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Startups face challenges in investing large amounts of money in business promotion due to resource constraints and operational size. Hence, business promotion strategies like advertising, public relations, sales promotions, billboards, and event sponsorship are generally avoided by startup companies. Instead, Startups tend to employ social media strategies to run promotional campaigns on platforms like Facebook, Twitter, Instagram, and YouTube, among others. However, there is a paucity of research to understand whether such promotional campaigns are delivering the desired value and able to achieve the objectives set by the startups. The present study makes an endeavor to explore whether promotions through social media are effective in delivering significant outcome to startups. Therefore, this study aims to empirically investigate whether Facebook Promotion is delivering value to Indian startups. To conduct the research, cross-sectional data has been collected from 100 startup located in different cities in India. The data has been analyzed following the “Partial Least Squared-Structural Equation Modelling (PLS-SEM)” technique. The findings from this study may contribute towards the literature on understanding the importance of social media strategies in marketing campaigns for startups. Furthermore, this study may enhance clarity about the value obtained by startups, particularly during the early stage of their existence. Consequently, the study findings may help startups plan their investments in promoting their products and services on social media, in general, and Facebook, in particular.

Introduction: Measles, a highly transmissible disease marked by fever and a maculopapular rash, posed a substantial threat to life in the 1960s. Nevertheless, the advent of the measles vaccine had a profound impact, significantly diminishing its toll on mortality. Similarly, through effective influenza surveillance and early epidemic warning systems, public health officials can timely identify influenza trends and provide crucial scientific support for prevention and control measures. This proactive approach holds great public health significance. Aim: To analyse the long-term trend of measles cases in Rajasthan, India, and the impact of Coronavirus Disease-2019 (COVID-19) on it, with future predictions using Auto-Regressive Integrated Moving Average (ARIMA) modelling. Materials and Methods: The present study was a retrospective, descriptive observational study in which monthly diagnosed measles cases were collected from the Measles Rubella Laboratory, Department of Microbiology, Sawai Man Singh Medical College, Jaipur, Rajasthan, India, for the period of April 2010 to April 2023. An ARIMA model was developed using data from 2010 to 2020 to predict the monthly number of measles cases in 2021. The predicted values were then compared to the actual cases in 2021 to assess the model’s accuracy. Results: Out of the total positive cases, males were slightly more prone to acquire infection than females (1734 males, 54%; 1477 females, 46%). The monthly index for new measles cases ranged from 0.11 to 2.6. It reached its lowest point in July (0.106) and August (0.25) and peaked in March (2.594) and April (1.84). The overall trend was fluctuating; however, the incidence of measles cases clearly increased after the year 2021. The difference between observed cases and predicted cases for the period of April 2020 to December 2021 was not statistically significant (t-value=0.261 and p-value=0.797). Conclusion: The fluctuating trend of measles was observed during the last decade; however, the observed cases of measles showed an upward trajectory during and after the COVID-19 outbreak. This study also highlighted the monthly index of the measles cases, which peaked in March to April and was lowest in July to August.

Abstract The sensor‐enabled in‐vehicle communication and infrastructure‐centric vehicle‐to‐everything (V2X) communications have significantly contributed to the spark in the amount of data exchange in the connected and autonomous vehicles (CAV) environment. The growing vehicular communications pose a potential cyber security risk considering online vehicle hijacking. Therefore, there is a critical need to prioritize the cyber security issues in the CAV research theme. In this context, this paper presents a cyber security analysis of connected vehicle traffic environments (CyACV). Specifically, potential cyber security attacks in CAV are critically investigated and validated via experimental data sets. Trust in V2X communication for connected vehicles is explored in detail focusing on trust computation and trust management approaches and related challenges. A wide range of trust‐based cyber security solutions for CAV have been critically investigated considering their strengths and weaknesses. Open research directions have been highlighted as potential new research themes in CAV cyber security area.

Abstract This data descriptor elaborates the details of a high-resolution digital bathymetric elevation model generated for the region, namely, Adam’s Bridge, which encompasses a chain of shoals between Rameswaram Island, off the southeastern coast of Tamil Nadu, India, and Mannar Island, off the northwestern coast of Sri Lanka. The proposed dataset has taken advantage of the photon penetrability in the shallow waters by the green laser of ICESat-2 LiDAR to derive the seabed topography. Seafloor depths from ~0.2 million geolocated photons of ICESat-2 for the study area were accrued and interpolated to generate a 10 m digital bathymetric elevation model. Adam’s Bridge, an isthmus and submerged reefal assemblage in shallow and super-shallow waters, is a feature of scientific curiosity. Our dataset has the potential to enhance the understanding of Adam’s Bridge structure by providing substantial information to reconstruct its evolution.

Abstract Adam’s Bridge is a submerged ridge connecting India and Sri Lanka, generally regarded as a chain of shoals extending for ~ 29 km from Dhanushkodi on the Indian side to Talaimannar Island of Sri Lanka. A high-resolution digital bathymetric elevation model generated using the seafloor returned photons of ICESat-2 was used to understand the intricate details of Adam’s Bridge structure. Photons emanating from ICESat-2’s green laser have the potential to detect the seafloor up to a depth of ~ 40 m; taking a cue from this potentiality, in our research, we have accrued ~ 0.2 million photons representing the depth information and generated a 10 m resolution bathymetric data for the extent of Adam’s Bridge. Visual interpretations made from this bathymetric data through 3D perspectives with multi-directional lighting effects, and also with the derived parameters like contours, slope, and volumetric analysis, enabled us to recognize the current form of Adam’s Bridge’s physical features. The results from our research confirm that, in its entirety, Adam’s Bridge is a submarine continuation of Dhanushkodi and Talaimannar Island. Throughout the crest line of Adam’s Bridge, approximately 1.5 km on either side is highly undulating within the super-shallow water with occurrences of sudden depths. There is an asymmetry of transverse slopes to the base on both sides of Adam’s Bridge, indicating dominant transgression of material energy from the waters of the Gulf of Mannar compared to the Palk Strait. The volume of Adam’s Bridge computed in our research yielded a value of ~ 1 km3; interestingly, only 0.02 percent of this volume is above the mean sea level, and in general, the same is visible in optical satellite imagery—in total ~ 99.98 percent of the Adam’s Bridge is submerged in shallow and super-shallow waters.

Abstract Objective This review specifically investigates ketamine’s role in SRSE management. Methods PubMed, EMBASE, and Google Scholar databases were searched from inception to May 1st, 2023, for English-language literature. Inclusion criteria encompassed studies on SRSE in humans of all ages and genders treated with ketamine. Results In this systematic review encompassing 19 studies with 336 participants, age ranged from 9 months to 86 years. Infections, anoxia, and metabolic issues emerged as the common causes of SRSE, while some cases had unknown origins, termed as NORSE (New Onset RSE) or FIRESs (Febrile Infection-Related Epilepsy Syndrome). Most studies categorized SRSE cases into convulsive (N = 105) and non-convulsive (N = 197). Ketamine was used after failed antiepileptics and anesthetics in 17 studies, while in others, it was a first or second line of treatment. Dosages varied from 0.5 mg/kg (bolus) and 0.2-15 mg/kg/hour (maintenance) in adults and 1-3 mg/kg (bolus) and 0.5-3 mg/kg/hour (maintenance) in pediatrics, lasting one to 30 days. Ketamine was concurrently used with other drugs in 40–100% of cases, most frequently propofol and midazolam. Seizure resolution rate varied from 53.3 to 91% and 40–100% in larger (N = 42–68) and smaller case series (N = 5–20) respectively. Seizure resolution occurred in every case of case report except in one in which the patient died. Burst suppression in EEG was reported in 12 patients from two case series and two case reports. Recurrence was reported in 11 patients from five studies. The reported all-cause mortality varied from 38.8 to 59.5% and 0-36.4% in larger and smaller case series., unrelated directly to ketamine dosage or duration. Significance Ketamine demonstrates safety and effectiveness in SRSE, offering advantages over GABAergic drugs by acting on NMDA receptors, providing neuroprotection, and reducing vasopressor requirement.

