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Stream speed pattern of traffic plays a crucial role in urban transportation. The presence of on-street parking significantly reduces this speed by narrowing the carriageway width available for traffic movement, impeding the traffic flow. Therefore, understanding the traffic flow behavior in the context of on-street parking could be challenging. In this context, the present study explores the influence of on-street parking on the stream speed of regular traffic. To achieve this, data were collected at various ideal and parking sections. The stream speed ranges from 39.28 km/h to 51.47 km/h for ideal sections with significant percentage reduction observed at parking sections, ranging from 39.09% to 81.30%. This speed reduction was then modelled considering the most significant parking parameters conceptualized in this study. The findings of the study offer valuable insights that can be implemented for developing the on-street parking norms.

Efficient energy management is crucial for optimizing greenhouse (GH) operations and promoting sustainability. This paper presents a novel multi-objective optimization approach tailored for GH energy management, aiming to minimize grid energy consumption while maximizing battery state of charge (SOC) within a specified time frame. The optimization problem integrates decision variables such as network power, battery power, and battery energy, subject to constraints based on battery capacity and initial energy, along with minimum and maximum energy from the battery storage system. Through the comparison of a smart energy management system (EMS) with traditional optimization algorithms, the study evaluates its efficiency. Key hyperparameters essential for the optimization problem, including plateau time, prediction time, and optimization time, are determined using the ellipse optimization method. Treating the GH as a microgrid, the analysis encompasses energy management indicators and loads. A simulation conducted via Simulink in MATLAB software (R2021b) demonstrates a significant enhancement, with the smart EMS achieving a more than 50% reduction in the objective function compared to conventional EMS. Moreover, the EMS exhibits robust performance across variations in the load power and irradiation profile. Under partial shading conditions, the EMS maintains adaptability, with a maximum objective function increase of 0.35553%. Aligning the output power of photovoltaic (PV) systems with real-world conditions further validates the EMS’s effectiveness in practical scenarios. The findings underscore the efficiency of the smart EMS in optimizing energy consumption within GH environments, offering promising avenues for sustainable energy management practices. This research contributes to advancing energy optimization strategies in agricultural settings, thereby fostering resource efficiency and environmental stewardship.

Pseudomonas sp. SBMCH11 was newly isolated from maritime soil samples which was identified by morphological, biochemical, and 16S rRNA gene sequencing. The isolated Pseudomonas sp. SBMCH11 had significant antibacterial activity against clinical bacterial strains including Pseudomonas aeruginosa and Staphylococcus aureus. Subsequently, high concentrations of antibacterial substances were achieved by optimizing the following parameters: pH (7.0), carbon (1 %), nitrogen sources (casein 0.2 %), NaCl (10 %), and incubation time (120 hrs). Furthermore, the extracted component from the Pseudomonas sp. SBMCH11 was shown to have a significant inhibitory effect on tested clinical pathogens. On the other hand, the extracted compound was confirmed as 2,4 di-tertbutylphenol (2,4 DTBP) by GC–MS with a molecular weight of 206.5 Daltons. Based on these findings, the isolated 2,4 DTBP could be recognized as a promising bioactive molecule for further antibacterial medication development. Compounds identified in the maritime environment from microorganisms, especially Pseudomonas sp. SBMCH11 could be regarded as a potential bio-factory for the synthesis of antibacterial compounds to suppress large numbers of pathogenic bacteria in the natural environment.

The increasing popularity and number of electric vehicles (EVs) globally have resulted in a growing demand for efficient, reliable, and effective electric vehicle charging station (EVCS) infrastructure. However, the development and implementation of this infrastructure involves various challenges, including the variety of EVs, charging and battery technologies, high installation costs, limited grid capacity, and uncertainties regarding future demand, and raises issues regarding the quality, security, and stability of the power system. This paper presents a holistic understanding of the challenges, mitigation approaches, and available technologies and protocols related to EVCS network deployment. Moreover, optimization strategies such as location planning, network integration, scheduling charging time, and planning price, which involve maximizing the utilization of charging stations and minimizing associated costs, and their modeling techniques are highlighted. This review aims to provide insights to develop sustainable, efficient EVCS infrastructure while overcoming the challenges and optimizing the benefits.

