Abstract: Palynomorph assemblages and mineral microfossils from five southern Red Sea coastal environments were studied to demonstrate their distribution pattern and suggest their source. The environments studied were 1. mangrove swamp 2. middle Holocene paleochannel 3. algal mat, 4. Sabia Island coral reef, and intertidal zone. The samples studied were from the top 3 cm semi-consolidated sediments from various environments. Standard palynological maceration technique was used to isolate palynomorphs. These sediment samples are mainly clay and fine sand and yielded low numbers but high diversity of palynomorph assemblages. They are grouped into pollen and spores, dinoflagellate cysts, and algal remains, fungal spores, hyphae and fruit bodies, protists, and invertebrates. A few Ascidian and sponge spicules, and phytoliths (mineral microfossils) occur in the Sabia Island coral reef environment. The protists and invertebrate remain include microforaminifera, thecamoebians, tintinnomorphs, crustacean and annelid palynomorphs. The assemblage also includes six form taxa belonging to the form genera Katora and Mangrovia. These palynomorphs belong to both marine and terrestrial environments and are of autochthonous and allochthonous origins. The source and genetic relationship of each palynomorphs is discussed.

The utilization of wild genera in sugarcane has been recognized as an important strategy to enhance the genetic base to impart biotic and abiotic stress tolerance in hybrid cultivars. A set of 15 Erianthus procerus derived hybrids along with five popular check varieties were evaluated for two years (2018–19 and 2019–20) for agro-morphological, quality, physiological traits and three years (2018–19, 2019–2020, and 2020–21 for winter sprouting potential. The E. procerus hybrid GU 12-19 recorded the highest winter sprouting potential with a winter sprouting index (WSI) of 10.6 and a percent superiority of 279 over best check (Co 0238) followed by GU 12-22 with WSI: 8.5 and % superiority over best check was 204. The other top-performing hybrids, GU 12-21 and GU 12-29, recorded the excellent winter sprouting potential with WSI of 7.2 and 6.9 respectively. The four E. procerus hybrids identified with higher WSI were also resistant to the prevalent races of red rot in both tropical and subtropical conditions. The association analysis revealed significant correlations between various traits, particularly fibre content with a maximum number of associations, which indicates its multifaceted impact on sugarcane characteristics. Principal component analysis (PCA) summarized the data, explaining 57.6% of the total variation for measured traits and genotypes, providing valuable insights into the performance and characteristics of the E. procerus-derived hybrids under subtropical climate. The anthocyanin content of E. procerus hybrids was better than the check varieties with a mean of 0.147 (2018–19) and 0.144 (2019–20) and range of 0.123–0.179 (2018–19) and 0.111–0.172 (2019–20), anthocyanin plays a vital role in mitigating the cold injury, acting as an antioxidant in cool weather conditions, particularly in sugarcane. Further, seven hybrids recorded more than 22% fibre threshold, indicating their industrial potential. These hybrids would be potential donors for cold tolerance and high ratooning ability along with red rot resistance under subtropical climate.

Municipal solid waste management is a growing worldwide challenge. Landfill mining is a promising technique to reduce MSW landfills. In the present study, arbitrary embankments made of different MSW fractions are analyzed to find the safety factor of their slopes. Properties of Municipal solid waste fines (MSWF), Shredded MSW, MSW Incineration Ash, and MSW having particles less than 35 mm are used in the analysis. For doing the same, finite element-based application 'Plaxis-2D' is used. The safety of slopes is assessed while the water table is inserted, and a uniform load is applied to the embankment to establish how well they will perform in critical situations. It was found that the slope made of shredded MSW is most safe due to its low density and high friction angle, while the least safe slope is made of MSW having less than 35 mm fractions.

Land degradation is a critical issue globally putting our future generations at risk. The decrease in farm productivity over the years is evidence of land degradation severity in Nepal. Among the many strategies in place, agroforestry, which is an integrated tree-based farming, is widely recommended to address this productivity issue. This paper thoroughly examines what influences the choice of agroforestry adoption by farmers and what discourages the adoption. For this, a total of 288 households were surveyed using a structured questionnaire. Two agroforestry practices were compared with conventional agriculture with the help of the Multinomial Logistic Regression (MNL) model. The likelihood of adoption was found to be influenced by gender; the male-headed households were more likely to adopt the tree-based farming practice. Having a source of off-farm income was positively associated with the adoption decision of farmers. Area of farmland was found being the major constraint to agroforestry adoption for smallholder farmers. Some other variables that affected positively included livestock herd size, provision of extension service, home-to- forest distance, farmers’ group membership and awareness of farmers about environmental benefits of agroforestry. Irrigation was another adoption constraint that the study area farmers were faced with. The households with means of transport and with larger family (household) size were found to be reluctant towards agroforestry adoption. A collective farming practice could be a strategy to engage the smallholder farmers in agroforestry.

Water pollution, driven largely by the discharge of organic dyes from various industrial processes, presents a grave environmental threat. This study delves into the promise of an innovative adsorptive composite material composed of chitosan and activated charcoal, offering a sustainable and efficient solution for removing methylene blue (MB) dye from water sources. Our comprehensive investigation encompasses the synthesis, characterization, and adsorption capabilities of this composite material, revealing its remarkable physicochemical attributes and its substantial capacity to adsorb MB dye. These findings establish it as a compelling candidate for water treatment applications. The assessment of adsorbent dosage shows a direct correlation between higher dosages and enhanced MB dye removal, with an optimal dosage determined at 0.4 g/25 mL. Furthermore, pH-dependent studies demonstrate exceptional performance at lower pH levels, achieving an impressive 95% removal rate at pH 3 after 240 minutes of contact time. The composite exhibits consistent high removal percentages across a wide range of MB dye concentrations, showcasing its adaptability. In terms of reaction time, the composite achieves peak adsorption capacity within the initial 360 minutes and maintains a stable equilibrium, sustaining an impressive 99% removal efficiency thereafter. This study underscores the eco-friendliness and cost-effectiveness of the composite material, emphasizing its potential to address water pollution challenges and promote sustainable water resource management. Overall, this research yields valuable insights into a practical approach for mitigating the adverse impact of organic dyes on aquatic ecosystems and public health.

We derive a quantum speed limit for unitary evolution for the case of mixed quantum states using the stronger uncertainty relation for mixed quantum states. This bound can be optimized over different choices of Hermitian operators for a better bound. We illustrate this with some examples and show its better performance with respect to three existing bounds for mixed quantum states.

Hydrolysate prepared from water hyacinth biomass, containing a considerable amount of solubilised carbohydrate and nutrients, was utilised as a medium for the cultivation of two strains of Chlorella sorokiniana. These strains were isolated from an oxidation pond using two different media, i.e., BG-11 and Knop's media maintained at pH-9. Different light intensities, light-dark cycles, and various concentrations of external carbon sources (monosaccharides and inorganic carbon) were used to optimise the microalgal growth. It was observed that in the presence of organic carbon (glucose), biomass productivity increased significantly (~300 mgL-1day-1) as compared to that in the presence of only inorganic carbon (~100 mgL-1day-1). For the accumulation of stress products (lipids and carbohydrates), the microalgal strains were transferred to nutrient-amended media (N-amended and P-amended). The combined effects of glucose, inorganic carbon, and a 12h:12h light-dark cycle proved to be optimum for biomass productivity. For Chlorella sp. isolated from BG-11, maximum carbohydrate content (22%) was found in the P-amended medium, whereas high lipid content (17.3%) was estimated in the N-amended medium. However, for Chlorella sp. isolated from Knop's medium, both the lipid (17%) and carbohydrate accumulation (12.3%) were found maximum in the N- amended medium. Kinetic modelling of the lipid profile revealed that kinetic coefficients obtained for strain isolated from BG-11 media were statistically significant from each other.

Powdery mildew (PM), caused by the fungal pathogen Blumeria graminis f. sp. tritici (Bgt), significantly threatens global bread wheat production. Although the use of resistant cultivars is an effective strategy for managing PM, currently available wheat cultivars lack sufficient levels of resistance. To tackle this challenge, we conducted a comprehensive genome-wide association study (GWAS) using a diverse panel of 286 bread wheat genotypes. Over three consecutive years (2020-21, 2021-22, and 2022-23), these genotypes were extensively evaluated for PM severity under field conditions following inoculation with virulent Bgt isolates. The panel was previously genotyped using the Illumina 90K SNP Infinium iSelect SNP assay to obtain genome-wide SNP marker coverage. By applying FarmCPU, a multilocus mixed model, we identified a total of 113 MTAs located on chromosomes 1A, 1B, 2B, 3A, 3B, 4A, 4B, 5A, 5B, 6B, 7A, and 7B at a significance level of p≤0.001. Notably, four novel MTAs on chromosome 6B were consistently detected in 2020-21 and 2021-22 environments. Furthermore, within the confidence intervals of the identified SNPs, we identified 96 candidate genes belonging to different proteins including 12 disease resistance/host-pathogen interactions related protein families. Among these, protein kinases, leucine-rich repeats, and zinc finger proteins, were of particular interest due to their potential roles in PM resistance. These identified loci can serve as targets for breeding programs aimed at developing disease-resistant wheat cultivars.

The wind flow patterns and pressure distribution around a plus-shaped building are significantly influenced by the dimensions of its re-entrant corners and the overall building height. The present study aims to find the wind effects and study of the pressure distribution with different flow patterns. Plan area of the building is around 300 square meter while the height of the building is 50 meters by keeping the equal length of the re-entrant corners. The research is performed using ANSYS CFX academic version and the results are depicted in various forms such as pressure coefficient (Cpe), stream lines in both vertical as well as in specific surface and pressure contours. The analysis is carried out by varying the wind incident angles, from 0° to 90° at the interval of 15°. The building dimension are scale down to perform the test on length scale of 1:100. Since the considered building model exhibits symmetry along both the axes, present study mostly emphasis on examining re-entrant corners located in the building. This method yields valuable information about how air circulates and how pressure is distributed across a broad spectrum of wind angles. This study provides valuable insights into flow circulation and pressure distribution for a wide range of wind angles.

Building situated in the flow path of wind is subjected to differential velocity and pressure distribution around the building envelope. Wind effects are influenced and vary for each individual shape of the tall building. Tall building structures are considered as cantilever structures with fixed ends at the ground. Wind exponential velocity acting along the height of the building makes velocity and pressure distribution more complex as the height of the building structure increases. This study discussed the effect of wind on an irregular cross-section shape. The study was conducted numerically with a building model placed in a virtual wind tunnel using the ANSYS (CFX) software tool. Wind effects are investigated on building model situated in a terrain category - II defined in IS: 875 (Part 3): 2015 wind scale model of 1:100 and turbulence intensity is 5 % and power law index α is considered as 0.143. Validation and verification of the study were made by comparing pressure coefficients on faces of a rectangular model of similar floor area and height as taken for a C-plan diamond-shaped model under similar boundary conditions, wind environment, and solver setting of numerical setup. The values of surface pressures generated on the recessed faces of the model and wind flow patterns within the recessed cavity were studied at wind incident angles 0°, 300, 60°, 1050, 1350 & 1800. The critical suction on all the recessed faces was observed to be at a 105° angle of wind attack.

The study presents the synthesis and characterization of dual-layer sulfonated polyphenylenesulfone (SPPSu) nanocomposite hollow fiber nanofiltration membranes incorporating titanium dioxide (TiO2) nanoparticles using the phase inversion technique. The newly developed membranes were systematically characterized using advanced tools and methods to evaluate their properties and performance. The study focused on investigating the effects of TiO2 addition in the SPPSu inner layer on pure water permeability, and salt rejection. The nanocomposite hollow fiber nanofiltration membranes exhibited a significant enhancement in pure water permeability, with a three-fold increase compared to the pristine membranes, achieving a flux of 5.4 L/m2h.bar. The addition of TiO2 also led to an improvement in the mechanical properties of the membranes, as evidenced by the increase in the expected tensile strength from 2.4 to 3.9 MPa. To evaluate the salt rejection performance, rejection tests were conducted using a laboratory-scale filtration setup in recycle mode. Aqueous solutions containing different divalent ions, specifically magnesium sulfate (Mg2SO4) and sodium sulfate (Na2SO4) at a concentration of 500 ppm, were used as the feed solution. The modified dual-layer hollow fiber nanocomposite membranes exhibited a maximal rejection of 95% for Mg2SO4, demonstrating their effective separation capabilities for divalent ions. The findings of this study highlight the successful synthesis and characterization of dual-layer SPPSu nanocomposite hollow fiber nanofiltration membranes incorporating TiO2 nanoparticles. The incorporation of TiO2 resulted in improved pure water flux, mechanical strength, and salt rejection performance. These enhanced properties make the developed nanocomposite membranes promising candidates for applications in nanofiltration processes, particularly for the selective separation of divalent ions from aqueous solutions.