State of Uttarakhand in India have gone through transitional change in the last decade. Urban population share have increased from ten percent to near about thirty percent of the total population. Due to this rapid urbanization the state of Uttarakhand, the state is finding difficult to attain sustainable development. Through this study we tried to identify the major challenges and issues which are blocking the urban areas of Uttarakhand from attaining sustainable development through a systematic review framework. The article attempts to highlight the issues and challenges which can be evaluated by researchers, academicians and policy makers in India and the world to study, evaluate and analyze the sustainable urban development of Uttarakhand. The methodology can also be used by researchers, academicians and policy makers to identify the challenges of sustainable urban development for any hill or mountain side terrain. Received: 17 November 2023 Accepted: 12 April 2024 Published: 30 May 2024

Context: The existence of more than one antibody in systemic autoimmune rheumatic diseases (SARDs) or connective tissue disease (CTD) along with features of more than one autoimmune disease (AD) in an individual is suggestive of overlap syndrome (OS). Line immunoassay (LIA) can target many autoantibodies in a single approach, thus making the identification of OS feasible. Aims and Objectives: This study aimed to identify the pattern of distribution of antinuclear antibodies by LIA prevalent in a hospital population in eastern India and identify common forms of SARD in this belt based on laboratory findings. Material and Methods: A total of 1660 samples received for ANA profile testing by LIA were analysed. Statistical Analysis: Factor analysis was performed with factor loading scores used in the k-means algorithm to identify clustering of various autoantibodies. Results: U1-snRNP positivity was the highest at 16.69%, and the least frequent autoantibody noted was anti-Jo-1 at 0.71% positivity. Based on the outcome of factor analysis, three clusters were determined. Cluster 1 showed a predominance of anti-PM/Scl antibodies, cluster 2 showed a predominance of anti-dsDNA, anti-histone, anti-SmD1, anti-nucleosomes, anti-PCNA, anti-Po, anti-SSA/Ro52, anti-SSA-Ro60, anti-SSB/La, anti-Scl-70, anti-Mi-2, anti-Ku and anti-AMA-M2, and cluster 3 showed a predominance of anti-U1-snRNP. Conclusions: Mixed connective tissue disease (MCTD) and overlap syndrome (OS) are prevalent more than pure form of an AD in our study population. OS may be missed out by monospecific immunoassays and hence adds to diagnostic challenges. LIA may be more useful in identifying specific autoantibodies by a single approach rather than monospecific immunoassays in populations after a positive screen by indirect immunofluorescence (IIF).

The Archimedes Screw Turbine (AST) is an innovative type of hydroelectric power plant that can be particularly useful in locations with very low-head sites (less than 10 m head). Compared to alternative hydroelectric turbines like Pelton, Francis, and Kaplan, the AST can provide a clean renewable energy source that is safer for fish and other aquatic species. While the AST is not universally superior to these other turbine technologies, it can offer unique advantages in certain low-head applications. Unlike Pelton, Francis, and Kaplan turbines, which typically require greater maintenance, debris collection systems, and continuous design improvements, the AST can operate effectively with fewer of these supporting requirements. To explore the potential of the AST in low-head hydropower generation, the present study conducted a comparative analysis of the AST against Pelton, Francis, Kaplan, bulb, and Vortex turbines. A meta-analysis was performed to synthesize data from various theoretical, experimental, and numerical studies, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, ensuring a rigorous and comprehensive review. The findings demonstrate that the AST can be a viable and advantageous option for power generation in sites with head heights below 10 m, generating between 4 kW and 140 kW of power with flow rates of 1–6 m³/s and efficiencies ranging from 72 % to 94 %. Additionally, this study provides an easy and quick method, along with analytical equations, for estimating the design parameters needed to predict screw power output. However, the suitability of the AST versus other turbines is highly dependent on the specific site characteristics and requirements. The analysis provides insights into the performance, maintenance needs, and environmental impacts of the AST compared to conventional hydroelectric turbines. These insights can inform decision-making on appropriate turbine selection for low-head hydropower projects.

Nature-based solutions (NBS) have been promoted as a holistic way to solve a variety of societal issues while benefiting biodiversity at the same time. To date, applications of NBS approaches that help ensure food security have yet been systematically reviewed. In this paper, we critically review the specific NBS for food security, highlighting their limitations, to provide recommendations that promote their applications for improving global food security. We accessed and evaluated publications on four different scholastic databases, and our systematic review of relevant materials indicated that many NBS approaches can be applied to enhance food security dimensions individually or together. However, there is a strong bias towards food availability, and not enough research has been done to link NBS with improvements in food access and utilization. Over 80 % of the reviewed papers were of short-term studies or without specific timeframes, and 25 % offered no information on the economic effectiveness of NBS. Environmental benefits of NBS were explicitly described in about 60 % of these papers, and biodiversity enhancement was measured in only about 10 %. We, therefore, recommend future applications of NBS to safeguard food security be shifted to food access and utilization with careful consultation with local communities to address their specific context, using indicators that are easily measured and managed. Systematic monitoring regimes and robust and diversified financial support systems are also equally important in efforts to successfully implement NBS. Moreover, environmental and societal benefits, especially water productivity and biodiversity, must be incorporated into the planning and design of NBS.

The lack of vocal emotional expression is a major deficit in social communication disorders. The current scenario of artificial intelligence focuses on collaborative training of deep learning models without losing data privacy. The primary objective of this paper is to propose a federated learning-based classification model to identify and analyze the emotional capabilities of individuals with vocal emotion deficits. The methodology has developed a collaborative and privacy-preserved approach using federated learning for training the deep learning models. The proposed methodology utilizes Mel-frequency Cepstral Coefficients (MFCC) to preprocess audio recordings. The four datasets (RAVDESS, CREMA, TESS, SAVEE) including emotion-based classified audio recordings were collected from open sources. The collected audio recordings are 3 s each and the total data set has 668376 audio files with happy - 175119 files, sad – 172611 files, angry – 176346 files, and normal - 144300 files. Further, the input audio was pre-processed to generate MFCC features. The study began with extracting features from multiple pre-trained DL models as its base model. Then, the performance of the federated learning (FL) model was tested on independent and identically distributed (IID) and non-IID data. Further, this paper presents a federated deep learning-based multimodal system for verbal communication emotions classification that uses audio datasets to meet data privacy requirements by DL on the FL ecosystem. As per the findings, the federated learning trained model provides nearly similar parametric results in comparison to base model training. For IID data, the model had 99.71 % validation accuracy, precision (99.73 %), recall (99.69 %), and validation loss (0.01). The FL architecture with non-IID data outperformed these measures with validation accuracy (99.97 %), precision (99.97 %), recall (99.97 %), and least loss (0). Hence the acquired results support the utilization of federated learning ecosystem-based trained models with identically and non-identically distributed audio features from emotion identification without losing parametric results. In conclusion, the proposed techniques could be applied to identify verbal emotional deficits in individuals and could support developing emerging technological interventions for their well-being.