In an era characterized by severe climate change, dwindling resources, and a growing world population, the agricultural industry is facing unprecedented challenges. On the other hand, overuse of natural resources has emerged as a major concern worldwide. Greenhouses (GHs) have been developed as central environments capable of growing a diverse range of high-quality agricultural products throughout the year, regardless of external weather conditions. However, conventional GHs often impose significant costs on energy resources for their heating and cooling operations, thus presenting sustainability challenges. To address these pressing concerns, using new smart technologies as well as the integration and development of renewable energy sources, including photovoltaics (PVs), wind turbines (WT), and geothermal systems, have gained momentum. This integration not only increases the ecological footprint of GHs but also reduces their dependence on conventional energy sources. Furthermore, the adoption of smart GH technologies, characterized by advanced control and automation systems, holds significant promise in energy optimization and efficiency. Hence, this systematic review attempts to carefully examine the optimal and practical methods that include the design, fabrication, control, energy management, and operation of smart GHs. This review includes an in-depth analysis of GH structures, building materials, cooling and heating systems, new dark GH concepts, and smart lighting systems. In addition, it addresses effective strategies to curb energy consumption in smart GHs. By synthesizing and synthesizing existing research and practical experiences, this paper seeks to provide valuable insights and recommendations to facilitate the efficient and sustainable design, construction, and operation of smart GHs. Ultimately, this work aims to promote resource-efficient and environmentally conscious practices in the agricultural energy sector.

AbstractEnvironmental DNA (eDNA) methods complement traditional aquatic monitoring surveys and are especially advantageous for rare and listed species to detect spatial and temporal distribution patterns. However, improvements in ease of use and portability could increase the utility of eDNA methods, leading to more widespread application, including expanding its role in management decision‐making processes. We describe the development of an eDNA detection assay for delta smelt (Hypomesus transpacificus), an endangered fish in the San Francisco Estuary, using SHERLOCK (Specific High‐Sensitivity Enzymatic Reporter Unlocking). SHERLOCK is a clustered regularly interspaced short palindromic repeats (CRISPR)‐based diagnostic tool with the ability to detect species‐specific genetic variants, making it ideal for genetic‐based taxonomic identification of any organism. Because of its high sensitivity and specificity, SHERLOCK is adaptable to eDNA detection in water samples. Here, we describe adaptation of a delta smelt SHERLOCK assay for use with estuarine water eDNA samples. This version of the assay exhibits increased sensitivity compared to the original delta smelt SHERLOCK protocol (new limit of detection approximately three copies per reaction compared to ~300 in original assay) and successfully detected delta smelt eDNA in both experimental and natural contexts. Overall, our results demonstrate that SHERLOCK eDNA detection offers managers an alternative, isothermal methodology, and highlights some challenges for detection of rare, endangered species at low abundance.

The present investigation was aimed at studying the improvement of fermentation and nutritive quality of rice straw-maize silage by the inclusion of different additives. In the experiment, paddy straw and green maize fodder were mixed in ratios of 100:0, 75:25, 50:50, 25:75, and 0:100 for silage preparation. These combinations were made in a triplicate and added with no additive (C), 2% urea (T1), 1% molasses (T2) and a mixture of 2% urea and 1% molasses (T3) in completely randomized design (CRD). The silages were harvested after 45 days and then analyzed for chemical composition, fermentation characteristics and anti-nutritional factors. Results revealed that dry matter (DM), acid detergent fibre (ADF), neutral detergent fibre (NDF), crude fibre (CF), ash and pH increased with an increase in the proportion of paddy straw in all combinations. Addition of 2% urea increased in vitro dry matter digestibility (IVDMD), crude protein (CP) and total gas production (TGP) of paddy straw and maize fodder silage. Urea treatment considerably reduced the oxalate content and increased the tannin content of paddy straw and maize fodder silage. In the present study, silage prepared by combining paddy straw and maize fodder in ratio of 25:75 had good aroma and fermentation characteristics which can be, therefore, utilized for effective silage making.

