Interaction between multiple phases especially liquid-gas is one of the most common phenomena in industrial systems. Computer Vision enables modern systems to derive an automated and robust image-processing technique to address this issue. However, diverse experimental conditions still make it a challenging task to overcome. In Deep Learning, instance segmentation has created a niche in various computer vision applications as it aims to provide different instance IDs to objects belonging to the same class. In this paper, we propose a novel approach employing the YOLO (You Look Only Once) an end-to-end deep learning architecture for the detection and segmentation of bubbles in fluid flows. YOLOv5 offers significant improvements in both speed and accuracy compared to its predecessors like YOLOv3. Therefore, we train the YOLOv5 network on a dataset consisting of annotated images representing instances of bubbles across varied fluid flow environments. This paper provides both qualitative and quantitative evaluation of three YOLOv5 networks (small, medium, and extra-large) in detecting and segmenting bubbles with high accuracy and efficiency. Based on the metrics all three YOLOv5 models achieved high precision above 0.98 for bounding box detection and 0.97 for segmentation mask, and high recall value greater than 0.97 for box and 0.96 for mask quality was achieved. The achieved results indicate that the models accurately localize bubbles within the image frame, and distinguish bubble pixels from the background. Also, mean average precision (mAP50-95) consistently exceeds 0.84 across all models for the bounding box and 0.73 for the segmentation mask. The ascertained results emphasize the potential of YOLOv5 architecture as a powerful tool for automated bubble analysis in real-world applications. Our research contributes to advancing the field of deep neural networks in fluid systems and provides a fresh approach for future developments in automated bubble analysis.

The human eye is a vital source of collecting information worldwide via daily observation. The computer science area recognizes it in research as a human-computer interaction. Human blink is an integral part of this observation as a research topic. Several studies have been conducted on eye blinking and left-right eye movements. Previous studies conducted on the eye blink consider the availability of hardware devices high in the budget, high Precision, and low light expo-sure, unlike our study, which uses low-budget devices as simple as a webcam and more versatile usable techniques, incredibly both dim and high light to name a few. This study offers the observational approach via ResNet101v2, VGG-19, and Convolution Neural Network (CNN) architectures. Outperforming both VGG-19 and CNN in this study, ResNet101v2 achieves an impressive accuracy of 98.2%. In contemporary times, deep learning in AI is taking an advanced form. This study attempts to provide a new insight into the real-world implementation of the eye blink.

The COVID-19 pandemic has triggered seismic shifts in how we work, and organizations behave. It has caused many organizations to transition from an office-centric culture to more flexible ways of working. This shift is necessitated by health conditions and the need for controls. It is also driven by the assumption that remote work or working from home offer a certain assurance of safety for employees against the threat of infection in highly vulnerable office conditions. The shift to remote work has so far been mainly experimental as most businesses continue to learn about what works and what doesn’t. There is also the assumption that all that matters for the efficient operability of a remote work regime is the availability and effectiveness of computing technologies and internet connectivity. Thus, once those supplies are in place remote work is expected to be fully functional and without problems. As learning continues about what works and what doesn’t, it has also become increasingly clear that beyond the threat of covid-19 and the relative safety that individual homes may offer, there are other vulnerabilities which are ignored or underestimated in the process. In most instances, the home environment of the employee, the conditions under which employees operate from home and the health and safety such environments provide (or not) are either ignored or underestimated in discussions around remote work practices. This paper highlights remote work as an emergent practice while exploring associated, but ignored, health and safety issues in employee homes.

This paper assesses the association of ESG scores with stock returns and highlights the moderating role of the COVID-19 pandemic and the country's governance. The study uses panel data regressions to analyze how ESG performance influences plain, absolute, and risk-adjusted returns in a sample of European and selected non-European countries. These suggest that higher overall ESG scores are related positively to financial performance, and this relation is enhanced during the COVID-19 pandemic. Specifically, the two dimensions of ESG that matter most are environmental and governance. Country-level governance is important because firms in well-governed countries amplify the benefits of high ESG scores. The opposite is true for the higher Controversies scores, whose bad financial outcome is magnified during the pandemic. These results present an argument for the resilience of firm financial performance, dependent on strong ESG practices and governance frameworks. This holds great interest for investors and policymakers in associating good ESG considerations with the effective management of financial risks, leading to sustainable returns during periods of widespread economic uncertainty.

In this study, a novel oral formulation of berberine hydrochloride (BBH) hydrogel was successfully synthesized through physical cross-linking using chitosan (CS) and carboxymethyl-β-cyclodextrin (CMCD). The characterization results confirmed the successful synthesis of CS/CMCD hydrogel and the subsequent loading of BBH into this composite (CS/CMCD/BBH) was effectively accomplished. BBH was used as a model drug and the resulting hydrogel demonstrated a sustained drug release profile. In addition to its improved solubility and sustained release characteristics, the hydrogel exhibited excellent antibacterial activity against common pathogens such as Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Candida albicans (C. albicans). Additionally, in vitro studies indicated that the hydrogel was not cytotoxic to NIH3T3 and HaCaT cells, suggesting its safety for biomedical applications. This lack of cytotoxic effects, combined with the mechanical strength, solubility improvements, and antibacterial properties of the hydrogel, positions the CS/CMCD/BBH hydrogel as a promising candidate for effective oral delivery of BBH. By addressing the solubility and delivery challenges of BBH, this hydrogel offers a viable solution for the oral administration of berberine hydrochloride, with potential applications in various biomedical fields.

The importance of contact with nature for human health was confirmed by numerous research. One of the sometimes neglected fields is the landscape design of hospital premises. This study focuses on the perception and preferences of prospective patients regarding the hospital site design. The methodology included anonymous survey with images and lists of adjectives. The online questionnaire was distributed using e-mails and social media from 4th May to 8th July 2024. The objective was to include all age groups. The results confirm previous studies and demonstrate the importance of landscape architecture design of hospital premises for the well-being of patients. The findings may inform the design of hospital sites.

A low cost, scalable and robust process has been proposed as innovative method for coating solar mirrors with a self-cleaning, transparent in the full solar range and versatile material based on auxetic aluminium nitrides, previously obtained on the laboratory scale. This work presents the scaling-up of fabrication process from laboratory to prototypal scale and pre-liminary results of outdoor self-cleaning solar mirror prototypes testing in the demonstrative CSP plant ENEASHIP located in Casaccia (Rome) ENEA research centre. Prototypes 50x40cm have shown stability in external conditions: no degradation occurs during the test campaign. Their washing restores the initial reflectance affected by soiling and the self-cleaning performance allows the utilization of a reduced quantity of water for cleaning operations with respect to uncoated glass of back surface mirrors. A similar self-cleaning AlN coating could be utilized on other solar components affected by soiling, such as glass envelopes of heat collecting elements, PV panels and everywhere are required self-cleaning performance combined to optical ones.

Researches on the runoff and sediment reduction effects of soil and water conservation measures are being on the rise, which is of great significance for carrying out strategic on soil and water conservation in the Yellow River Basin. Through the analysis of various soil and water conserva-tion measures, runoff, sediment, and rainfall datas in the Sanchuan River Basin from 1960 to 2019, we use the lagrange multiplier method to determining the threshold year of soil and water con-servation measures on runoff and sediment processes. The preliminary conclusion is as follows: The trend of flood season rainfall and annual rainfall in the Sanchuan River Basin is consistent. The 10-year average rainfall in each periods indicates that before 2000, it gradually decreased and then significantly increased. The 10-year average runoff showed a gradual decrease before 2010, followed by a sudden increase, while the 10-year average sediment has shown a decreasing trend years by years, especially after the centralized treatment period. Terrace and dam measures show a trend of first decreasing, then increasing, and then approaching stability during different treat-ment periods, while the trend of forest and grass measures is slightly decreasing and then in-creasing rapidly. The runoff and sediment reduction effects of various soil and water conservation measures during different treatment periods indicate that the runoff reduction effect reached its peak in 2005, while the sediment reduction benefit reached its best in 2015. Based on the compre-hensive benefits of runoff and sediment regulation, 2015 are considered as the threshold year for various soil and water conservation measures, with each measure areas being 4.86 × 104, 17.91 × 104, 1.20 × 104, and 0.83 × 104hm2, respectively. The research results will have certain reference significance for the high-quality development of soil and water conservation in the Yellow River Basin.

Although a lot of research has been carried out on hand sanitizer as an effort to prevent Covid-19, there is still limited research on non-alcoholic hand sanitizer lotion from the brown algae Scytosiphon lomentaria (S. lomentaria) as a raw material that provides antibacterial effects and maintains healthy skin. Therefore, this study aimed to analyze microbial inhibitory ability, physical and chemical characteristics of hand sanitizer lotion made from S. lomentaria algae. S. lomentaria powder was tested for phytochemicals, total phenolic content, free radical scavenging activity (IC50), and antibacterial tests. S. lomentaria slurry was prepared by adding distilled water (1:1) for lotion preparations in four treatment groups, such as normal control (lotion base without adding algae), lotion with the addition of algae 20%, 30%, and 40%. The lotion preparations for each treatment group were tested for antibacterial activity of Staphylococcus aureus and Escherichia coli, phytochemicals, pH, adhesion, spreadability, homogeneity, emulsion type, and hedonic. S. lomentaria powder contains bioactive polyphenolic compounds with a total phenolic content of 117.70±1.40 mg GAE/g dry weight and an IC50 value of 455±3.4 ppm, while lotion with the addition of S. lomentaria contains polyphenols and saponins The best treatment was shown by 40% S. lomentaria hand sanitizer lotion with inhibition of 6.30 ± 0.64 mm E. coli, 6.85 ± 1.12 mm S. aureus, hedonic test for color, texture and absorption with likes to likes very much level, neutral pH, greenish-white color, O/W emulsion type, high adhesion, homogeneous, and easily absorbed by the skin. This research can be an alternative reference in making non-alcoholic hand sanitizer lotion that is safe for the skin.

Non-Vitamin K Oral Anticoagulants (NOACs) have revolutionized anticoagulant therapy, offering improved safety and efficacy over traditional agents like warfarin. This review comprehensively examines the dual roles of NOACs—Apixaban, Rivaroxaban, Edoxaban, and Dabigatran—not only as anticoagulants but also as modulators of inflammation via Protease-Activated Receptor (PAR) signaling. We highlight the unique pharmacotherapeutic properties of each NOAC, supported by key clinical trials demonstrating their effectiveness in preventing thromboembolic events. Beyond their established anticoagulant roles, emerging research suggests that NOACs influence inflammation through PAR signaling pathways, implicating factors such as FXa and Thrombin in the modulation of inflammatory responses. This review synthesizes current evidence on the anti-inflammatory potential of NOACs, exploring their impact on inflammatory markers and conditions like atherosclerosis and diabetes. By delineating the mechanisms by which NOACs mediate anti-inflammatory effects, this work aims to expand their therapeutic utility, offering new perspectives for managing inflammatory diseases. Our findings underscore the broader clinical implications of NOACs, advocating for their consideration in therapeutic strategies aimed at addressing inflammation-related pathologies. This comprehensive synthesis not only enhances understanding of NOACs' multifaceted roles but also paves the way for future research and clinical applications in inflammation and cardiovascular health

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

While the role of safe riding behavior as a safety contributor for cyclists has been increasingly studied in recent years, there have been few studies analysing cycling behavior in relation to crash-related outcomes in Baltic countries. Indeed, to the best of our knowledge, this is the first time this issue has been addressed in the case of Latvia. Aim: The objective of this study was to assess the relationships among self-repotted cyclists’ behavior, traffic safety literacy, and their cycling crash involvement rates. Method: A total of 299 cyclists aged M=32.8 from across Latvia (42% females) participated in an online survey, which comprised questions regarding respondents’ demographics, frequency of riding, and the number of crashes in the past five years. The Cycling Behavior Questionnaire (CBQ) and the Cyclist Risk Perception and Regulation Scale (RPRS) were applied to assess cyclists' behavior patterns and traffic safety literacy. Results: According to the findings, it can be inferred that cyclists frequently engage in riding errors and traffic violations while cycling. Those who exhibit more antisocial behavior patterns are also more likely to be involved in road crashes. Conversely, cyclists with greater positive behavior rates more often also tend to possess better knowledge of traffic rules and exhibit a heightened risk perception, indicating a greater awareness of road traffic safety. Conclusion: All in sum, this study underscores key age differences, with older individuals significantly less involved in riding crashes, exhibiting fewer driving errors and a higher level of risk perception, which serves as a crucial factor in road safety. At the practical level, these results stress the need to address both traffic safety literacy and protective cycling factors of cyclists, in a manner to improve overall road safety and promote active transport modes in Latvia.

