II. This indicates that the model should apply the Stability Strategy and focus on the Selective Maintenance Strategy for improvement. The stability strategy goal is to maintain the current situation by leveraging opportunities and addressing weaknesses. For effectiveness and efficiency, the strategy emphasizes fostering collaboration with PLN, which holds the legal authority as the sole utility company in Indonesia with an extensive electricity network, as well as advocating for regulations that support the independent purchase and sale of solar-powered electricity, particularly in areas without PLN network coverage.

The energy transition is a challenge that affects all sectors, from transport to civil structures and industry. In the industrial sector, the greatest need is the decarbonisation of energy-intensive in-dustries, such as producers of iron and steel, aluminum, cement, petrochemicals, paper, and more. The steel industry, in particular, is a hard-to-abate high-emissivity industry that, due to chemical processes and high thermal demands (often above 500 °C), contributed to 7.4% of global CO2 emissions in 2021. This paper explores the potential applications of hydrogen in these hard-to-abate sectors, highlighting its versatility and significance in decarbonization efforts, especially as a me-dium to facilitate the transition to green electric energy uses. It provides an overview of hydrogen production methods, emphasizing the importance of sustainable and green hydrogen production. It reviews hydrogen production methods, storage, and potential in blended combustion. In the final part of the article, some considerations are introduced on the possible role of hydrogen in the steel sector (both as a supplementary fuel and as a reducing agent in innovative processes), showing that while there is potential for its inclusion as an element for decarbonization, it is necessary to carefully evaluate the energy balances of the various processes and the methods of hydrogen production, in order to avoid achieving only marginal effects.

Assessing observation noise is a critical step in the development of a stochastic model for GNSS navigation and positioning. This process ensures that the statistical properties of the observational data are accurately characterized, leading to more reliable and precise positioning results. Traditionally, the one sigma values for observation noise, 0.3 m for code and 3 mm for carrier phase, alongside elevation-dependent weighting schemes, have been standard. However, these may no longer be suitable due to significant advancements in GNSS systems, receivers, and antennas. Previous research predominantly focused on code type and PPP techniques, often limited by the inability to separately assess observation types across different frequency bands due to ionospheric delay. Furthermore, these studies were generally constrained by limited experimental data. This research advocates for the use of ultra-short baselines to eliminate atmospheric delay and other error sources, providing a detailed assessment of observation noise for various frequency bands, GNSS systems, and receiver & antenna types over an extensive period and across multiple baselines. The findings suggest a need to reconsider traditional one sigma values and elevation-dependent weighting schemes for current applications.

Limited knowledge is available about the association between autistic spectrum disorder (ASD) and precocious puberty. Our study examined the association between the two medical conditions, and the effect modification by sex and neuropsychiatric comorbidities in a nationwide population. To compare the risk of precocious puberty between ASD and non-ASD cases, we conducted Cox regression analysis, using ASD as exposure and time-to-precocious puberty as outcome. We adjusted for sex, attention-deficit/hyperactivity disorder (ADHD), tics disorder, obsessive–compulsive disorder (OCD), anxiety disorder, intellectual disability, and epilepsy. We performed a moderation analysis to examine the potential moderating effects by sex or comorbidities. Patients with ASD were prone to have precocious puberty, with an adjusted hazard ratio (aHR) of 1.80 (95% CI: 1.61-2.01). For the effect modification, sex, specifically females, moderated the association between ASD and precocious puberty, with relative excess risk due to interaction (RERI) 7.35 (95% CI 4.90-9.80). No significant effect modification was found for any of the comorbidities within the scope of additive effect modification. We found that patients with ASD were prone to precocious puberty, regardless of sex or comorbid neuropsychiatric disorders. Girls with ASD are at particularly higher risk to develop precocious puberty.