Summary: Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health—Climate Risk framework.

Peripheral arterial disease (PAD) is one of the underdiagnosed and undertreated vascular diseases despite its significant burden in India. In India, the etiological aspects, diagnostic approaches, treatment modalities, and other preventive measures probably vary in different regions. Therefore, this consensus was developed that provides a unified approach for physicians to effectively diagnose and manage PAD in India. In this consensus, we identify that the prevalence of PAD varies from 5% to 25% in Indian setting. Both atherosclerotic and non-atherosclerotic risk factors may underlie PAD. Asymptomatic PAD remains the most common presentation of the disease. The detailed clinical history, physical changes in the lower leg skin, and examination of peripheral pulses can provide clues to the diagnosis. Ankle-brachial index and Duplex ultrasound are advised as the initial choice of diagnostic measures. Besides control of risk factors such as hypertension, diabetes, dyslipidemia, and smoking, pharmacological treatment with anti-platelet and antithrombotic drugs is advised. By efficacy, ticagrelor is considered equivalent to clopidogrel and cilostazol is advised in intermittent claudication. In the revascularization of tibio-pedal lesions, endovascular therapy is effective and arterial bypass with vein graft may be needed in difficult and extensive revascularization scenarios. In these lesions, prosthetic grafts must be avoided. Diabetic foot ulcer management is challenging as foot care among diabetics is poor. In limb, salvation should always be a priority with avoidance of amputation if possible. Stem cell therapy has been successful in PAD which can be advised to “no-option” patients to prevent amputation. Physicians should undertake effective screening of PAD and be considered “PAD Clinics” in India.

Abstract The COVID-19 pandemic outbreak led to a global ventilator shortage. Hence, various strategies for using a single ventilator to support multiple patients have been considered. A device called Ventil previously validated for independent lung ventilation was used in this study to evaluate its usability for shared ventilation. We performed experiments with a total number of 16 animals. Eight pairs of pigs were ventilated by a ventilator or anesthetic machine and by Ventil for up to 27 h. In one experiment, 200 ml of saline was introduced to one subject’s lungs to reduce their compliance. The experiments were analyzed in terms of arterial blood gases and respiratory parameters. In addition to the animal study, we performed a series of laboratory experiments with artificial lungs (ALs). The resistance and compliance of one AL (affected) were altered, while the tidal volume (TV) and peak pressure (Ppeak) in the second (unaffected) AL were analyzed. In addition, to assess the risk of transmission of pathogens between AL respiratory tracts, laboratory tests were performed using phantoms of virus particles. The physiological level of analyzed parameters in ventilated animals was maintained, except for CO2 tension, for which a permissive hypercapnia was indicated. Experiments did not lead to injuries in the animal’s lungs except for one subject, as indicated by CT scan analysis. In laboratory experiments, changes in TV and Ppeak in the unaffected AL were less than 11%, except for 2 cases where the TV change was 20%. No cross-contamination was found in simulations of pathogen transmission. We conclude that ventilation using Ventil can be considered safe in patients undergoing deep sedation without spontaneous breathing efforts.

Ochradenus baccatus, also known as "Taily Weed," is a perennial shrub that belongs to the Resedaceae family and is often used as a folk medicine for the treatment of headache, fever or sexual disorders in the Middle Eastern countries. It is also used as an antibiotic, cooling agent and deodorant. Due to its widespread use in traditional medicine in the Middle Eastern countries and lack of scientific evidence, it is being investigated for its phytotherapeutic potential in different disease conditions.