Proper Post-Activation Performance Enhancement helps to improve athletic performance. This study aimed to investigate the effects of two different velocity loss (VL), 10%VL and 20%VL, on post-activation performance enhancement (PAPE) in 20m sprint performance among sprint athletes. Twenty-four male sprint athletes (100m sprint time: 10.96±0.15 s) were recruited. A randomized crossover experimental design was used for traditional group (TG), 10%VL, and 20%VL interventions. Sprint tests were conducted at the 4th, 8th, 12th, and 16th minutes after the intervention. Two-way repeated measures ANOVA revealed an interaction effect between group and time on 20m sprint performance (F=2.817, p=0.037, partial η²=0.585). Simple effect analyses showed significant differences compared to baseline at the 4th minute for the 20%VL group (P<0.05). Cohen's d values indicated improvement in 10m sprint times at the 8th minute of the rest interval for all three intervention groups (TG: ES=-0.270, 10%VL: ES=-0.038, 20%VL: ES=-0.279). Improvement in 20m sprint times was observed at the 4th minute for the 20%VL group (ES=-0.296) and at the 16th minute for the 10%VL group (ES=-0.276). Compared to traditional PAPE schemes based on 1RM, PAPE schemes based on velocity loss (20%VL) can better induce PAPE effects in sprint athletes.

Students have historically fared poorly on the West African Examinations Council’s (WAEC) mathematics exam. This study investigated senior high school students’ difficulties with studying Geometry in the Cape Coast Metropolis, Central Region, Ghana. Using the descriptive survey design, data were collected from 300 Senior High School Two (SHS 2) students using simple random sampling. Students responded to the questionnaire and a 30-item multiple-choice achievement test on geometry. Four geometry concepts students perceived difficult to study are Circle theorems, Perpendicularity of Tangent and radius of a circle, Angle between Tangent and a chord and Tangents from an external point. The reasons for the difficulty in studying geometry topics are the unavailability of instructional materials, the geometry topics being complex, and teachers not teaching geometry concepts to the students’ understanding. Students’ gender did not influence the learning of concepts in geometry at a 0.05 level of significance. There was an insignificantly weak positive correlation between the students’ performance and their perceived difficult geometry concepts. It was concluded that the Ministry of Education does not provide relevant instructional materials to the various schools to teach geometry concepts. Schools do not organise workshops and seminars for teachers on effectively teaching geometry concepts in mathematics.

In recent years, the rapid development of computer-aided planning and design technology has provided a new perspective for the study of complex problems such as the generation of architectural complex forms. This study focuses on how to apply parameterization technology to analyze and articulate traditional spatial form composition rules, aiming to minimize reliance on subjective human judgment in the protection and renewal design of the historical style of traditional villages. It aims to establish digital generative design tools to address the challenges of accurately inheriting and innovatively utilizing historical and cultural information in traditional settlements. It introduces how to rely on parameterization technology to analyze the spatial form composition rules, parameter extraction rules, and spatial reconstruction rules of traditional villages, facilitating the complete process from spatial features to parameterization rules, and then to the application of computational methods to deduce spatial features. It also includes case studies demonstrating the application of parameterization technology tools for village protection and explores the role of generative design tools in preserving the spatial style of these settlements.

In this paper, we present a method for estimating GPS signals from visual information captured by a monocular camera mounted on a fixed-wing Unmanned Aerial Vehicle. The main challenge in visual odometry from aerial images is the computation of scale due to irregularities in the elevation of the terrain. That is, it is not possible to accurately convert from pixels in the image to meters in space, and the error accumulates. The contribution of this work is to reduce the accumulated error by comparing the images from the camera with satellite images. The algorithm has been tested in real-time experiments, and the results show that it is possible to eliminate the accumulated error using satellite images.

To decrease privacy risks, consumers may choose to misrepresent when they are asked to offer personal information. This paper examines the impact of consumer misrepresentation on a monopolistic firm and consumers with an economic model. The results show that consumer misrepresentation may benefit the firm but hurt consumers. In addition, consumers misrepresentation may encourage the firm to provide higher personalized service level in certain scenarios, such as, when the unit cost of personalized service is low. Thirdly, when consumers misrepresent, and the firm only covers part of the market, a greater unit value of consumer’s privacy information will reduce the firm’s profit, but a greater unit cost of personalized service increases the firm’s profit.

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

The concept of a Social License to Operate (SLO) has become increasingly important in the sustainability literature in recent years. Having its origins in the business discourse of the mining industry with respect to limiting opposition to mining projects, the notion of a social contract above and beyond legal requirements has since become applied across a number of different industries. Despite the concepts adoption confusion exists over the practices and outcomes of SLO, and particularly the nature of engagement. Given this situation it is surprising that not more attention to the role of marketing, and social marketing in particular, in operationalizing the concept. The paper discusses the potential of social marketing to contribute to SLO. Economic, political and social relations are complex in SLO and exchange is intricate in such relational environments. A community-based social marketing orientation is proposed as a means to improve exchange relations and enhance engagement. Seven models of SLO related social marketing models are discussed with community-based social marketing and adaptive co-marketing models being regarded as the most positive for the achievement of an SLO. Potential barriers to adoption of these approaches are noted.

As the most active plateau on the Earth, the Qinghai-Tibet Plateau has a complex crust-mantle structure. Knowledge of the distribution of such a structure provides information for understanding the underlying geodynamic processes. We obtains a three-dimensional density model of crustal and upper mantle beneath Qinghai-Tibet plateau and its surrounding areas from the residual geoid anomalies using the Earth Gravitational Model (EGM) 2008. We estimate a refined density model by iterations, using an initial density contrast model. We confirm that the EGM2008 mission products can be used to constrain the crust-mantle density structures. Our major findings are: (1). At 300-400 km depth, high-D anomalies terminate around Jinsha River Suture (JRS) in the central TP, suggesting that the Indian plate has been reached over the Bangong Nujiang Suture (BNS) and almost reach to the JRS. (2). On the eastern TP, low-D anomalies at the depth of 0-300 km together with high-D anomalies at 400-670 km further verified the current eastward subduction of Indian plate. The ongoing subduction provides forces to the occurrences of frequent earthquakes and volcano. (3). At 600 km depth, low-D anomalies inside the TP illustrate the existence of hot weak material beneath there, contributing to the external material inward-thrusting.

Cycle threshold (Ct) values of SARS-CoV-2 real-time reverse transcriptase-polymerase chain reaction (RT-PCR) tests are associated with infectivity and viral load, and they could be an aid to forecast the evolution of SARS-CoV-2 outbreaks. The objective was to know the Ct values related to the incidence and reinfection of SARS-CoV-2 in successive outbreaks, which took place in nursing homes in Castellon (Spain) during 2020-2022, and to test its usefulness as an instrument of epidemic surveillance in nursing homes. Poisson regression and multinomial logistic regression were used in the analysis. We studied four nursing home SARS-CoV-2 outbreaks, and the average infection rate, reinfection rate, and case fatality were 72.7%, 19.9%, and 5.5%, respectively; 98.9% of residents were vaccinated with three doses of a mRNA SARS-CoV-2 vaccine. Ct values for first infections and reinfections were 27.1±6.6 and 31.9±5.4 (p = 0.000). Considering Ct values ≥30 versus

The viticulture sector, spanning over 7.3 million hectares worldwide, plays a crucial economic role but faces challenges such as labor shortages, rising production costs, market competition, and climate change stresses. Addressing these issues requires monitoring the spatial and temporal variability in vineyard productivity. Traditional ground-based observations, though accurate, are time-consuming and limited in scope. Precision viticulture, leveraging technologies like GPS, remote sensing, and artificial intelligence, offers efficient, non-destructive monitoring tools. This study aims to develop and test a technological workflow using the mobile app Digivit, integrated with the AgroSat platform, to estimate yield variability in vineyards. The workflow was performed during the 2023 growing season in a series of vineyards near Siena (Italy) and involved two main steps: spatial variability characterization using AgroSat and yield estimation using the mobile Digivit app. AgroSat processed Sentinel-2 NDVI data to identify homogeneous zones, while Digivit used smartphone images of grape clusters to estimate yields. The field campaign, performed three weeks before harvest, involved monitoring representative vines within identified zones and uploading georeferenced images for cluster segmentation analysis. Yield estimates were validated against measured weights, showing a strong linear correlation (R²=0.85, RMSE=43.74g). Excluding one outlier improved correlation to R²=0.95, RMSE=14.58g. Vineyard-level yield predictions were compared with harvest data, achieving an overall error of approximately 7%, in agreement with other methods in the literature. The study demonstrates that the Digivit app provides accurate, timely yield prediction, supporting farmers in harvest planning and winemaking management. The user-friendly mobile app approach facilitates a broader adoption of precision viticulture technologies among farmers, overcoming barriers related to technical expertise.

Formaldehyde (HCHO), an indoor volatile organic compound, is seriously harmful to human health. Therefore, green and effective decomposition of HCHO is essential. TiO₂ has been employed for the degradation of HCHO via photocatalytic generation of reactive oxygen species (ROS) (O^2-, ·OH), yet the low specific surface area of crystalline TiO₂ depressed the catalytic performance. Herein, we prepared TiO₂ aerogels with high specific surface area and high porosity by sol-gel method, and added PVA to introduce flexible molecular chains for pore size regulation. The photocatalytic performance test verifies that the pore size of TiO₂ aerogel is one of the important factors for HCHO decomposition. Notably, through the establishment of theoretical model and calculation, we validated that the efficiency of HCHO decomposition is related to the oxygen pressure in the pores of TiO₂ aerogel, and the oxygen pressure is inversely proportional to the pore size. Accordingly, the optimal pore size of TiO₂ aerogel for the photocatalytic HCHO decomposition is 2 nm~10 nm. This study provides a theoretical idea for TiO₂ aerogels in the decomposition reaction of HCHO, which is expected to inspire more breakthroughs in the study of TiO₂ aerogels for green chemistry.

: Climate change necessitates urgent actions to mitigate carbon dioxide (CO2) emissions from fossil fuel-based energy generation. Among various strategies, the deployment of carbon capture and storage (CCS) solutions are critical for reducing emissions from point sources such as power plants and heavy industries. In this context, cryogenic carbon capture (CCC) via desublimation has emerged as a promising technology. While CCC offers high separation efficiency, minimal downstream compression work, and integration potential with existing industrial processes, challenges such as low operating temperatures and equipment costs persist. Ongoing research aims to address these hurdles in order to optimize the desublimation processes for widespread implementation. This review consolidates diverse literature works, providing insights into the strengths and limitations of CCC technology, including the latest pilot plant scale demonstrations. The transformative potential of CCC is first assessed on a theoretical basis, such as thermodynamic aspects and mass transfer phenomena. Then, recent advancements in the proposed process configurations are critically assessed and compared through key performance indicators. Furthermore, future research directions for this technology are clearly highlighted.

During the last two decades several cases of venous thrombosis (VTE) after a prolonged period at a computer has been described, denominated “eThrombosis”. Video gaming on a computer has become very popular and can be a social activity where several players are gathered to play against each other or in a virtual environment for several days (“LAN (i.e., Local Area Network) parties”) where the participants are sedentary and consuming calorie-rich food items. The aim of this study was to investigate a potential coagulation activation during a 42 hour LAN party. Nine male gamers volunteered for the LAN party. Citrated blood was sampled before and every 6 hours, and plasma was analyzed for thrombin generation, and Thrombin-antithrombin-complexes (TAT), prothrombin Fragment 1+2 (F1+2), and D-dimer. Thrombin generation increased slightly but not significantly during the LAN party, whereas the coagulation activation markers were unchanged. These results do not indicate that the coagulation system is activated significantly during 42 h gaming with minimal physical activity. Although an increased activity cannot be excluded, it does not directly indicate a risk of VTE in general. It may be specific and particularly susceptible in-dividuals who are prone to thrombosis and, therefore, are at risk of developing e-thrombosis.

The late diagnosis of Type 2 Diabetes Mellitus can occur due to lack of access to the primary health care system and the non-manifestation of symptoms. Faced with this problem, this work presents the creation of a mobile application, called DiabetesCheck, for predicting the risk of Type 2 Diabetes Mellitus. A mathematical model is used, which classifies the risk of Type 2 Diabetes Mellitus for a group of patients with intervention and for a comparative group, using Fuzzy Classification and Decision Trees. The proposed application allows the health professional to monitor patients through the history stored in a database, allowing a representation of the evolution of patients and indication of medications. Therefore, this proposal aims to carry out the diagnosis in the initial phase of the disease and help in the prescription of more effective treatments and in the proposition of public policy strategies in epidemiology and screening.

This report provides a comprehensive overview of occupational asthma and respiratory hypersensitivity, focusing on some chemicals used in the workplace Includes numerous case studies and research papers related to occupational exposure methacrylates, such as HEMA-HPMA, and respiratory hypersensitivity are discussed And the relationship is explored The book also examines asthma pathophysiology, emerging drug delivery systems used to treat asthma, and the potential of nanoparticles , dendrimers and micellar systems have to improve pulmonary drug delivery in detail The worldwide prevalence of asthma is highlighted, with higher rates in high-GDP countries. The book highlights the need to improve asthma diagnosis, treatment and biomarkers, particularly in rural and low-income countries where the disease is often underdiagnosed and inadequately treated, and discusses the role of inflammation in asthma, in particular secondary inflammation characterized by specific cytokines and inflammation cells In addition, the paper explores various drug delivery methods, such as parenteral and parenteral drugs, pressurized inhalers (pMDIs), dry powder inhalers ( DPIs), nebulizers, nanoparticles, liposomes, micellar systems, microparticles , dendrimers, and gene therapy . These systems aim to increase pulmonary delivery of drugs and improve clinical outcomes. The potential of dendrimer bilirubin-based nanoparticles and micellar systems in the treatment of asthma and lung inflammatory diseases, including asthma, has been discussed in summary, this paper provides an overview of occupational asthma and respiratory hypersensitivity, and this discussion highlights the association between methacrylate exposure and respiratory hypersensitivity.