Aim: This study aimed to understand the role of workforce agility as a coping strategy to curtail the COVID-19 pandemic. Method: The study reviewed and integrated two lines of literature to develop a theoretical framework to help business organizations to respond, adapt, and recover from the COVID-19 pandemic crisis. Results: The results showed that there are several commonalities between the workforce agility literature and the crisis management literature, mostly manifested in the speed of responding to uncertain and unpredictable, adverse events in the business environment. A thorough review of key themes in both kinds of literature led to developing a theoretical framework that links crisis drivers, crisis enablers, crisis capabilities, and response strategy. Workforce agility can be used as a coping strategy to deal with the COVID-19 pandemic crisis. Both kinds of literature evolve to respond to any crisis; the crisis management literature focuses on Meso-level (organizational level) or collective actions to mitigate the crisis, while the workforce agility literature focuses on the Micro-level (individual level). However, the successful response to any crisis requires the synergy of both actions. Future Studies: The results of this research are of prime importance for both researchers and practitioners. Researchers can use the theoretical framework as a baseline for building empirical research design. The current study also sets the context for future researchers who are interested in workforce agility to test the validity of agile work behaviors in real adverse context. It also opens a new stream of debate by deconstructing understudied links between workforce agility, resilience, and crisis management. Mangerial implication: For practitioners to ensure a successful response to any impending crisis, they must develop their employees’ agile behaviors. Practitioners can also redesign their recruitment strategy to select the right individuals with the right agile attributes, abilities, and behaviors to easily alter their behaviors according to the progressing crisis phases. Finally, practitioners can design continual learning interventions to include required agile skills and competencies to prepare their employees for future crises.

Pyrocumulonimbus (pyroCb) thunderclouds, produced from extreme bushfires, can initiate frequent cloud-to-ground (CG) lightning strikes containing extended continuing currents. This, in turn, can ignite new spotfires and inflict massive harm on the environment and infrastructures. This study presents a 3D numerical thundercloud model for estimating the lightning of different types and its striking zone for the conceptual tripole thundercloud structure which is theorized to elucidate the lightning phenomenon in pyroCb storms. More emphasis is given to the lower positive charge structure thundercloud to thoroughly examine various electrical parameters including the longitudinal electric field, electric potential, and surface charge density. The simulation outcomes on pyroCb thunderclouds with a tripole structure confirm the presence of negative longitudinal electric field initiation at the cloud’s lower region. This initiation is accompanied by enhancing the lower positive charge region, resulting in an overall positive electric potential increase. Consequently, negative surface charge density appears underneath the pyroCb thundercloud which has the potential to induce positive cloud-to-ground (+CG) lightning flashes. The suggested model would establish the basis for identifying the potential area impacted by lightning and could also be expanded to analyze the dangerous conditions that may arise in wind energy farms or power substations in times of severe pyroCb events.

Это исследование сосредоточено на разработке системы искусственного зрения для гибкого дельта-робота-манипулятора и ее интеграции с межмашинной связью для оптимизации взаимодействия устройств в реальном времени. Эта интеграция направлена ​​на увеличение скорости роботизированной системы и улучшение ее общей производительности. Предлагаемое сочетание системы искусственного зрения с межмашинной связью позволяет обнаруживать и распознавать цели с высокой точностью в режиме реального времени в ограниченном пространстве, предназначенном для позиционирования, дальнейшей локализации и выполнения производственных процессов, таких как сборка или сортировка деталей. . В данном исследовании RGB-изображения используются в качестве входных данных для алгоритма MASK-R-CNN, а результаты обрабатываются в соответствии с особенностями прототипа дельта-манипулятора робота. Данные, полученные от MASK-R-CNN, адаптированы для использования в системе управления дельта-роботом с учетом ее уникальных характеристик и требований к позиционированию. Технология M2M позволяет манипулятору робота быстро реагировать на изменения, например, на перемещение объектов или изменение их положения, что имеет решающее значение для задач сортировки и упаковки. Система была протестирована в условиях, близких к реальным, чтобы оценить ее производительность и надежность.