This study introduces a promising and practical method for the removal of paracetamol from aqueous environments, employing graphene oxide-polymer nanocomposite beads. The approach involves the utilization of a straightforward and facile phase inversion method, offering a convenient and efficient one-step process for the creation of adsorbent beads by integrating polymers and graphene oxide (GO). The synthesized nanocomposite beads are tailored for the removal of paracetamol from simulated wastewater in batch systems. Extensive characterization techniques are employed to scrutinize the chemical properties and structural attributes of the prepared beads. The investigation explores the impact of critical parameters such as adsorbent dosage, adsorption duration, initial paracetamol concentration, and solution pH on the adsorption process. These nanocomposite beads exhibit an exceptional paracetamol removal efficiency, achieving up to 99% removal. This research not only contributes to the advancement of efficient and sustainable adsorbent materials for pollutant removal but also underscores their potential for environmentally friendly and cost-effective solutions in the domain of wastewater treatment.

With all the sophisticated threats to network security, intrusion detection is a section of the security technology industry that is becoming increasingly significant. In this research paper, we have discussed in detail the detection, effects, and prevention protocols of security issues. Security issues are a wide range of elements. Hence, we narrowed our research to two main sectors which are malware attacks and distributed denial of service (DDOS). To make the research more informative, we looked at three selected real-life cases of security intrusion that occurred around the world in recent years. Malware attacks and DDOS are constantly being developed creatively to challenge all the current security systems. In addition, we have analysed and highlighted the potential threats of the security issue and included proposed countermeasure ideas to avoid the security issues. The research findings also show us that malware is evolving simultaneously with our security technology growth. This gives us an understanding that prevention is significantly a continual improvement process.

The rapid proliferation of Internet of Things (IoT) technology has ushered in a new era of connectivity, allowing billions of devices to produce extensive data. Significant challenges in software engineering need to be addressed for full utilization of Internet of Things (IoT) applications. This article examines the challenges in Internet of Things, software engineering and discusses current developments aimed at addressing these issues and seizing new opportunities. We examine the challenges associated with Internet of Things software development, including resource constraints, device diversity, security vulnerabilities, and data management concerns. New studies have indicated the use of advanced techniques like as containerization, model-driven development, AI and ML integration, and robust security frameworks. Moreover, the significance of system architecture is explained, including the device, network, and cloud layers, with an emphasis on the principles of reusability, scalability, and modularity. Results and conversations explore the complexities of security measures, emerging opportunities, and scaling solutions made possible by simulation tools, penetration testing, and cross-domain development platforms. The study expects IoT system evolution and emphasises the need for continual software and firmware changes, testing, and deployment.

(1) Background: Type-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medication to cure T2DM, the review of the literature found that various Pyrimidine derivative act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic beta-cells and its mechanism of action with fewer adverse effects.; (2) Methods: In the present research work, in-silico investigations were carried out to investigate the potential of Pyrimidine analogue as an agonists to the protein target GPR119 receptor. We performed exhaustive molecular modelling and protein modelling methodologies such as homology mod-elling, molecular docking along with various drug designing tools such as 3D-QSAR and pharmacophore mapping to ascertain the design of better GPR119 agonists.; (3) Results: On the basis of in-depth computa-tional studies, we designed new pyrimidine moiety and analyzed them for GPR-119 receptor agonist and fur-ther explored the ADME properties. Designed compounds found to exhibit better predicted activities as com-pared to reference compound; (4) Conclusions: The current research on pyrimidine derivatives, using molec-ular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of −11.696, -9.314 and -8.721 respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidate for the treatment of diabetes acting via GPR119 agonist mechanism.

The management of user data in the cloud is easily poised to become a giant issue for any business, with so much digital information floating around these days that open it up as an easy target when companies aren’t vigilant. In this paper, a novel cloud-based service is proposed that employs various advanced NLP and encryption methods with the use of blockchain. These techniques are combined to provide a solid solution to secure fundamental data such as credit card numbers, passports or any government identity cards etc. Using a hybrid NLP model, integrating Transformer Models and Named Entity Recognition (NER), to automatically catagorzing data as critical vs non-critical. Only the most important data is encrypted by a user’s cryptographic wallet before being divided into multiple chunks and stored on an exclusive cloud cluster; metadata then takes turns managing securely through blockchain to provide traceable means of retaining integrity. Smart contracts provide strict access control measures and change the cryptographic nonce if need be to prevent illegal entrance into a specific zone, thus create security. This all-inclusive strategy maintains well-known high security standards for protecting the confidentiality, availability and integrity of your sensitive data on a global scale—delivering you simple yet scalable secure world-class cloud-based data management. A proposed framework developed to fulfil the security requirements for current cloud services, which is a beneficial contribution in context of data protection and cloud Security.

The study investigated the effect of a multi-strain probiotic compound containing Bacillus coagulans, Enterococcus faecalis, Clostridium butyricum and Bacillus mesentericus as in-feed zinc oxide (ZnO) alterna-tive on growth performance, diarrhea incidence, antioxidant status, lipid profile, stress and immunity in weaned piglets. A total of 72 piglets were randomly divided into 3 groups with four replicates of six piglets each. The details of the groups were as follows; (i) weaned control group (WC) received basal diet, (ii) weaned probiotic group (WB) received basal diet and probiotics and (iii) positive control (PC) group received basal diet with 2500 mg/kg ZnO. The experiment lasted for 28 days. Probiotic supple-mentation improved growth performance and reduced diarrhea rate. Probiotics supplementation im-proved lipid profile; significantly lower levels of total cholesterol and low-density lipoprotein cholesterol and higher level of high-density lipoprotein cholesterol in WB group as compared to those of the control group (WC) were recorded. Probiotic supplementation stimulated antioxidant defense system by in-creasing total antioxidant capacity and decreasing lipid peroxidation. Probiotic supplementation down-regulated the stress biomarkers like serum cortisol and serum heat shock proteins. WB group showed higher serum levels of IgG and IgM throughout the study period and higher IgA at day 28 as compared to WC. These data suggest that supplementation of the probiotic minimizes the weaning stress, thereby improves the growth performance, lipid profile, antioxidant status and systemic as well as mucosal immunity. Therefore, the multi-strain probiotic compound may be used to replace ZnO in weaned piglets.

Resistance training is beneficial to adults for improving muscle strength and reducing the body composition. Nevertheless, little is known regarding online resistance training on anthropometric parameters and muscular strength (MS) in overweight female adolescents. This study aimed to examine the effects of online resistance training on anthropometric parameters and muscular strength (MS) in overweight female adolescents. This prospective, single-center, single-blinded, randomized controlled study included 60 overweight female adolescents who were divided into a control group (n=30) and an intervention group (n=30). The intervention group performed online resistance training, which focused on body weight training of 12 components (4 sets, 12 repetitions) for 45 min, three times per week, for 12 weeks. The intensity of training was 65–75%. Anthropometric parameters, including body weight (BW), body mass index (BMI), body circumference measurements (BCM), and muscle strength (MS), were assessed. All parameters were measured at weeks 0, 8, and 12. Within-group and between-group comparisons were performed. The results revealed improvements in MS, BW, BMI, and BCM in the intervention group. However, chest circumference was not significant. These findings suggest that online resistance training was effective in improving MS and reducing the body composition and circumference.

Before calcification begins, the early embryonic and fetal skeletal development of both mammalian Homo sapiens and the chondrichthyan fish Raja asterias consists exclusively of cartilage. This cartilage is formed and shaped through processes involving tissue segmentation and the frequency, distribution, and orientation of chondrocyte mitoses. In the subsequent developmental phase, mineral deposition in the cartilage matrix conditions the development further. The stiffness and structural layout of the mineralized cartilage have a significant impact on the shape of the anlagen (early formative structures of organs or tissues) and the mechanical properties of the skeletal segments. The fundamental difference between the two studied species lies in how calcified cartilage serves as a scaffold for osteoblasts to deposit bone matrix, which is then remodeled. In contrast, chondrichthyans retain the calcified cartilage as the definitive skeletal structure. This study documents the distinct mineral deposition pattern in the cartilage of the chondrichthyan R. asterias, in which calcification progresses with the formation of focal calcification nuclei or “tesserae”. These are arranged on the flat surface of the endo-skeleton (crustal pattern) or aligned in columns (catenated pattern) in the radials of the appendicular skeleton. This anatomical structure is well adapted to meet the mechanical requirements of locomotion in the water column. Conversely, in terrestrial mammals, endochondral ossification (associated with the remodeling of the calcified matrix) provides limb bones with the necessary stiffness to withstand the strong bending and twisting stresses of terrestrial locomotion. In this study, X-rays of marine mammals (reproduced from previously published studies) document how the endochondral ossification in dolphin’s flipper adapts to the mechanical demands of aquatic locomotion. This adaptation includes the reduction in the length of the stylopodium and zeugopodium and an increase in the number of elements in the autopodium’s central rays.

Cancer is a catchall term that refers to a collection of more than one chronic disease that can adversely affect the body, including the organs of the body. These diseases can be grouped together under the umbrella term "cancer." Cancer is a catch-all term that is used to refer to a number of different diseases. During the process of looking for new chemical entities, it was found that certain compounds with a basic nucleus of benzoic acid (BA) exhibit a remarkable anticancer potential. This was discovered while the researchers were looking for new chemical entities. In the sixteenth century, the aromatic chemical known as BA, which is also known as an aromatic carboxylic acid, was discovered. BA is also referred to as an aromatic carboxylic acid. When it comes to the chemical synthesis of a wide range of different active molecules, the utilization of a sizeable quantity of BA as a raw material is absolutely necessary. In addition to being present in a variety of other naturally occurring compounds, the BA moiety is the component that is responsible for the activity of the naturally occurring compounds vanillin, gallic acid, and syringic acid. In the synthesis of a wide variety of synthetic bioactive molecules, the BA scaffold is utilized as a building block. The drugs furosemide, bumetanide, benzocaine, tetracaine, and bexarotene are all examples of molecules that fall into this category. The scope of this review article allows for the discussion of a number of noteworthy and recent achievements of BA derivatives in terms of their effectiveness against cancer.

This study deals with vibrational and crystallographic aspects of the thermally induced transformation of serpentine-like garnierite into quartz, forsterite, and enstatite occurring at about 620 °C. Powder specimens of garnierite have been annealed in static air between room temperature and 1000 °C. The resulting products from the transformations detected based on thermogravimetric and differential thermal analysis, have been extensively characterized via microRaman spectroscopy, and X-ray diffraction. Our study shows that serpentine-like garnierite consists of a mixture of different mineral species. Furthermore, these garnierites and their composition can provide details based on the mineralogy and the crystalline phases resulting from the thermal treatment.

The aims of this work were to examine the new electrode, based on polymer bacteria modified aluminum electrode for simultaneous production of electricity and degradation of phenol. This electrode is based aluminum modified by bacteria inserted in the polymer matrix, developed in situ on the surface. This electrode, designated subsequently by bacteria-polymer-aluminum, Showed stable response and was characterized with voltametric methods, as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The experimental results revealed that the prepared electrode could be a feasible for degradation of hazardous phenol pollutants. The sensor was successfully applied to the determination of phenol in a real sample with satisfactory results.

The coronavirus disease caused by SARS-CoV-2 (known as COVID 19) is highly contagious and has spread rapidly over 200 countries over last three months. WHO suggested urgent escalation in testing, isolation and contact tracing, as the "backbone" of managing the pandemic. Globally, the detection of SARS-CoV-2 in patients are done by RT-PCR and blood antibody-based testing. In addition to the existing processes, flow-cytometry could be used as a high-throughput and efficient diagnostic method for detection of COVID 19. The suspected COVID 19 samples can be analyzed using ‘Indirect flow cytometry’, with the specific primary antibody and fluorescent tagged secondary antibodies. The fluorescence signal can distinguish the infected v/s non-infected samples. In the present article, we have summarized the applications of Flow virometry to study various viruses and have proposed possible application in the detection of COVID 19.