Type II pneumocytes are the target of SARS-CoV-2 which alters their redox homeostasis to increase reactive oxygen species (ROS). Melatonin (MT) has antioxidant proprieties and protects mitochondrial function. Here we evaluated whether the treatment with MT compensated for the redox homeostasis alteration in serum from COVID-19 patients. We determined oxidative stress (OS) markers such as carbonyls, glutathione (GSH), total antioxidant capacity (TAC), thiols, nitrites (NO2–), lipid peroxidation (LPO), and thiols groups in serum. We also studied the enzymatic activities of glutathione peroxidase (GPx), -S-transferase (GST), reductase (GR), thioredoxin reductase (TrxR), extracellular superoxide dismutase (ecSOD) and peroxidases. There was a significant increase in LPO and carbonyls (p≤0.03) and a decrease in TAC, NO2–, thiols, GSH, (p<0.001) in COVID-19 patients. The activities of the ecSOD, TrxR, GPx, GST, GR and peroxidases were decreased (p≤ 0.04). The treatment with MT favored the activity of the antioxidant enzymes which contributed to increase TAC and restored the lost redox homeostasis. MT also modulated glucose homeostasis functioning as a glycolytic agent and inhibited the Warburg effect. Thus, MT restores the redox homeostasis which is altered in COVID-19 patients and can be used as adjuvant therapy in the SARS-CoV-2 infection.

The possible future emergence of new SARS-CoV-2 virus variants pushes the development of new chemoprophylaxis protocols complementary to the unspecific and specific immune-prophylaxis measures currently used. The SARS-CoV-2 virus is particularly sensitive to oxidation due to the relevant positive electrical charge of its spike protein used as a ligand for target cells. The present study evaluated the safety and efficacy of a new oxidant preparation, liquid hyperoxygen (IOL), to neutralize the SARS-CoV-2 virus. IOL was incubated with throat swabs containing a human wild-type virus. The samples were then incubated with cells expressing the ACE2 receptor and therefore very sensitive to SARS-CoV-2 infection. The ability to neutralize SARS-CoV-2 was determined by assessing the amount of viral nucleic acid inside cells by PCR. The results obtained indicate that IOL, even at considerable dilutions, is capable, after incubation times of less than 30 min and even equal to 5 min, to completely inhibit SARS-CoV-2 infection. This inhibitory effect has been shown to be due to the oxidizing capacity of the IOL. This oxidizing capacity is exerted towards the virus but does not damage eukaryotic cells either in the in vitro or in the in vivo skin model. Obtained results indicate that the use of IOL, a hydrophilic liquid mixture saturated with highly reactive oxygen and nitrogen species, is a new powerful, safe, and effective tool for preventing possible future outbreaks of COVID-19 disease.

Nowadays, it is highly desired to develop highly active and humidity resistive ozone decomposition catalyst to eliminate the ozone contaminant, one of the primary pollutants in air. In this work, a series of Cu2S hollow structured materials are rapidly synthesized using different structured Cu2O templates. The Cu2S from porous Cu2O shows the highest ozone catalytic decomposition efficiency of >95% to 400 ppm ozone with a weight hourly space velocity of 480,000 cm3g-1h-1 in dry air. Importantly, the conversion still keeps >85% in a high relative humidity of 90%. The mechanism is explored by diffusive reflectance infrared spectroscopy which shows the decomposition intermediate of O22-, and the X-ray photoelectron spectroscopy reveals the dual active site of both Cu and S. All these results show the effective decomposition of ozone by Cu2S especially in harsh environments, promising for active ozone elimination.

As humans age, aberrancies in several signaling pathways occur. In the aging population, some patients display abnormal bone morphogenetic protein (BMP) signaling. This can lead to osteoporosis (OP), a debilitating bone disorder caused by an imbalance between osteoblasts and osteoclasts. In 2002, the Food and Drug Administration (FDA) approved usage of recombinant human BMP-2 (rhBMP-2) during spinal fusion surgery as it is crucial for bone formation. However, complications have been reported with rhBMP-2 and primary osteoblasts isolated from OP patients are unresponsive to BMP-2. While patient samples are available, previous medical history may alter results. Therefore, C57BL/6 mice, an aging model that displays aberrant BMP-signaling, can be utilized to investigate OP and aging. We show that BMP receptor type Ia (BMPRIa) is upregulated in the bone marrow stromal cells (BMSCs) of 15-month mice similar to previous data. We show that a conjugation between BMP-2 and Quantum Dots (QDot®s) effectively binds to BMPRIa and can investigate BMP-2 activity. After incubating BMSCs with methyl-β-cyclodextrin (MβCD), BMP-signaling is restored in 15-month mice as shown by western blotting and the von Kossa assay. MβCD may be used to rescue BMPRIa and the BMP-signaling pathway can be utilized by future therapeutics to treat OP.

Cognitive reserve is the adaptability of cognitive processes in the face of brain aging and pathology. This study aimed to validate the Arabic version of the Cognitive Reserve Index Questionnaire (CRIq) in a healthy Lebanese sample. CRIq assesses cognitive reserve through three domains: education, working activity, and leisure time. Statistical measures, including descriptive and regression analysis along with structural equation modeling, were utilized to investigate the convergent and discriminant validity of CRIq, incorporating fluid intelligence (Gf) and measures of cognitive function, long-term memory encoding and retrieval (Glr), and processing speed (Gs). Results from 174 participants revealed that the activities assessed by CRIq-Arabic were comparable to the original CRIq study, with slight cultural differences. The internal consistency of CRIq-Arabic was good (Cronbach's α = 0.88), indicating reliability. Convergent validity was confirmed, with moderate to high loadings on the cognitive reserve latent construct. Discriminant validity was supported as correlations between cognitive reserve variables and non-target constructs (Gf, Glr, Gs) were less than 1. The findings provide an initial psychometric validation of the CRIq-Arabic. Further research in clinical samples is needed to enhance its utility in neuropsychological practice.

Optimal detection strategies for effective convalescent immunity after SARS-CoV-2 infection and vaccination remain unclear. The objective of this study was to characterize convalescent immunity targeting the SARS-CoV-2 spike protein using a multiparametric approach. At the beginning of the pandemic, we recruited 30 COVID-19 unvaccinated convalescent donors and 7 unexposed asymptomatic controls. Peripheral blood mononuclear cells (PBMCs) were obtained from leukapheresis cones. The humoral immune response was assessed by measuring serum anti-SARS-CoV-2 spike S1 subunit IgG semiquantitative ELISA and T cell immunity against S1 and S2 subunits were studied by IFN-γ Enzyme-Linked Immune absorbent Spot (ELISpot), flow cytometric (FC) activation-induced marker (AIM) assays and the assessment of cytotoxic CD8+ T-cell function (in the subset of HLA-A2 positive patients). No single immunoassay was sufficient in identifying anti-spike convalescent immunity among all patients. There was no consistent correlation between adaptive humoral and cellular anti-spike responses. Our data indicate that the magnitude of anti-spike convalescent humoral and cellular immunity is highly heterogeneous and highlights the need for using multiple assays to comprehensively measure SARS-CoV-2 convalescent immunity. These observations might have implications for COVID-19 surveillance, and optimal vaccination strategies for emerging variants. Further studies are needed to determine the optimal assessment of adaptive humoral and cellular immunity following SARS-CoV-2 infection, especially in the context of emerging variants and unclear vaccination schedules.

COVID-19 has rapidly spread worldwide since December 2019. During the pandemic, SARS-CoV-2 repeatedly mutated from Alpha to Omicron. The severity and mortality are related to age, sex, and underlying diseases (respiratory, cerebrovascular, cardiovascular, metabolic, cancer, and immune diseases). We retrospectively studied 44 hospitalized stroke patients infected with the SARS-CoV-2 Omicron variant. The mortality rate of hospitalized stroke patients with COVID-19 was 6 (13.6%). The cause of death was coagulopathy in 3 cases of ischemic stroke. High modified Rankin Scale score（mRS）of stroke patient was correlated with severity of COVID-19. The timing of vaccination is inversely correlated with COVID-19 severity. In conclusion, stroke patients with COVID-19 have high mortality rates attributed to coagulopathy. Stroke patients with high mRS scores are more likely to develop severe COVID-19. In high mRS scores, therapy for severe COVID-19 should be administered.

Type 2 diabetes mellitus (T2DM) is a common metabolic disease characterised by insulin resistance and elevated blood glucose levels, affecting millions of people worldwide. T2DM patients with dyslipidaemia have an increased risk of cardiovascular disease (CVD). A complex interplay of risk factors such as hyperglycaemia, dyslipidaemia, hypertension, obesity, inflammation and oxidative stress favour the development of atherosclerosis, a central mechanism in the pathogenesis of cardiovascular disease. Dyslipidaemia, a hallmark of T2DM, is characterised by elevated triglycerides, decreased high-density lipoprotein (HDL) cholesterol and the presence of small, dense low-density lipoprotein (LDL) particles, all of which promote atherosclerosis. In this article, we have attempted to present various treatment strategies that include pharmacological interventions such as statins, ezetimibe, PCSK9 inhibitors, fibrates and omega-3 fatty acids. We have also tried to highlight the pivotal role of lifestyle modifications, including physical activity and dietary changes, in improving lipid profiles and overall cardiovascular health in T2DM patients. We have also tried to present the latest clinical guidelines for the management of dyslipidaemia in T2DM patients. In conclusion, the treatment of dyslipidaemia in T2DM patients is of great importance as it lowers lipid particle levels, slows the progression of atherosclerosis and ultimately reduces susceptibility to cardiovascular disease.

The Main Protease (Mpro) plays a pivotal role in the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is considered a highly conserved viral target. Disruption of the catalytic activity of Mpro produces a detrimental effect on the course of the infection, making this target one of the most attractive for the treatment of COVID-19. The current success of the SARS-CoV-2 Mpro inhibitor Nirmatrelvir, the first oral drug for the treatment of severe forms of COVID-19, has further focused the attention of researchers on this important viral target, making the search for new Mpro inhibitors a thriving and exciting field for the development of antiviral drugs active against SARS-CoV-2 and related coronaviruses.

The SARS-CoV-2 virus, causative agent of COVID-19, is known for its genetic diversity. Virus variants of concern (VOCs) as well as variants of interest (VOIs) are classified by the World Health Organization (WHO) according to their potential risk to global health. This study seeks to enhance the identification and classification of such variants by developing a novel bioinformatics criterion centered on the virus's spike protein (SP1), a key player in host cell entry, immune response, and a mutational hotspot. To achieve this, we pioneered a unique phylogenetic algorithm which calculates EIIP-entropy as a distance measure based on the distribution of the Electron-Ion Interaction Potential (EIIP) of amino acids in SP1. This method offers a comprehensive, scalable, and rapid approach to analyze large genomic data sets and predict the impact of specific mutations. This innovative approach provides a robust tool for classifying emergent SARS-CoV-2 variants into potential VOCs or VOIs. It could significantly augment surveillance efforts and understanding of variant characteristics, while also offering potential applicability to the analysis and classification of other emerging viral pathogens and enhancing global readiness against emerging and re-emerging viral pathogens.

D-Glucaric acid is an important bio-based building block of polymers and is a high value-added chemical that can be used in a variety of applications. In the present study, the Udh target genes from Pseudomonas putida and Pseudomonas syringae were used together to construct the expression vector pETDuet-2×Udh. The transformants of BL21(DE3) with vector pETDuet-2×Udh was applied to produce glucaric acid from glucuronic acid. After optimization of induction conditions, the highest Udh expression were achieved when 0.4 mmol L-1 isopropyl-β-d–thiogalactoside (IPTG) was added to cell cultures at an OD600 value of 0.6 followed by culture at 26℃ for 6 hours. The production of glucaric acid substantially reached 5.24 ± 0.015 g L-1 in fed-batch cultures in a 30 L tank. In the present study, a new system for glucaric acid production was established, which was more economic and friendly to environment.

N'-(5-bromofuran-2-carbonyl)isonicotinohydrazide (1) was obtained as a white solid in 83% yield by 2-methyl-6-nitrobenzoic anhydride (MNBA)/4-dimethylaminopyridine (DMAP)-catalyzed reaction of 5-bromofuran-2-carboxylic acid and isoniazid in dichloromethane at room temperature. The structure of N'-(5-bromofuran-2-carbonyl)isonicotinohydrazide (1) was elucidated by 1H NMR, 13C NMR, FTIR, and the high resolution mass spectrometers. Molecular docking screening of the title compound (1) on the cyclooxygenase-2 (COX-2) protein (PDB ID: 5IKR) exhibited that compound (1) has a good binding affinity, suggesting that it is very interesting for further structure optimization and in-depth research as a potential COX-2 inhibitor.