The current study investigates the utilization of gum acacia (GA) & tragacanth gum (TG) for the synthesis of silver nanoparticles (NPs) and their subsequent incorporation into hydrogels for potential applications in drug delivery (DD). Cefoperazone, an antibiotic drug, was encapsulated into hydrogels to enhance their antimicrobial activity. Copolymers were characterized by UV–Vis, TEM, FESEM, AFM, XPS, XRD, FTIR, TGA and DSC techniques. UV–Vis spectroscopy revealed the formation of NPs at a wavelength of 436 nm with an optical density of 2.65. TEM images depicted AgNPs with an average size of 37.29 ± 7.25 nm with their uniform distribution. XRD analysis demonstrated distinct crystalline peaks at 2θ = 38.34o, 43.80o, 64.60o and 77.42o attributed to AgNPs. XPS peaks observed at 368 & 374 eV, corresponding to the 3d5/2 and 3d3/2 modes of silver, respectively, confirmed the incorporation of AgNPs in the polymer matrix. Hydrogels demonstrated pH responsive sustained release of cefoperazone. The diffusion mechanism was non-Fickian and described by the Higuchi kinetic model. In the DPPH assay, copolymers exhibited a 32.36 % inhibition of free radicals, whereas in the F–C reagent assay, antioxidant activity was measured as 22.25 μg equivalent of gallic acid. The copolymers displayed blood compatible nature, as evidenced from haemolysis (2.11 ± 0.03 %) and thrombogenicity (74.71 ± 1.63 %) results. The interactions of copolymer with intestinal membrane attributed to mucoadhesive properties and required detachment force of 55.30 ± 2.80 mN to separate from the biological membrane. Growth of E. coli, P. aeruginosa and S. aureus bacteria was inhibited by copolymers with and without antibiotic drug. These characteristic properties of copolymers make them ideal materials for DD carriers.

This study was designed to deduce the inter-relationship between external genitalia measurement, antral follicular count (AFC) and body weight (BW) and evaluate estrus induction rate following the administration of clomiphene citrate in pre-pubertal Murrah buffalo heifers. For this study, twenty pre-pubertal heifers (age: 30–36 months; BW: 367±8.6 kg) were selected and their external genitalia along with their relative rima length (RRL) and vulval width (RVW) and AFC using trans-rectal ultrasonography were recorded. Two groups were studied: control (n=9) and treatment (n=11). Treated heifers were given clomiphene citrate at 300 mg/heifer orally for 9 days and in control group, placebo (copper sulphate tablets) were given and onset of cyclicity as well as estrus signs was detected at the end of the treatment. All the heifers showed signs of estrus, but none ovulated. Also, AFC differed between heifers with low and high RRL (6.5±0.44 vs 8.6±0.67) and RVW (6.53±0.47 vs 8.16±0.70). Likewise, BW was correlated with RRL and AFC with BW, RRL and RVW. Non-significant difference was observed between the two groups with respect to dominant and sub-ordinate I and II follicles’ size. Following clomiphene citrate supplementation, crestar treatment was administered to both groups resulting in pregnancy in control animals (n=2) and treated animals (n=6). In conclusion, this study showed that BW, external genital measurements and AFC are correlated and oral administration of clomiphene citrate failed to induce fertile estrus in pre-pubertal Murrah buffalo heifers.

Abstract To ascertain the ideal dosage of ZnO NPs (Zinc Oxide Nanoparticles), we conducted an investigation on the priming effects of varying concentrations of ZnO NPs on germination and physio-biochemical parameters of wheat. In this study, ZnO NPs were synthesized and characterized for their physico-chemical properties followed by confirmation of the formation of ZnO NPs. Throughout this study, wheat seeds were subjected to ZnO NPs at various concentrations of 5, 50, 100, 250, and 500 ppm for a period of 4 h via continuous aeration. The primed seeds were sowed in plastic bags, allowed to grow for 21 days, following which comprehensive evaluations of physio-biochemical attributes were conducted. At 250 ppm, an impressive 100% of seeds successfully germinated compared to the control group. The examined physiological factors such as shoot length, root length, and fresh as well as dry weights of leaf and root tissues all exhibited notable increases with the ascending concentrations of ZnO NP up to 250 ppm. However, beyond this threshold, at 500 ppm, these parameters experienced a decline. Inductively coupled plasma atomic absorption spectrophotometer (ICP-AAS) measurements validated the progressive increase in Zinc content in the nanoprimed seedlings, further affirming the dose-dependent trend. Zinc oxide nanoparticles notably improved key biochemical features, including elevated levels of total chlorophyll, malondialdehyde (MDA), total protein, and the accumulation of osmolytes such as proline and glycine-betaine. Additionally, the presence of ZnO NPs led to increased activity of antioxidant enzymes like superoxide dismutase (SOD) and catalase in a dose-dependent mananer. Collectively, the amassed data underscores the efficacy of the 250 ppm ZnO NPs treatment, which emerged as superior in comparison to both the control group and other administered treatments. These findings underscore the potential of ZnO NPs at a concentration of 250 ppm as a valuable seed nanopriming agent, effectively enhanced germination and robust early-stage growth in young plants.

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains highly lethal due to limited therapeutic options and expensive/burdensome drug discovery processes. Utilizing genomic-data-driven Connectivity Mapping (CMAP) to identify a drug closer to real-world PC targeting may improve pancreatic cancer (PC) patient outcomes. Initially, we mapped CMAP data to gene expression from 106 PC patients, identifying nine negatively connected drugs. These drugs were further narrowed down using a similar analysis for PC cell lines, human tumoroids, and patient-derived xenografts datasets, where ISOX emerged as the most potent agent to target PC. We used human and mouse syngeneic PC cells, human and mouse tumoroids, and in vivo mice to assess the ability of ISOX alone and in combination with 5FU to inhibit tumor growth. Global transcriptomic and pathway analysis of the ISOX-LINCS signature identified HDAC 6/cMyc as the target axis for ISOX. Specifically, we discovered that genetic and pharmacological targeting of HDAC 6 affected non-histone protein cMyc acetylation, leading to cMyc instability, thereby disrupting PC growth and metastasis by affecting cancer stemness. Finally, KrasG12D harboring tumoroids and mice responded effectively against ISOX and 5FU treatment by enhancing survival and controlling metastasis incidence. Overall, our data validate ISOX as a new drug to treat advanced PC patients without toxicity to normal cells. Our study supports the clinical utility of ISOX along with 5FU in future PC clinical trials.

Abstract Dissolved oxygen (DO) is an important parameter in assessing water quality. The reduction in DO concentration is the result of eutrophication, which degrades the quality of water. Aeration is the best way to enhance the DO concentration. In the current study, the aeration efficiency (E20) of various numbers of circular jets in an open channel was experimentally investigated for different channel angle of inclination (θ), discharge (Q), number of jets (Jn), Froude number (Fr), and hydraulic radius of each jet (HRJn). The statistical results show that jets from 8 to 64 significantly provide aeration in the open channel. The aeration efficiency and input parameters are modelled into a linear relationship. Additionally, utilizing WEKA software, three soft computing models for predicting aeration efficiency were created with Artificial Neural Network (ANN), M5P, and Random Forest (RF). Performance evaluation results and box plot have shown that ANN is the outperforming model with correlation coefficient (CC) = 0.9823, mean absolute error (MAE) = 0.0098, and root mean square error (RMSE) = 0.0123 during the testing stage. In order to assess the influence of different input factors on the E20 of jets, a sensitivity analysis was conducted using the most effective model, i.e., ANN. The sensitivity analysis results indicate that the angle of inclination is the most influential input variable in predicting E20, followed by discharge and the number of jets.