Direct-seeded rice (DSR) is a promising alternative to the traditional puddled rice system. It has become more popular among rice growers as a result of socioeconomic shifts and global climate change. Although DSR offers advantages, rice plants experience greater anaerobic stress at sowing from unpredicted rainfall. Rice is unique among cereals in its ability to germinate under anaerobiosis. The coleoptile of rice rapidly elongates above the water surface to obtain more oxygen and enhance vigorous seedling growth. A panel of 115 landraces and four check varieties were subjected to anaerobic stress with a water level of 10 cm for up to 15 days. The present study observed significant variation in anaerobic germination percentage (AGP) (10%–100%) and anaerobic vigor index (AVI) (150–4,433). Landraces Karuthakar, Poovan samba, Mattaikar, Edakkal, Manvilayan, and Varappu kudainchan were identified as genotypes tolerant to early water submergence. The shoot and root length of susceptible landraces were significantly lower than the tolerant landraces under hypoxia condition, implying that landraces with longer shoots and roots had a higher survival rate. The response index substantiated this. The results clearly show that tolerant and moderately tolerant landraces possessed higher mean values for root and shoot lengths than susceptible landraces. The landraces grouped under the long–bold category had superior AGP and AVI scores to other grain type groups. This raises the possibility that differences in kernel breadth, which is linked to grain type, could affect anaerobic germination potential. Molecular confirmation using gene-specific markers, viz., DFR, TTP_G4, RM478, RM208, and RM24161, for which the polymorphic information content (PIC) value ranged from 0.36 (RM478) to 0.68 (RM206) suggests that this diverse panel of landraces must be assessed further using advanced molecular tools to precisely clarify the genetic mechanism behind this phenomenon. The tolerant landraces thus identified may become donors in breeding programs. The introduction of these traits would contribute to the development of rice varieties tolerant to anaerobic stress, resulting in sustainable yields. This solution could promote the DSR system across the world.

Non-Alcoholic Fatty Liver Disease (NAFLD) is a common condition affecting around 10–25% of the general adult population, 15% of children, and even > 50% of individuals who have type 2 diabetes mellitus. It is a major cause of liver-related morbidity, and cardiovascular (CV) mortality is a common cause of death. In addition to being the initial step of irreversible alterations of the liver parenchyma causing cirrhosis, about 1/6 of those who develop NASH are at risk also developing CV disease (CVD). More recently the acronym MAFLD (Metabolic Associated Fatty Liver Disease) has been preferred by many European and US specialists, providing a clearer message on the metabolic etiology of the disease.The suggestions for the management of NAFLD are like those recommended by guidelines for CVD prevention. In this context, the general approach is to prescribe physical activity and dietary changes the effect weight loss. Lifestyle change in the NAFLD patient has been supplemented in some by the use of nutraceuticals, but the evidence based for these remains uncertain. The aim of this Position Paper was to summarize the clinical evidence relating to the effect of nutraceuticals on NAFLD-related parameters. Our reading of the data is that whilst many nutraceuticals have been studied in relation to NAFLD, none have sufficient evidence to recommend their routine use; robust trials are required to appropriately address efficacy and safety.

(1) Background: Understanding the physicians’ knowledge, attitudes, and antimicrobial prescribing behavior is a crucial step towards designing strategies for the optimal use of these agents. (2) Methods: A cross-sectional online survey was conducted among clinicians across India between May and July 2022 using a self-administered questionnaire in English comprising 35 questions pertaining to demographic characteristics, knowledge, attitude, and practices domains. (3) Results: A total of 544 responses were received from 710 physicians contacted. Sixty percent of participants were males, with mean age of 34.7 years. Mean ± Standard Deviation scores for knowledge, attitude, and practices domains were 8 ± 1.6, 20.2 ± 3.5, and 15.3 ± 2.1, respectively. Higher scores were associated with basic [odds ratio (95% Confidence Interval), p value: 2.95 (1.21, 7.2), 0.02], medical and allied sciences [2.71 (1.09, 6.67), 0.03], and central zone [3.75 (1.39, 10.12), 0.009]. A substantial proportion of dissatisfactory responses were found regarding hospital antibiograms, antibiotics effective against anaerobes, WHO AWaRe (access, watch, and reserve) classification of antibiotics, and the role of infection prevention and control (IPC) measures in the containment of antimicrobial resistance (AMR). (4) Conclusions: There is a need to sensitize and educate clinicians on various issues related to antimicrobial use, such as antibiograms, double anaerobic cover, IPC practices, and guideline-based recommendations, to curb the AMR pandemic.