In the field of railroad safety, effective detection of surface cracks is critical, necessitating reliable, high-speed non-destructive testing (NDT) methods. This study introduces a hybrid Eddy Current Testing (ECT) probe, specifically engineered for railroad inspection, to address the common issue of ’lift-off noise’ due to varying distances between the probe and test material. Unlike traditional ECT methods, this probe integrates transmit and differential receiver coils, aiming to enhance detection sensitivity and minimize lift-off impact. The study optimizes ECT probes employing different driver coils, emphasizing three main objectives: a) quantitatively evaluating each probe using signal- to-noise ratio (SNR) and outlining a real-time data processing algorithm based on SNR methodology; b) exploring the frequency range proximal to the electrical resonance of the receiver coil; c) examining sensitivity variations across varying lift-off distances. The experimental outcomes indicate that the newly designed probe with figure 8-shape driver coil significantly improves sensitivity in detecting surface cracks on railroads. It achieves an impressive SNR exceeding 100 for defects with minimal dimensions of 1 mm in width and depth. Simulation results closely align with experimental findings, validating the investigation of optimal operational frequency and lift-off distance for selected probe performance, determined to be 0.3 MHz and 0.5 mm, respectively. The realization of this project would lead to notable advancements in enhancing railroad safety by improving crack detection efficiency.

The Simulation analogy presented in this work enhances the accessibility of abstract quantum theories, specifically the stochastic hydrodyanimc model (SQHM), by relating them to our daily experiences. The SQHM incorporates the influence of fluctuating gravitational background, resembling dark energy, into quantum equations. This model successfully addresses key aspects of Objective-Collapse Theories, including resolving the 'tails' problem through the definition of quantum potential length in addition to the De Broglie length, beyond which coherent Schrödinger quantum behavior and wavefunction tails cannot be maintained. The SQHM emphasizes that an external environment is unnecessary, asserting that the quantum stochastic behavior leading to wave-function collapse can be an inherent property of a system in a spacetime with fluctuating metrics. Embedded in relativistic quantum mechanics, the theory establishes a coherent link between the uncertainty principle and the constancy of light speed, aligning seamlessly with finite information transmission speed. Within a fluctuating quantum system, the SQHM derives the indeterminacy relation between energy and time, offering insights into measurement processes impossible within a finite time interval in a truly quantum global system. Experimental validation is found in confirming the Lindemann constant for solid lattice melting points and the transition from fluid to superfluid states. The SQHM's self-consistency lies in its ability to describe wavefunction collapse and the measure process. Additionally, the theory resolves the Pre-existing Reality problem by showing that large-scale systems naturally decay into decoherent states stable in time. Continuing, the paper demonstrates that the physical dynamics of SQHM can be analogized to a computer simulation employing optimization procedures for realization. This perspective elucidates the concept of time in contemporary reality and enriches our comprehension of free will. The overall framework introduces an irreversible process impacting the manifestation of macroscopic reality at the present time, asserting that the multiverse exists solely in future states, with the past comprising the formed universe after the current moment. Decoherence at the present time functions as a reduction of the multiverse to a single universe. The macroscopic reality, characterized by fractal consistency where microscopic domains with quantum properties coexist, provides insights into how our consciousness apprehends dynamic reality, the spontaneous emergence of gravity in discrete spacetime evolution, and the attainment of the classical General Relativity limit in Quantum Loop Gravity and Causal Dynamical Triangulation. The Simulation Analogy highlights a strategy focused on minimizing information processing, facilitating the universal simulation in solving its predetermined problem. From within, reality becomes the manifestation of specific physical laws emerging from the inherent structure of the simulation devised to address its particular issue. In this context, the reality simulation appears to employ an entropic optimization strategy, minimizing information loss while efficiently compressing data in line with the simulation's intended purpose.