Predictive analytics involves the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to analyze current and historical data, identify patterns, and make predictions about future outcomes. In the context of healthcare, predictive analytics is invaluable for understanding and addressing various challenges, with a particular emphasis on predicting mortality rates in specific communities during illnesses such as diabetes, heart disease, and drug overdose. In this study, we propose a unique approach combining Feature Selection Regression based on Neighborhood Component Analysis (FSRNCA) with a less complex single-layer Functional Link Artificial Neural Network (FLANN) model to predict mortality rates using publicly available open-source inventory, i.e., Big Cities Health Inventory (BCHI). Our methodology leverages regularized FSRNCA to select relevant features from the BCHI dataset, considering factors such as demographics, socio-economic indicators, and health metrics. Subsequently, the FLANN model is trained using the selected features to predict mortality rates in diverse urban populations. The model achieves a high R2 score of 91%, outperforming other competitive ML algorithms. Additionally, the proposed technique is successfully tested with datasets such as PIMA, BUPA, ECOLI, and LYMPHOGRAPHY for the classification of various other illnesses. Furthermore, FLANN exhibits minimal computational complexity and rapid training-testing times, highlighting its practicality for real-world applications. The minimal computational complexity and training-testing time between the dense multilayer neural networks reveal the excellent potential and utility of the proposed technique.

Smart robotic wheelchairs have emerged as promising assistive devices to enhance mobility and independence for individuals with mobility impairments. The successful integration of advanced sensor systems plays a critical role in improving the functionality and safety of these wheelchairs. This paper presents a comprehensive review of the design and implementation of advanced sensor systems for smart robotic wheelchairs. Through an extensive literature review, the limitations of existing sensor technologies are identified, and the potential of advanced sensors is explored. Vision-based sensors, range and proximity sensors, force and pressure sensors, inertial sensors, and environmental sensors are discussed in detail. Furthermore, this review highlights the design considerations, hardware components, software development, and calibration procedures involved in implementing advanced sensor systems. Evaluation and performance analysis metrics are discussed to assess the effectiveness of the sensor systems. The research findings indicate that advanced sensor systems have the potential to significantly enhance the functionality and safety of smart robotic wheelchairs. However, challenges such as sensor integration, data fusion, and user feedback must be addressed. This review paper concludes by discussing the implications of advanced sensor systems in improving wheelchair functionality and user experience, and proposes future directions for research in this domain.

Abstract Background Chickpea (Cicer arietinum L.) production is affected by many biotic factors, among them Fusarium wilt caused by Fusarium oxysporum f. sp. ciceri and Botrytis gray mold caused by Botrytis cinerea led to severe losses. As fungicide application is not advisable, biological management is the best alternative for plant protection. The rhizosphere-dwelling antagonistic bacteria are one of the important successful alternative strategy to manage these diseases of chickpea. Rhizosphere dwelling bacteria serve as biocontrol agents by different mechanisms like producing antibiotics, different enzymes, siderophores against pathogens and thereby reducing the growth of pathogens. Results The present study aimed to isolate rhizospheric bacteria from the soils of different chickpea fields to evaluate biocontrol efficacy of the isolated bacteria to manage Fusarium wilt and Botrytis gray mold in chickpea. A total of 67 bacteria were isolated from chickpea rhizosphere from Bundelkhand region of India. Study revealed the isolated bacteria could reduce the Fusarium oxysporum f. sp. ciceris and Botrytis cinerea infection in chickpea between 17.29 and 75.29%. After screening of all the bacteria for their biocontrol efficacy, 13 most promising bacterial isolates were considered for further study out of which, three bacterial isolates (15d, 9c and 14a) have shown the maximum in vitro antagonistic effects against Fusarium oxysporum f. sp. ciceri and Botrytis cinerea comparable to in vivo effects. However, Isolate (15d) showed highest 87.5% and 82.69% reduction in disease against Fusarium wilt and Botrytis gray mold respectively, under pot condition. Three most potential isolates were characterized at molecular level using 16S rRNA gene and found to be Priestia megaterium (9c and 14a) and Serratia marcescens (15d). Conclusion This study identified two native biocontrol agents Priestia megaterium and Serratia marcescens from the rhizospheric soils of Bundelkhand region of India for control of Fusarium wilt, Botrytis gray mold. In future, efforts should be made to further validate the biocontrol agents in conjugation with nanomaterials for enhancing the synergistic effects in managing the fungal diseases in chickpea. This study will definitely enhance our understanding of these bioagents, and to increase their performance by developing effective formulations, application methods, and integrated strategies.

Abstract The developments of antibodies for cancer therapeutics have made remarkable success in recent years. There are multiple factors contributing to the success of the biological molecule including origin of the antibody, isotype, affinity, avidity and mechanism of action. With better understanding of mechanism of cancer progression and immune manipulation, recombinant formats of antibodies are used to develop therapeutic modalities for manipulating the immune cells of patients by targeting specific molecules to control the disease. These molecules have been successful in minimizing the side effects instead caused by small molecules or systemic chemotherapy but because of the developing therapeutic resistance against these antibodies, combination therapy is thought to be the best bet for patient care. Here, in this review, we have discussed different aspects of antibodies in cancer therapy affecting their efficacy and mechanism of resistance with some relevant examples of the most studied molecules approved by the US FDA.

The present study aimed to investigate the influence of extrusion process parameters, specifically screw speed (300 to 500 rpm) and temperature (130 to 150 °C) on the stability of phytosterols and the physical, functional, and structural characteristics of extrudates made from composite blends containing pea protein isolate (PPI). Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA) were employed to optimize the process parameters.Extrudates produced at lower temperatures exhibited higher phytosterol retention compared to those produced at higher temperatures. X-ray diffraction analysis showed that incorporating PPI significantly increased crystallinity from 22% to 33%. Fourier Transform Infrared analysis revealed a reduction in the Amide II stretching of the secondary structure in pea protein isolate following extrusion. Scanning electron microscopy images demonstrated that the addition of PPI and functional oil altered the structure of the extrudates.Statistical comparison of the process parameters using higher R2 values, lower root mean square as well as mean absolute percentage error indicated that the ANN model outperformed the RSM model in predicting all responses. Overall, incorporating PPI and phytosterols into corn-based extrudates improved their nutritional quality. These findings contribute to meeting the demand for fortified foods.

Cytokinin oxidase/dehydrogenase (CKX), responsible for irreversible cytokinin degradation, also controls plant growth and development and response to abiotic stress. While the CKX gene has been studied in other plants extensively, its function in cotton is still unknown. Therefore, a genome-wide study to identify the CKX gene family in the four cotton species was conducted using transcriptomics, quantitative real-time PCR (qRT-PCR) and bioinformatics. As a result, in G. hirsutum and G. barbadense (the tetraploid cotton species), 87 and 96 CKX genes respectively and 62 genes each in G. arboreum and G. raimondii, were identified. Based on the evolutionary studies, the cotton CKX gene family has been divided into five distinct subfamilies. It was observed that CKX genes in cotton have conserved sequence logos and gene family expansion was due to segmental duplication or whole genome duplication (WGD). Collinearity and multiple synteny studies showed an expansion of gene families during evolution and purifying selection pressure has been exerted. G. hirsutum CKX genes displayed multiple exons/introns, uneven chromosomal distribution, conserved protein motifs, and cis-elements related to growth and stress in their promoter regions. Cis-elements related to resistance, physiological metabolism and hormonal regulation were identified within the promoter regions of the CKX genes. Expression analysis under different stress conditions (cold, heat, drought and salt) revealed different expression patterns in the different tissues. Through virus-induced gene silencing (VIGS), the GhCKX34A gene was found to improve cold resistance by modulating antioxidant-related activity. Since GhCKX29A is highly expressed during fibre development, we hypothesize that the increased expression of GhCKX29A in fibres has significant effects on fibre elongation. Consequently, these results contribute to our understanding of the involvement of GhCKXs in both fibre development and response to abiotic stress.