Recently nanopolyphenols are gaining widespread interest in the drug discovery domain. Nanonization of polyphenols has greatly affected the therapeutic index owing to improvement in pharmacokinetic and biopharmaceutical obstacles linked with the use of natural polyphenols. They have been looking at an emerging paradigm for an array of disease symptoms. In this article, we have explored the therapeutic potential of nanopolyphenols in oxidative stress-induced diseases such as neurodegeneration, cancer, obesity, and diabetes. This article will present the current state of the art of various nanopolyphenols targeting oxidative stress-induced diseases. The advanced fabrication strategies presented for polyphenols including nanocrystal, mesoporous silica nanoparticles, nanoparticles, nanoliposome, gold nanoparticle, and nanosuspension are discussed. The information presented in light of recent in vitro, in vivo, and clinical evidence for nanoformulation and delivery of polyphenols may show a new dimension to future research in the realm of herbal therapy for oxidative stress-induced diseases. Significant information on the molecular mechanisms underlying linkages of oxidative stress with neurodegenerative diseases, cancer, obesity, and diabetes is discussed. Valuable information on dietary polyphenols in these diseases and their clinical data is presented. Based on different experimental evidence, the review findings support phenomenal therapeutic strategies for nanopolyphenolic fabrication with extended benefits and a condensed time frame. The status of clinical trials conducted on nanopolyphenols is presented. Although clinical trials conducted on nanopolyphenols for mentioned diseases are few, we have tried to present as much available clinical data in this article.

Background: Atherosclerotic cardiovascular diseases (ASCVD) including myocardial infarction, stroke and peripheral arterial disease continue to be major causes of premature death, disability and healthcare expenditure globally. Preventing the accumulation of cholesterol-containing atherogenic lipoproteins in the vessel wall is central to any healthcare strategy to prevent ASCVD. Advances in current concepts about reducing cumulative exposure to apolipoprotein B (apo B) cholesterol-containing lipoproteins and the emergence of novel therapies provide new opportunities to better prevent ASCVD. The present update of the World Heart Federation Cholesterol Roadmap provides a conceptual framework for the development of national policies and health systems approaches, so that potential roadblocks to cholesterol management and thus ASCVD prevention can be overcome. Methods: Through a review of published guidelines and research papers since 2017, and consultation with a committee composed of experts in clinical management of dyslipidaemias and health systems research in low-and-middle income countries (LMICs), this Roadmap identifies (1) key principles to effective ASCVD prevention (2) gaps in implementation of these interventions (knowledge-practice gaps); (3) health system roadblocks to treatment of elevated cholesterol in LMICs; and (4) potential strategies for overcoming these. Results: Reducing the future burden of ASCVD will require diverse approaches throughout the life-course. These include: a greater focus on primordial prevention; availability of affordable cholesterol testing; availability of universal cholesterol screening for inherited dyslipidaemias; risk stratification moving beyond 10-year risk to look at lifetime risk with adequate risk estimators; wider availability of affordable cholesterol-lowering therapies which should include statins as essential medications globally; use of adequate doses of potent statin regimens; and combination therapies with ezetimibe or other therapies in order to attain and maintain robust reductions in LDL-C in those at highest risk. Continuing efforts are needed on health literacy for both the public and healthcare providers, utilising multi-disciplinary teams in healthcare and applications that quantify both ASCVD risk and benefits of treatment as well as increased adherence to therapies. Conclusions: The adverse effects of LDL-cholesterol and apo B containing lipoprotein exposure are cumulative and result in ASCVD. These are preventable by implementation of different strategies, aimed at efficiently tackling atherosclerosis at different stages throughout the human life-course. Preventive strategies should therefore be updated to implement health policy, lifestyle changes and when needed pharmacotherapies earlier with investment in, and a shift in focus towards, early preventive strategies that preserve cardiovascular health rather than treat the consequences of ASCVD.