Layered halide perovskites have emerged as a promising contender in solid-state lighting thanks to their tunable bandgap, high luminescence quantum yield, and high color purity. However, the fabrication of perovskite light-emitting devices in laboratories usually experiences low de-vice-to-device reproducibility since perovskite crystallization is highly sensitive to ambient condi-tions, such as humidity and temperature. Although device processing inside gloveboxes is primarily used to reduce the influence of oxygen and moisture, several extraneous variables, including gas-eous pollution traces and thermal fluctuations in the inert atmosphere or contaminations from re-sidual solvents confined in the enclosed environment, can destabilize the crystallization process and alter the properties of the emissive layers. Here, we examine different experimental set-ups for spin-coating deposition of layered perovskites in inert atmospheres and their influences on the formation of polycrystalline thin films. Our results demonstrate that fluctuations in the glovebox properties (concentrations of residual O2 and H2O or solvent traces), even in very short timescales, can negatively impact the consistency of the perovskite film formation, while thermal variation plays a relatively minor role in this phenomenon. Furthermore, careful storage of chemical species inside the workstation is critical for reproducing high-quality perovskite layers. Consequently, when applying our most controlled environment for perovskite deposition, the photoluminescence life-time of perovskite thin films shows a standard deviation of only 3%, whereas the reference set-up yields a 15% standard deviation. Regarding complete perovskite light-emitting diodes, the uncer-tainties in statistical luminance and EQE data are significantly reduced from 230% and 140% to 38% and 42%, respectively.

Children with severe acute malnutrition (SAM) are at high risk of impaired development. Contributing causes include inadequate intake of specific nutrients such as polyunsaturated fatty acids (PUFA) and lack of adequate stimulation. We conducted a pilot study assessing developmental and nutritional changes in children with SAM provided with a modified ready-to-use therapeutic food and a context-specific psychosocial intervention in Mwanza, Tanzania. We recruited 82 children with SAM (6-36 months) and 88 sex- and age-matched non-malnourished children. We measured child development, using the Malawi Development Assessment Tool (MDAT), measures of family and maternal care for children, and whole blood PUFA levels. At baseline, the mean total MDAT z-score of children with SAM was lower than non-malnourished children; -2.37 (95% confidence interval: -2.92; -1.82) as was their total n-3 fatty acids, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) levels. After 8 weeks’ intervention, MDAT z-scores improved in all domains, especially fine motor, among children with SAM. Total n-3, and EPA levels increased, total n-6 fatty acids decreased, and DHA remained unchanged. Family and maternal care also improved. The suggested benefits of the combined interventions on developmental and nutritional status of children with SAM will be tested in a future trial.

Gallium oxide (Ga2O3) is an emerging wide bandgap semiconductor promising a wide range of important applications. However, mass production of high-quality crystalline Ga2O3 still suffers from limitations associated with poor reproducibility and low efficiency. Low-temperature grown amorphous Ga2O3 demonstrates comparable performance with its crystalline counterparts. Lanthanide Er3+-doped Ga2O3 (Ga2O3: Er) possesses great potential for developing light-emitting devices, photodetectors and optical waveguides. The host circumstance can exert a crystal field around the lanthanide dopants and strongly influence their photoluminescence properties. Here we present a systematical study of the impact of amorphous-to-crystalline transition on the upconversion photoluminescence in Ga2O3: Er thin films. Through controlling the growth temperature of Ga2O3: Er films, the upconversion luminescence of as-grown thin films are strongly enhanced over 100 times. Moreover, the variation of photoluminescence reflects the amorphous-to-crystalline transformation of the Ga2O3: Er thin films. These results will aid further design of favorable optoelectronic devices integrated with lanthanide-doped Ga2O3 thin films.

The fate of critically sick patients with infections in intensive care units (ICUs) is significantly influenced by antimicrobial resistance, which has become a serious concern in developing nations. This observational study was conducted at the IBN Sina Specialised Hospital in Dhaka, Bangladesh, over a 12-month period from January 2021 to December 2021, in order to track the pattern of antibiotic resistance among the patients admitted to the intensive care unit (ICU). Aspiration pneumonia (29%) and diabetes mellitus (24%), among 200 patients, were the most common main diagnoses. 65 samples (or 26%) of the 250 samples had 85 bacteria identified from them. Urine (14.12%) and tracheal aspirate (64.71%) were the most frequently found sites of infection. In the sample from the tracheal aspirate, Pseudomonas spp. (30.59%), Escherichia coli (24.71%), Acinetobacter spp. (20%), and Klebsiella spp. (14.12) were the most frequently isolated microorganisms. The following antibiotics were shown to have the highest overall patterns of resistance: levofloxacin (68.24), amikacin (64.71), meropenem (49.41), ceftazidime (75.29), ciprofloxacin (78.82), and gentamicin (82.35). The most effective antibiotic against Klebsiella species was meropenem (64.61%), while Acinetobacter species were mostly susceptible to cotrimoxazole (64.67%) and piperacillin + tazobactam (60.50%). Most susceptible to netilmicin (70.48%) and meropenem (49.32%) were Escherichia coli, while Pseudomonas spp. were mostly responsive to colistin (55.14%) and netilmicin (52.25%). Antibiotic resistance is common among intensive care unit (ICU) patients, and most isolated microbes have resistance to traditional medicines.