The emergence of multiple herbicide resistance in Phalaris minor is a major threat to wheat (Triticum aestivum L.) production in north-western Indo-Gangetic Plains of India. The present study was carried out during winter (rabi) seasons of 2020–21 and 2021–22 at research farm of Chaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana for management of herbicide resistance in Phalaris minor Retz. in wheat using pre and post-emergence herbicide mixtures with different mode of action. The experiment was laid out in randomized block design (RBD) with 15 treatments, replicated thrice. Sequential application of flumioxazin 125 g/ha with pendimethalin (tank mix) 1500 g/ha fb clodinafop + metribuzin 174 g/ha resulted in significantly lowest weed density, dry matter of P. minor and broad-leaf weeds, and it was statistically comparable to application of flumioxazin alone or as mixture with pendimethalin as pre-emergence; pyraxosulfone + pendimethalin 127.5 + 1500 g/ha fb PoE (post-emergence) application of either mesosulfuron + iodosulfuron 14.4 g/ha; sulfosulfuron + metsulfuron, pinoxaden + metsulfuron 50 + 4 g/ha, clodinafop + metribuzin 174 g/ha, respectively. Phytotoxicity of flumioxazin was observed on wheat after 2–3 days of 1st irrigation i.e. 25 DAS (days after sowing). Application of pyroxasulfone + pendimethalin pre fb PoE mesosulfuron + iodosulfuron resulted in significantly higher grain yield (5847 and 5369 kg/ha, during 2021 and 2022, respectively) as compared to other herbicides.

Air pollution is increasing daily, causing global warming and many environmental issues, and it is also the cause of many diseases. According to many reports, brick kilns play a major role in the emission of black carbon that causes air pollution. It is necessary to find another way to produce bricks. The trend these days is to increase applications of natural fibers and eco-friendly materials and to reuse waste materials to control pollution. Synthetic and chemical materials are also causes of pollution, diseases, and even the deaths of many people. In this direction, eco-friendly materials were used to produce bricks. Abaca fiber, Pinus-Roxburghi leaves, fiber, wood, wheat straw, animal dung, sand, cement, phenolic resin, and gypsum were used in various percentages to create novel brick. In the investigation, it was discovered that hybrid natural fiber-based bricks had strong physical-mechanical, mechanical-chemical, and thermal stability properties, were light in weight, and had good sound absorption capabilities. Significant improvement of has been identified, AB-4 Brick shows the maximum porosity with 42.5% improvement as compared to AB-1 brick.

BackgroundSchistosomiasis is a common cause of pulmonary hypertension (PH) worldwide. Type 2 inflammation contributes to the development of Schistosoma-induced PH. Specifically, interstitial macrophages (IMs) derived from monocytes play a pivotal role by producing thrombospondin-1 (TSP-1), which in turn activates TGF-β, thereby driving the pathology of PH. Resident and recruited IM subpopulations have recently been identified. We hypothesized that in Schistosoma-PH, one IM subpopulation expresses monocyte recruitment factors, whereas recruited monocytes become a separate IM subpopulation that expresses TSP-1.MethodsMice were intraperitoneally sensitized and then intravenously challenged with S. mansoni eggs. Flow cytometry on lungs and blood was performed on wildtype and reporter mice to identify IM subpopulations and protein expression. Single-cell RNA sequencing (scRNAseq) was performed on flow-sorted IMs from unexposed and at day 1, 3 and 7 following Schistosoma exposure to complement flow cytometry based IM characterization and identify gene expression.ResultsFlow cytometry and scRNAseq both identified 3 IM subpopulations, characterized by CCR2, MHCII, and FOLR2 expression. Following Schistosoma exposure, the CCR2+ IM subpopulation expanded, suggestive of circulating monocyte recruitment. Schistosoma exposure caused increased monocyte-recruitment ligand CCL2 expression in the resident FOLR2+ IM subpopulation. In contrast, the vascular pathology-driving protein TSP-1 was greatest in the CCR2+ IM subpopulation.ConclusionSchistosoma-induced PH involves crosstalk between IM subpopulations, with increased expression of monocyte recruitment ligands by resident FOLR2+ IMs, and the recruitment of CCR2+ IMs which express TSP-1 that activates TGF-β and causes PH.

This review article explores the multifaceted significance of fermented bamboo shoots, a culinary tradition deeply rooted in the practices of local tribes in Northeastern India. The therapeutic properties of fermented bamboo shoots span anti-aging, anticancer, antioxidant, cardioprotective, and weight loss benefits, positioning them as valuable functional foods enriched with probiotics. Northeast India, encompassing the states of Assam, Arunachal Pradesh, Nagaland, Meghalaya, Mizoram, Sikkim, Manipur, and Tripura, serves as a hub for the cultivation and consumption of fermented bamboo shoot-based products. The unique microbial ecosystem associated with bamboo shoots contributes to the synthesis of diverse health-promoting compounds, with rich concentrations of glycosides and flavones. Microorganisms, including Lactobacillus species, Bacillus species, Candida species, and Saccharomyces cerevisiae play a pivotal role in the fermentation process, contributing to the distinct characteristics of these products. The active involvement of tribal communities, constituting 75% of the regional population, underscores the cultural and traditional significance of this culinary practice. The review also delineates an array of fermented bamboo shoot-based products offerings, such as ekung, heccha, eup, mesu, lung-siej, soibum, soidon, soijim, and hirring, reflecting the rich culinary diversity arising from this traditional practice. Beyond their cultural importance, these products hold substantial industrial and economic value, and are integral to the livelihoods of local communities in Northeastern India. In summary, fermented bamboo shoots have emerged as a complex resource intertwining cultural heritage, health benefits, and economic dimensions within the unique context of Northeastern Indian communities.

In recent years, evacuated tube solar water heaters (ETSWH) have become popular due to their efficiency and low maintenance based on trends in India's solar thermal market. Numerous studies have focused on improving system performance. In the scientific literature, there is a lack of information on the selection of appropriate fin material and the benefits associated with it. The thermal efficiency (ηt) of ETSWH is directly impacted by the choice of fin material. In this context, the goal of this study was to assess the impact of copper and aluminum using fin material as well as the inclination angle on ETSWH's ηt. The experiments are conducted for mass flow rate (mwt) varying from 2 to 5l/h. With a mwt of 2l/h, the highest outlet temperature of 55°C was recorded, while the highest ηt was found at 41.2°C with a mwt of 5l/h. At all mwt, copper fin is more efficient than aluminum fin due to their superior thermal conductivity. Among the considered inclination angles, at an inclination angle of 30°, the efficiency of ETSWH is found to be optimal. ETSWH with a copper fin attains (ηt = 58.57%), which is more significant than the case when the aluminum fin is used (ηt = 51.50%).

The World Health Organization has reported that over one million individuals drink contaminated water, resulting in over 30,000 deaths daily. Every year, over 7×107 tons of synthetic dyes are produced globally, with the textile industry utilizing over 104 tons of such materials. To protect freshwater from pollutants, wastewater treatment methods such as permeable reactive barrier disinfection use activated carbon. Bamboo charcoal is an emerging substance with great potential in this area. Bamboos represent a renewable biological resource for long-term development. This paper reviews the dye removal processes that can be utilized to avoid water pollution, using bamboo charcoal as a natural adsorbent. A literature search using used various keywords from several bibliographic databases yielded seven studies that supported the adsorptive properties of bamboo charcoal. These investigations used FTIR, EDS, SEM and XRD to demonstrate the porous nature of bamboo charcoal, activated bamboo charcoal and/or modified bamboo charcoal, as well as showing the effects of pH and temperature on dye removal. The best-fitting kinetic model and isotherm data were identified. Bamboo charcoal was an effective adsorbent, while modified or activated bamboo charcoal rapidly increased absorptive capacity, indicating the future potential of bamboo charcoal in the cleaning up of water pollutants and contributing to a clean environment.