Diabetes Mellitus is a metabolic disease that leads to microvascular complications like Diabetic retinopathy (DR), a major cause of blindness worldwide. Current medications for DR are expensive and report multiple side effects; therefore, an alternative medication that alleviates the disease condition is required. An interventional approach targeting the vascular endothelial growth factor (VEGF) remains a treatment strategy for DR. Anti-VEGF medicines are being investigated as the main therapy for managing vision-threatening complications of DR, such as diabetic macular oedema. Therefore, this study investigated the effect of flavonoid naringenin (NG) from citrus fruits on inhibiting early DR in zebrafish. When exposed to 130 mM glucose, the zebrafish larvae developed a hyperglycaemic condition accompanied by oxidative stress, cellular damage, and lipid peroxidation. Similarly, when adult zebrafish were exposed to 4% Glucose, high glucose levels were observed in the ocular region and massive destruction in the retinal membrane. High glucose upregulated the expression of VEGF. In comparison, the co-exposure to NG inhibited oxidative stress and cellular damage and restored the glutathione levels in the ocular region of the zebrafish larvae. NG regressed the glucose levels and cellular damage along with an inhibition of macular degeneration in the retina of adult zebrafish and normalized the overexpression of VEGF as a promising strategy for treating DR. Therefore, intervention of NG could alleviate the domestication of alternative medicine in ophthalmic research.

Genomic instability is a prominent hallmark of cancer, however the mechanisms that drive and sustain this process remain elusive. Research demonstrates that numerous cancers with increased levels of genomic instability ectopically express meiosis-specific genes and undergo meiomitosis, the clash of mitotic and meiotic processes. These meiotic genes may represent novel therapeutic targets for the treatment of cancer. We studied the relationship between the expression of the meiosis protein HORMAD1 and genomic instability in squamous cell carcinomas (SCCs). First, we assessed markers of DNA damage and genomic instability following knockdown and overexpression of HORMAD1 in different cell lines representing SCCs and epithelial cancers. shRNA-mediated depletion of HORMAD1 expression resulted in increased genomic instability, DNA damage, increased sensitivity to etoposide, and decreased expression of DNA damage response/repair genes. Conversely, overexpression of HORMAD1 exhibited protective effects leading to decreased DNA damage, enhanced survival and decreased sensitivity to etoposide. Furthermore, we identified a meiotic molecular pathway that regulates HORMAD1 expression by targeting the upstream meiosis transcription factor STRA8. Our results highlight a specific relationship between HORMAD1 and genomic instability in SCCs, suggesting that selectively inhibiting HORMAD1, possibly, through STRA8 signaling, may provide a new paradigm of treatment options for HORMAD1-expressing SCCs.

Abstract Background Olfactory neuroblastoma (ONB) or esthesioneuroblastoma (ENB) is a rare malignancy of the nasal cavity believed to arise from the olfactory epithelium. The goal of this study was to systematically review the genomics, epigenetics, and cytogenetics of ONB and to understand the potential clinical implications of these studies. Methods A systematic literature review was performed for articles published before May 2020 using Cochrane, Embase, Pubmed, and Scopus databases. Inclusion criteria included genomics, cytogenetics, and epigenetics studies on ONB. Exclusion criteria included studies not in English or systematic reviews. Articles and abstracts were reviewed by two independent reviewers to reduce bias during article selection and synthesis of results. Of the 36 studies included in this review, 24 were research articles and 12 were abstracts. Results Although recurrent mutations among ONB tumors are uncommon, alterations in TP53, DMD, PIK3CA, NF1, CDKN2A, CDKN2C, CTNNB1, EGFR, APC, cKIT, cMET, PDGFRA, CDH1, FH, SMAD4, FGFR3 and IDH2 genes have been reported in several recent studies. In addition, cytogenetic studies revealed that the landscape of chromosomal aberrations varies widely amongst ONB tumors. Conclusions The rare character of ONB has limited the sample size available for cytogenetic, genomic, and epigenetic studies and contributes to the limitations of this systematic review. Comprehensive genomic and epigenomic studies with larger cohorts are warranted to validate the initial reports summarized in this review and to identify potential therapeutic targets for ONB.