Keywords: Marine sulfated glycans; SARS-CoV-2; Omicron XBB.1.5, Spike protein; Heparin

Recent studies have confirmed that lung microvascular endothelial injury plays a critical role in the pathophysiology of COVID-19. Our group and others have demonstrated the beneficial effects of H2S in several pathological processes and provided a rationale for considering the therapeutic implications of H2S in COVID-19 therapy. Here, we evaluated the effect of the slow-releasing H2S donor, GYY4137, on the barrier function of a lung endothelial cell monolayer in vitro, after challenging the cells with plasma samples from COVID-19 patients or inactivated SARS-CoV-2 virus. We also assessed how the cytokine/chemokine profile of patients’ plasma, endothelial barrier permeability, and disease severity correlated with each other. Alterations of barrier permeability after treatments with patient plasma, inactivated virus, and GYY4137 were monitored and assessed by electrical impedance measurements in real-time. We present evidence that GYY4137 treatment reduced endothelial barrier permeability after plasma challenge and completely reversed the endothelial barrier disruption caused by inactivated SARS-CoV-2 virus. We also showed that disease severity correlated with the cytokine/chemokine profile of the plasma but not with barrier permeability changes in our assay. Overall, these data demonstrate that treatment with H2S-releasing compounds has the potential to ameliorate SARS-CoV-2–associated lung endothelial barrier disruption.

The mRNA vaccines for SARS-CoV-2 have demonstrated efficacy and immunogenicity in the re-al-world setting. However, most of the research on vaccine immunogenicity has been centered on characterizing the antibody response, with limited exploration into the persistence of spike-specific memory B cell response. Here we monitored the durability of the memory B cell response and characterize the trajectory of spike-specific B cell phenotypes in healthy individuals who have received two doses of the BNT162b2 vaccine up to 9 months post-vaccination. To profile the spike-specific B cell response we applied the tSNE and Cytotree automated approaches. Our data showed the induction of spike-specific IgA+ and IgG+ plasmablasts and IgA+ activated cells 7 days after the second dose which disappeared 3 months later, while subsets of spike-specific IgG+ resting memory B cells became predominant 9 months after vaccination, and they were capable to differentiate into spike-specific IgG secreting cells when in vitro restimulated. Other subsets of spike-specific B cells, such as IgM+ or unswitched IgM+IgD+ or IgG+ double negative/atypical cells, were also elicited by the BNT162b2 vaccine and persisted up to month 9. The analysis of circulating spike-specific IgG, IgA and IgM was in line with the plasmablasts observed. The longitudinal analysis of the antigen-specific B cell response elicited by mRNA-based vaccines provides valuable insights into our understanding of the immunogenicity of this novel vaccine platform destined to a future widespread use, and it is crucial in guiding future decisions and vaccination schedules.

Erectile dysfunction (ED) is a common and feared complication of radical prostatectomy (RP) for prostate cancer. Recently, tissue engineering is being attempted for post-prostatectomy ED, with controlled interactions between cells, growth factors, and extracellular matrix (ECM) being important for nerve regeneration's structural integrity. In this study, we evaluated the effects of biomechanical ECM patch on human bone marrow-derived mesenchymal stem cells (hBMSCs) morphology and behavior in bilateral cavernous nerve injury (BCNI) rat model. The ECM patch, made of decellularized human fibroblast-derived ECM (hFDM) and a biocompatible polyvinyl alcohol (PVA) hydrogel, was tested with human bone marrow-derived mesenchymal stem cells (hBMSCs) on a bilateral cavernous nerve injury (BCNI) rat model. In vitro analysis showed that the hFDM/PVA + hBMSCs patches significantly increased neural development markers. In vivo experiments demonstrated that the rats treated with the hFDM/PVA patch had higher ICP/MAP ratio, a higher ratio of smooth muscle to collagen, increased content of nNOS, higher levels of eNOS protein expression, and a higher cGMP level compared to the BCNI group. These results indicate that the hFDM/PVA patch is effective in promoting angiogenesis, smooth muscle regeneration, and nitrergic nerve regeneration, which could contribute to improved erectile function in post-prostatectomy ED.

Natural herbs and functional foods contain bioactive molecules capable of augmenting the immune system and mediating anti-viral functions. Functional foods, such as prebiotics, probiotics, and dietary fibers, have been shown to have positive effects on gut microbiota diversity and immune function. The use of functional foods has been linked with en-hanced immunity, regeneration, improved cognitive function, maintenance of gut mi-crobiota, and significant improvement in overall health. The gut microbiota plays a critical role in maintaining overall health and immune function, and disruptions to its balance have been linked to various health problems. SARS-CoV-2 infection has been shown to affect gut microbiota diversity, and the emergence of variants poses new challenges to combat the virus. SARS-CoV-2 recognizes and infects human cells through ACE2 receptors prevalent in lung and gut epithelial cells. Humans are prone to SARS-CoV-2 infection because the respiratory and gastrointestinal tracts are rich in microbial diversity and contain high ACE2 and TMPRSS2. This review article explores the potential use of functional foods in mitigating the impact of SARS-CoV-2 variants on gut microbiota diversity and the potential use of functional foods as a strategy to combat these effects.

Abstract: The SARS-CoV-2 pandemic has significantly impacted world health and economic status. In response, much work has been undertaken to provide effective, safe vaccines, antibodies and antiviral drugs with which to address this pandemic. Treatment of a pandemic population presents multiple challenges in addition to the primary issue of drug efficacy and safety, such as large scale drug manufacture and distribution, drug stability, oral dosing and pharmacoeconomic considerations. Ideally, these factors must be addressed if new candidate drugs are to be advanced for treatment of large (pandemic) populations. Subsequently, new antivirals have reached the market but choices are few. According to the NIH Covid Treatment Guidelines, only three small molecule antiviral drugs are available to treat COVID-19 disease. As such, a significant part of the research towards discovery of new antiviral drugs has focused on screening and evaluation of ‘repurposed drugs’ or previously approved or clinical stage drugs. Yet, in spite of this increased research activity, one promising clinical stage candidate drug has received little attention regarding its potential as a monotherapy or component of combination therapy for treatment of COVID-19 disease. Tucaresol, with documented human safety and pharmacokinetic data, is an orally active, stable, small molecule amenable to large scale manufacture by a proprietary two-step synthesis developed by us. Tucaresol functions as a host-targeted antiviral by selective protection/reconstitution of CD4+ T helper cells as demonstrated in HIV patients and SIV macaques. In view of similarities between HIV and SARS-CoV-2, especially with respect to host CD4+ T helper cells, and the suitability of Tucaresol for facile treatment of pandemic populations, Tucaresol is presented herein for treatment of mild-to-moderate COVID-19 patients but may also be useful for treatment of advanced disease accompanied by lymphopenia.

This research intended to report amine-functionalized multiwall carbon nanotubes (MWCNTs) prepared by a simple method for efficient and rapid removal of Reactive Yellow 2 (RY2) from water. EDS analysis showed that the N content increased from 0 to 2.42% and from 2.42 to 8.66% after modification by APTES and PEI, respectively. BET analysis displayed that the specific surface area, average pore size, and total pore volume were reduced from 405.22 to 176.16 m2/g, 39.67 to 6.30 nm, and 4.02 to 0.28 cm3/g, respectively. These results proved that the PEI/APTES-MWCNTs were successfully prepared. pH edge experiment indicated that pH 2 was optimal for RY2 removal. At pH 2 and 25 °C, the time required for adsorption equilibrium was 10, 15, and 180 min at initial concentrations of 50, 100, and 200 mg/L, respectively; and the maximum RY2 uptake calculated by the Langmuir model was 714.29 mg/g. Thermodynamic studies revealed that the adsorption process was spontaneous and endothermic. 0-0.1 mol/L of NaCl showed negligible effect on RY2 removal by PEI/APTES-MWCNTs. Five adsorption/desorption cycles confirmed the good reusability of PEI/APTES-MWCNTs in RY2 removal. Overall, the PEI/APTES-MWCNTs are a potential and efficient adsorbent for reactive dye wastewater treatment.

The global threat of COVID-19 has led to the increasing use of metabolomics to study SARS-CoV-2 infection in humans and animals. Despite this, understanding SARS-CoV-2's metabolome during infection remains difficult and incomplete. Here, metabolic responses were characterized from sampled nasal washes collected from an asymptomatic ferret model (n = 20) at different time points before and after the SARS-CoV-2 challenge using an LC-MS-based metabolomics approach. Multivariate analysis of the nasal wash metabolome data resulted in several statistically significant features being observed. Despite no effects of gender or interaction between gender and time on the time course of SARS-CoV-2 infection, 16 metabolites were significantly different at every time point post-infection. Among these altered metabolites, the relative abundance of taurine was elevated post infection which could be an indication of hepatotoxicity, while the accumulation of sialic acids could indicate SARS-CoV-2 invasion. The pathway analysis identified several pathways influenced by SARS-CoV-2 infection. Of these, sugar, glycan, and amino acid metabolisms were the key altered pathways in the upper respiratory channel during infection. These findings provide some new insights into the progression of SARS-CoV-2 infection in ferrets at the metabolic level which could be useful for the development of early clinical diagnosis tools and new or repurposed drug therapies.

Vehicle HVAC systems can accumulate and recirculate highly infectious respiratory diseases via aerosols. Integrating UVC to complement automobile HVAC systems can protect occupants from developing allergies, experiencing inflammatory problems, or acquiring respiratory infectious diseases by inactivating pathogenic organisms. UVC can add little to no static pressure with minimal space, unlike mercury lamps which are larger and heavier. Additionally, UVC LEDs are effective at low voltage and have no mercury or glass. While previous experiments have shown UVC LED technology can reduce bacteriophage Phi6 concentrations by 1 log in 5 minutes (selected as the average time to clean the cabin air), those studies had not positioned LED within the HVAC itself or studied the susceptibility of the surrogate at the specific wavelength. This study aimed to assess the disinfection performance of UVC LEDs in automotive HVAC systems and determine the dose-response curve for bacteriophage Phi6, a SARS-CoV-2 surrogate. To achieve this, UVC LEDs were installed in a car HVAC system. To determine inactivation efficacy, a model chamber of 3.5 m3, replicating the typical volume of a car, containing the modified automobile HVAC system was filled with bacteriophage Phi6, and the HVAC was turned on with and without the UVC LEDs being turned on. The results revealed that HVAC complemented with UVC reduced bacteriophage Phi6 levels significantly more than the HVAC alone and reduced the viral concentration in the cabin by more than 1 LRV (90% viral reduction) in less than 5 minutes. The performance after 5 minutes is expected to be significantly better against SARS-CoV-2 because of its higher sensitivity to UVC, especially at lower wavelengths (below 270 nm). HVAC alone could not achieve a 90% viral reduction of bacteriophage Phi6 in 15 minutes. Applying UVC LEDs inside an HVAC system is an effective means of quickly reducing the number of aerosolized viral particles in the chamber, by inactivating microorganisms leading to improved cabin air quality.

Low back pain is a clinically highly relevant musculoskeletal burden and is associated with inflammatory as well as degenerative processes of the intervertebral disc. However, the pathophysiology and cellular pathways contributing to this devastating condition are still poorly understood. Based on previous evidence, we hypothesize that tissue renin-angiotensin system (tRAS) components, including the SARS-CoV-2 entry receptor angiotensin-converting enzyme 2 (ACE2), are present in human nucleus pulposus (NP) cells and associated with inflammatory and degenerative processes. Experiments were performed with NP cells from 4 human donors. The existence of angiotensin II, angiotensin II type 1 receptor (AGTR1), AGTR2, MAS-receptor (MasR), and ACE2 in human NP cells was validated with immunofluorescent staining and gene expression analysis. Hereafter the cell viability was assessed after adding agonists and antagonists of the target receptors as well as angiotensin II in different concentrations for up to 48 hours of exposure. A TNF-α-induced inflammatory in vitro model was employed to assess the impact of angiotensin II addition and the stimulation or inhibition of the tRAS receptors on inflammation, tissue remodeling, expression of tRAS markers, and the release of nitric oxide (NO) into the medium. Further, protein levels of IL-6, IL-8, IL-10, and intracellular as well as secreted angiotensin II were assessed after exposing the cells to the substances, and inducible nitric oxide synthase (iNOS) levels were evaluated utilizing Western Blot. The existence of tRAS receptors and angiotensin II were validated in human NP cells. Cell viability analysis revealed no cytotoxic effects of angiotensin II. The AGTR1 inhibitor Candesartan and the MAS receptors AVE0991 showed cytotoxic effects at high concentrations (100 µM). The addition of angiotensin II only showed a mild impact on gene expression markers. However, there was a significant increase in NO secreted by the cells. The gene expression ratios of pro-inflammatory/anti-inflammatory cytokines IL-6/IL--10, IL-8/IL-10, and TNF-α /IL-10 were positively correlated with the AGTR1/AGTR2 and AGTR1/MAS1 ratios, respectively. The stimulation of the AGTR2 MAS-receptor and the inhibition of the AGTR1 receptor revealed beneficial effects on the gene expression of inflammatory and tissue remodeling markers. This finding was also present at the protein level. We did not find alterations in iNOS protein concentrations after adding the drugs. The current data showed that tRAS components are expressed in human NP cells and are associated with inflammatory and degenerative processes. Further characterization of the associated pathways is warranted. The findings indicate that tRAS modulation might be a novel therapeutic approach to intervertebral disc disease.