Present study was carried out during winter (rabi) seasons of 2019–20 and 2020–21 at Rani Lakshmi Bai Central Agricultural University, Jhansi, Uttar Pradesh to decipher underlying gene effects for green forage quality characters in barley (Hordeum vulgare L.) in Bundelkhand region of Uttar Pradesh. Eight diverse barley genotypes, viz. BH902, BH946, DWRB160, DWRB180, RD2552, RD2794, RD2899 and RD2907 were evaluated and crossed in half diallel design. A total of 28 F1s along with 8 parents were sown in randomized complete block design (RCBD) with 3 replications. The green fodder was harvested after 55 days of sowing (DAS) and fodder quality analysis was conducted. The crude protein (CP) and nitrogen (N) contents showed mean values of 14.19 and 2.49% ranged from 12.62–15.26% and 2.22–2.68%, respectively. The characters, viz. organic matter (OM), CP, N, lignin (L) and hemicellulose (HCL) showed prepondrance of additive gene effects, whereas acid detergent fibre (ADF), neutral detergent fibre (NDF) and cellulose (CL) showed the prevalnce of dominance gene effects. The genotype DWRB180 and two rowed malt barley variety DWRB160 were estimated with desirable additive gene effects for forage intake and digestibility traits. The cross combinations, DWRB160/RD2899, BH946/RD2552 and RD2794/DWRB180 can be further utilized for CP and N contents, whereas, the progenies, viz. BH946/DWRB180 and RD2552/RD2907 were promising for ADF and NDF. GT biplot corroborated positive correlations of NDF with ADF (0.43**), HCL (0.88**) and CL (0.41*). The improvement in forage intake and digestibility characters like ADF, NDF and CL is suggested through complex crossing followed by selection.

IntroductionHypoxia is a common pathological driver contributing to various forms of pulmonary vascular diseases leading to pulmonary hypertension (PH). Pulmonary interstitial macrophages (IMs) play pivotal roles in immune and vascular dysfunction, leading to inflammation, abnormal remodeling, and fibrosis in PH. However, IMs’ response to hypoxia and their role in PH progression remain largely unknown. We utilized a murine model of hypoxia-induced PH to investigate the repertoire and functional profiles of IMs in response to acute and prolonged hypoxia, aiming to elucidate their contributions to PH development.MethodsWe conducted single-cell transcriptomic analyses to characterize the repertoire and functional profiles of murine pulmonary IMs following exposure to hypobaric hypoxia for varying durations (0, 1, 3, 7, and 21 days). Hallmark pathways from the mouse Molecular Signatures Database were utilized to characterize the molecular function of the IM subpopulation in response to hypoxia.ResultsOur analysis revealed an early acute inflammatory phase during acute hypoxia exposure (Days 1-3), which was resolved by Day 7, followed by a pro-remodeling phase during prolonged hypoxia (Days 7-21). These phases were marked by distinct subpopulations of IMs: MHCIIhiCCR2+EAR2+ cells characterized the acute inflammatory phase, while TLF+VCAM1hi cells dominated the pro-remodeling phase. The acute inflammatory phase exhibited enrichment in interferon-gamma, IL-2, and IL-6 pathways, while the pro-remodeling phase showed dysregulated chemokine production, hemoglobin clearance, and tissue repair profiles, along with activation of distinct complement pathways.DiscussionOur findings demonstrate the existence of distinct populations of pulmonary interstitial macrophages corresponding to acute and prolonged hypoxia exposure, pivotal in regulating the inflammatory and remodeling phases of PH pathogenesis. This understanding offers potential avenues for targeted interventions, tailored to specific populations and distinct phases of the disease. Moreover, further identification of triggers for pro-remodeling IMs holds promise in unveiling novel therapeutic strategies for pulmonary hypertension.

Skin diseases are commonly identified problems all over the world. There are various kinds of skin diseases, such as skin cancer, vulgaris, ichthyosis, and eczema. Vitiligo is one of the skin diseases that can occur in any area of the body, including the inner part of the mouth. This type of skin can have immense negative impacts on the human body, involving memory issues, hypertension, and mental health problems. Conventionally, dermatologists use biopsy, blood tests, and patch testing to identify the presence of skin diseases and provide medications to patients. However, these treatments don't always provide results due to the transformation of a macule into a patch. Various machine learning (ML) and deep learning (DL) models have been developed for the early identification of macules to avoid delays in treatments. This work has implemented a DL-based model for predicting and classifying vitiligo skin disease in healthy skin. The features from the images have been extracted using a pre-trained Inception V3 model and substituted for each classifier, namely, naive Bayes, convolutional neural network (CNN), random forest, and decision tree. The results have been determined as accuracy, recall, precision, area under the curve (AUC), and F1-score for Inception V3 with naive Bayes as 99.5%, 0.995, 0.995, 0.997, and 0.995, respectively. The Inception V3 with CNN has achieved 99.8% accuracy, 0.998 recall, 0.998 precision, 1.00 AUC, and 0.998 F1-score. Further, Inception V3 with random forest shows 99.9% accuracy, 0.999 recall, 0.999 precision, 1.00 AUC, and 0.999 F1-score values whereas, Inception V3 with decision tree classifier shows an accuracy value of 97.8%, 0.978 recall, 0.977 precision, 0.969 AUC, and 0.977 F1-score. Results exhibit that Inception V3 with a random forest classifier outperforms in terms of accuracy, recall, precision, and F1-score, whereas for the AUC metric, Inception V3 with a random forest and Inception V3 with CNN have shown the same outcomes of 1.00.

The purpose of this study was to identify motivational factors for consumers in making a purchase decision for a fast fashion product. The term fast fashion is used to refer to cheaper replicas of luxury fashion trends. Apart from impacting the environment adversely, fast fashion has several other issues as well. Fast fashion has many sustainability issues but its demand is growing at a tremendous pace. The motives for the preference for fast fashion were explored in this study. Both primary and secondary data were used to conduct this research. The primary data was collected for this study via questionnaire. All the factors are rated on the 7-point Likert scale. Furthermore, the laddering technique of interviewing was employed to investigate the underlying values. The study revealed that “creating self-identity” is the most influencing motive for consumers in making a purchase decision for a fast fashion product, while “showing dominance” is the least influencing motive for consumers in making a purchase decision for a fast fashion product. This study offers insight into the factors influencing buying decisions for a fast fashion product. This research can help address the issue of sustainability in the fashion industry. These findings can also be used to promote sustainable fashion.

Castor (Ricinus communis L.) is an industrially important oil producing crop belongs to Euphorbiaceae family. Castor oil has unique chemical properties make it industrially important crop. It is a member of monotypic genus even though it has ample amount of variability. Using this variability, conventionally many varieties and hybrids have been developed. But, like other crops, the modern and unconventional methods of crop improvement has not fully explored in castor. This article discusses the use of polyploidy induction, distant/wide hybridization and mutation breeding as tools for generating variety. Modern approaches accelerate the speed of crop breeding as an alternative tool. To achieve this goal, molecular markers are employed in breeding to capture the genetic variability through molecular analysis and population structuring. Allele mining is used to trace the evolution of alleles, identify new haplotypes and produce allele specific markers for use in marker aided selection using Genome wide association studies (GWAS) and quantitative trait loci (QTL) mapping. Plant genetic transformation is a rapid and effective mode of castor improvement is also discussed here. The efforts towards developing stable regeneration protocol provide a wide range of utility like embryo rescue in distant crosses, development of somaclonal variation, haploid development using anther culture and callus development for stable genetic transformation has reviewed in this article. Omics has provided intuitions to the molecular mechanisms of (a)biotic stress management in castor along with dissected out the possible genes for improving the yield. Relating genes to traits offers additional scientific inevitability leading to enhancement and sympathetic mechanisms of yield improvement and several stress tolerance.