Currently, the pesticides are the global core concern because it is a boon to farmers against increasing disease-pest and simultaneously, pesticide residue is the major anxiety regarding human health. For that reason, identification and determination of factors affecting the application of pesticides are essential. To identify and evaluate determinants of pesticides application in Nepal, a household survey of 300 households was carried-out and an empirical analysis was done using multivariate probit model. Moreover, powder and liquid forms of pesticides were considered for summer and winter season in vegetable farming, which was assigned as outcome variables. Likewise, socio-economic, demographic, farm-level and perception data were considered as explanatory variables. Use of chemical fertilizers, age and gender of head of household, household size and access to weather information were found the most influencing factors. Moreover, forms of pesticides and growing seasons were found complementary to each other. Therefore, devising the policy options accordingly should balance needs of farmers and health of consumers.

Platelets have long been associated with sustaining the balance between hemostasis and thrombosis. Platelets, however, are also involved in a wide range of biological activities, including inflammation, immunology, wound healing, cancer biology, and angiogenesis. Platelets' diverse roles are mediated by the expression of various adhesive and immune receptors and the secretion of a diverse array of bioactive proteins, ions stored in granules, and several lipid mediators. Platelets also release pro-inflammatory and anti-inflammatory, and angiogenic factors and shed microparticles into the bloodstream. The challenge for therapeutic intervention in non-hemostatic disease is identifying the factors that primarily inhibit specific targets implicated in platelets' complicated contribution to inflammation or tumor growth while leaving their hemostatic function intact. In addition, blood platelets are involved in infection and innate and adaptive immunity by mediating complicated vascular homeostasis via specialized receptors and granule release, RNA transfer, and mitochondrial secretion. Anti-platelet drugs/bioactive compounds are developed based on their platelet anti-aggregatory properties; however, very little information is available on their effects on non-hemostatic function. Therefore, a better understanding of the impact of the anti-platelet bioactive on the platelets' diverse roles and mechanisms may help develop new strategies and prevent CVD and other diseases. In this review, a comprehensive overview of platelet multifunctional roles in CVD and other diseases and dietary factors' modulatory effects are described.

Pesticides are among the most widely used synthetic chemicals worldwide to protect crops, but besides being beneficial, they pose several environmental and health issues. The present study evaluates toxic effects of acetamiprid (ACMP) in rat liver and kidney tissues. Rats were exposed to ACMP (21.7 mg/kg b.wt; 1/10th LD50) for 21 days. Oxidative stress generation, apoptotic progression, and structural changes were evaluated via biochemical assays, semi-quantitative PCR, western blotting, and histopathology. ACMP exposure significantly decreased body weight and altered relative organ weight in hepato-renal tissues. Significant oxidative stress was evident by increased oxidative injuries to lipids and proteins and alterations of endogenous anti-oxidative enzymes. The administration of ACMP upregulated mRNA expression of Bax and caspase-3, while downregulated the mRNA expression of Bcl-2 and released cytochrome c into the cytosol of the liver and kidney tissues. Likewise, exposure to ACMP caused severe degenerative changes in the histo-architecture of hepato-renal tissues. The results of the present study confirmed the toxicity of ACMP in rats’ liver and kidney tissues and emphasized the need for strict regulation and more mechanistic understanding to delineate the toxicity of ACMP in mammals.

The fifth Generation (5G) mobile networks use millimeter Waves (mmWaves) to offer giga bit data rates. However, unlike microwaves, mmWave links are prone to user and topographic dynamics. They easily get blocked and end up forming irregular cell patterns for 5G. This in turn cause too early, too late, or wrong handoffs (HOs). To mitigate HO challenges, sustain connectivity and avert unnecessary HO, we propose a HO scheme based on Jump Markov Linear System (JMLS) and Deep Reinforcement Learning (DRL). JMLS is widely known to account for abrupt changes in system dynamics. DRL likewise emerges as an artificial intelligence technique for learning highly dimensional and time-varying behaviors. We combine the two techniques to account for time-varying, abrupt, and irregular changes in mmWave link behaviour by predicting likely deterioration patterns of target links. The prediction is optimized by meta training techniques that also reduces training sample size. Thus, the JMLS-DRL platform formulates intelligent and versatile HO policies for 5G. Results show our proposed prediction scheme about target link behavior post HO to be highly reliable. The scheme also averts unnecessary HOs thus ably supports longer dew time.

There are different treatment options in modern dentistry for the replacement of lost dentition. Of these the most upcoming and acceptable treatment option is Dental implants. The common problem usually with immediate implant placement in the anterior region is the post-operative soft tissue contour as a part of the bone modelling during healing. Hurzeler et al in 2010 introduced a new technique called the “socket shield technique”. This technique has been used as an alternative treatment modality for immediate implant placement in the aesthetic zone.This review articles provides a detailed information regarding the clinical concept of Root membrane technique.

The changing dynamics in climate is the primary and important determinant of agriculture productivity. The effects of this changing climate on overall productivity in agriculture can be understood when we study the effects of individual components contributing to the changing climate on plants and crops. Elevated CO₂ (eCO₂) and drought due to high variability in rainfall is one of the important manifestations of the changing climate. There is a considerable amount of literature that addresses climate effects on plant systems from molecules to ecosystems. Of particular interest is the effect of increased CO₂ on plants in relation to drought and water stress. As it is known that one of the consistent effects of increased CO₂ in the atmosphere is increased photosynthesis, especially in C₃ plants, it will be interesting to know the effect of drought in relation to elevated CO₂. The potential of elevated CO₂ ameliorating the effects of water deficit stress is evident from literature suggesting that these two are agents are brothers in arms protecting the plant from stress rather than partnering in crime, specifically water deficit when in isolation. The possible mechanisms by which this occurs will be discussed in this minireview. Interpreting the effects of short-term and long-term exposure of plants to elevated CO₂ in the context of ameliorating the negative impacts of drought will show us the possible ways by which there can be effective adaption to crops in the changing climate scenario.

The falling cost of cameras, the advancement of AI based computer vision algorithms, and powerful hardware accelerators for deep learning have enabled wide-spread deployment of surveillance cameras with the ability to automatically analyze streaming video feeds to detect events of interest. While streaming video analytics is currently largely done in the cloud, edge computing has emerged as a pivotal component due to its advantages of low latency, reduced bandwidth, and enhanced privacy. However, a distinct gap persists between the state-of-the-art computer vision algorithms, and successful practical implementation of edge-based streaming video analytics systems. This paper presents a comprehensive review of more than 30 research papers published over the last 6 years on edge video analytics systems. The papers are analyzed across 17 distinct dimensions. Unlike prior reviews, we examine each system holistically, identifying their strengths and weaknesses in diverse implementations. Our findings suggest that certain critical topics necessary for the practical realization of edge video analytics systems are not sufficiently addressed in current research. Based on these observations, we propose research trajectories across short, medium, and long term horizons. Additionally, we explore trending topics in other computing areas that can significantly impact the field of edge video analytics.

This hypothesis demonstrates that the efficiency of Loop-Mediated Isothermal Amplification (LAMP) for nucleic acid detection can be positively influenced by preconcentration of microbial cells onto hydrophobic paper surfaces. The mechanism of this model is based on the high attraction of microbes towards hydrophobic surfaces. Extensive studies have demonstrated that hydrophobic surfaces exhibit enhanced bacterial and fungal adhesion. The preconcentration approach by exploiting this inherent affinity of hydrophobic paper substrates enables the adherence of a greater number of target cells, resulting in a higher concentration of target templates for amplification directly from urine samples. In contrast to conventional methods, which often involve complex procedures, this approach offers a simpler, cost-effective, and user-friendly alternative. Moreover, the integration of cell adhesion, LAMP amplification, and signal readout within paper origami-based devices can provide a portable, robust, and highly efficient platform for rapid nucleic acid detection. This innovative hypothesis holds significant potential for point-of-care (POC) diagnostics and field surveillance applications. Further research and development in this field will advance the implementation of this technology, contributing to improved healthcare systems and public health outcomes.

The design of torsional springs for Series Elastic Actuators (SEAs) is challenging, especially when it comes to balancing good stiffness characteristics and efficient torque robustness. This study focuses on the design of a lightweight, low-cost, and compact torsional spring for use in rotary series elastic actuator (ES-RSEA) of lumbar support exoskeleton. The exoskeleton is used as an assistive device to prevent lower back injuries. The torsion spring was designed following design for manufacturability (DFM) principles, focusing on minimal space and weight. The design process consisted of determining the potential topology and optimizing the selected topology parameters through finite element method (FEM) to reduce equivalent stress. The prototype was made using a waterjet cutting process with low-cost material (AISI-4140-alloy) and tested using a custom-made test rig. The results showed that the torsion spring had a linear torque-displacement relationship with 99% linearity, and the deviation between FEM simulation and experimental measurements was less than 2%. The torsion spring has a maximum torque capacity of 45.7 Nm and a stiffness of 440 Nm/rad. The proposed torsion spring is a promising option for lumbar support exoskeletons and similar applications requiring high stiffness, low weight-to-torque ratio, and cost-effectiveness.

: Alluvial soils naturally possess abundant soil nutrients. Nevertheless, excessive nitrogen addition and inappropriate use of nitrogen fertilizers lead to conditions where soil nutrients become immo-bilized, ultimately reducing productivity. This study investigates the potential of natural nano-material zeolite which is important land resources to improve nutrient utilization efficiency and mitigate the harmful effects of excessive fertilizer application. Specifically, the research ex-plores the incorporation of clinoptilolite zeolite and processed sewage sludge blends, alongside reduced recommended nitrogen fertilizer doses, to evaluate their impact on soil quality and plant growth. A greenhouse experiment was conducted (three-year study), comprising eight treatments with varying proportions of zeolite and sewage sludge. The efficacy of these treatments in en-hancing soil carbon pools, nutrient indices, and plant growth responses was assessed. Results in-dicate that a combination of 50% recommended fertilizer dose, 4-6% zeolite, and 5-10% sewage sludge significantly improved multiple aspects of plant growth, including leaves, tillers, culms, and panicles, leading to increased straw and grain yields. The addition of 6% zeolite in conjunc-tion with sewage sludge positively influenced plant tillering capacity. Certain treatment combina-tions exhibited a greater impact on plant height at different growth stages. For example, the treatment with 75% recommended fertilizer dose, 4% zeolite, and 5% sewage sludge significantly affected plant height at 40 and 55 days after treatment. Additionally, the combination of 50% recommended fertilizer dose, 6% zeolite, and 10% sewage sludge promoted plant height, carbon levels, and various yield parameters in later stages. Principal component analysis effectively dis-tinguished treatments incorporating zeolite and sewage sludge based on plant responses. The combination of 6% zeolite and 10% sewage sludge, along with a 50% recommended fertilizer dose, positively influenced soil carbon fractions, nutrient levels, and the growth response of rice plants.

The synthesis of the presented benzo[d]thiazol-2-amine derivatives was performed by condensing-(4-chlorobenzylidene) benzo[d]thiazol-2-amine with a number of substituted phenols in the presence of potassium iodide and anhydrous potassium carbonate in dry acetone. IR spectroscopy, 1HNMRspectroscopy and spectroscopy methods were used to characterize the structural properties of newly synthesized derivatives. In order to observe the attributes of drug-like candidates of these derivatives, the number of their molecular properties was estimated. Benzo[d]thiazol-2-amine derivatives were molecularly docked with selective enzymes COX-1 and COX-2. Findings suggested that Compounds G3, G4, G6, G8 and G11 possess higher binding affinity than diclofenac sodium, when docking was performed with enzyme COX-1. Compounds G1, G3, G6, G8and G10 showed lower binding affinity than Indomethacin when docking performed with enzyme COX-2.In vitro evaluation of the COX-1 and COX-2 enzyme inhibitory activities were performed for synthesized compounds. Compounds 10 and 11 exhibited significant COX-1 and COX- enzyme inhibitory action with IC50 values of 5.0 and 10 µM, respectively. Using the hot plate method and the carrageenan-induced rat paw edema model, the synthesized compounds were screened for their biological activities, including analgesic and anti-inflammatory activities. The highest analgesic action was exhibited by derivative G11and the compound G10 showed the highest anti-inflammatory response.

For a hierarchy of large scale structures, like galaxies, galaxy clusters, super-clusters, etc. the requirement that their gravitational (binding) self-energy density must at least equal or exceed the background repulsive dark energy density implies a universal mass-radius relation given by M/R² ~ 1g/cm². Here we point out that this mass-radius relation also holds for important individual biological structures, and even various organisms as a whole such as humans, trees, and to behemoths like whales, even though the physics is different. Here we try to understand this universality from two different physical considerations. We also point out the coincidence that the densities of most biological entities are close to that of water, and that the average density of main-sequence stars and giant planets are close to this density. We give a physical basis for the same.