One of the models that could be used to understand the adoption of vaccine uptake is the Health Belief Model (HBM). The aim of this study is to assess the role of HBM constructs and perceived health status (PHS) on vaccination status of individuals and to understand the role of socio-demographic variables on HBM scoring. A comparative cross-sectional telephone survey was conducted among 1,325 vaccinated (60.0%) and non-vaccinated (40.0%) vaccinated individuals aged 40 years and above in July 2021 in Punjab province, Pakistan. A higher level of education was the strongest predictor of positive HBM. All constructs of HBM, PHS and cues-to-action were significant predictors of COVID-19 vaccination uptake with perceived benefits as the strongest predictor. In order to expand the vaccination coverage, doubled pronged interventions utilizing both ICT and human resources should be designed that address each barrier perceived by individuals and understandably communicate the benefits of COVID-19 vaccine to the broader population.

During the SARS-CoV-2 vaccination campaign, people with CF (pwCF) were considered a clinically vulnerable population. However, data on immunogenicity of anti-SARS-CoV-2 vaccines in pwCF are lacking. We conducted a prospective study enrolling all patients aged >12 and followed-up in our CF centre, who received two doses of the BNT162b2 vaccine in March-­­­October 2021. They underwent a blood sample for quantification of antibodies to the SARS-CoV-2 spike protein receptor binding domain immediately before receiving the first dose and after 3 and 6 months from the second dose. We enrolled 143 patients (median age: 21 years, range: 13-38); of whom 16 had a previous infection. Median antibody titer (interquartile range) after 3 months from vaccination was 1288 U/mL (730-2115) and decreased to 918 U/mL (534-1488) after 6 months (P<0.0001). Median values were higher among previously infected patients as compared to those naïve to SARS-CoV-2 (9107 vs 1229 U/mL at 3 months and 4810 vs 829 U/mL at 6 months, P<0.0001) with no significant differences in the rate of decline over time (P=0.135). All pwCF mounted an antibody response after two-doses of BNT162b2 vaccine that waned at 6 months from vaccination. Age ≥30 years and use of inhaled corticosteroids were associated with a lower humoral response.

Conventional methods of crop mapping need ground truth information to train the classifier. Thanks to the frequent acquisition allowed by recent satellite missions (Sentinel 2), we can identify temporal patterns that depend on both phenology and crop management. Some of these patterns are specific to a given crop and thus can be used to map it. Thus, we can substitute ground truth information used in conventional methods with agronomic knowledge. This approach was applied to identify irrigated permanent grasslands (IPG) in the Crau area (Southern France) which play a crucial role in groundwater recharge. The grassland is managed by making three mows during the May-October period which leads to a specific temporal pattern of leaf area index (LAI). The mowing detection algorithm was designed using the temporal LAI signal derived from Sentinel 2 observations. The algorithm includes some filtering to remove noise in the signal that might lead to false mowing detection. A pixel is considered a grassland if the number of detected mows is greater than 1. A data set covering five years (2016-2020) was used. The detection mowing number was done at the pixel level and then results are aggregated at the plot level. A validation data set including 780 plots was used to assess the performances of the classification. We obtained a Kappa index ranging between 0.94-0.99 according to the year. These results were better than other supervised classification methods that include training data sets. The analysis of land-use changes shows that misclassified plots concern grasslands managed less intensively with strong intra-parcel heterogeneity due to irrigation defects or year-round grazing. Time series analysis, therefore, allows us to understand different management practices. Real land-use change in use can be observed, but long time series are needed to confirm the change and remove ambiguities with heterogeneous grasslands.

In this paper, the phases in the Mg-Ti-O system using the 1:1 formulation of MgO:TiO2 mixing synthetic brucite of Mexican origin with TiO2 microparticles of high purity and with a heat treatment at 1100°C for 1 h were studied. The raw materials and formulation by XPS and DRX techniques were characterized. The results demonstrate the presence of different oxidation states in titania and the formation of different oxides in the Mg-Ti-O system when mixed and calcined at 1100°C; additionally, the formation of vacancies in the crystal lattice during the transformation from hexagonal brucite to magnesia with a cubic structure centered on the faces is estimated. With the results, its thermal behavior is warned based on the MgO-TiO2 phase diagram.

During the novel coronavirus disease (COVID-19) pandemic, several environmental factors have influenced the activities and the protection policy measures. This has had a major effect on climate change and global environmental catastrophe. In many countries, the strategy of closing various activities such as tourism, industrial production, stopped normal life, transportation, among others. This closure has a positive impact on the environment. However, the massive use of masks and personal protection could significantly increase pollution worldwide. The impact on the environment needs to be calculated to have information for public health actions. In this study, we present a first overview of the potential impacts of COVID-19 on some environmental matrices in Bogota, Colombia.

The purpose of the current study was directed to investigate the effectiveness of docosahexaenoic acid (DHA) as a chemopreventive agent on experimentally induced hamster buccal pouch (HBP) carcinogenesis; Material and methods: 40 Syrian male hamsters, five weeks old, were divided into 4 groups of 10 animals in each as follows, GI: Topical application of liquid paraffin alone (thrice a week for 14 weeks), GII: Topical application of 7, 12 dimethyl benz[a]anthracene (DMBA) alone (0.5 % in liquid paraffin, thrice a week for 14 weeks), GIII: Topical application of DMBA (0.5 % in liquid paraffin, thrice a week for 14 weeks) + Oral administration of DHA (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks on alternative days of DMBA application), GIV : Oral administration of DHA alone (125 mg/kg b.w. in 1 ml distilled water by oral gavage, thrice a week for 14 weeks); Results: Gross observations and histopathological findings revealed a-GI: normal stratified squamous epithelium b- GII: well and moderately differentiated squamous cell carcinoma (SCC) c-: GIII: showed variable results ranges from hyperkeratosis, hyperkeratosis and focal hyperplasia, mild dysplasia, and well differentiated SCC with superficial invasion of tumor cells not extended to deeper areas d: GIV: normal similar to GI. Immunohistochemical results revealed that oral DHA treatment to DMBA treated hamsters restored the normal expression of bcl-2; Conclusion: DHA has the potential to be a dietary chemopreventive agent due to its capacity to improve carcinogen detoxification and to block/suppress the initiation and promotion stages of experimentally produced HBP carcinogenesis.

(1) Background: Mouse-mammary tumor virus (MMTV) might play a role in the etiology of some breast cancers in humans. The purpose of our study was to identify MMTV DNA sequences in breast tissue samples from breast cancer patients operated in our regional center from Romania. (2) Methods: We have selected 75 patients with non-metastatic breast cancer treated with curative intent and searched with PCR the MMTV-like DNA sequence in the breast cancer tissue and normal breast tissue obtained from the same patients. (3) Results: None of the examined samples was positive for MMTV-like target sequences on PCR. (4) Conclusions: We could not prove that MMTV plays a role in the etiology of breast cancer in our patient group. This finding is similar to findings of other geographically related research groups and might be due to the fact that only the Mus musculus domesticus mouse species was proven to carry infectious MMTV, but not the Mus musculus musculus species, which is specific to South-Eastern Europe and some parts of Asia.

Several hypotheses have been presented on the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from its identification as the agent causing the current coronavirus disease 19 (COVID-19) pandemic. So far, no hypothesis has managed to identify the origin, and the issue has resurfaced. Here we have unfolded a pattern of distribution of several mutations in the SARS-CoV-2 proteins across different continents comprising 24 geo-locations. The results showed an evenly uneven distribution of unique protein variants, distinct mutations, unique frequency of common conserved residues, and mutational residues across the 24 geo-locations. Furthermore, ample mutations were identified in the evolutionarily conserved invariant regions in the SARS-CoV-2 proteins across almost all geo-locations we have considered. This pattern of mutations potentially breaches the law of evolutionary conserved functional units of the beta-coronavirus genus. These mutations may lead to several novel SARS-CoV-2 variants with a high degree of transmissibility and virulence. A thorough investigation on the origin and characteristics of SARS-CoV-2 needs to be conducted in the interest of science and to be prepared to meet the challenges of potential future pandemics.

It has been more than a year since the first case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was found. This coronavirus has infected more than 110 million people worldwide by the end of February, 2021, and several virulent as well as more spreadable mutant forms of SARS-CoV-2 have emerged subsequently. In the latter group, three variants B.1.1.7, B.1.351, and P1 lineages, have been reported. Using computer simulation, the present paper investigates the structural differences between the wild type SARS-CoV-2 spike protein and its Asn501Tyr (N501Y) mutant variant. Time-based structural changes between the receptor binding domains of these two species are also examined. The N501Y mutation is common to all the three aforesaid mutant variants.

COVID-19 is a contagious respiratory disease that is causing significant global morbidity and mortality. Understanding the impact of a SARS-CoV-2 infection on the host metabolism is still in its infancy but of great importance. Herein, we investigated the metabolic response during viral shedding and post-shedding in an asymptomatic SARS-CoV-2 ferret model (n=6) challenged with two SARS-CoV-2 isolates. Virological and metabolic analyses were performed on (minimally invasive) collected oral swabs, rectal swabs, and nasal washes. Fragments of SARS-CoV-2 RNA were only found in the nasal wash samples in four of the six ferrets, and in the samples collected 3 to 9 days post-infection (referred to as viral shedding). Central carbon metabolism metabolites were analyzed during viral shedding and post-shedding periods using a dynamic MRM (dMRM) database and method. Subsequent untargeted metabolomics and lipidomics of the same samples were performed using an LC-QToF-MS methodology, building upon the identified differentiated central carbon metabolism metabolites. Multivariate analysis of the acquired data identified 29 significant metabolites and three lipids that were subjected to pathway enrichment and impact analysis. The presence of viral shedding coincided with the challenge dose administered and significant changes in the citric acid cycle, purine metabolism, and pentose phosphate pathways, amongst others, in the host nasal wash samples. An elevated immune response in the host was also observed between the two isolates studied. These results support other reported metabolomic-based findings found in clinical observational studies and indicate the utility of metabolomics applied to ferrets for further COVID-19 research that advances early diagnosis of asymptomatic and mild clinical COVID-19 infections, in addition to assessing the effectiveness of new or re-purposed drug therapies.

This article analyses the environmental impact of the measures imposed during the SARS-CoV-2 pandemic. We compare the evolution of atmospheric pollution levels in recent years and during lockdown, and assess the effects of the decrease in mobility and changes in patterns and lifestyles during the latter period. Thus, the reduction in the risk to human health brought about by the improvement of air quality during the months of confinement through the use of dose-response functions is estimated. The focus of the case study is the island of Tenerife. The island of Tenerife has been selected because it can serve as an example for other sites in Europe. We distinguish between the three areas with the highest population concentrations: the Metropolitan, Southern, and Northern areas. The impacts of air pollution and its relationship with changes in consumption and activity patterns are clearly distinguishable. Therefore, the lessons learned can be easily extrapolated to other areas, in both island and mainland contexts.

In the context of the COVID-19 pandemic, thousands of healthcare workers (HCWs) infected with COVID-19 have lost their lives worldwide. At the early stage of the epidemic, when COVID-19 was still not considered as a pandemic, a large number of Chinese HCWs were infected. Officials reported that more than 3,000 HCWs in Hubei contracted the virus at the early stage of the outbreak due to limited knowledge of the virus. Following reports of overloaded local hospitals, more than 42,000 medical staff, including those from the military, were dispatched to Hubei from across the country. At the peak of the fight, one in 10 intensive care medics in China were working in Wuhan. During fighting against COVID-19 in China, although a large number of HCWs were infected by SARS-CoV-2 in the early stages of the epidemic, the timely adoption of measures indicated that, a faster rate of diagnosis could be achieved, patients were isolated in-time, HCWs’ safety was prioritized, training on basic protective knowledge and unified management of HCWs was strengthened, and effective protective measures were implemented. This resulted in the accomplishment of zero SARS-CoV-2 infection among the 42,632 members of the national medical teams sent to Hubei, and the number of COVID-19 cases among HCWs in local hospitals also significantly decreased, thereby indicating that hospital-acquired infections of SARS-CoV-2 among HCWs are fully preventable.

Four new zoonotic coronaviruses outbreak occurred in the past two decades. The first coronavirus outbreak happened in 2003 and was named Severe Acute Respiratory Syndrome Coronavirus-1 (SARS-CoV-1), followed by Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2013, and by Swine Acute Diarrhoea Syndrome (SADS) in 2017. In late December 2019, a patient from Wuhan Seafood Wholesale Market, China, was admitted to Huang's hospital with respiratory distress syndrome (RDS) of apparently unknown etiology, which later was diagnosed with SARS-CoV-2-induced coronavirus disease-19 (COVID-19). SARS-CoV-2 was identified from another clade within the subgenus Sarbecovirus of the genus Betacoronavirus. This new CoV variant showed 96.2% similarity at whole-genome level to bat coronavirus. Based on genetic studies, pangolin, bats, and snakes are suspected to be a possible intermediate host of this virus, but further research is in progress to determine how this virus appeared and what is the exact source of infection. The SARS-CoV-2 outbreak has higher transmissibility, contagiosity and pathogenicity compared to that of SARS-CoV-1 and MERS-CoV. SARS-CoV-2 swiftly spread from continent to continent and is persistently causing a shocking global public health concern albeit the rate of infected cases and mortality is relatively decreasing over time. In this review, we provide an update on the origin, transmissibility, etiology, epidemiology, and evolution of COVID-19. We also highlight the current diagnostics, therapies, and prognostics for SARS-CoV-2. Eventually, we report and provide our humble opinion about the preventive strategies to control the ongoing related pandemic situation at global and individual levels, considering the international public health emergency and possible future epidemics and pandemics.