There is less attention to use an environmental perspective in economic valuation and individuals' willingness to pay for recreational sites. Therefore, the aim of this study is to use contingent valuation methods to estimate the recreational value and willingness to pay of visitors to the protected area of Helen forest, considering the scale of the new environmental paradigm (NEP). To achieve this, the sample size for survey was determined using the Cochran method, and then economic valuation and environmental perspective questions were designed and completed through the completion of a dual-dimensional questionnaire and NEP scale. To determine the factors influencing individuals' willingness to pay, the logistic regression model was employed. In this study, two modeling approaches were used. The first utilized a base model containing socio-economic variables, while the second model integrated a NEP into the base, and subsequent estimations were conducted. The results indicated that 83.04% of visitors are willing to pay an amount for the recreational use of the study area. The estimated model results demonstrated that variables such as the proposed amount, frequency of visits, environmental statement, age, gender, education, individual monthly income, residency, and the NEP are among the most influential factors affecting the likelihood of accepting the proposed amount by tourists. The strong and positive correlation between the NEP and willingness to pay indicates that individuals with a favorable environmental perspective tend to exhibit a higher willingness to pay. In this study, the average willingness to pay per household per visit was 199,793 Rials, and the annual recreational value for the entire Helen forest area was 23746832564 Rials. Furthermore, the survey results regarding visitors' perspective on the NEP revealed that the average NEP score for visitors to Helen forest was 36.57, with the statement 'plants and animals have similar rights to humans' receiving the highest average score of 28.4. The result of this study shows the importance of environmental perspective for sustainable management of a recreational site to balance economic development with environmental conservation and social well-being.

Endothelial function is regulated by a myriad of complex pathways. In our previous study, the expression of miR-378a-3p was shown to inhibit endothelial autophagy and impair endothelial function. However, the mechanism underlying the effect of miR-378a-3p in endothelial cells remains to be elucidated. By employing an in silico approach, Protein Disulfide Isomerase 4 (PDIA-4) was identified as a target of miR-378-3p; however, its’ role in endothelial cells is not known. We here report that endothelial cell-specific loss of PDIA-4 leads to impaired autophagic flux accompanied by loss of endothelial function and apoptosis. Endothelial cell-specific loss of PDIA-4 also induced marked changes in endothelial cells’ architecture, accompanied with the loss of endothelial markers and gain of mesenchymal markers consistent with endothelial-to-mesenchymal transition (EndMT). Loss of PDIA-4 activates TGF-signaling, and inhibition of TGF-signaling inhibits EndMT in PDIA-4 silenced endothelial cells in vitro. Our findings help elucidate the role of PDIA-4 in endothelial autophagy and endothelial function and provide a potential target to modulate and/or limit autophagy and EndMT in (patho-)physiological conditions.

The negative impact of drought on plant growth may be modified by different availability of mineral nutrients and by their adaptation to different local habitat conditions. In this study, we examine the impact of drought, fertilization with phosphorus and provenance, as well as their interactions, on the growth and allometric growth relationships between belowground and aboveground organs of common beech (Fagus sylvatica) and sessile oak (Quercus petraea). The research was conducted on saplings originating from two mature mixed stands (dry and wet provenances) dominated by these species. In the common garden experiment, saplings were exposed to regular watering and drought in interaction with moderate and high phosphorus concentrations in the growing substrate (achieved by phosphorus fertilization). Obtained results indicate negative impact of drought and phosphorus fertilization on the growth of both species. In common beech, phosphorus fertilization had a negative impact on its adaptive capacity to drought, because of the unfavourable ratios between fine root mass and mass of other organs. The sessile oak provenances under the impact of drought showed a different root collar diameter/stem height increment ratio, which indicates its different phenotypic plasticity as a consequence of adaptation to different frequencies of dry periods in their natural habitats.