Single-stand selective monofunctional uracil DNA glycosylase 1 (SMUG1) works to remove uracil and certain oxidized bases from DNA during base excision repair (BER). This review provides a historical characterization of SMUG1 and 5-hydroxymethyl-2'-deoxyuridine (5-hmdU) one important substrate of this enzyme. Biochemical and structural analyses provide remarkable insight into the mechanism of this glycosylase revealing SMUG1 has a unique helical wedge which influences damage recognition during repair. Rodent studies suggest that, while SMUG1 shares substrate specificity with another uracil glycosylase UNG2, loss of SMUG1 can have unique cellular phenotypes. This review highlights the multiple roles SMUG1 may play in preserving genome stability, and how the loss of SMUG1 activity may promote cancer. Finally, we discuss recent studies indicating SMUG1 has moonlighting functions beyond BER, playing a critical role in RNA processing including the RNA component of telomerase.

During the conceptual and preliminary design stage of a ship, designers need to ensure that the selected principal dimensions and parameters are good enough to deliver a stable ship (statically and dynamically) besides deadweight and speed. To support this, the initial intact stability of the proposed ship is required to be calculated, and in doing so, the lightship weight and its detailed breakdown are necessary to be known. After hull steel weight, machinery weight, mainly, marine propulsion and power generation machinery, play a vital role in the lightship weight estimate of a ship due to its robustness. The correct estimation of respective weights improves the accuracy of calculating a ship's initial stability typically to be designed and built. Hence, it would be advantageous for the designer to convince the ship owner. A total of 3006 marine propulsion (main marine diesel) engines and 348 power generation (auxiliary marine diesel) engines/generators of various power output (generators output for auxiliary engines), engine RPM and cylinder number of different engine makers are collected. These are analyzed and presented in both tabular and graphical forms to demonstrate the possible relationship between marine propulsion engine weight and power generation engine weight, and their respective power output, RPM, cylinder number, power-RPM ratio and power-RPM ratio per cylinder.In this article, the authors have attempted to investigate the behavior of marine propulsion engine weight and power generation engine/generator weight regarding engine power output, generator power output, engine RPM and cylinder number (independent variables). Further attempts have been made to identify those independent variables that influence the weight of the marine propulsion engine and power generation engine/generator (dependent variables), and their interrelationships. A mathematical model has thus been developed and proposed, as a guiding tool, for the designer to estimate the weight of main and auxiliary engines more accurately during the conceptual and preliminary design stage.

Hundreds of thousands of kilometers of communication and power (umbilical) cables and flowlines lie undersea worldwide. Most of these offshore cables and flowlines have reached or will soon be nearing the end of their service life, necessitating the need for a viable recycling approach to recover some valuable material, e.g., copper. However, separation into constituent materials has proven very challenging due to the highly robust design of the composite cables (and flowlines) to withstand service conditions and the tough external plastic sheaths that protect against seawater corrosion. Here, we summarize the findings of the cryogenic comminution of subsea cables and flowlines for an effective separation and recovery of component materials. Heat transfer analyses of complex multilayer flowlines and umbilicals were conducted to evaluate the time required for these structures to reach their respective critical brittle-transition temperatures. Subsequently, the time was used as a guide to crush the flowline and umbilical cables under cryogenic conditions. The results show that the flowlines and umbilical cables will reach the brittle-transition temperature after approximately 1000s (i.e., 17 min) of submergence in liquid nitrogen (LN). Comminution of the materials at temperatures near the brittle-transition temperature was proven relatively efficient compared to room-temperature processing. The present evaluation of heat transfer and lab-scale crushing will afford accurate process modelling and design of a pilot cryogenic comminution of decommissioned flowlines in an LN-doped atmosphere.

Most of the research in data mining concentrated on finding the positive associations that exist in frequent patterns. Frequent patterns have no bearing on the time duration and, therefore, lose interestingness. The Regularity of an itemset is related to the time at which the transaction occurred and the time distance between the transactions. Frequent Regular item sets can be generated considering the Frequency and the Regularity of the occurrence of the Item Sets. The frequent and regular Item sets will be so huge that they cannot be handled in real time. The count of Frequent and regular item sets gets reduced drastically when the properties “closed” and “Maximality” are applied. Finding negative associations among such patterns are important in the field of medicine. Many drugs administered to cure some diseases have counter reactions leading to many other diseases. Negative associations among the mined patterns are important as they reveal significant contradictions frequently among medical drugs administered by medical practitioners to cure some diseases. This paper proposes a method that mines medical databases to find regular, frequent patterns applied with closed and maximal properties and find negative associations among those patterns. The proposed algorithm is accurate to 98% and performs 9% more efficiently than the other algorithms presented in the literature.

The rapid advancement of large language models (LLMs), such as ChatGPT, has revolutionized natural language processing, enabling these models to generate coherent and contextually relevant text. These capabilities hold significant potential for various applications, particularly in the medical field. LLMs can assist healthcare professionals by providing accurate information, supporting diagnostic processes, and enhancing medical education. However, the implementation of LLMs in clinical settings faces several barriers, including technical limitations, ethical concerns, regulatory constraints, and practical challenges. Ensuring accuracy, reliability, and interpretability is crucial, along with addressing biases, ensuring data privacy, and establishing ethical guidelines. Future research should focus on improving training techniques, developing explainable AI methods, and creating efficient, resource-saving models. Expanding applications through domain-specific models and multi-modal integration can further unlock the potential of LLMs. By addressing these challenges and prioritizing responsible development, LLM technology can be safely and effectively integrated into various domains, driving innovation and improving outcomes. This paper explores the current state of LLM technology, its medical applications, barriers to implementation, and directions for future research and development

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a rare inherited disorder which is characterized by fibrofatty degeneration of cardiac muscles mainly in the right ventricular myocardium. It may cause tachyarrhythmias or right-heart failure or may cause sudden death, especially in young athletes. In our case report, we present a case of young age male patient who presented at a local community hospital with the complaint of atypical chest pain, palpitations, and vomiting and sustained ventricular tachycardia (VT) on electrocardiograph (ECG) showing sustained ventricular tachycardia, left bundle branch morphology with the superior axis. The normal sinus rhythm was achieved after multiple DC cardioversion attempts and he was referred to our tertiary care hospital. Later ECG demonstrated epsilon waves and T wave inversion in v1 to v4 and RBBB morphology. The echocardiography showed a severely dilated right ventricle with dysfunction and right ventricle ventricular apical aneurysm. The definitive diagnosis of ARVC was made as per Revised Task Force Criteria 2010 and the electrophysiology review suggested implantable cardiac defibrillator (ICD) device placement. The patient successfully received a dual-chamber ICD device and he remained asymptomatic.

The paper attempts to explore the relationship between federalism and rural development. Federalism is a division of power, responsibility and accountability to bring the administrative and political power closer to the ground and essentially to increase the good governance. On the other hand, rural development is a complex and multidimensional issue- especially much demanding for least developed and developing countries. A descriptive and qualitative approach was carried out to study the complex relationship between rural development and federalism. Similarly, a SWOT analysis was carried out to have a better understanding of the relationship. The study found that there is significant potentiality for accelerated development of rural landscape in federalism if carefully executed. However, on the other hand, federalism may pose several risks on rural development and may restrict the development pace if not executed with appropriate care and understanding. Therefore, the study concludes that cooperation and coordination among the federal structures are crucial for better development of the rural economy.

Lumbar support exoskeletons with active and passive actuators are currently the cutting-edge technology for preventing back injuries in workers while lifting heavy objects. However, many challenges still exist in both types of exoskeletons, including rigid actuators, risks of human-robot interaction, high battery consumption, bulky design, and limited assistance. In this paper, the design of a compact, lightweight energy storage device combined with rotary series elastic (ES-RSEA) is proposed for use in a lumbar support exoskeleton to increase the level of assistance and exploit the human bioenergy during the two stages of the lifting task. ES takes the responsibility to store and release passive mechanical energy while RSEA provides excellent compliance and prevents injury from the human body's undesired movement. The experimental tests on the spiral spring showed excellent linear characteristics (above 99%) with an actual spring stiffness of 9.96 Nm/rad. The results demonstrate that ES-RSEA can provide maximum torque assistance in the ascent phase with 66.6 Nm while generating nearly 21 Nm of spring torque during descent without turning on the DC motor. Ultimately, the proposed design can maximize the energy storage of human energy, exploit the biomechanics of lifting tasks, and reduce the burden on human effort to perform lifting tasks.

MicroRNAs (miRNAs) within the exosomes are short non-coding RNAs that are associated with many diseases including cancers and are crucial players in regulating gene expression and regula-tion. Owing to their potential role as emerging biomarkers, efficient isolation, and quantification methods of miRNA from the exosomes in the cell’s supernatant are complicated and challenging. The quantitative PCR method is the gold standard for miRNA identification and estimation. Nucleic acid-based assays are expensive, labour-intensive, and require expertise. In this work, we demon-strated an aptamer-based magnetic separation of the exosomes, and quantification of the miRNA using a fluorescence switching assay. The fluorescence assay relies on the fluorescence of the fluorophore labelled cDNA quenched by carbon nanomaterials coated on magnetic beads (OFF state). When the target miRNA210 is introduced to the system, the cDNA detaches from the quenching surface. As a result, the fluorescence intensity increases (ON state) with increasing miRNA concentration within the dynamic range of 0-100 nM. This method can detect miR210 as low as 5 pM. This method does not exhibit any cross-reactivity with other closely related miRNAs. The method was validated by spiking miRNA with the standard RT-PCR method using SYBR green as a fluorescent probe. This method can be used for the minimally invasive detection of cancer biomarkers in breast cancer patients.

The genus Eucalyptus is a globally captivated source of hardwood and is well known for its medicinal uses. The hybrid and wild species of Eucalyptus are widely used as exotic plantations due to their renowned potential of adapting to various systems and sites, furthermore, making the species the most extensively propagated. Despite unquestionable progression in biotechnological and tissue culture approaches, the productivity of plantations is still limited often due to the low efficiency of clonal propagation from cuttings. The obtained F1 hybrids yield high biomass and High-quality low-cost raw material for large-scale production, however, the development of hybrid, clonal multiplication, proliferation, and post-developmental studies are still major concerns. This riveting review describes the problems concerned with in-vitro and clonal propagation of Eucalypt plantation; recent advances in biotechnological and tissue culture practices for massive and rapid micro-propagation of Eucalyptus; as well, highlights the Eucalypt germplasm preservation techniques.

Although the presence of dark energy is well established from various observations, its true nature is still not well understood. The cosmological constant term seems to be the preferred candidate. In earlier work we had a constant cosmological constant term to limit the sizes of large-scale structures at lower redshifts. In this work, we extend this to large scale structures at higher redshifts. Here we invoke a time varying cosmological constant to set constraints on sizes of galaxies at high redshifts and see that they are consistent with their observed sizes. The time-varying cosmological constant also provides a possible solution to the puzzle of structure formation of large disk galaxies (like the Wolfe disk) observed at very early stages of the Universe. Future observations of galaxies at even higher redshifts could support our approach.

The load cell is an indispensable component of many engineering machinery and industrial automation for measuring and sensing force and torque. This paper describes the design and analysis of the strain gauge load cell, from the conceptional design stage to shape optimization (based on the finite element method (FEM) technique) and calibration, providing ample load capacity with low-cost material (aluminum 6061) and highly accurate force measurement. The amplifier circuit of the half Wheatstone bridge configuration with two strain gauges has been implemented experimentally with an actual load cell prototype. The calibration test was conducted to evaluate the load cell characteristics and derive the governing equation for sensing the unknown load depending on the measured output voltage. The measured sensitivity of the load cell is approximately 15 mV/N and 446.8 µV/V at a maximum applied load of 30 kg. The findings are supported by FEM results and experiments with an acceptable percentage of errors, which revealed an overall error of 6% in the worst situation. Therefore, the proposed load cell meets the design considerations for axial force measurement for the laboratory test bench, which has a light weight of 20 g and a maximum axial force capacity of 300 N with good sensor characteristics.

One of the biggest challenges in modern physics is how to unify gravity with quantum theory. There is an absence of a complete quantum theory of gravity, and conventionally it is thought that the effects of quantum gravity occur only at high energies (Planck scale). Here we suggest that certain novel quantum effects of gravity can become significant even at lower energies and could be tested at laboratory scales. We also suggest a few indirect effects of dark energy that can show up at laboratory scales. Using these ideas, we set observational constraints on radio recombination lines of the Rydberg atoms. We further suggest that high-precision measurements of Casimir effects for smaller plate separation could also show some manifestations of the presence of dark energy.