A signal analysis of the genoma sequenced of coronavirus variants: B.1.1.7, B.1.135, B.1.429-B.1.427, B.1.525 and P1 is presented. We deal with a certain type of finite alternating sum series having independently distributed terms associated with binary (0,1) indicators for the nucleotide bases A,C,G,T. This method provides additional information to conventional Similarity comparisons and Power Spectrum approaches. It leads to uncover distinctive patterns regarding the intrinsic data organization of genomic sequences according to its progression along the nucleotide bases position. Hence, the method could be useful for survelliance of genoma variants.

The novel coronavirus SARS-CoV-2 likely emerged from a wildlife source with transmission to humans followed by rapid geographic spread throughout the globe and severe impacts on both human health and the global economy. Since the onset of the pandemic, there have been many instances of human-to-animal transmission involving companion, farmed and zoo animals, and limited evidence for spread into free-living wildlife. The establishment of reservoirs of infection in wild animals would create significant challenges to infection control in humans and could pose a threat to the welfare and conservation status of wildlife. We discuss the potential for exposure, onward transmission and persistence of SARS-CoV-2 in an initial selection of wild mammals (bats, canids, felids, mustelids, great apes, rodents and cervids). Dynamic risk assessment and targeted surveillance are important tools for the early detection of infection in wildlife, and here we describe a framework for collating and synthesising emerging information to inform targeted surveillance for SARS-CoV-2 in wildlife. Surveillance efforts should be integrated with information from public and veterinary health initiatives to provide insights into the potential role of wild mammals in the epidemiology of SARS-CoV-2.

In this article, the geometry of pseudoparallel, Ricci-generalized pseudoparallel and 2-Ricci-generalized pseudoparallel invariant submanifolds of an almost $\alpha$-cosymplectic $(\kappa,\mu,\nu)$ space has been searched under the some conditions. We also give some characterizations for such submanifolds. I think that obtained new results contribute to differential geometry.

Abstract. The purpose of this review is to investigate the nature of privacy concerns in the context of Smart Local Energy Systems (SLES) to understand how SLES providers can minimize both users’ concern, and cause for concern, around privacy. We conducted a rapid realist review and thematic framework analysis against Bronfrenbrenner’s socio-ecological model to understand privacy concerns in different contexts. A common privacy concern was that sharing detailed energy use data had the potential to reveal information about home life, and to intrude upon people’s sense of autonomy, choice and control. Evidence suggests that people are willing to accept newdata sharing technologies if the benefits of doing so are clear, anticipated, and mutually beneficial. Building trust, through increasing knowledge and understanding was a mechanism for overcoming privacy concerns, but this was mediated by the organization providing the information. Non-profit organizations were more trusted to ensure appropriate safeguards to privacy were in place. One key barrier to participation with good supporting evidence was that people can resist perceived intrusions on their privacy. This could be actively resisted by refusing to install data collection technologies or passively by non-participation in adapting energy use behaviors: both of which are necessary for SLES to achieve their goals of managing energy demand and building resilience in smart grids.

The urgent need to improve performance in the construction industry has led to the adoption of many innovative technologies. 3D laser scanners are amongst the leading technologies being used to capture and process assets or construction project data for use in various applications. Due to its nascent nature, many questions are still unanswered about 3D laser scanning, which in turn contribute to the slow adaptation of the technology. Some of these include the role of 3D laser scanners in capturing and processing raw construction project data. How accurate is the 3D laser scanner or point cloud data? How does laser scanning fit with other wider emerging technologies such as Building Information Modelling (BIM)? This study adopts a proof-of-concept approach, which in addition to answering the afore-mentioned questions, illustrates the application of the technology in practice. The study finds that the quality of the data, commonly referred to as point cloud data is still a major issue as it depends on the distance between the target object and 3D laser scanner’s station. Additionally, the quality of the data is still very dependent on data file sizes and the computational power of the processing machine. Lastly, the connection between laser scanning and BIM approaches is still weak as what can be done with a point cloud data model in a BIM environment is still very limited. The aforementioned findings reinforce existing views on the use of 3D laser scanners in capturing and processing construction project data.

Conventionally, eukaryotic mRNAs were thought to be monocistronic, leading to the translation of a single protein. However, large-scale proteomics has led to a massive identification of proteins translated from mRNAs of alternative ORF (AltORFs), in addition to the predicted proteins issued from the reference ORF or from ncRNAs. These alternative proteins (AltProts) are not represented in the conventional protein databases and this “Ghost proteome” was not considered until recently. Some of these proteins are functional and there is growing evidence that they are involved in central functions in physiological and physiopathological context. Based on our experience with AltProts we have got interested in finding out their involvement in development of the SARS-CoV-2 virus, responsible for the 2020 Covid-19 outbreak. Thus, we have scrutinized the recently published data by Krogan and coworkers (2020) on the SARS-CoV-2 interactome with host cells by co-IP in the perspective of drug repurposing. The initial work has revealed the interaction between 332 human cellular RefProts with the 27 viral proteins. Re-interrogation of this data using 23 viral targets and including AltProts, followed by enrichment of the interaction networks, leads to identify 218 RefProts (in common to initial study) plus 56 AltProts involved in 93 interactions. This demonstrates the necessity to take into account the Ghost proteome for discovering new therapeutic targets and establish new therapeutic strategies. Missing the ghost proteome in the drug metabolism and pharmacokinetic (DMPK) drug development pipeline will certainly be a major limitation to the establishment of efficient therapies.

The COVID-19 pandemic has wreaked havoc on the whole world, taking over half a million lives and capsizing the world economy in unprecedented magnitudes. With the world scampering for a vaccine, early detection and containment is the only redress. Existing diagnostic technologies with high accuracy like RT-PCRs are expensive and sophisticated, requiring skilled individuals for specimen collection and screening, resulting in lower outreach. So, methods excluding direct human intervention are much sought after, and artificial intelligence-driven automated diagnosis, especially with radiography images, captured the researchers' interest. This survey marks a detailed inspection of the deep-learning-based automated detection of COVID-19 works done to date, a comparison of the available datasets, methodical challenges like imbalanced datasets, and others, along with probable solutions with different pre-processing methods, and scopes of future exploration in this arena. We also benchmarked the performance of 315 deep models in diagnosing COVID-19, Normal, and Pneumonia from x-ray images of a custom dataset created from four others. The dataset is publicly available at https://github.com/rgbnihal2/COVID-19-X-ray-Dataset. Our results show that DenseNet201 model with Quadratic SVM classifier performs the best (accuracy: 98.16%, sensitivity: 98.93%, specificity: 98.77%) and maintains high accuracies in other similar architectures as well. This proves that even though radiography images might not be conclusive for radiologists, but it is so for deep learning algorithms for detecting COVID-19. We hope this extensive review will provide a comprehensive guideline for researchers in this field.

The regioselectivity in non-polar [3+2] cycloaddition (32CA) reactions has been studied within the Molecular Electron Density Theory (MEDT) at the B3LYP/6-311G(d,p) level. To this end, the 32CA reactions of nine simplest three-atom-components (TACs) with 2-methylpropane were selected. The electronic structure of the reagents has been characterised through the Electron Localisation Function (ELF) and the Conceptual DFT. The energy profiles of the two regioisomeric reaction paths and ELF of the transition state structures are studied to understand the origin of the regioselectivity in these 32CA reactions. This MEDT study permits to conclude that the least electronegative ends X1 atom of these TACs controls the asynchronicity in the C-X (X = C,N,O) single bond formation, and consequently, the regioselectivity. This behaviour is a consequence of the fact that the creation of the non-bonding electron density required for the formation of the new CX single bonds has a lesser energetic cost at the least electronegative X1 atom than that at the Z3 one.

Sun-Induced chlorophyll Fluorescence (SIF) relates directly to photosynthesis yield and stress but there are still uncertainties in its interpretation. Most of these uncertainties concern the influences of the emitting vegetation’s structure (e.g., leaf angles, leaf clumping) and biochemistry (e.g., chlorophyll content, other pigments) on the radiative transfer of fluorescent photons. The Caatinga is a large region at northeast Brazil of semiarid climate and heterogeneous vegetation, where such biochemical and structural characteristics can vary greatly even within a single hectare. With this study we aimed to characterize eleven years of SIF seasonal variation from Caatinga vegetation (2007 to 2017) and to study its responses to a major drought in 2012. Orbital SIF data from the instrument GOME-2 was used along with MODIS MAIAC EVI and NDVI. Environmental data included precipitation rate (TRMM), surface temperature (MODIS) and soil moisture (ESA CCI). To support the interpretation of SIF responses we have used red and far-red SIF adjusted by the Sun’s zenith angle (SIF-SZA) and by daily Photosynthetically Active Radiation (dSIF). Furthermore, we have also adjusted SIF through two contrasting formulations using NDVI data as proxy for structure and biochemistry, based on previous leaf-level and landscape level studies: SIF-Yield and SIF-Prod. Data was tested with time-series decomposition, rank correlation, spatial correlation and Linear Mixed Models (LMM). Results show that GOME-2 SIF and adjusted SIF formulations responded consistently to the observed environmental variation and showed a marked decrease in SIF emissions in response to a 2012 drought, that was generally larger than the corresponding NDVI and EVI decreases. Drought sensitivity of SIF, as inferred from LMM slopes, was correlated to land cover at different regions of the Caatinga. This is the first study to show correlation between landscape-level SIF and an emergent property of ecosystems (i.e., resilience), showcasing the value of remotely sensed fluorescence for ecological studies.

Background: To prioritize the development of antiviral compounds, it is necessary to compare their relative preclinical activity and clinical efficacy. Methods: We reviewed in vitro, animal model, and clinical studies of candidate anti-coronavirus compounds and placed extracted data in an online relational database. Results: As of July 2020, the Coronavirus Antiviral Research Database (CoV-RDB; covdb.stanford.edu) contained &gt;2,400 cell culture, entry assay and biochemical experiments, 240 animal model studies, and 56 clinical studies from &gt;300 published papers. SARS-CoV-2, SARS-CoV, and MERS-CoV account for approximately 85% of the data. Approximately 75% of experiments involved compounds with a known or likely mechanism of action, including receptor binding inhibitors and monoclonal antibodies (20%); viral protease inhibitors (18%); polymerase inhibitors (9%); interferons (8%); fusion inhibitors (8%); host endosomal trafficking inhibitors (7%); and host protease inhibitors (5%). For 724 compounds with a known or likely mechanism, 95 (13%) are licensed in the US for other indications, 72 (10%) are licensed outside the US or are in human trials, and 557 (77%) are pre-clinical investigational compounds. Conclusion: CoV-RDB facilitates comparisons between different candidate antiviral compounds, thereby helping scientists, clinical investigators, public health officials, and funding agencies prioritize the most promising compounds and repurposed drugs for further development.

Objective: To examine the burnout syndrome among the healthcare personnel in Puerto Rico during the COVID-19 pandemic. Methods: Descriptive study that pursues to understand burnout syndrome in the clinical personnel in Puerto Rico. The Maslach Burnout Inventory (MBI) was sent via email to healthcare professionals around the island. Furthermore, open questions were asked to the participants. Results: The overall burnout level on the clinical personnel was found to be moderate. Nonetheless, in physicians, 12.1% had severe burnout levels compared to a 13.1% score in nurses. Additionally, 92.4% of physicians and 100% of nurses had moderate to severe burnout. In the three subscales, nurses scored high levels in all of them, and physicians were high in Emotional Exhaustion and moderate level in Depersonalization and Personal Accomplishment at Work. There were high levels of burnout syndrome of the clinical personnel in Puerto Rico. Conclusion: Since the beginning of the COVID-19 pandemic, over 90% of healthcare professionals in Puerto Rico have been working with moderate to severe burnout syndrome, being the nurses the most affected. Key Words: Burnout syndrome, MBI, Clinical personnel, COVID-19, SARS-CoV-2

In this paper, a solenoid based linearly movable armature system is designed using robust control theory in order to improve the performance of the system. Reference track method is the best performance analysis for position control systems. Among the robust controllers, H infinity mixed-sensitivity and Mixed H 2 /H∞ with Regional Pole Placement Controllers are used to improve the performance of the system. Comparison of the proposed controllers for tracking a reference displacement signals (step and sine wave) and a promising simulation result have been obtained.

The coronavirus disease-2019 (COVID-19) pandemic is an ongoing pandemic caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Although COVID-19 pandemic is not a direct surgical problem, its impact on the surgical units has been substantial. Many operations have been cancelled or deferred due to risk of disease spread and staff shortages. Operating theatres are identified as areas of high risk of disease transmission due to aerosol generation during the surgical procedures and prolonged patient contact. Resource limitations, including lack of personal protective equipment (PPE) and limited availability of testing, continue to expose the surgical community to COVID-19. In this review, evidence and consensus guidelines on surgical practice during the COVID-19 pandemic are summarised and described. Immediate action is deemed essential to ensure unhindered provision of surgical care while optimizing the use of limited resources and ensuring staff safety.

