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An experiment was conducted during kharif season 2020 at Instructional Farm, College of Agriculture, Ummedganj, Kota. The experiment comprised twenty-four treatment combinations, having four levels of phosphorus viz., 0, 20, 40 and 60 kg ha-1, three levels of sulphur viz., 15, 30 and 45 kg ha-1 and foliar spray of gibberellic acid viz., no spray and spray of GA3 @ 75 ppm laid out in sub-sub split-plot design with three replications. Results showed that application of 60 kg P2O5 ha-1 had significant effect on plant height, dry matter accumulation plant-1, branches plant-1 at 30, 60 DAS and at harvest, root nodules plant-1 and their dry weight at 45 DAS while root nodules plant-1 and their dry weight at 45 DAS andseed yield (1956 kg ha-1) over application of 40, 20 kg P2O5 ha-1 and control. Significantly higher seed yield (1956 kg ha-1) was recorded under application of 60 kg P2O5 ha-1 over application of 20 kg P2O5 ha-1 and control. However, it was found at par with application of 40 kg P2O5 ha-1. Application of 45 kg sulphur ha-1 had significantly higher plant height (cm) at 60 DAS and at harvest, dry matter accumulation (g plant-1) at 30, 60 and at harvest stages, branches plant-1 at 30, 60 and at harvest stage, number of root nodules and their dry weight (g) and seed yield (1742 kg ha-1) which was found at par with application of 30 kg sulphur ha-1 over 15 kg sulphur ha-1. Application of gibberellic acid @ 75 ppm as foliar spray gave significantly higher plant height (cm) at 60 DAS and at harvest stage, dry matter accumulation (g plant-1) at 60 DAS and at harvest, branches plant-1 at 30, 60 DAS and harvestand seed yield (1770 kg/ha) over control.

Chingus, an almost mountainous village of district Rajouri, falls under Jammu province of the UT of Jammu and Kashmir. The village is replete with local heritage which includes culinary heritage and handicrafts. Though rich in heritage, it cannot be considered as a sustainably developed area. Identification and utilisation of its available heritage can be helpful in its sustainable development. Years ago, Mahatma Gandhi also laid stress on the utilisation of local heritage for sustainable development. When it comes to the identification and utilisation of local heritage of Chingus, the local communities (Gujjars/ Bakarwals/ Paharies) of the area can do a lot. But, the locals would not come forward on their own. They must be channelised by local government and other government/private or non-profit agencies. Such channelisation would help in making Chingus, a self-reliant village, thus, giving practical shape to the Gandhian dream of self reliant villages. Moreover, establishment of ‘Mahatma Gandhi Museum of Heritage’ would make the process of sustainable development of Chingus more speedy.

The selection of climate resilient animal is necessary to secure the future of sustainable animal production. The present investigation therefore was an effort to unravel answers to the adaptation at physiological, hematological, and molecular levels in cows of hot arid region that helps them to survive harsh environment, to continue production and reproduction. This investigation was carried out in indicine cows over a period of one year, encompassing four seasons, wherein physiological data of 50 animals, hematological data of 15 animals, and gene expression profile of 5 animals from each of Sahiwal and Kankrej breeds per season was generated. In total, 5600 physiological observations, 1344 hematological observations, and 480 molecular samples were processed. The meteorological data revealed a high diurnal variation of temperature across seasons, with THI exceeding 80 during the months of summer and hot-humid seasons, indicating significant heat stress (HS). The physiological parameters showed an increasing trend with the incremental THI, with significantly (p 0.05) higher values of rectal temperature (RT), respiration rate (RR), pulse rate (PR), and body surface temperature (BST) at ventral (VT), lateral (LT), dorsal (DT), and frontal (FT), in both breeds recorded during HS. The hematological pictures also revealed significant (p 0.05) seasonal perturbations in erythrocytic and leucocytic parameters. Moreover, the molecular response was driven by a significant (p 0.05) upregulation of all the key HSPs, HSP70, HSP90, HSP60, and HSP40, except HSP27 during the hotter months of summer and hot-humid seasons. The expression of HSF1, an important transcriptional regulator of HSP70 was also significantly (p 0.05) upregulated during summer season in both breeds. All the molecular chaperones revealed a significant upregulation during the summer season, followed by a decreasing trend by hot-humid season. The study indicated a well-developed thermotolerance mechanism in animals of both breeds, with Kankrej cows exhibiting better thermotolerance compared to Sahiwal cows.

Emotions are something that makes one realize how other people are feeling but sarcasm needs to be understood by putting in some extra effort. Sarcasm, a verbal irony, is a practice of using words or sentences that are different from their literal meaning. Researchers are still making effort in developing an algorithm that can identify sarcasm completely. Since sometimes humans also take time to understand sarcasm, making a machine learn to recognize is also not a simple task. The need for Deep Learning (DL) is rapidly growing for detection and classification operations. Different research works focused on Sarcasm detection using various methodologies but the issue with existing research work is their performance and accuracy. Our survey provides several helpful examples, the most notable of which is a table that lists prior studies according to several criteria, including the kinds of methodologies with accuracy, and datasets employed. This paper also throws light on multimodal detection, sarcasm detection from typographic images (memes), feature set analysis, and different phases of a model with various issues and milestones in sarcasm detection.