It has been suggested that primordial planets could have formed in the early Universe and the missing baryons in the Universe could be explained by primordial free-floating planets of solid hydrogen. Many such planets were recently discovered around the old and metal poor stars and such planets could have formed at early epochs. Another possibility for missing baryons in the Universe could be that these baryons are admixed with DM particles inside the primordial planets. Here we discuss the possibility of admixture of baryons to the DM primordial planets discussed earlier. We consider gravitationally bound DM objects with the DM particles constituting them varying in mass from 20 to100GeV. Different fractions of DM particles mixed with baryonic matter in forming the primordial planets are discussed. For the different mass range of DM particles forming DM planets, we have estimated the radius and density of these planets with different fractions of DM and baryonic particles. It is found that for heavier mass DM particles with the admixture of certain fractions of baryonic particles, the mass of the planet increases and can reach or even substantially exceed Jupiter-mass. The energy released during the process of merger of such primordial planets is discussed. Also the energy required for the tidal breakup of such an object in the vicinity of a black hole is also discussed.

Gravitational waves have been detected in the past few years from several transient events such as merging stellar mass black holes, binary neutron stars, etc. These waves have frequencies in a band ranging from a few hundred hertz to around a kilohertz to which LIGO type instruments are sensitive. LISA would be sensitive to much lower range of frequencies from SMBH mergers. Apart from these cataclysmic burst events, there are innumerable sources of radiation which are continuously emitting gravitational waves of all frequencies. These include a whole mass range of compact binary and isolated compact objects as well as close planetary stellar entities. In this work, quantitative estimates are made of the gravitational wave background produced in typical frequency ranges from such sources emitting over a Hubble time and the fluctuations in the h values measured in the usual devices. Also estimates are made of the high frequency thermal background gravitational radiation from hot stellar interiors and newly formed compact objects.

The aim of this research study was to develop hydrogels samples for using in potential biomedical applications. Hydrogels consisting of different volumes of keratin, polyvinyl alcohol (PVA), Polyvinylpyrrolidone (PVP), and starch. The keratin is derived from the chicken was the primary material on the hydrogels due to attractively for the potential wound healing application. The hydrogel samples were made by using the freeze‑thawing method, and they were examined using the Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), porosity amusement, swelling ratio and keratin release kinetic models that analyzed using (zero-order, first-order Higuchi and Korsmeyer-Peppas models). These results were indicated that feather keratin could use with formulated hydrogels suitably for controlled keratin release studies .

Phosphorus deficiency highly interferes with plant growth and development. Plants respond to the persistent P deficiency by coordinating the expression of genes involved in the alleviation of the stress. Promoters of phosphate transporter genes are of great choice for the development of genetically modified plants with enhanced phosphate uptake abilities, which improve crop yields in phosphate-deficient soils. In our previous study, the sugarcane phosphate transporter PHT1;2 gene, showed a significantly high expression under salinity stress. In this study, the Erianthus arundinaceus EaPHT1;2 gene was isolated and characterized using various in-silico tools. The deduced 542 amino acid residues have 10 transmembrane domains, with a molecular weight and isoelectric point of 58.9 kDa and 9.80, respectively. They displayed 71–96% similarity with Arabidopsis thaliana, Zea mays, and Saccharum hybrid. To elucidate the function of the 5’ regulatory region, the 1.1kb promoter was isolated and validated in tobacco transgenics under Pi stress. The EaPHT1;2 promoter activity was detected using the β-glucuronidase (GUS) assay. While the EaPHT1;2 promoter showed 3 to 4.2-fold higher expression than the most widely used CaMV35S promoter. The 5’ deletion analysis with and without 5’UTR regions, revealed that a small size 374 bp fragment with the highest promoter activity among 5′ truncated fragments, which was 2.7 and 4.2 times higher than the well-used CaMV35S promoter under normal and Pi-deprivation conditions, respectively. The strong and short promoter of EaPHT1;2 with 374 bp showed significant expression in low Pi-stress conditions and it could be a valuable source for the development of stress-tolerant transgenic crops

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

Vehicle driveability is one of the important vehicle attributes in range-extender electric vehicles due to the electric motor torque characteristics at low-speed events. The process of validating and rectifying vehicle driveability attributes is typically utilised by a physical vehicle prototype that can be expensive and required several design iterations. In this paper, a model-based energy method to assess vehicle driveability is presented based on a high-fidelity 49 degree-of-freedom powertrain and vehicle systems. Multibody dynamics components were built according to their true centre of gravity relative to the vehicle datum for providing an accurate system interaction. The work covered a frequency at less than 20 Hz. The results that consisted of the component frequency domination are structured and examined to identify the low-frequency sensitivity based on different operating parameters such as a road surface coefficient. An energy path technique was also implemented on the dominant component by decoupling its compliances to study the effect on the vehicle driveability and low-frequency response. The outcomes of the research provided a good understanding of the interaction across the sub-systems levels. The powertrain rubber mounts were the dominant components that controlled the low-frequency contents (< 15.33 Hz) and can change the vehicle driveability quality.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

Base excision repair (BER) is a cellular process that removes damaged bases arising from exogenous and endogenous sources including reactive oxygen species, alkylation agents, and ionizing radiation. BER is mediated by the actions of multiple proteins that work in a highly concerted manner to resolve DNA damage efficiently to prevent toxic repair intermediates. During the initiation of BER, the damaged base is removed by one of 11 mammalian DNA glycosylases resulting in abasic sites. Many DNA glycosylases are product inhibited by binding to the abasic site more avidly than the damaged base. Traditionally apurinic/apyrimidinic endonuclease, APE1, was believed to help turnover the glycosylases to undergo multiple rounds of damaged base removal. However, in a series of papers from our laboratory we have demonstrated that UV-damaged DNA binding protein (UV-DDB) stimulates the glycosylase activities of human 8-oxoguanine glycosylase (OGG1), MUTY DNA glycosylase (MUTYH), alkyladenine glycosylase/N-methylpurine DNA glycosylase (AAG/MPG), and single-strand selective monofunctional glycosylase (SMUG1), between three-to-five-fold. Moreover, we have shown UV-DDB can assist chromatin decompaction facilitating access of OGG1 to 8-oxoguanine damage in telomeres. This review summarizes the biochemistry, single-molecule, and cell biology approaches that our group used to directly demonstrate the essential role of UV-DDB in BER.

We investigate new graph characteristics namely total (vertex, edge) face irregularity strength of gen- eralized plane grid graphs Gmn under k-labeling Phi of type (Alpha, Beta, Gamma). The minimum integer k for which a vertex-edge labelled graph has distinct face weights is called the total face irregularity strength of the graph and is denoted by tfs(Gmn). In this article, the graphs G = (V;E; F) under consideration are simple, finite, undirected and planar. We will estimate the exact tight lower bounds for the total face irregularity strength of some families of generalized plane grid graphs.

In recent years, rainfall-induced waterlogging has become a common hazard in the highly urbanized coastal city of Chattogram, Bangladesh resulting in high magnitude of property damage and economic loss. Therefore, the primary objective of this research is to prepare a waterlogging inventory map and understand the spatial variation of the risk by means of hazard intensity, exposure, and vulnerability of waterlogging. In this research, the inventory map and factors influencing waterlogging hazard were determined from a participatory survey and other spatial data including land elevation, population, and structural data were collected from secondary sources. Analytical Hierarchy Process was applied to measure the hazard intensity and the exposure and vulnerability were estimated by overlaying the spatial data onto the hazard intensity map. A total of 58 locations in 22 wards have been identified as waterlogging affected, which covers ~8.42% of the city area. Obtained waterlogging vulnerability index map suggests that ward no. 5, 6, 16, 17, and 33 are greatly vulnerable to waterlogging in terms of their social, infrastructure, critical facilities, economic and environmental vulnerability. We show that ~2.71% of the study area is at very high risk, while the risk score is considerably higher for ward no. 5, 8, 17, 19, and 33.

Drydocking a ship is essential to the routine maintenance process during its service/operational life. During the drydocking time, various surveys/inspections are carried out per requirements of the classification society, flag administration, and statutory bodies, particularly the underwater items. For shipyards, optimum utilization of drydock capacity (deadweight) is the most considered factor to optimize the physical performance indicators like drydock occupancy rate, capacity utilization rate, and drydock utilization. However, in real life, even after mobilizing all available resources to achieve the optimum usage rate, the overall physical performance could be higher or lower or not up to the expectation. The average size (deadweight) of ships calling to the drydock is observed to be far below the expected capacity, resulting in under-utilization of installed capacity. However, although the drydock occupancy rate is satisfactory, even 100%. For a substantial amount of time, the drydock has been under-utilized in terms of capacity utilization and drydock utilization rate. Drydocking activities of ships in two (2) drydocks of a shipyard are collected and analyzed. Various physical performance indicators (PPIs) are calculated. They are diagnosed year-wise and presented in tabular and graphical form to demonstrate their behavior over the operating period. Authors have investigated the behavior of the above-mentioned physical performance indicators to justify, technically, the selection of capacity of a drydock. A further attempt has been made to propose some recommendations and guidelines from technical viewpoints for the selection criteria of a drydock capacity based on available resources.

Background: COVID-19, a member of corona virus family is spreading its tentacles across the world due to lack of drugs at present. Associated with its infection are cough, fever and respiratory problems causes more than 15% mortality worldwide. It is caused by a positive, single stranded RNA virus from the enveloped coronaviruse family. However, the main viral proteinase (Mpro/3CLpro) has recently been regarded as a suitable target for drug design against SARS infection due to its vital role in polyproteins processing necessary for coronavirus reproduction.Objectives: The present in silico study was designed to evaluate the effect of Eucalyptol (1,8 cineole), a essential oil component from eucalyptus oil, on Mpro by docking study.Methods: In the present study, molecular docking studies were conducted by using 1-click dock and swiss dock tools. Protein interaction mode was calculated by Protein Interactions Calculator.Results: The calculated parameters such as RMSD, binding energy, and binding site similarity indicated effective binding of eucalyptol to COVID-19 proteinase. Active site prediction further validated the role of active site residues in ligand binding. PIC results indicated that, Mpro/eucalyptol complexes forms hydrophobic interactions, hydrogen bond interactions and strong ionic interactions.Conclusions: Therefore, eucalyptol may represent potential treatment potential to act as COVID-19 Mpro inhibitor. However, further research is necessary to investigate their potential medicinal use.

This study assessed farmers’ perception of climate change, estimated the determinants of, and evaluated the relationship among adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, are found to be more influential compared to other factors. All four adaptation-options are found to be complimentary to each other. Importantly, the intensity of impact of dependent variables in different models, and for available adaptation-options, are found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

Alternative fuels have the potential to reduce exhaust emissions in the transportation sector. In this study, the effects of oxygenated fuels on the performance and emissions of a gasoline single-cylinder spark-ignition engine have been investigated experimentally. Experiments were conducted using a DIDACTA-T85 testbed under full load conditions and variable engine speed. Performance tests were performed by measuring the brake torque, brake power, brake mean effective pressure (BMEP), brake specific fuel consumption (BSFC), and brake thermal efficiency (BTE). The tested fuel blends were G0, E10, A10, and M10. G0 represented the base fuel and pure gasoline. E10, A10, and M10 were represented by a 10% volume of ethanol, acetone, and methanol in gasoline respectively. Results showed that M10 produced better engine performance in terms of brake torque, brake power, and BMEP, while E10 performed better results in terms of BSFC and BTE. A10 gave the lowest value in NOx emission at all engine speeds. On the other hand, it increased the NOX emission for E10 and M10 blends. This study showed that oxygenated fuel blends significantly reduced carbon monoxide emission at all engine speeds whereas carbon dioxide emission was higher at the highest engine speed.

Atopic dermatitis (AD) is a chronic inflammatory condition which significantly affects quality of life in both patients and their caregivers. Calcineurin inhibitors (CNI) are a class of immunosuppressive drugs predominantly inhibiting T cell mediated immune processes. CNI form complex by binding with immunophilins and in turn inhibit calcineurin and suppress downstream inflammatory pathway. Tacrolimus and pimecrolimus are topical CNI approved for the treatment of mild to severe AD in both children and adults. Application site reactions are frequently seen. They have been issued with black box warning towards increased risk of malignancies but supportive evidence is lacking. Cyclosporine, though highly effective, is used off-label for AD management. It is used for controlling acute flares of AD due to its very rapid onset of action. Nephrotoxicity and hypertension are its serious complications. CNI have not been reported with teratogenicity and may be used conditionally during pregnancy and lactation.