Since the severe acute respiratory syndrome (SARS) outbreak in 2003, human coronaviruses (hCoVs) have been identified as causative agents of severe acute respiratory tract infections. Two more hCoV outbreaks have since occurred, the most recent being SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19). The clinical presentation of SARS and MERS is remarkably similar to COVID-19, with hyperinflammation causing a severe form of the disease in some patients. Previous studies show that the expression of the SARS-CoV E protein is associated with the hyperinflammatory response that could culminate in acute respiratory distress syndrome (ARDS), a potentially fatal complication. This immune-mediated damage is largely caused by a cytokine storm, which is induced by significantly elevated levels of inflammatory cytokines interleukin (IL)-1beta and IL-6, which are partly mediated by the expression of the SARS-CoV E protein. The interaction between the SARS-CoV E protein and the host protein, syntenin, as well as the viroporin function of SARS-CoV E, are linked to this cytokine dysregulation. This review aims to compare the clinical presentation of virulent hCoVs with a specific focus on the cause of the immunopathology. The review also proposes that inhibition of IL-1beta and IL-6 in severe cases can improve patient outcome.

It is unclear why European countries have been more severely affected by COVID-19 than East Asian countries. In this ecological study we compared the COVID-19 epidemics (cumulative incidence and mortality rates), host genetic susceptibility and national responses (testing intensity) in all European versus all Western Pacific/East Asian countries reporting cases in the first month of the epidemic. The host-genetic-susceptibility assessment was limited to the frequency of the D-allele of the angiotensin converting enzyme-1 (ACE-1) which has been found to be positively associated with COVID-19 incidence within European countries. Despite earlier epidemics, countries from the Western Pacific reported lower cumulative numbers of COVID-19 cases/100 000 inhabitants than European countries (P=0.0002). The Western Pacific countries also reported fewer cumulative COVID-19 deaths/100 000 (P=0.0024). Whilst there was little difference in the cumulative number of tests conducted/100 000, the percent of COVID-19 tests reported positive was higher in Europe than the Western Pacific (P=0.0076). The frequency of the ACE-1 D-allele was lower in the Western Pacific than European countries (P=0.0007). Our results suggest that a combination of different testing strategies and host genetic susceptibility contribute to difference in severity of the COVID-19 epidemics in the Western Pacific/East Asia and Europe.

Several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to a high level of uncertainty or even lack of essential data, the standard epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. As an alternative to the susceptible-infected-resistant (SIR)-based models, this study proposes a hybrid machine learning approach to predict the COVID-19 and we exemplify its potential using data from Hungary. The hybrid machine learning methods of adaptive network-based fuzzy inference system (ANFIS) and multi-layered perceptron-imperialist competitive algorithm (MLP-ICA) are used to predict time series of infected individuals and mortality rate. The models predict that by late May, the outbreak and the total morality will drop substantially. The validation is performed for nine days with promising results, which confirms the model accuracy. It is expected that the model maintains its accuracy as long as no significant interruption occurs. Based on the results reported here, and due to the complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research.

The fast spread of COVID-19 constitutes a worldwide challenge to the public health, educational, and trade systems, affecting the overall wellbeing of human societies. The high transmission and mortality rates of this virus, and the unavailability of a vaccine or treatment, resulted in the decision of multiple governments to enact measures of social distancing. Thus, it is of general interest to consider the validity of the proposal for keeping a social distancing of at least 2 m from other persons to avoid the spread of COVID-19. The exposure to the bioaerosol can result in the deposition of the pathogen in the respiratory tract of the host causing disease and an immunological response. In the atmospheric context, the work evaluates the effect of aerodynamic diameter (size) of particles in carrying RNA copies of the novel coronavirus. A SARS-CoV-2 carrier person talking, sneezing, or coughing at distance of 2 m can still provide a pathogenic bioaerosol load with submicron particles that remain viable in air for up to 3 hours for exposure of healthy persons near and far from the source in a stagnant environment. The deposited bioaerosol creates contaminated surfaces, which if touched can act as a path to introduce the pathogen by mouth, nose, or eyes and cause disease.

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models need to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak.

Water quality retrieval for small urban waterbodies by remote sensing get used to be difficult due to coarse spatial resolution of the remote sensing imagery. The recently launched Sentinel-2 produces imagery with a spatial resolution of 10 m. It provides an opportunity to solve the problem of retrieving water quality for small waterbodies. Additionally, many water management issues also require fine resolution of imagery, e.g. illegal discharge to an urban waterbody. Since illegal discharges are an important issue for urban water management, chemical oxygen demand (COD), total phosphorous (TP), and total nitrogen (TN) were chosen as the target parameters for water quality retrieval in this study. COD, TP and TN, however, are non-optically active parameters. There were limited studies in the past to retrieve these parameters in comparison with optically active parameters, e.g. Chlorophyll-A etc. This study compared three machine learning models, namely Random Forest (RF), Support Vector Regression (SVR), and Neural Networks (NN), to investigate the opportunity to retrieve the above non-optically active parameters. Results showed that R² of TP, TN, and COD by NN, RF and SVR were 0.94, 0.88, and 0.86, respectively. The performances of water quality retrieval for these non-optically active parameters were significantly improved by the optimized machine learning models. These models hence solved the problem to use remote sensing data to retrieve these non-optically active water quality parameters and provided a new monitoring strategy for small waterbodies. Water quality mapping obtained by Sentinel-2 imagery provided a full spatial coverage of the water quality characterization for the entire water surface. Compared with water samples collecting and testing, it greatly reduced labor cost, reagents cost, and waste treatment cost. It also may help identify illegal discharges to urban waterbodies. The method developed in this research provides a new practical and efficient water quality monitoring strategy in managing water with consideration of environmental sustainability.

We applied a generalized SEIR epidemiological model to the recent SARS-CoV-2 outbreak in the world, with a focus on Italy and its Lombardia, Piemonte, and Veneto regions. We focus on the application of a stochastic approach in fitting the model numerous parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We analyze the official data and the predicted evolution of the epidemic in the Italian regions, and we compare the results with data and predictions of Spain and South Korea. We link the model equations to the changes in people’s mobility, with reference to Google’s COVID-19 Community Mobility Reports. We discuss the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.

Recent emergence of novel coronavirus (SARS-CoV-2) all over the world has resulted more than 33,106 global deaths. To date well-established therapeutics modules for infected patients are unknown. In this present initiative, molecular interactions between FDA-approved antiviral drugs against the Hepatitis-C virus (HCV) have been investigated theoretically against the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. HCV and SARS-CoV-2 are both +ssRNA viruses. At 25^o C beclabuvir, a non-nucleoside inhibitor of the RdRp_HCV can efficiently bind to RdRp _SARS-CoV-2 (ΔG_AutoDock = -9.95 kcal mol^-1) with an inhibition constant of 51.03 nM. Both the ΔG_London and ΔG_{GBVI / WSA} values were - 9.06 and - 6.67 kcal mol^-1, respectively for binding of beclabuvir to RdRp_SARS-CoV-2. In addition, beclabuvir has also shown better binding free energy with RdRp_SARS-CoV-2 (ΔG_vina = -8.0 kcal mol^-1) than that observed with the Thumb 1 domain of RdRp_HCV (ΔG_vina = -7.1 kcal mol^-1). InterProScan has suggested the RNA-directed 5'-3' polymerase activity exists within 549^th to 776^th amino acid residues of RdRp_SARS-CoV, where the major amino acid residues interacting being I591, Y621, C624, D625, A690, N693, L760, D762, D763, and E813-N817. Molecular interaction suggests occupancy of beclabuvir inside the active site environment of the RdRp_SARS-CoV-2, the enzyme essential for viral RNA synthesis. In conclusion, results suggest beclabuvir may serve as an anti-SARS-CoV-2 drug.

One notable features of the SARS-CoV-2 genome is that the spike protein of SARS-CoV-2 has a functional polybasic (furin) cleavage site (RRAR) at the S1–S2 boundary through the insertion of 12 nucleotides encoding PRRA. To date, the furin cleavage site (FCS) remains an experimentally uncharted territory both structurally and functionally. For instance, whether or not FCS is actually cleaved, before or after viral cell entry or exit, still remains to be experimentally investigated. With currently available structural data, this article presents a computational structural characterization of the FCS inserted into SARS-CoV-2 spike glycoprotein, and puts forward a set of structural hypothesis against the hypothesis of SARS-CoV-2 from purposeful manipulation: (1), the inserted FCS does not alter, neither stabilize nor de-stabilize, the overall structure of SARS-CoV-2 spike glycoprotein; (2), the net structural consequence of FCS is the insertion of a furin cleavage site into SARS-CoV-2 spike glycoprotein, whose S1 and S2 subunits will still be bonded together even if the FCS is actually cleaved by furin protease.

The COVID-19 pandemic is placing unprecedented stress on healthcare systems around the world. Although Radiation Oncology Departments are not at the frontline of fighting this infectious disease, it is important to implement COVID-19 policies to reduce risk of staff and patient exposure, and to limit the risk of department shutdown or downtime. This brief report describes the policy implemented at George Washington University Radiation Oncology to manage the risks of COVID-19. This includes a General Statement related to the priorities of the Radiation Oncology department, a screening procedure for new and follow-up patients, management policies for critical and non-critical patients with COVID-19 or under quarantine, a policy for the management of patients currently under treatment who are diagnosed or placed in quarantine, a clinical escalation action plan, guidelines for staff meetings and travel, and procedure management. This policy was implemented at George Washington University Radiation Oncology after the first case of COVID-19 was reported in Washington DC on March 7, 2020.

The transnational spread of coronavirus (2019-nCoV) first detected in Wuhan is causing global panic; thus, accelerated research into clinical intervention is of high necessity. The spike glycoprotein structure has been resolved, and its affinity to human angiotensin-converting enzyme 2 (ACE-2) has been experimentally validated. Here, using computational methods, a metastable conformation of 2019-nCoV-RBD/ACE-2 complex has been revealed and FDA-database of approved drugs have been docked into the interface. Darunavir has been discovered as high ligand affinity candidate capable of disrupting communication between 2019-nCoV-RBD and ACE-2. Darunavir, in addition to its previously known anti-HIV protease inhibitor is now repurposeable for the treatment 2019-nCoV disease acting via disruption of cellular recognition, binding and invasion.

A novel coronavirus (SARS-CoV-2) that is initially found to trigger human severe respiratory illness in Wuhan City of China in 2019, has killed 2,718 people in China by February 26, 2020, and which has been recognized as a public health emergency of international concern as well. And the virus has spread to more than 38 countries around the world. However, the drug has not yet been officially licensed or approved to treat SARS-Cov-2 infection. NSP12-NSP7-NSP8 complex of SARS-CoV-2, essential for viral replication and transcription, is generally regarded as a potential target to fight against the virus. According to the NSP12-NSP7-NSP8 complex (PDB ID: 6NUR) structure of SARS, two homologous models were established for virtual screening in the present study, namely NSP12-NSP7 interface model and NSP12-NSP8 interface model. Seven compounds (Saquinavir, Tipranavir, Lonafarnib, Tegobuvir, Olysio, Filibuvir, and Cepharanthine) were selected for binding free energy calculations based on virtual screening and docking scores. All seven compounds can combine well with NSP12-NSP7-NSP8 in the homologous model, providing drug candidates for the treatment and prevention of SARS-CoV-2.

The NA61/SHINE experiment studies hadron production in hadron-hadron, hadron-nucleus and nucleus-nucleus collisions. The physics programme includes the study of the onset of deconfinement and search for the critical point as well as reference measurements for neutrino and cosmic ray experiments. For strong interactions, future plans are to extend the programme of study of the onset of deconfinement by measurements of open-charm and possibly other short-lived, exotic particle production in nucleus-nucleus collisions. This new programme is planned to start after 2020 and requires upgrades to the present NA61/SHINE detector setup. Besides the construction of a large acceptance silicon detector, a 10-fold increase of the event recording rate is foreseen, which will necessitate a general upgrade of most detectors.

The Biginelli reaction is a highly versatile reaction, which leads to dihydropyrimidinones/thiones. This scaffold is reported as being a privileged structure due to its ability to interact with biological targets. Synthesis of ethyl 4-(2-fluorophenyl)-6-methyl-2-thioxo-1-(p-tolyl)-1,2,3,4-tetrahydropyrimidine-5-carboxylate was achieved through the Biginelli reaction using a functionalized thiourea. In silico studies demonstrated that the compound title showed good potential for interacting with ecto-5’-nucleotidase, which has been considered as a target in designs for anti-cancer drugs.