The accelerated adoption of distance learning in post-pandemic times has resulted in increasing research publications and review studies in a short time. This necessitates the exploration of a large corpus of academic publications for effective distance learning and learning strategies. As distance learning stakeholders have assimilated the transactional approach to understanding distance learning, transactional distance theory (TDT) is relevant to understand ways to reduce the distance between learners and educators for maximum effectiveness of distance learning. Our study applies TDT to review distance learning from a supply perspective and as a tool to ensure the improved quality of distance learning. This paper has two key contributions: we have presented evidence synthesis and conducted a foresight exercise. Following preferred reporting items for systematic reviews and meta-analyses guidelines, 275 documents published between 1994 and 2022 were identified for review. Our analysis revealed patterns, relationships, and trends in the application of TDT in various distance learning contexts. Most TDT research is conducted in social sciences (83.7%), with computer science accounting for 42.6% of the studies. The course materials' structure and design have also received considerable attention, with around 40.0% of the research focused on this area. For distance learning, studies revolve around factors such as student engagement, satisfaction, and TDT, which examine the distance between learners and instructors in various learning environments. Through systematic review and metaanalysis, we identify the three thematic areas in TDT research on distance learning. We have chartered themes on the effect of alternate design distance learning platforms on learner success, pushing the development boundaries in distance learning success through TDT, and the practical processes for designing successful distance learning courses via TDT-based pedagogical frameworks. In doing so, we streamline research in TDT and distance learning thematically and provide insight into further work. In addition, this study analyzed the relationships between sustainable development goal (SDG) and TDT literature. The co-citation analysis suggested that the strongest links were observed between education and innovation (SDG 4 and SDG 9), followed by education and gender equality (SDG 4 and SDG 5).

This study profiled various levels of engagement and related communication behaviours among 50 Asian Indian Tamil autistic children (AUT) and their mothers. The interaction was compared with two groups of mother-child dyads of non-autistic (NA) children, 50 in each group, matched for chronological age (CA), and for language level (LL). Results indicated that despite mother's efforts to engage with their children, autistic children were often 'engaged with objects' or remained 'unengaged' due to children's preference for solitary play, while NA children were often engaged in 'co-ordinated' and 'people engagement'. Across the three groups, mothers predominantly took the lead and dominated the interaction, irrespective of children's language levels. These initiations by the mothers were often to provide instructions and to ask 'What' questions. Autistic children initiated communication predominantly to ask for an object and responded often in the form of negations and protests with limited verbal output or non-verbally. Most of the communication behaviours of both children and mothers in AUT group was quantitatively and qualitatively different when compared to those in both the NA groups, indicating unique nature of interactions despite matching for CA or LL. The observations from the study highlights the need for considering adult's contingent behaviours also, while assessing communication skills of autistic children in order to provide effective intervention.