Background: Combinatorial therapy- “nano antibiotics” is an emerging field in nanoscience. In this present investigation, we attempted to combine the green synthesized noble metal nanoparticle and the antibiotic Streptomycin to form bio-conjugated nanoparticles. The newly synthesized Nano antibiotics acted as the antibiotic carrier, functioned as cargo, and delivered the antibiotic. Methods: Comparative studies between the noble metal nanoparticles were attempted for the first time on the grounds of their antibacterial activity. The antibacterial activity of the three noble metal nanoparticles was assessed against Streptomycin-resistant Bacillus sp.; the results obtained proved that silver nanoparticles were a potent antibacterial agent. Still, no antibacterial activity was exerted by gold, and platinum nanoparticles were for the Streptomycin-resistant strain Bacillus sp. To our surprise, the gold and platinum fabricated/bio-conjugated nanoparticle with the antibiotic showed 100% antibacterial activity, whose antibacterial activity was zero when functioning as a nanoparticle alone. Results: The combinatorial therapy of two different clauses of drugs majorly increased antibacterial activity. It enhanced the antibiotic to overcome the resistance exhibited by the bacterial pathogen, and the possible mechanism is elucidated in the present study. Also, an attempt has been made to assess the nanotoxicity of the nano-bioconjugates on RBC and compare their hemocompatibility. The results obtained in the current investigation demonstrate the enhanced antibacterial activity of the green synthesized nanoparticles conjugated with the streptomycin; their efficacy for combinational therapy against resistance in pathogenic organisms highlights the novelty of the work and the comparative study of three different noble metals nanoparticles (Ag, Au, Pt) from single agro-waste for the first time.

The definitive negative results of various direct searches for dark matter particles and non-observation of them has increasingly indicated that we should consider alternate models like the Modification of Newtonian Dynamics (MOND) and Modification of Newtonian Gravity (MONG). It is puzzling how the Oort cloud, despite its great distance from the Sun, is gravitationally bound to the Sun’s gravity. In this work, we suggest that this could be explained by the modifications to Newtonian dynamics (MOND) and to gravity (MONG).

Drought negatively affects the growth and development of barley. To explore the genetic variation in barley under drought stress, ten breeding genotypes were tested using polyethylene glycol-6000 to simulate drought conditions. We observed that drought stress adversely affected germination-related traits across all barley genotypes and this impact varied between genotypes, suggesting genotype-specific drought tolerance. The drought tolerance index was an ideal criterion for selecting drought-tolerant genotypes as it well characterized the gradient responses of barely genotypes to drought stress. Based on this indicator, genotype OB1878-ON-50 is recommended as a significant germplasm resource for breeding programs under lower precipitation conditions due to its superior tolerance to drought stress.

Olive mill wastewater (OMW) has serious environmental problems considering its high organic matter, especially its phenolic compounds. The OMW application in crop protection is an alternative environmentally eco-friendly method reducing the chemicals pesticides impact on human health and environment. The present work aimed to study the antifungal activity of fresh and stored OMW and its ethyl acetate extract against phytopathogenic fungi: Syncephalastrum racemosum (S. racemosum), Paramyrothecium roridum (P. roridum), Fusarium oxysporum (F. oxysporum) and Verticilium dahlia (V. dahlia). The OMW was stored at 25 and 45 °C for 3 months. Fresh and stored OMW were used non-sterile, sterile and centrifuged. Phenolic and flavonoid compounds were extracted and identified by HPLC analysis. High inhibition of studied fungi was shown by fresh OMW and its derivative compounds, while OMW storage, sterilization, and centrifugation increased mycelium growth of studied fungi, especially S. racemosum that showed a relative resistance against stored OMW effect and its ethyl acetate extract. Under storage conditions, some phenolic and flavonoid compounds disappeared (resorcinol and vanillic acid), while the concentration of other compounds increased (gallic acid, chlorogenic acid and quercetin). This work highlighted the ability to use fresh OMW as a bio-agent to protect plants from fungi diseases.

Hypertrophic obstructive cardiomyopathy (HOCM) is an autosomal dominant disorder leading to left ventricular outflow tract obstruction (LVOTO). It can present with chest pain, syncope, breathlessness, or in some cases sudden cardiac death. Primarily, it is diagnosed based on echocardiographic findings but cardiac computed tomography (CT) or cardiac magnetic resonance imaging (MRI) can be helpful in selected cases. In this case report, we discuss a case of a young-aged female patient previously diagnosed as HOCM and presented with chest pain, shortness of breath, and palpitations. Her echocardiography revealed severe asymmetrically hypertrophied left ventricle (LV) with normal function and systolic anterior motion of the mitral valve was present and a subvalvular aortic membrane was also seen. The computed tomography (CT) was also performed showing severe asymmetrical hypertrophied and thickened trileaflet tricommissural aortic valve with no calcification or significant valvular aortic stenosis but there was a subaortic membrane (concentric only sparing anteriorly). The presence of subaortic membrane with HOCM is a rare finding and it can be a diagnostic challenge and untreated cases are susceptible to progressive heart failure and worsening of the symptoms by further increasing left ventricular outflow tract obstruction (LVOTO). A thorough investigation and planning before surgical intervention is required to achieve optimal results.

The present study aimed to undertake a detailed investigation of pathological epidemiology and molecular confirmation of Ehrlichia canis among pet dogs in smart city Bhubaneswar, Odisha, a state in eastern India. A total of 178 dogs were screened for Ehrlichiosis on the basis of history, clinical signs, blood, and buffy coat smear examination, resulting in only 56 dogs (31.46%) screening positive. The epidemiological study recorded an increase in incidences among dogs less than one year of age (41%), males (68%), German Shepherds (25%), dogs more than 20 kg body weight (75%), summer months (55%) and dogs housed on pukka houses with exposure to the outside (59%). The majority of the infected dogs had a history of tick infestation (79%) at some point in their life. Clinical signs showed non-typical manifestations like fever, lethargy, diarrhoea, epistaxis, hind limb edema, and corneal opacity. Haematological studies revealed anaemia and thrombocytopenia along with neutrophilia with relative lymphopenia and monocytosis. A decreasing trend was observed in the levels of total protein and albumin with an increase in the levels of globulin, AST, ALT, BUN, and creatinine. The ultrasonography studies revealed hepatosplenomegaly along with hyper-echogenicity in various organs. Pro-teinuria and haematuria were consistent, along with the presence of bile salts in the urine of affected dogs. Molecular confirmation from n-type PCR data using Ehrlichia-specific primers targeting p28 gene (843 bp) was done, and the identified gene sequences submitted to NCBI databases have accession numbers OQ383671-OQ383674 and OP886674-OP886677. Ticks collected from dogs were identified morphologically through microscopy and scanning electron microscopy as Rhipicephalus sanguineus.

This paper focuses on the new users cold-start issue in the context of recommender systems. New users who do not receive pertinent recommendations may abandon the system. In order to cope with this issue, we use active learning techniques. These methods engage the new users to interact with the system by presenting them with a questionnaire that aim to understand their preferences to the related items. Example of questions may include "do you like this book?" and the users answer,"yes", "no", "I have not read it (unknown)", will reflect the degree of interest for the item by the users. As a consequence, the system can learn the users' preferences from these answers. The goal of active learning is to correctly choose the questions (items) for users. Thus it is necessary to personalize the questionnaires to retrieve the maximum information by avoiding "unknown" answers. In this paper, we propose an active learning technique that exploits past users' interests and past users' predictions in order to identify the best questions to ask.

Coronavirus disease is the current cause of global concern. The massive outbreak of COVID-19 has led the World Health Organization (WHO) to declare this as a pandemic situation. The Severe Acute Respiratory Syndrome Coronavirus-2 (SARSCoV-2) is responsible for COVID-19 leading to acute respiratory distress and substantial mortality in humans. However, the first laboratory confirmation of SARS-CoV-2 in a pet dog in Hong Kong has shown the possibility of human-to-animal transmission (zooanthroponotic) of the virus. Thereafter, many animals including cat, tiger, lion and mink have also been reported to acquire the virus in several countries. In this situation the role of veterinarian assumes important in treating the animals, helping in food security, disease diagnosis, surveillance and boosting the economy of livestock stakeholders at the grassroot level. In the absence of any selective vaccine or drug against SARS-CoV-2, the world is anticipated to triumph over this pandemic with collaborative, multisectoral, and transdisciplinary approach linking human, animal and environmental health. This article gives an insight into the confirmed SARS-CoV-2 outbreaks in animals, including the factors behind the shuffling of the virus among variety of species and also emphasizes on the role of veterinarian in managing and safeguarding public health so as to pave the way for adopting one health approach in order to conserve biodiversity.

The ternary Bi2MoO6-reduced graphene oxide (rGO)-TiO2 catalyst were synthesized using a simple hydrothermal method. The improvement of the photocatalytic decomposition efficiency of Bi2MoO6-rGO-TiO2 composite is 92.3% than the pure and binary photocatalyst. The effects of operational parameters like catalyst ratio, the different catalyst, different ratio rGO and different pH, have been analyzed. As prepared ternary photocatalyst is low Photoluminescence and high photocurrent density responsible, it exhibited that photon-induced electron and hole-recombination were suppressed and also charged separation is effective. The present study shows the rGO is an excellent electron transfer performance and enhanced the photocatalytic reaction stability.

Maternal and child nutrition has been a critical component of health, sustainable development, and progress in low- and middle-income countries (LMIC). While a decrement in maternal mortality is an important indicator, simply surviving pregnancy and childbirth does not imply better maternal health. One of the fundamental obligations of nations under international human rights law is to enable mothers and teenage girls to endure pregnancy and delivery as an aspect of their enjoyment of reproductive and sexual health and rights and live a dignified life. The aim of this study was to discover the correlation between the Maternal Observation and Motivation (MOM) program and m-Health support for maternal and newborn health. A Comparative study was done among 109 pregnant mothers (study group-94; control group-102 mothers) with not less than 20 weeks of gestation. Maternal outcomes such as Hb, weight gain and newborn results like birth weight and crown- heel length was obtained on the baseline, 28 and 36 weeks of gestation. Other secondary data collected were abortion, stillbirth, low birth weight, major congenital malformations, twin or triplet pregnancies, physical activity and maternal wellbeing. The MOM intervention included initial face to face education, three in-person visits and eight virtual health coaching by WhatsApp. The baseline data on Hb of the mothers show that 31(32.98%) vs 27(28.72%) of the study and control group had anaemia, which improved to 27.66% and 14.98% among study group mothers at 28 and 36 weeks of gestation (p<0.001). The weight gain (p< 0.001), level of physical activity (p< 0.001), and maternal wellbeing (p< 0.01) also had significant differences after the Intervention. Even after controlling for potentially confounding variables, the maternal food practices regression model revealed that birth weight was directly correlated with consumption of milk (p 0.001), fruits (p 0.01), and green vegetables (p 0.05).As per the physical activity and maternal wellbeing regression model, the birth weight and crown heel length were strongly related with the physical activity and maternal wellbeing of mothers at 36 weeks of gestation (p <0.05). Combining the MOM intervention with standard antenatal care is a safe and effective way to improve maternal welfare while upholding pregnant mothers' human rights.

The novel coronavirus has affected the mental state of the general public, more so among healthcare workers. During the pandemic when the infectivity had become intense, dental professionals were at stake as their work demanded more proximity with oral and nasal secretions. Many dentists had to close their clinics for fear of infection. This had a significant impact on their financial, social and emotional wellbeing. Stress is what arises when something we care about is at stake. Dentistry which is already a stressful discipline, the pandemic has multiplied the already existing pressures of isolation, the focus on perfectionism, compromise on treatment, and time pressures. Our study has attempted to assess the perceived stress among dentists and the various correlates impacting the same. Resilience is the capacity to bounce back productively during stressful situations. Resilience acts like a buffer to wither stress. Resilience is neither permanent nor global. In our study, we have attempted to assess resilience among dentists using a standard validated scale and various sociodemographic factors impacting resilience. Further, we have tried to assess the correlation between stress and resilience. We found that senior dentists with more years of experience had more resilience and their perceived stress was less. Though we found increased perceived stress among women dentists, resilience did not have any gender difference. It is essential to be pandemic prepared with the implementation of resilience-building strategies at various levels.