In this paper we compare the effects of forecasting demand using individual (disaggregated) components versus first aggregating the components either fully or into several clusters. Demand streams are assumed to follow autoregressive moving average (ARMA) processes. Using individual demand streams will always lead to a superior forecast compared to any aggregates, however we show that if several aggregated clusters are formed in a structured manner then these subaggregated clusters will lead to a forecast with minimal increase in mean-squared forecast error. We show this result based on theoretical MSFE obtained directly from the models generating the clusters as well as estimated MSFE obtained directly from simulated demand observations. We suggest a pivot-algorithm, that we call Pivot Clustering, to create these clusters. We also provide theoretical results to investigate sub-aggregation, including for special cases such as, aggregating MA(1) streams and ARMA streams with similar or same parameters.

Traditional diagnosis of patent foramen ovale (PFO) in the heart has involved the use of transcranial doppler (TCD). However, TCD is essentially a blind test that cannot directly visualize the location of blood vessels. Since TCD relies on qualitative assessments by examiners, there is room for errors, such as misalignment of the ultrasound's angle of incidence with the actual blood vessels. This limitation affects the reproducibility and consistency of the examination. In this study, we presented an alternative approach for assessing right-to-left shunt (RLS) associated with PFO using contrast transcranial color-coded doppler (C-TCCD) with bubble contrast. The patient under consideration had been diagnosed with an ischemic stroke through imaging, but the subsequent cardiac work-up failed to determine the cause. Employing C-TCCD for RLS screening revealed a confirmed RLS of Spencer’s three grades. Subsequently, transesophageal echocardiography (TEE) was conducted to evaluate PFO risk factors, confirming an 8 mm PFO size, a 21 mm tunnel length, a hypermobile interatrial septum, and persistent RLS. The calculated high-risk PFO score was 4 points, categorizing it as a very high-risk PFO. This case underscores the importance of C-TCCD screening in detecting RLS associated with PFO, especially in cryptogenic stroke patients when identifying the underlying cause of ischemic stroke becomes challenging.

Ever since the tremendous success of the rapid vaccine development against COVID‑19, its availa-bility, distribution, and deployment have been a significant concern; however, evidence suggests that vaccine hesitancy has become a greater problem. Therefore, trust in vaccines is crucial and critically dependent on regimes' ability to communicate the benefits of immunization. This study investigated ideas on ways to reduce barriers to COVID-19 vaccination uptake. It explores methods to overcome COVID-19 vaccine barriers through qualitative research: interviews and group discussions involving healthcare providers, administration personnel, teachers, and individuals with chronic conditions across urban (Mombasa) and rural (Kilifi) Kenya. Audio-recorded discussions were transcribed and thematically analyzed across locations. Five themes emerged in our results regarding how to reduce barriers to the COVID vaccine in the context of Kenya, including awareness campaigns, engaging diverse stakeholders, using various communication techniques, capacity building to increase vac-cination centers and trained staff, and lastly, revising relevant government health policies and guidelines. These results indicate the importance of adopting multiple approaches, as no single strategy could boost vaccine acceptance. Moreover, this study provides recommendations for con-ceiving actionable interventions to potentially boost vaccine demand and maintain routine immun-ization in Kenya.

This study examined if people who reside in different regions of South Korea exhibit different WTP for the mitigation of PM2.5 emissions from coal power plants by restricting the operation of such plants during the winter and spring when air pollution becomes severe. A contingent valuation method combined with a double bounded dichotomous choice was used to derive people’s WTP for the mitigation of PM2.5 emissions. Sample group was divided into central, western, eastern, and southern regions. It is known that the eastern region is affected by northwesterly winds in the winter and spring seasons, so air pollutants in the eastern areas fly to the eastern sea. According to the estimation results, respondents who live in eastern regions showed significantly lower WTP than the average WTP. We suggest that the mitigation policy on PM2.5 emissions should consider regional differences in the contributions of coal power plants to PM2.5 emissions.