This study presents a comprehensive comparison between Resistance Spot Welding (RSW) and Laser Spot Welding (LSW) in sheet metal fabrication. We investigated the mechanical properties, microstructure, and process efficiency of welds produced by both methods on various sheet metal materials, including low carbon steel, stainless steel, and aluminum alloys. The study employed tensile-shear tests, microhardness measurements, and microstructural analysis to evaluate weld quality. Additionally, we assessed the energy consumption, production rate, and overall cost-effectiveness of both welding techniques. Our findings reveal that while RSW remains a robust and cost-effective method for many applications, LSW offers superior precision, flexibility, and quality for specific high-performance applications. This comparative analysis provides valuable insights for manufacturers in selecting the most appropriate welding technique for their specific sheet metal fabrication requirements.

A brief review on history, progress and development of perovskite solar cells fabricated via conventional solution based deposition methods and vacuum based deposition method is discussed in the present article. Working principle and functioning of layers used in perovskite based solar cells like, absorber layer, hole transporting layer, electron transporting layer, contact electrodes is discussed. Various deposition techniques are discussed for the growth of perovskite thin films to make perovskite based solar cells (PSCs) via conventional solution based techniques and vacuum based deposition techniques. Solution based methods like spin coating, spray coating, pyrolysis and dip coating is discussed and vacuum based deposition techniques like RF-magnetron sputtering, chemical vapour deposition, thermal evaporation method, physical vapour deposition, atomic layer deposition etc. is discussed. Significant improvement in efficiency has been achieved within a decade with 2.2% in 2006 to over 26% for perovskite based solar cells and by 33.9% for perovskite/Silicon tandem solar (Best Researcha; Longi claims 33). Few problems associated with these types of solar cells like stability and toxicity, and solutions to overcome these problems are also discussed briefly. Doping of perovskite and its application for self-doped perovskite solar cell and doped perovskite with silicon as heterojunction solar cell is discussed. Finally, development and prospects of perovskite based solar cells for manufacturing at industrial scale by using vacuum based techniques is discussed.

IntroductionA limited subset of HIV-1 infected adult individuals typically after at least 2-3 years of chronic infection, develop broadly neutralizing antibodies (bnAbs), suggesting that highly conserved neutralizing epitopes on the HIV-1 envelope glycoprotein are difficult for B cell receptors to effectively target, during natural infection. Recent studies have shown the evolution of bnAbs in HIV-1 infected infants.MethodsWe used bulk BCR sequencing (BCR-seq) to profile the B cell receptors from longitudinal samples (3 time points) collected from a rare pair of antiretroviralnaïve, HIV-1 infected pediatric monozygotic twins (AIIMS_329 and AIIMS_330) who displayed elite plasma neutralizing activity against HIV-1.ResultsBCR-seq of both twins revealed convergent antibody characteristics including V-gene use, CDRH3 lengths and somatic hypermutation (SHM). Further, antibody clonotypes with genetic features similar to highly potent bnAbs isolated from adults showed ongoing development in donor AIIMS_330 but not in AIIMS_329, corroborating our earlier findings based on plasma bnAbs responses. An increase in SHM was observed in sequences of the IgA isotype from AIIMS_330.DiscussionThis study suggests that children living with chronic HIV-1 can develop clonotypes of HIV-1 bnAbs against multiple envelope epitopes similar to those isolated from adults, highlighting that such B cells could be steered to elicit bnAbs responses through vaccines aimed to induce bnAbs against HIV-1 in a broad range of people including children.

Selecting female cows for productivity based on udder and teat traits is essential in field due to lack of available records. The objective of the present study was to reduce the dimensionality of the 17 udder and teat traits and to analyse their impact on milk productivity. The data on 256 cattle comprising 133 Sahiwal and 123 Karan Fries cows were used in this study over the years 2017-2019 from Livestock Research Centre (LRC) of ICAR-National Dairy Research Institute, Karnal. The 17 udder and teat traits were fore udder attachment (FUA), rear udder width (RUW), rear udder height (RUH), udder balance (UB), udder depth (UD), udder length (UL), udder width (UW), udder circumference (UC), central ligament/udder cleft (CL), teat circumference (TC), fore teat length (FTL), rear teat length (RTL), distance between fore and rear teat (DFR), distance between left and right teat (DLR), shortest distance from floor to fore teat (SDFT), shortest distance from floor to rear teat (SDRT) and teat diameter (TD). In the factor analysis, first five latent factors accounted for 62.22% of total variance in udder and teat measurements for Sahiwal cows and 65.67% in Karan Fries (KF) cows, respectively. In Sahiwal cows F1 represented better udder support and wideness (wide udders, udders were supported by strong suspensory ligament), whereas in KF cows, first factor reflected better udder dimension and distance between teats (longer length, width of udder and well placed teats). Factor analysis could reduce the multicollinearity of the data. It can be concluded that inclusion of udder and teat measurements in selection index can be a reliable criteria for selecting cows for higher milk yield.

We report on an experiment performed at the FLASH2 free-electron laser (FEL) aimed at producing warm dense matter via soft x-ray isochoric heating. In the experiment, we focus on study of the ions emitted during the soft x-ray ablation process using time-of-flight electron multipliers and a shifted Maxwell–Boltzmann velocity distribution model. We find that most emitted ions are thermal, but that some impurities chemisorbed on the target surface, such as protons, are accelerated by the electrostatic field created in the plasma by escaped electrons. The morphology of the complex crater structure indicates the presence of several ion groups with varying temperatures. We find that the ion sound velocity is controlled by the ion temperature and show how the ion yield depends on the FEL radiation attenuation length in different materials.

Background Human microsporidiosis presents as an important and rapidly emerging opportunistic infection. However, the exact burden of this infection especially in the pediatric population of Northern India remains unknown. In this study, we investigated the prevalence of microsporidia among human immunodeficiency virus (HIV)-positive and HIV-negative pediatric patients who presented with diarrhea.

Abstract Aberrantly expressed onco-mucin 16 (MUC16) and its post-cleavage generated surface tethered carboxy-terminal (MUC16-Cter) domain are strongly associated with poor prognosis and lethality of pancreatic (PC) and non-small cell lung cancer (NSCLC). To date, most anti-MUC16 antibodies are directed towards the extracellular domain of MUC16 (CA125), which is usually cleaved and shed in the circulation hence obscuring antibody accessibility to the cancer cells. Herein, we establish the utility of targeting a post-cleavage generated, surface-tethered oncogenic MUC16 carboxy-terminal (MUC16-Cter) domain by using a novel chimeric antibody in human IgG1 format, ch5E6, whose epitope expression directly correlates with disease severity in both cancers. ch5E6 binds and interferes with MUC16-associated oncogenesis, suppresses the downstream signaling pFAK(Y397)/p-p70S6K(T389)/N-cadherin axis and exert antiproliferative effects in cancer cells, 3D organoids, and tumor xenografts of both PC and NSCLC. The robust clinical correlations observed between MUC16 and N-cadherin in patient tumors and metastatic samples imply ch5E6 potential in targeting a complex and significantly occurring phenomenon of epithelial to mesenchymal transition (EMT) associated with disease aggressiveness. Our study supports evaluating ch5E6 with standard-of-care drugs, to potentially augment treatment outcomes in malignancies inflicted with MUC16-associated poor prognosis.