Cardiovascular diseases are a major cause of death worldwide, making early detection and diagnosis critical for reducing mortality and morbidity. The interpretation of complex medical images can be made easier with the use of machine learning algorithms, which could result in more precise cardiovascular imaging diagnosis. In this review paper, we give an overview of the state-of-the-art in machine learning-based cardiovascular imaging, including the datasets, imaging modalities, and algorithms that are currently accessible. We also discuss the major challenges and opportunities in the field and highlight recent advances in machine learning algorithms for automated cardiac image analysis. Specifically, we focus on the use of deep learning and convolutional neural networks for cardiac image segmentation and classification of cardiac conditions, such as heart failure, myocardial infarction, and arrhythmias. We explore the potential of these algorithms to improve the accuracy and efficiency of cardiovascular imaging and discuss the need for standardized datasets and evaluation metrics to enable better comparison of different algorithms. We also discuss the importance of interpretability in machine learning algorithms to enhance trust and transparency in their predictions. Overall, this review provides a comprehensive overview of the current state and future potential of machine learning in cardiovascular imaging, highlighting its significant impact on improving the diagnosis and treatment of cardiovascular diseases.

The present study was aimed to assess genetic variation among rice germplasm lines employing a multivariate biometrical approach, viz., Principal Component Analysis. Analysis of variance as per Augmented Block Design indicated the presence of sufficient genetic variation among rice germplasm lines, while estimates of components of variation revealed a maximum contribution of genotypic variance to the phenotypic variance, suggesting its exploitation through selection and hybridization. Simultaneously, correlation estimates revealed a significant positive association of grain yield with panicle length, 1000 grain weight and grain length indicating suitability of these traits for indirect selection. D2 statistics grouped germplasm lines into sixteen clusters and among these cluster I consists of 67 germplasm lines forming the largest cluster followed by cluster III (26 lines), cluster II (18 lines), cluster IV (15 lines), cluster V (13 lines), cluster VI (5 lines), cluster VIII (3 lines), cluster VII and cluster IX (2 lines each), while clusters X, XI, XII, XIII, XIV, XV, XVI (1 line each). Inter cluster distances were found to be higher than intra cluster distances and the maximum inter cluster distance was observed between cluster IX and VI (73.47) followed by cluster IX and X (73.14). Principal component analysis transformed eleven interrelated variables into four major principal components having an eigen value of more than 1, thereby, indicating that these components are responsible for a higher magnitude of variance in the population (76.60 per cent). Among these principal components, the first component accounted for 32.80 per cent of the total variation while, the second, third and fourth components explained 18.50 per cent, 13.90 per cent and 11.40 per cent of total variation, respectively. Factor loadings of the principal components revealed that principal component 1 had high positive loadings for grain length, panicle length, length/breadth ratio, 1000 grain weight and plant height whereas, principal component 2 had high positive loadings for total number of tillers per plant and number of effective tillers per plant indicating that the first two principal factors can be collectively designated as yield attributing factors. Principal component 3 had high positive loadings for grain breadth, 1000 grain weight and plant height, whereas, principal component 4 had high positive loadings for 1000 grain weight, days to maturity and days to 50% flowering. PCA biplots revealed that germplasm lines viz., GPL-1, GPL-4, GPL-131, GPL-128, GPL-20, GPL-127, GPL-135, GPL-100, GPL-130 were found to be superior performers for desirable traits and can be used as parents in hybridization programme.

Natural surfactants have gained importance as the usage of synthetic surfactants shows economical aspects, health, and environmental effect. This study examined the anti-microbial activity of safflower seed waste (Ssw) isolated surfactant against dandruff-causing Malassezia furfur and skin diseases causing bacterial strains. Saponin was the major component and non-ionic surfactants derived from plants, which have a special molecular structure with hydrophilic glycoside backbone and lipophilic triterpene derivative. The antimicrobial activity of isolated surfactants was confirmed by the MIC and kill-time assays. Our results showed that the isolated saponin may interact with the cell wall and membrane first and destroy the cell wall and membranes, which finally results in bacterial death. Besides, isolated saponin penetrates the cytoplasmic membrane or enters inside the cell after the destruction of cell structure, and then inhibits the normal synthesis of DNA and proteins that are required for bacterial growth. These results suggested that the effects of the Ssw isolated saponin on the growth inhibition of selected bacterial strains may be at the molecular level rather than only physical damage. Extraction of Biosurfactant (saponin) from Safflower seed waste and its antimicrobial activity.