The disaster response operational strategies requires tool that a may provide time bound clear picture of potential spots. Natural disaster sometimes comes slowly like increment of water level resulting flood or early warning of tsunami whereas in manmade disasters like 1CBRNE attack or chemical accident or industrial structure collapse or leakage through a pipeline of some toxic hazardous gas requires very accurate and quick response strategies. 2Unmanned Aerial System is commercially used tools present in the market and also used by military organization for various operations throughout the world. The accuracy and time bound pictorial representation of the spots by these tow tools makes them very useful for providing clear picture of potential disaster sites and enabling decision makers to take decision on these representation. Apart of these the potential to deliver important material faster than any other mode also makes these equipment and technology a very important asset for making disaster risk reduction strategies. This paper elaborates the efficacy and utility of Unmanned Aerial System or Drones in developing robust and time bound strategies for disaster risk reduction. This paper also evaluates some experiences and describes some initiatives using Unmanned Aerial System to support disaster risk reduction strategies and post disaster decision making efforts.

There are evidences of shared biological mechanisms between obesity and hypertension during childhood in the adulthood, and loads of research literatures have proven that, it will cost the economies and health of nations profoundly if neglected. The Prevention and early diagnosis of cardiovascular risk factors such as overweight and hypertension is an essential strategy for control, effective treatment and prevention of its’ complications. The aim of the study is to assess the effect of school based Exercise and Life style Motivation Intervention (SEAL-MI) on adolescent's cardiovascular risk factors and academic performance. An experimental study was conducted among 1005 adolescents - 520 and 485 adolescents were randomly selected for control and study group, respectively. Demographic details and the data related to dietary habits, physical activity and sleep quality were collected by a structured interview questionnaire. The study group adolescents were given the SEAL-MI for six months which includes a school based rope exercise for 45 minutes per day for 5 days a week and a motivation intervention related to dietary habits, physical activity and sleep. Post-test 1 and 2 were done after 3 and 6 months of intervention. The prevalence of overweight among adolescents was 28.73% and prehypertension was 9.26%. Among overweight adolescents, the prevalence of prehypertension was found to be very high (32.25%). In post intervention, there was a significant reduction in weight, BP (p=0.000) and improvement in dietary habits, physical activity, sleep (p=0.000) and academic performance. A significant positive correlation was found between BMI and SBP (p=0.000) and BMI and academic performance (p=0.003). The linear regression analyses revealed that the gender (ß: 0.47, 95% CI: 0.39, 0.81), age (ß: 0.39, 95% CI: 0.17, 0.46), family income (ß: 0.2, 95% CI: 0.41, 0.5), residence (ß: 0.19, 95% CI: 0.01, 0.27) and type of family (ß: 0.25, 95% CI: 0.39, 0.02) had the strongest correlate with the BMI of the adolescents. Also, Mother’s education Mother’s education (ß: 0.35, 95% CI: 0.18, 0.59) had the strongest correlate with the SBP of the adolescents. In contrast, the DBP was negatively persuaded by age (ß: -0.36, 95% CI: 1.54, 0.29) and gender (ß: -0.26, 95% CI: 1.34, 0.12) of the adolescents. Regular practice of rope exercise and lifestyle modification such as diet, physical activity and sleep quality among adolescents prevent and control childhood CVD risk factors like overweight, hypertension. The SEAL-MI may lead to age appropriate development of adolescents and improves their academic performance and quality of life. Giving importance to the adolescents from urban habitat, from affluent nuclear family and catching them young will bring significant change in the disease burden.

Molluscs are significant species in aquatic ecology. Molluscs are crucial for maintaining ecological balance as secondary consumers and serving as bioindicator species in biomonitoring systems. Molluscs are threatened by pesticides such as commonly used pyrethroid insecticides. Pyrethroids are typical insecticides used to control insects in agriculture and gardening. Pyrethroids are increasingly being utilized in both agricultural and human activities. Pyrethroids enter aquatic bodies through rainfall and drainage systems. The use of pyrethroids is becoming a significant concern for aquatic creatures, particularly molluscs. The discussion will focus on the increasing issue of pyrethroids becoming a nightmare for molluscs. Pyrethroids, due to their lipophilic nature, pose a significant risk to molluscs by affecting their metabolites, producing reactive oxygen species, and influencing neurotransmitter actions. Molluscs are crucial organisms in aquatic ecosystems, and their threats warrant significant discussion and attention. This review will delve into the behaviour of pyrethroids on molluscs.

Polyhymnia (33 Polyhymnia) is a main belt asteroid in our solar system with a diameter of around 54km. The density of asteroid 33 Polyhymnia, located in the main asteroid belt, is calculated to be 75g/cc. Researchers have speculated the possibility that Polyhymnia could be composed of high-density superheavy elements near atomic number 164. Here we propose that Polyhymnia could be an asteroid composed of degenerate Dark Matter (DM) and there could be many such asteroids in our solar system (this is following our earlier work suggesting Planet Nine could be such an object).

We point out that field equations of general relativity are implied by a maximal force given by c⁴/4G, analogous to the way that special relativity is implied by a maximal speed given by c. We present some of the arguments for this equivalence. The maxi-mal force naturally plays the role of an elastic constant for space-time. Implications of the maximal force for gravitational wave measurements, cosmology and black holes are highlighted. Quantum aspects of the maximal force are discussed.

Steels studs are an inevitable part of drywall construction as they are lightweight and offer the required structural stability. However, the studs act as sound bridges between the plasterboards reducing the overall sound insulation of the wall. Overcoming this often calls for wider cavity walls and complex stud decoupling fixtures that increase the installation cost while reducing the floor area. As an alternative approach, this research reveals the potential of perforated studs to improve the acoustic insulation of drywall partitions. The acoustic and structural performance is characterized using a validated finite element model that acted as a prediction tool in reducing the number of physical tests required. The results established that an acoustic numerical model featuring fluid-structure-interaction can predict the weighted sound reduction index of a stud wall assembly at an accuracy of ±1 dB. The model was used to analyze six perforated stud designs and found to outperform the sound insulation of non-perforated drywall partitions by reducing the sound bridging. Overall, the best performing perforated stud design was found to offer improvements in acoustic insulation of up to 4 dB, while being structurally compliant.

The estimation of the Hubble constant in the past few decades has increasingly become more accurate with the advance of new techniques. But its value seems to depend on the epoch at which the measurements are made. The Planck estimate of the Hubble constant from the observations of the CMBR in the early Universe is about 67.

December 4, 2020 marks 90 years since the concept of neutrinos was proposed as a consequence of the observed discrepancies in several experiments on radioactive decays of various isotopes. There have been great many developments in our understanding of this elusive particle over the past nine decades, also leading to several Nobel Prizes awarded to work on neutrino physics. But there are many aspects of the neutrinos that are still not completely understood, including even its actual rest mass. The neutrino still remains an enigma and we have yet to learn a lot about its different properties. This article summarises the overall picture of the current understanding of the neutrino, right from its inception.

The presence of dark matter, though well established by indirect evidence is yet to be observed directly. Various dark matter detection experiments running for several years have yielded no positive results so far. In view of these negative results, we had earlier proposed alternate models by postulating a minimum gravitational field strength (minimum curvature) and also a minimum acceleration. These postulates led to the modified Newtonian dynamics and modified Newtonian gravity (MONG). The observed flat rotation curves of galaxies had also been accounted for through these postulates. Here we extend these postulates to galaxy clusters and model the dynamical velocity-distance curves for such large-scale structures. The velocity-distance curve of the Virgo cluster, plotted with this model is found to be in accordance with that observed.

Here we propose a modification of the gravitational field on large scales as an alternate explanation for the discrepancy in the value of the Hubble constant as implied by Planck observations of the CMBR in the early Universe and that deduced from other distance indicators in the present epoch.

This paper presents an on-device semi-supervised human activity detection system that can learn and predict human activity patterns in real time. The proposed semi-supervised learning (SSL) framework uses sparsely labelled user activity events acquired from Inertial Measurement Unit (IMU) sensors installed as wearable device. The objective is to learn classification of multiple classes of human activities in real-time. The proposed cluster-based learning model in this approach is trained with data from the same target user, thus preserving data privacy while providing personalized activity detection services. Two different cluster labelling strategies, namely, population-based, and distance-based, are employed to achieve the desired classification performance. A comparative study of these strategies has been presented in terms of classifiability and classification accuracies. The proposed system is shown to be computationally efficient, which is relevant in the context of limited computing resources on typical wearable devices. The trade-off between classification accuracy and computation complexity is analyzed for different algorithmic hyper-parameters and other system parameters. Extensive experimentation and simulation study have been conducted on a multi-user human activity data from the public do-main in order to validate the proposed learning paradigm.

In a recent paper we had discussed possibility of DM at high redshifts forming primordial planets composed entirely of DM to be one of the reasons for not detecting DM (as the flux of ambient DM particles would be consequently reduced). In this paper we discuss the evolution of these DM objects as the universe expands. As universe expands there will be accretion of DM, Helium and Hydrogen layers (discussed in detail) on these objects. As they accumulate more and more mass, the layers get heated up leading to nuclear reactions which burn H and He when a critical thickness is reached. In the case of heavier masses of these DM objects, matter can be ejected explosively. It is found that the time scale of ejection is smaller than those from other compact objects like neutron stars (that lead to x-ray bursts). These flashes of energy could be a possible observational signature for these dense DM objects.

Initial evaluations of the System of Rice Intensification in India and elsewhere have mainly fo-cused on its impact on yield and income and have usually covered just one or two seasons. Re-searchers at the ICAR-Indian Institute of Rice Research conducted a more comprehensive evalua-tion of SRI methods over six years (six wet and six dry seasons), comparing these methods with three other rice crop management systems: modified, partially mechanized SRI (MSRI); direct-seeded rice (DSR); and normal transplanting with inundated fields (NTP). SRI grain yield was found to be about 50% higher than with NTP (6.35 t ha-1 vs 4.27 t ha-1), while the MSRI yield was essentially the same (6.34 t ha-1) and 16% higher than with DSR (5.45 t ha-1). Compared to NTP, SRI methods significantly enhanced soil microbial populations over time, bacteria by 12%, fungi by 8%, and actinomycetes by 20%. Indicators of biological activity in the rhizosphere were also higher, dehydrogenase by 8.5% and FDA enzymes by 16%. Glucosidase activity, an indicator of soil organic matter, was 78% higher. Relative to normal transplanting methods, SRI reduced GHG emissions by 21%, while DSR reduced them by 23% and MSRI by 13%, which indicated pos-itive effects of the alternate and improved methods over normal transplanting. Economic analy-sis showed that both gross and net economic returns to be higher with SRI than with MSRI and the other management systems evaluated. While the six-year study documented many ad-vantages of SRI crop management, the MSRI version evaluated is a promising adaptation that provide similar benefits but with lower labor requirements.

Atmospheric lightning is an outcome of extreme complex physical processes occurring in the atmosphere. Cloud-to-ground (CG) lightning is considered as a natural disaster. Understanding the importance of CG lightning and implication of the lightning phenomena, Global Climate Observing System (GCOS), world meteorological organization, in its report in the year 2016, introduced the lightning as an Essential Climate Variable (ECV). The present report uses the Lightning Detection Sensor Network (LDSN) established by the National Remote Sensing Centre, Indian Space Research Organization over India to generate the Lightning ECV. A use case of these ECVs are also showcased for an event in Bihar, India, when 42 deaths were reported at locations with large number of CG occurrences.

COVID-19 manifests regarding extreme acute respiratory conditions caused by a novel beta coronavirus (SARS-CoV-2) which is reported to be the seventh coronavirus to infect humans. Like other SARS-CoVs it has a large positive-stranded RNA genome. But specific furin site in the spike protein, mutation prone and phylogenetically mess Orf1ab separates SARS-CoV-2 from other RNA viruses. Since, the outbreak (February - March 2020) which originated in China, researchers, scientists, and medical professionals are inspecting all possible facts from every possible aspect including its replication, detection, and prevention strategies. This led to the prompt identification of its basic biology, genome characterization, structural based functional information of proteins, and strategies to prevent its spread. Due to the rapid mutation rate, the functional characterization of a few proteins is still lagging. This review summarizes the recent updates on the basic molecular biology of SARS-CoV-2 and prevention strategies undertaken worldwide to tackle COVID-19. This recent information can be implemented for the development and designing of therapeutics against SARS-CoV-2.