Pearl millet stands as an important staple food and feed for arid and semi-arid regions of India and South Africa. It is also a quick supplier of important micronutrients like Fe and Zn via grain to combat micronutrient deficiencies among people in developing countries. India has notably spearheaded advancements in pearl millet production and productivity through the All India Coordinated Pearl Millet Improvement Project. There were 21 hybrids evaluated over arid and semi-arid ecologies of the western and southern regions of India. AMMI and GGE biplot models were adopted to recommend a specific hybrid for the particular locality. A joint analysis of variation indicated a significant genotype–environment interaction for most of the agronomical and grain micronutrient parameters. Pearson’s correlation values dissected the significant and positive correlation among agronomic traits and the negative correlation with grain micronutrient traits. GGE biplot analysis recommended the SHT 106 as a dual-purpose hybrid and SHT 115 as a biofortified hybrid for the grain’s Fe and Zn content. SHT 110 and SHT 108 were selected as stable and high grain yield-producing hybrids across all environments and specifically for E1, E2, and E4 as per the Which-Won-Where and What biplot. SHT 109 and SHT 103 hybrids were stable and high dry fodder yield-producing hybrids across all environments. In this study, the Multi-Trait Stability Index (MTSI) was employed to select the most stable and high-performing hybrids for all traits. It selected SHT 120, SHT 106, and SHT 104 for stability and great performance across all environments. These findings underscored the significance of tailored hybrid recommendations and the potential of pearl millet in addressing both food security and malnutrition challenges in various agro-ecological regions.

The paper deals with the notion of quasi hemi-slant submersions from Lorentzian para Sasakian manifolds onto Riemannian manifolds. These submersions are generalization of hemi-slant submersions and semi-slant submersions. In this paper, we also study the geometry of leaves of distributions which are involved in the definition of the submersion. Further, we obtain the conditions for such distributions to be integrable and totally geodesic. Moreover, we also give the characterization theorems for proper quasi hemi-slant submersions and provide some examples of it.

Abstract T cell receptor repertoires can be profiled using next generation sequencing (NGS) to measure and monitor adaptive dynamical changes in response to disease and other perturbations. Genomic DNA-based bulk sequencing is cost-effective but necessitates multiplex target amplification using multiple primer pairs with highly variable amplification efficiencies. Here, we utilize an equimolar primer mixture and propose a single statistical normalization step that efficiently corrects for amplification bias post sequencing. Using samples analyzed by both our open protocol and a commercial solution, we show high concordance between bulk clonality metrics. This approach is an inexpensive and open-source alternative to commercial solutions.

Abstract Pomegranate crops are prone to wilt complex disease, which is known to severely hamper the crop yield. There have been limited studies that have explored bacteria–plant–host associations in wilt complex disease affecting pomegranate crops. In the present study, wilt infected rhizosphere soil samples (ISI, ASI) in pomegranate were studied in comparison to a healthy control (HSC). The 16S metagenomics sequencing approach using the MinION platform was employed for screening of bacterial communities and predictive functional pathways. Altered physicochemical properties in the soil samples were recorded showing a comparatively acidic pH in the ISI (6.35) and ASI (6.63) soil samples to the HSC soil (7.66), along with higher electrical conductivity in the ISI (139.5 µS/cm), ASI soil (180 µS/cm), HSC soil sample (123.33 µS/cm). While concentration of micronutrients such as Cl and B were significantly higher in the ISI and ASI soil as compared to the HSC, Cu and Zn were significantly higher in the ASI soil. The effectiveness and accuracy of 16S metagenomics studies in identifying beneficial and pathogenic bacterial communities in multi-pathogen–host systems depend on the completeness and consistency of the available 16S rRNA sequence repositories. Enhancing these repositories could significantly improve the exploratory potential of such studies. Thus, multiple 16S rRNA data repositories (RDP, GTDB, EzBioCloud, SILVA, and GreenGenes) were benchmarked, and the findings indicated that SILVA yields the most reliable matches. Consequently, SILVA was chosen for further analysis at the species level. Relative abundance estimates of bacterial species showed variations of growth promoting bacteria, namely, Staphylococcus epidermidis, Bacillus subtilis, Bacillus megatarium, Pseudomonas aeruginosa, Pseudomonas putida, Pseudomonas stutzeri and Micrococcus luteus. Functional profiling predictions employing PICRUSt2 revealed a number of enriched pathways such as transporter protein families involved in signalling and cellular processes, iron complex transport system substrate binding protein, peptidoglycan biosynthesis II (staphylococci) and TCA cycle VII (acetate-producers). In line with past reports, results suggest that an acidic pH along with the bioavailability of micronutrients such as Fe and Mn could be facilitating the prevalence and virulence of Fusarium oxysporum, a known causative pathogen, against the host and beneficial bacterial communities. This study identifies bacterial communities taking into account the physicochemical and other abiotic soil parameters in wilt-affected pomegranate crops. The insights obtained could be instrumental in developing effective management strategies to enhance crop yield and mitigate the impact of wilt complex disease on pomegranate crops.

The industries utilize fluid heating and cooling in various applications such as production, power generation, electronics, and transportation. Many techniques have been applied / proposed to efficiently convert solar energy into thermal energy. These enhancements techniques include employing corrugated absorber plate, adding extended surfaces to the upper or lower channels, integrating artificial roughness on heated plate, jet impingement on plate and use of energy storage medium. Jet impingement is a well-known method which enhances the amount of heat that is transferred convectively from the working fluid to the absorber plate. The study of the heat transfer process employing diverse geometrical jet configurations, which are of relevance in a wide range of engineering applications, is still lacking despite the enormous number of jet impingement studies. The present study rigorously analyzed the previous works to provide essential information regarding crucial roughened geometries and geometric parameters for optimum heat transfer enhancement. This is very crucial information/aid for technical people and researchers working in the field, performance improvement of solar air heaters. The precise information related to flow parameters and heat transfer can be used by researcher in their future work which save the time as well as cost of experimental set up. The current review research's goal is to analyze and assess the systems and technologies that are already in use and those that will likely be developed in the future. If decision-makers and practitioners wish to choose the most cutting-edge and inventive technologies for heat transfer enhancement, this article may help to provide guidance. As a result, the findings of this review article may be very beneficial to distinct energy sector stakeholders.

Abstract The problem of management and treatment of wastewater from commercial laundries is a matter of concern. The present study provides an effective and eco-friendly solution to the treatment of wastewater from commercial laundries in Quebec (Canada) by using the extracellular polymeric substance (EPS) as a bio-flocculant. EPS was produced from the valorization of crude glycerol and paper mill sludge by a bacterial strain (BS-04). Two different types of EPS: Slime EPS (S-EPS) and Broth EPS (B-EPS) were used for the treatment of commercial laundry wastewater (CLWW). This is the first study for the treatment of CLWW using bio-flocculant EPS. A comparison between the conventional treatment of laundry wastewater (LWW) by chemical coagulants (FeSO4, CaCl2, Alum) and enhanced treatment by bio-flocculant EPS has been drawn in the study. Moreover, LWW treatment by a combination of EPS and chemical coagulants was also investigated. It was observed that S-EPS (0.6 g/L) gave better flocculation activity (FA) than B-EPS. S-EPS alone can remove 83.20% of turbidity, 77.69% of suspended solids (SS), and 76.37% of chemical oxygen demand (COD). The best results were obtained by combining S-EPS (0.6 g/L) with alum (300 mg/L) at pH 7 for a treatment time of 30 min. This combination was able to remove 98% of turbidity, 95.42% of SS, and 83.08% of COD from LWW. When treatment time has been increased to 4 h at pH 7, it resulted in more than 88% COD removal from CLWW. Graphical Abstract