The current life-threatening and tenacious pandemic eruption of coronavirus disease in 2019 (COVID-19) has posed a significant global hazard concerning high mortality rate, economic meltdown, and everyday life distress. The rapid spread of COVID-19 demands countermeasures to combat this deadly virus. Currently, there are no drugs approved by the FDA to treat COVID-19. Therefore, discovering small molecule therapeutics for treating COVID-19 infection is essential. So far, only a few small molecule inhibitors are reported for coronaviruses. There is a need to expand the small chemical space of coronaviruses inhibitors by adding potent and selective scaffolds with anti-COVID activity. In this context, the huge antiviral chemical space already available can be analysed using cheminformatic and machine learning to unearth new scaffolds. We created three specific datasets called “antiviral dataset” (N = 38,428) “drug-like antiviral dataset” (N = 20,963) and “anticorona dataset” (N = 433) for this purpose. We analyzed the 433 molecules of “anticorona dataset” for their scaffold diversity, physicochemical distributions, principal component analysis, activity cliffs, R-group decomposition, and scaffold mapping. The scaffold diversity of the “anticorona dataset” in terms of Murcko scaffold analysis demonstrates a thorough representation of diverse chemical scaffolds. However, physicochemical descriptor analysis and principal component analysis demonstrated negligible drug-like features for the “anticorona dataset” molecules. The “antiviral dataset” and “drug-like antiviral dataset” showed low scaffold diversity as measured by the Gini coefficient. The hierarchical clustering of the “antiviral dataset” against the “anticorona dataset” demonstrated little molecular similarity. We generated a library of frequent fragments and polypharmacological ligands targeting various essential viral proteins such as main protease, helicase, papain-like protease, and replicase polyprotein 1ab. Further structural and chemical features of the “anticorona dataset” were compared with SARS-CoV-2 repurposed drugs, FDA-approved drugs, natural products, and drugs currently in clinical trials. Using machine learning tool DCA (DMax Chemistry Assistant), we converted the “anticorona dataset” into an elegant hypothesis with significant functional biological relevance. Machine learning analysis uncovered that FDA approved drugs, Tizanidine HCl, Cefazolin, Raltegravir, Azilsartan, Acalabrutinib, Luliconazole, Sitagliptin, Meloxicam (Mobic), Succinyl sulfathiazole, Fluconazole, and Pranlukast could be repurposed as effective drugs for COVID-19. Fragment-based scaffold analysis and R-group decomposition uncovered pyrrolidine and the indole molecular scaffolds as the potent fragments for designing and synthesizing the novel drug-like molecules for targeting SARS-CoV-2. This comprehensive and systematic assessment of small-molecule viral therapeutics' entire chemical space realised critical insights to potentially privileged scaffolds that could aid in enrichment and rapid discovery of efficacious antiviral drugs for COVID-19.

AIMS: Heart failure (HF) is a clinical syndrome with no definitive diagnostic tests. HF registries are often based on manual reviews of medical records of hospitalized HF patients identified using International Classification of Diseases (ICD) codes. However, most HF patients are not hospitalized, and manual review of big electronic health record (EHR) data is not practical. The US Department of Veterans Affairs (VA) has the largest integrated healthcare system in the nation, and an estimated 1.5 million patients have ICD codes for HF (HF ICD-code universe) in their VA EHR. The objective of our study was to develop artificial intelligence (AI) models to phenotype HF in these patients. METHODS AND RESULTS: The model development cohort (n = 20 000: training, 16 000; validation 2000; testing, 2000) included 10 000 patients with HF and 10 000 without HF who were matched by age, sex, race, inpatient/outpatient status, hospital, and encounter date (within 60 days). HF status was ascertained by manual chart reviews in VAs External Peer Review Program for HF (EPRP-HF) and non-HF status was ascertained by the absence of ICD codes for HF in VA EHR. Two clinicians annotated 1000 random snippets with HF-related keywords and labelled 436 as HF, which was then used to train and test a natural language processing (NLP) model to classify HF (positive predictive value or PPV, 0.81; sensitivity, 0.77). A machine learning (ML) model using linear support vector machine architecture was trained and tested to classify HF using EPRP-HF as cases (PPV, 0.86; sensitivity, 0.86). From the HF ICD-code universe, we randomly selected 200 patients (gold standard cohort) and two clinicians manually adjudicated HF (gold standard HF) in 145 of those patients by chart reviews. We calculated NLP, ML, and NLP + ML scores and used weighted F scores to derive their optimal threshold values for HF classification, which resulted in PPVs of 0.83, 0.77, and 0.85 and sensitivities of 0.86, 0.88, and 0.83, respectively. HF patients classified by the NLP + ML model were characteristically and prognostically similar to those with gold standard HF. All three models performed better than ICD code approaches: one principal hospital discharge diagnosis code for HF (PPV, 0.97; sensitivity, 0.21) or two primary outpatient encounter diagnosis codes for HF (PPV, 0.88; sensitivity, 0.54). CONCLUSIONS: These findings suggest that NLP and ML models are efficient AI tools to phenotype HF in big EHR data to create contemporary HF registries for clinical studies of effectiveness, quality improvement, and hypothesis generation.