Abstract Background: Diabetes mellitus is dramatically increasing in the wide world. The managing of diabetes care emphasized the self-management education and support into patients’ care and family care. Objective: to review and synthesizes the effectiveness of DSME strategies involving family as a key person to provide social support for diabetes mellitus self-management of glycemic uncontrolled patients Method: Three databases through PubMed, CINAHL, and Scopus were reviewed to assess the relevant articles. The following search terms: “type 2 diabetes,” “self-management,” “family support,” and “glycemic uncontrolled.” We summarized details of family support on self-management among glycemic uncontrolled patients for 14 existing studies. Results: A total of 22 intervention studies were identified. Those studies have a heterogeneous of the education strategies, support perceived, follow-ups strategies and outcomes among type 2 DM. Family integration on diabetes self-management education (DSME) has a positive impact on several outcomes including, self-care behaviors, psychological outcomes, self-efficacy and clinical outcomes Conclusions: This systematic review found robust data related to the integration of family support on diabetes self-management among glycemic uncontrolled patients. Consequently, the improvement in outcomes was identified. Implications: The findings suggest model of family engagement is better and needed for sustaining the diabetes care in the long-term care

Glacier dynamics play an important role in the mass balance of many glaciers, ice caps and ice sheets. In this study we exploit Radarsat-2 (RS-2) Wide Fine (WF) data to determine the surface speed of Svalbard glaciers in the winters of 2012/2013 and 2013/2014 using Synthetic Aperture RADAR (SAR) offset and speckle tracking. The RS-2 WF mode combines the advantages of the large spatial coverage of the Wide mode (150 x 150 km) and the high pixel resolution (9m) of the Fine mode and thus has a major potential for glacier velocity monitoring from space through offset and speckle tracking. Faster flowing glaciers (1.95 m d^-1 - 2.55 m d^-1) which are studied in detail are Nathorstbreen, Kronebreen, Kongsbreen and Monacobreen. Using our Radarsat-2 WF dataset, we compare the performance of two SAR tracking algorithms, namely the GAMMA Remote Sensing Software and a custom written MATLAB script (GRAY method) that has primarily been used in the Canadian Arctic. Both algorithms provide comparable results, especially for the faster flowing glaciers and the termini of slower tidewater glaciers. A comparison of the WF data to RS-2 Ultrafine and Wide mode data reveals the superiority of RS-2 WF data over the Wide mode data.

Ca2+ can boost protein-protein interactions and, if present at an appropriate level, can potentially improve the physicochemical properties of protein gels and films. This study aimed to determine the effect of CaCl2 (0, 0.01 0.025 0.05% w/w) on the optical, water affinity, and mechanical char-acteristics of glycerol (Gly)- and sorbitol (Sor)-plasticized pea protein isolate (PPI) films. The CaCl2 caused darkening and a color shift of the films from yellow to yellow-green. Additionally, de-creased light transmission, particularly in the UV range, and reduced moisture content were observed. The CaCl2 decreased the water vapor permeability (WVP) of the Gly-plasticized film by an average of 20%, with no effect on the Sor-plasticized film. All films were completely soluble in water. The CaCl2 negatively impacted the mechanical integrity of the films, reducing the tensile strength of the Gly- and Sor-plasticized films by ~16% and 14-37%, respectively. Further increases in CaCl2 content (0.1% and 0.2% w/w) led to concentration-dependent cracks, suggesting protein over-crosslinking. In summary, the incorporation of CaCl2 into PPI films did not provide signif-icant benefits and actually worsened key properties such as transparency and mechanical strength. The type of plasticizer influenced how CaCl2 affected some properties of the PPI film.

Seedling emergence is crucial for the establishment and growth of crops and is influenced by topsoil temperature and moisture. Mulching has been widely used to promote seedling emergence in areas with a cold spring. This study was conducted to determine and simulate the effects of transparent plastic film mulch on surface soil moisture, temperature, and seedling emergence of spring maize in Northwest China. Four treatments were used: no mulching (CK), full plastic film mulch (PMF), and partial plastic film mulch, 60 cm in width (PM60, 40 cm uncovered between rows of mulch) or 30 cm in width (PM30, 20 cm uncovered between rows of mulch). The effects of soil water conservation and temperature enhancement gradually decreased as the plastic film width decreased, but there was little difference between PMF and PM60 treatments. Soil-water-modified growing degree days (WGDD) described the beneficial effects of soil moisture and temperature with respect to seedling emergence under mulching conditions. Plastic film mulching markedly accelerated seedling emergence and increased final seedling emergence rate because mulching can shorten the autotrophy duration and maintain surface soil moisture, which leads to increased germination. The effects of seedling emergence improvement decreased as the plastic film width decreased. The relationship between WGDD and cumulative relative seedling emergence (CRE) was adequately described by a Gompertz function.

This paper introduces a novel framework for zero-shot learning (ZSL), i.e., to recognize new categories that are unseen during training, by distilling knowledge from foundation models. Specifically, we first employ ChatGPT and DALL-E to synthesize reference images of unseen categories from text prompts. Then, the test image is aligned with text and reference images using CLIP and DINO. Finally, the predicted logits are aggregated according to their confidence to produce the final prediction.Experiments are conducted on multiple datasets, including CIFAR-10, CIFAR-100, and TinyImageNet. The results demonstrate that our model can significantly improve classification accuracy compared to previous approaches, achieving AUROC scores above 96\% across all test datasets. Our code is available at https://github.com/1134112149/MICW-ZIC.

المستخلص تصنيع لقاح مكون من الحمض النووي الريبوزي الرسول الخاص بالبروتينات المسئولة عن انتاج البروتينات نيورامنيديز والهيم اجليوتونين لفيروسي الانفلونزا الخنازير والطيورمحاط بجزيئات دهنية بحجم النانوميتر عدوى انفلونزا الخنازير وانفلونزا الطيور مشكلة خطيرة تؤرق العالم كله هذه الايام خصوصا انها مميتة لكثير من اطفال العالم . بعد فترة التعافي من الاصابة تتكون المناعة المكتسبة ضدها لمدة عام تقريبا. هذه الانفلونزا تسبب تسمم فيروسي في الدم بالاضافة للالتهاب الرئوي وهذامن بين اكبرالاسباب للوفاة بين الاطفال قبل سن عامين عالميا بشكل مباشر. الهدف من الدراسة هو انتاج لقاح الحمض النووي الريبوزي الرسول من نوع الام بالنانوتكنولوجي لبروتينات الهيم اجليوتونين والنيورامنيديز الموجودة على سطح هذه الفيروسات التي تساعدتها في الاتصاق بالعائل الذي ستتكاثر داخل خلاياه بالجهاز التنفسي. هذه الدراسة دراسة استكشافية ومن خلالها استطاعنا تصميم هذا اللقاح باستعمال نظام توصيل للقاح بالنانوتكنولوجي حجم جزيئاته 70نانوميمتر. اللقاح الجديد اظهر فاعلية بنسبة 60% واظهر فاعلية حيوية مقاربة واثار جانبية اقل بالمقارنة باللقاحات المتوفرة حاليا بالسوق الدوائي ضد هذا النوع من الفيروسات الوبائية. ABSTRACT Background: Worldwide, Swine and Avian influenza, or the H1N1 and H5N1 serotypes of the Influenza A virus, is a highly contagious illness. In recent years, the global incidence of mortality rate has surpassed 284,000 fatalities. Aim of the study: The production of mRNA vaccine lipid nanoparticles (LNP) to combat the deadly strains of Avian and Swine influenza (H1N1 and H5N1 of the influenza A serotype). Methodology: Polymerase chain reaction (PCR) was used to clone genes of interest encoding Haemagglutinin (HA) and Neuraminidase (NA) of Influenza A virus strains (H5N1 and H1N1) known as Avian flu and Swine flu, respectively. The genes were then inserted using the EcoR1, BAM Hind II restriction endonuclease type II, and Ligase enzyme into the pET-21(+) transcription vector plasmid. On the other hand, the hybrid transcription vectors were mixed with T7 RNA polymerase and ribonucleotides within a test tube after being linearized using EcoR II. Following their purification via reversed-phase high-performance liquid chromatography (RP-HPLC), the mRNAs of the HA and NA were encased in 70 nm LNPs and subjected to reverse-phase high-performance liquid chromatography (RP-HPLC). Lastly, immunogenicity studies were performed in stages 1/2 of randomized human and preclinical clinical trials. Results: The bivalent vaccination had around 63% efficacy in preclinical studies and approximately 60% efficacy in randomized human clinical trials. As shown by the ELISA test, strong neutralizing antibodies against HA were prevalent. Conclusion: The current study is a promising effort because of the development of the novel LNP-mRNA vaccine, which could lower the incidence of Avian and Swine flu infectious disorders.

ABSTRACT Purpose: Tongue image analysis for disease diagnosis is an ancient traditional non-invasive diagnosis technique widely used by traditional medicine practitioners. Deep Learning based multi-label disease detection models offer tremendous potential to clinical decision support systems, by facilitating preliminary diagnosis. Methods: In this work, we propose a multi-label disease detection pipeline, where in observation and analysis of tongue images captured and received via smartphones assist in predicting the health status of an individual. All images are voluntarily given by subjects consulting collaborating physicians. Images thus acquired are first and foremost classified either into a diseased or a normal category by a 5-fold cross-validation algorithm using a convolution neural network (MobileNetV2) model for binary classification. Once the diseased label is predicted, the image is used to diagnose multiple diseases using the prediction algorithm based on DenseNet121. Results: Average accuracy of 93 % was achieved in classifying diseased from normal healthy tongue by detection model with MobileNetV2 architecture. Multilabel disease classification produced more than 90% accurate results for the seven class labels considered. Conclusion: AI based image analysis shows promising results and an extensive dataset could provide further improvements to this approach. Rather than employing high-cost sophisticated image capturing setup, experimenting with smartphone images opens opportunity to provide preliminary health status to individuals on smartphone prior to further line of treatment and diagnosis.

In an effort to enhance the efficiency and safety of open-pit mines, this study explores the optimization of end slope road parameters and slope structures, specifically focusing on unmanned driving lanes.A significant aspect of the study is the development of a truck trajectory offset model, which considers the different reaction times between automated sensors and human drivers in adapting to environmental changes. To test these concepts, the study uses numerical simulations to confirm the stability of the proposed end slope designs. Using Victory West Mine No. 1 as a case study, the research determines the optimized width for unmanned driving lanes and the maximum angle for safe steepening of end slopes. The findings indicate that the optimized unmanned lane width for NTE240 mining dump trucks is 1743 mm, allowing for a 2-degree increase in the slope angle at the south end slope. This optimization leads to a steep mining stripping volume of 3.2735 million m³ and a coal output of 2.49628 million tons, maintaining a stripping ratio of 1.31m³/t. These results demonstrate that the unmanned driving road width optimization not only ensures slope safety but also significantly boosts the economic benefits of steep mining in open-pit mines.

In the present work report, the MgAl₂O₄and the Ag/MgAl₂O₄ samples were successfully synthesized by the modified hydrothermal and the isovolumetric impregnation methods, respectively. The structural properties of the prepared samples were systematically characterized by XRD, SEM, TEM, DRS, XPS and et al techniques. The photocatalytic degradation of methylene blue by the Ag/MgAl₂O₄ and MgAl₂O₄ samples was comparatively studied under UV lamp irradiation. The results revealed that the prepared Ag/MgAl₂O₄ (pH=6) samples were the most active among the samples in photocatalytic of methylene blue. Under UV lamp irradiation, the Ag/MgAl₂O₄ (pH=6) photodegradation of methylene blue reached to 89.6% within 120 min. And the Ag/MgAl₂O₄ (pH=6) complex photocatalysts displayed a high photochemical stability under repeated irradiation. Repeated irradiate the Ag/MgAl₂O₄ (pH=6) compound, which indicated it had a high photochemical stability.

In this study, we provided an empirical testability of the FF3FM against the co-moment-augmented FF3FM using the Newey–West GMM methods to account for potential endogeneity. The results showed that value risk is not significantly priced, and systematic skewness and systematic kurtosis play more important roles in explaining asset return than market and size factors. We discovered that there is much to gain in moving from the incumbent FF3FM to the co-moment-augmented FF3FM. By extending this study to Nigeria and using out-of-sample data that span across the recent COVID-19 period, the study has contributed to existing knowledge significantly. The study concludes that the co-moment-augmented FF3FM is superior to the incumbent FF3FM in pricing assets, and the anomalies associated with the return-size risk factor relationship are reduced by accounting for systematic skewness and systematic kurtosis in the FF3FM. Therefore, we recommend that investors should take a long position in size-hedged portfolios and hold systematic skewness and kurtosis as constant, and vice visa.

Background/Objectives: This review examines the evolution of lyotropic liquid crystals (LLCs) in ocular drug delivery, focusing on their ability to address the challenges associated with traditional ophthalmic formulations. The study aims to underscore the enhanced bioavailability, prolonged retention, and controlled release properties of LLCs that significantly improve therapeutic outcomes; Methods: The review synthesizes data from various studies on both bulk-forming LLCs and liquid crystal nanoparticles (LCNPs). It also considers advanced analytical techniques, including the use of machine learning and AI-driven predictive modeling, to forecast the phase behavior and molecular structuring of LLC systems. Emerging technologies in biosensing and real-time diagnostics are discussed to illustrate the broader applicability of LLCs in ocular health; Results: LLCs are identified as pivotal in promoting targeted drug delivery across different regions of the eye, with specific emphasis on the tailored optimization of LCNPs. The review highlights principal categories of LLCs used in ocular applications, each facilitating unique interactions with physiological systems to enhance drug efficacy and safety. Additionally, novel applications in biosensing demonstrate LLCs' capacity to improve diagnostic processes; Conclusions: Lyotropic liquid crystals offer transformative potential in ocular drug delivery by overcoming significant limitations of conventional delivery methods. The integration of predictive technologies and biosensing applications further enriches the utility of LLCs, indicating a promising future for their use in clinical settings. This review points to continued advancements and encourages further research in LLC technology to maximize its therapeutic benefits.