Context: Bihar aims to achieve a maternal mortality ratio (MMR) of less than 70 per 1, 00, 000 live births, towards achieving its Sustainable Development Goal. The same can be achieved through robust monitoring of the health programs in the state. The present study critically analyses the use of a mobile-based reporting system on achieving the SDG for the state. Aims: The study aims to assess the use of mobile phone-based reporting systems for Sustainable Development Goals. Thus, establishing the usefulness of a mobile-based reporting system. The study also explores the cost of running the project. Settings and Design: It is a quasi-experimental design. The study was conducted with Front Line Workers (FLW -Accredited Social Health Activist & Auxiliary Nurse Midwife) of two intervention blocks in the Saharsa District of Bihar. The two blocks were using mobile phones for reporting RMNCHA services. A total of 109 FLWs were contacted in Jul 2017. Methods and Material: Quantitative methods were used in the study. Two tools were administered to the respondents at the facility level. Statistical Analysis Used: The study compares the increase in the utilization of health care services from FY 13-14 to FY 16-17. The case is defined as the block in which the front-line workers use mobile phones for reporting and control is where the reporting is through paper-based mode. To arrive at a net difference, the study used the difference in a different technique to analyse the data. Data were obtained from the government reporting system. To corroborate the results, the mean values were calculated, by dividing the blocks of the district into two groups case and control. The step-down costing of the project was performed to arrive at the unit cost of implementation.

Acinetobacter baumannii forms robust biofilms, which aid protection against antimicrobials and account for adaptation in hospital settings. Biofilm formation by A. baumannii has worsens the scenario of drug resistance. Therefore, new strategies are required to tackle biofilm-forming multidrug-resistant A. baumannii. The present study investigated compounds with antimicrobials and antibiofilm properties against A. baumannii. Different antimicrobials were selected from available reports. Initially, comparative antimicrobial activity against A. baumannii isolates was assessed. Most potent antimicrobial compounds were further analyzed for time-kill kinetics, biofilm inhibition, and exopolysaccharide (EPS) reduction in their presence and absence. The antibiofilm potentials were also confirmed with SEM analysis. The relative gene expression of the csuE gene and molecular docking was carried out to investigate the molecular mechanism of mature biofilm disruption. The results demonstrated eugenol and geraniol as the most potent inhibitors with MICs of 6.08 mM and 3.24 mM, respectively, with the potential to significantly inhibit growth and EPS production. Complete inhibition of A. baumannii mature biofilms was observed with a maximum of 60.89 mM and 129.6 mM concentrations of eugenol and geraniol, respectively. The SEM analysis and lower expression of the csuE gene showed the effectiveness of potent antibiofilm agents. In-silico docking showed efficient binding of eugenol and geraniol with the csuE protein of archaic pilus. The findings of molecular docking concordant the assumption that these molecules may prevent the assembly of mature pilus, which results in abolished biofilms. In conclusion, the antibiofilm virtues of eugenol and geraniol were elucidated to be used in the future to control the persistence of biofilm-forming drug-resistant A. baumannii.

Euryale ferox (also known as foxnut), belongs to the family Nymphaeaceae. It is mainly grown in India, China, Japan, and Korea. It is a highly nutritious food, abundant in nutritional and bioactive compounds such as carbohydrates, protein, fiber, vitamins, minerals, and polyphenols. It is considered a functional food owing to its various health benefits such as antidiabetic, antihyperlipidemic, antifatigue, hepatoprotective, cardioprotective, antimelanogenic, etc. E. ferox has immense potential in both food and non-food industries. Regardless of being recognized as a superfood packed with nutritional as well as medicinal properties, it is still neglected, and there has not been much attention given to its cultivation. Therefore, in this review, the potential of E. ferox as a superfood has been explored to enhance its utilization in the development of different foods and make it available outside its growing area. PRACTICAL APPLICATIONS: Euryale ferox is abundant in several macronutrients and micronutrients; and considered as a superfood in terms of various health benefits. E. ferox has the ability to be used in the development of different health, functional, and nutraceutical foods, which will open a new door for the food industry to combat with numerous diseases.

Study background: Traditional fermented foods are the source of probiotic bacteria which can be envisaged as formulation ingredients in various food and beverages. Scope and approach: The present research aimed to explore one of the Indian traditional recipes, “Tarvaani,” for nutritional and probiotic potential as a part of its healthy perspectives. Main findings and conclusion: The traditional recipe was found to contain the lactic acid bacteria and isolated. The isolated product showed prominent curdling activity after 48 h, and bacterial growth was seen in all the pH (pH 3–7) tested. The antibiotic susceptibility test found that streptomycin, vancomycin, and kanamycin were resistant to the bacterial culture, and imipenem, gentamycin, rifampicin, and tetracycline were found to be resistant susceptible to the bacterial culture according to zone diameter interpretative criteria given in ICMR SOP 2015. A clear halo zone around the tested colony was obtained in the amylase test, which indicated that starch was degraded and α-amylase was produced. The culture also showed prominent antimicrobial action and inhibited the growth of the pathogenic strains tested by a well-diffusion assay. Moreover, the isolates only showed no haemolysis activity after incubation at 30 ◦C for 24 h under anaerobic conditions. Overall, the present research findings showcase the nutritional and probiotic potential of Lactobacillus sp. of “Tarvaani” as a viable option as a formulation ingredient in traditional-based functional foods Universidade de Vigo/CISUG