Balancing the levels of ammonia, in poultry facilities plays a role in enhancing the welfare and productivity of animals. Various environmental factors such as temperature, humidity, ammonia concentrations, carbon dioxide concentration and exposure to light have an impact on the wellbeing and efficiency of poultry. It is essential to monitor these elements to achieve outcomes necessitating practical, reliable and cost-effective solutions. Leveraging the Internet of Things (IoT) in conjunction with LoRa-WAN (Long Range Wide Area Network) technology presents an opportunity in the industry by enhancing connectivity among devices and facilitating real time data transmission. This research introduces a hardware and software setup for monitoring conditions at poultry farms through LoRa WAN and IoT technologies. More-over researchers employed Random Forest Machine Learning prediction models to tune the concentration of Ammonia (NH3) in poultry facilities across a wide area or multiple Poultry houses. Comparative assessments were conducted to evaluate the proposed system against devices revealing a correlation exceeding 0.9830 between the sensors and standard equipment while costing 28% less than traditional tools. The prototype displayed outcomes underscoring its potential, for managing poultry facilities across multiple farms with centralized oversight.

Long COVID is a phenomenon in which individuals experience persistent symptoms after recovering from COVID-19. The symptoms are discovered to be unique for every individual and can affect multiple organs systems in the body. This study aims to identify effective natural remedies for long COVID by analyzing hub genes associated with the symptoms of the condition and evaluating the repurposed drugs catered and used for treating the symptoms of long COVID. The most common and prevalent symptoms of long COVID were identified; Fatigue, Shortness of Breath, Loss of Smell, Headache, Brain Fog, Chest Pain, Insomnia, Heart Palpitations, Dizziness, Joint Pain, Depression, Anxiety, Tinnitus, Loss of Appetite. Hub genes for each of the symptoms provided an insight on the key biological pathways of the symptom. Repurposed drugs identified, provided the template to identify the natural compounds with similar structure as a potential therapeutic drug. The natural compounds were retrieved using fingerprint search of the repurposed drugs from the NPASS Database. The findings of this study suggest several natural remedies for each symptom based on the molecular docking of the hub gene and natural compound using iGEMDOCK. The identified natural remedies may hold promise in treating long COVID, but further research is required to explore the efficacy and effectiveness of the proposed natural compounds. The results of the study pose important implications for the development of effective treatments for long COVID.

Pesticides are chemical compounds or mixtures of hazardous substances that are used by humans to increase and protect crops from pests and control disease-carrying insects. Because of its wide use, it may be poisonous to helpful and non-targeting plants and animals. Spraying or spreading pesticides over whole fields of crops can cause runoff to transfer the chemicals into aquatic ecosystems, and wind can carry the chemicals to nearby grazing regions, farms, and populated areas, where they can endanger other animals. This review summarises recent studies on pesticide combination toxicity to aquatic biota and approaches used to anticipate toxic effects. When toxicants harm economically significant organisms that humans consume, the negative effects become more severe and can cause stress conditions, vital organ damage, biochemical damage, or even the death of living things in both terrestrial and aquatic environments. Pesticides are highly toxic to aquatic organisms such as snails, fish, etc. Neurological dysfunction in freshwater organisms is also caused by pesticides. By producing excessive ROS, pesticides can cause severe biochemical and histological changes in freshwater organisms. So, it is therefore easy to understand the attention of the public on these substances. Because aquatic organisms play a major part in the food chain. However, through the biomagnification process, the quantity of pesticides increases in the higher organisms through the food chain. Which results play a terrific role in the higher organism’s body. So, It's essential to comprehend the way that insecticides work on aquatic organisms. In this review article, we are focusing on the way that pesticides work, which will help in the system of biomonitoring.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

Interpretive Structural Modelling (ISM) is widely used to understand the complex connections between different components. This study presents a bibliometric overview of ISM research with a focus on its linkages to the Sustainable Development Goals (SDG) and the impact of COVID-19. The study analyzed 1988 publications on ISM published between 2012 and 2021, of which 1202 were directly mapped to the SDG and 59 were related to COVID-19. The study identified key authors, institutions, countries, and journals involved in the research and their linkages to the SDG. The results showed that ISM research is strongly linked to SDG 12 (Responsible Consumption and Production) and SDG 9 (Industry, Innovation and Infrastructure). We also identified influential SDG based on centrality measures like betweenness and eigenvector. The top four countries contributing to ISM publications were India, China, the United Kingdom, and the United States. The most frequently cited journals were Benchmarking: An International Journal, Sustainability, Journal of Modelling in Management, and Journal of Cleaner Production. Four main clusters were identified in the ISM research, including (1) integration with AHP & Fuzzy Logic for promoting sustainability alignment, (2) ISM-based strategy development for various stakeholders, (3) ISM-based decision-making in various fields, and (4) ISM-based risk evaluation. For the first time studies that used ISM approach to understand the epidemiological characteristics of COVID-19 were identified and their key findings were discussed. The study also identified several emerging topics for future ISM research, such as blockchain & IoT, environmental management systems, climate change adaptation, smart cities, and humanitarian logistics and their potential linkages to SDG.

Background: Autonomic balance measurement (ABM) is a valuable tool in clinical practice for assessing the functioning of the autonomic nervous system (ANS), which controls involuntary bodily functions. Here we summarize the current understanding of the utility of autonomic balance measurement in clinical practice. Methods: A narrative review of relevant literature was conducted, focusing on studies investigating the use of autonomic balance measures in various clinical settings. Results: ABM holds potential benefits in clinical practice, including aiding in diagnosing autonomic dysfunction, monitoring treatment efficacy, and predicting potential health complications. ABM can be crucial for diagnosing various conditions, including cardiovascular diseases (Heart failure, arrhythmias, and hypertension), neurological disorders (Parkinson's disease, Alzheimer's disease, and diabetic neuropathy), in sports medicine athletes can undergo ABM to optimize training regimens, enhance performance, assessing the impact of training stress, preventing overtraining, and promoting overall well-being and probably to assess potential health risks, in metabolic syndromes ABM can aid in the early detection of autonomic neuropathy, a diabetes-related complication, allowing for timely intervention and better management of the disease, and psychiatric disorders (Anxiety, depression, and post-traumatic stress disorder). In addition, ABM can be helpful in monitoring of treatment efficacy, by tracking changes in autonomic balance, clinicians can assess if treatments for conditions impacting the autonomic nervous system are effective. ABM can also be helpful in predicting outcomes by facilitating early recognition of future health complications in certain populations. However, limitations exist, including non-specificity, variability in measurements, and limited evidence for routine use in specific clinical settings. Conclusion: Incorporating autonomic balance measurement into routine clinical assessments provides a more comprehensive understanding of a patient's health. It complements traditional diagnostic methods, offering additional insights into the body's regulatory mechanisms. While autonomic balance measurement offers potential benefits, careful interpretation and consideration of its limitations are crucial for its effective use in clinical practice. ABM remains a valuable and versatile tool in clinical practice for a deeper understanding of the autonomic nervous system, enabling early detection, targeted interventions, and improved management of various medical conditions across different specialties.

Legal consideration hold significant importance in the cloud migration process, encompassing contractual arrangements, data sovereignty concerns, and liability matters. Organizations need to make sure that their contracts with cloud service providers (CSPS) cover important aspects such as data ownership, usage rights, and indemnification clauses. In the ever-changing world of smart cities, the importance of ensuring secure, compliant, and efficient data migration across international borders has become more crucial than ever. This paper introduces a new framework that combines natural language processing (NLP), and blockchain smart contracts to tackle the intricate legal issues involved in moving data across borders in cloud settings. The framework starts by utilizing an NLP model to ensure compliance with data protection regulations, such as GDPR, CCPA, and DPDPA, which are specific to the destination jurisdiction of the data. After confirming the verification, the smart contract initiates the data transfer process, securely recording metadata such as file hash, timestamp, and transfer details on the blockchain, guaranteeing transparency and immutability. After the transfer, an international vendor at the destination verifies the data against the relevant legal requirements, guaranteeing compliance before storing it in the destination cloud. By adopting this approach, we can ensure the legal validity of cross-border data transfers, while also promoting trust and accountability among all parties involved in smart city ecosystems. The findings indicate that this framework has the potential to greatly reduce the risks associated with data sovereignty, liability, and contractual obligations when moving data to the cloud.

In the era of cloud computing, guaranteeing the safety and effectiveness of data management is of utmost importance. This investigation presents a novel approach that amalgamates sharding concept, encryption, zero-knowledge proofs (zkp), and blockchain technology for secure data retrieval and data access control to improve data security, efficiency in cloud storage and migration. Further we utilize user-specific digital wallets for secure encryption keys in order to encrypt the file before storing into the cloud. As Large files ( greater than 50 MB) or Big data file ( grater than 1 TB) computational complexity is more we leverage on sharding concept to enhance both space and time complexity in cloud storage, hence the large files are divided into shards and stored in different database servers. We also employed blockchain smart contract to enhance secure retrieval of the file and also a secure access method which ensures the privacy of the user. The zk-snark protocol is utilized to ensure the safe transfer of data between different cloud services. By utilizing this approach, data privacy is preserved, as only the proof of the data’s authenticity is shared with the verifier at the destination cloud, rather than the actual data itself. The suggested method tackles important concerns related to data protection, privacy, and efficient resource utilization in cloud computing settings by ensuring it meets all the cloud policies require to store data. As the environment maintains privacy of the user data and by not storing the raw data of the user anywhere, the entire environment is setup as a Zero trust model.

Antibiotic resistance among bacterial pathogens is recognized as a major threat to human health worldwide. The emergence of multidrug-resistant bacteria can also be found in the community settings, apart from hospital environment, which indicates that reservoirs of antibiotic resistance genes do exist outside the hospital. The growth of antibiotic resistance is a consequence of bacterial adaptations in response to selective pressures. To survive in this hostile environment, bacteria develop defence mechanisms such as chemical modification of antibiotics, enzyme-catalysed antibiotic degradation, altered permeability, antibiotic efflux, mutation of target sites and biofilm formation, resulting in resistance to nearly all currently available antibiotics used in the clinical practice. The present review summarizes insights into the molecular mechanisms underlying the antibiotic resistance which is useful for planning strategies to combat antibiotic resistance and devise innovative therapeutic tools to fight against multidrug-resistant bacterial species.

Long COVID, also referred to as post-COVID-19 condition, describes the lingering after-effects of COVID-19 infection. This complex syndrome encompasses a range of symptoms affecting physical well-being, cognitive function, and mental health. The widespread impact of long COVID extends beyond individual sufferers, placing significant strain on healthcare systems and causing far-reaching socioeconomic consequences. The scale of this multifaceted health crisis is unparalleled in recent history, affecting millions globally and challenging our understanding of post-viral conditions. This study aimed to explore the possibility of targeting G protein-coupled receptors (GPCRs) signaling pathway-related genes as therapeutics for long COVID using computational analysis. Targeting GPCRs and their signaling pathways holds significant promise for long COVID therapeutics, as these receptors are involved in crucial physiological processes including immune regulation, inflammation control, and neurotransmission. All of these are implicated in the diverse and persistent symptoms of long COVID, potentially offering a versatile approach to addressing multiple aspects of the condition simultaneously. This study identified 21 genes associated with GPCRs for further exploration as potential targets. Notably, GPCR genes such as HRAS, KRAS, GNAQ, and GNA11 were determined to be possible therapeutic targets for the pathophysiological mechanisms of long COVID. FDA-approved drugs targeting these genes were identified, including Binimetinib, Cabozantinib, Selumetinib, Panitumumab, Cetuximab, Adagrasib, Tipifarnib, and Sotorasib. Additionally, Naltrexone and Tipifarnib have emerged as potential new treatment options for long COVID. SARS-CoV-2 may hijack GPCR signaling pathways to dysregulate lung ion and fluid transport, contributing to the pathophysiology of pulmonary edema in patients with COVID-19. Further research is required to translate the findings into the development of therapeutics and to investigate the relationship between viral infection and GPCR signalling.

As the outbreak of coronavirus disease 2019 (COVID-19) is continuously increasing in India, so epidemiological modeling of COVID-19 data is urgently required for administrative strategies. Time series and is capable to predict future observations by modeling the data based on past and present data. Here, we have modeled the epidemiological COVID-19 Indian data using various models. Based on the collected COVID-19 outbreak data, we try to find the propagation rule of this outbreak disease and predict the outbreak situations in India. For India data, the time series model gives the best results in the form of predication as compared to other models for all variables of COVID-19. For new cases, new deaths, total cases and total deaths, the best fitted ARIMA models are as follows: ARIMA(0,2,3), ARIMA(0,1,1), ARIMA(0,2,0) and ARIMA(0,2,1). Based on time series analysis, we predict all variables for next month and conclude that the predictive value of Indian COVID-19 data of total cases is more than 20 lakhs with more than 43 thousand total deaths. The present chapter recommended that a comparison between various predictive models provide the accurate and better forecast value of the COVID-19 outbreak for all study variables.