Mustard (Brassica juncea) is the major edible oil crop of the Indian subcontinent. Genetic analysis of combining ability is a cornerstone in the development of high-yielding hybrids in rapeseed (Brassica napus L.) and mustard (Brassica juncea). The present study on maintainer restoration of fertility in rapeseed with the use of 75 f1s line and 15 testers data were recorded on important characters. The relative contribution of line tester components was higher than that of lines and tester to other variability for all the characters. Non-additive genetic components play a vital role in governing the expression of seed yield and its major determinant. The majority of parents show non significant GCA value. The present investigation for research work entitled Genetical analysis of general and specific combining ability variance for the characters under study for maintainer/ restoration fertility in rapeseed (Brassica napus L.) and mustard (brassica juncea L.) (czern & coss) for its cultivation in soil of western uttar pradesh in modern scenario was carried out together at the students instructional farm of the Agriculture department, Mangalayatan University and at nearby research farm of Mirzapur village ( nearby of Mangalayatan University Aligarh) during the rabi season of 2024 to 2025.

OBJECTIVE:To identify the risk factors for intrapartum stillbirth and examine whether these are different from that of antepartum stillbirth, and investigate the survival probabilities of fetuses by gestational age in high-risk pregnancies. METHODS:We conducted a secondary data analysis of a hospital-based cohort study from India, including 9774 singleton pregnancies from 13 hospitals across six states. We conducted modified Poisson regression analysis to assess associations between potential risk factors and intrapartum stillbirth. Kaplan-Meier survival curves were used to explore survival probabilities of fetuses among pregnant women who had anemia and hypertensive disorders in pregnancy (HDP) compared with those who did not have these problems. RESULTS:There were 167 intrapartum stillbirths and 9607 live births; representing an incidence of 17.1 per 1000 total births (95% confidence interval [CI]: 14.6-19.9). Risk factors identified were illiteracy (adjusted risk ratio [aRR]: 2.37, 95% CI: 1.33-4.38), age > 34 years (aRR: 3.17, 1.41-7.36), <4 antenatal check-ups (aRR: 1.90, 1.27-2.87), <100 days of iron and folic acid supplementation (aRR: 9.10, 4.15-21.05), other HDP (aRR: 2.48, 1.36-4.25), severe anemia (aRR: 3.33, 1.82-6.63), preterm birth (aRR: 3.25, 2.26-4.69) and <10th percentile birth weight-for-gestational age (aRR: 1.57, 1.14-2.17). These were similar to the risk factors for antepartum stillbirths. Survival probabilities for fetuses among women with pre-eclampsia/eclampsia and severe anemia decreased from 34 weeks' and 30 weeks' gestation, respectively. CONCLUSION:In this high-risk hospital cohort of pregnant women undergoing labor induction or augmentation, risk factors for intrapartum stillbirth overlapped substantially with those for antepartum stillbirth, although the antepartum analysis was underpowered. Targeted monitoring of women with severe anemia and HDP from 30 weeks may reduce intrapartum stillbirth risk in similar settings.

The present study holds the potential to inform agricultural management strategies, enabling practitioners to optimize soil health, enhance crop productivity, and ensure the long-term viability of rice-based cropping systems. The primary role of soil, concerning its chemical quality for crop production, is the provision of essential nutrients crucial for optimal crop growth. Within the realm of chemical parameters, soil organic carbon (SOC) emerges as a paramount indicator of soil health. The experiment was conducted at the BEDF (APEDA) farm, Sardar Vallabhbhai Patel University of Agriculture & Technology, campus, Meerut (U.P.), India.The study was primarily focused on testing of soil quality of 40 representative samples and the analytical results were supposed to represent the entire field. The treatment means were compared by using the transformed values. The treatment differences were tested by least significant difference at 5 per cent of probability. The obtained results from the study revealed that inclusion of pulses in cropping system improve the physical properties of soil. Although inclusion of pulses did not affect soil texture, bulk density, particle density and porosity significantly as compared to wheat or mustard based cropping systems but aggregate stability, hydraulic conductivity, availability of phosphorus, zinc, iron and organic carbon (%) influenced significantly. Growing of rice- pulses-pulses in cropping system enriched the sub-soil because wheat and mustard are deep rooted crops so they remove the nutrients from subsoil also therefore sub soils of cereals -pulses-pulses crop rotation are slightly healthy than surface soil.

This study outlines a comprehensive approach to exploring the interplay between serum uric acid levels, age, and BMI in hypertensive patients, aiming to provide actionable insights and contribute to the broader scientific understanding of these relationships. To fulfill this objective, a study at tertiary-care teaching hospital, Northern India (June 2017 - December 2018) involved 145 hypertensive patients and 145 matched controls, using a case-control, cross-sectional design. Participants were randomly selected and included those over 12 years old with hypertension per JNC 7/8 criteria, excluding individuals with severe hypertension, recent myocardial infarction, major infections, chronic diseases, or those on specific drugs affecting uric acid. Smokers and heavy drinkers were also excluded. Data collection included informed consent, venipuncture, history, physical exams, and tests such as blood pressure, serum uric acid, BMI, and various blood tests. Statistical analysis was performed with mean, standard deviation, t-tests, and Pearson's correlation, with significance set at p < 0.05. The study reveals a balanced age distribution with most participants over 40 years, and consistent blood pressure categories across cases and controls, with cases showing higher rates of hypertension. Cases also exhibit significantly higher average blood pressure levels. Weight categories are similarly distributed between cases and controls, with a trend towards higher SUA levels in individuals with higher BMI. A strong positive correlation is observed between SUA levels and both systolic and diastolic blood pressure. Males show a slightly higher prevalence of hypertension compared to females, reflecting a greater overall burden of the condition. The study concludes that elevated SUA levels are significantly correlated with higher blood pressure, both systolic and diastolic. The analysis reveals that hypertensive cases exhibit higher average blood pressure levels and a trend towards increased SUA levels with higher BMI. Additionally, males show a slightly greater prevalence of hypertension compared to females. These findings underscore the importance of monitoring SUA levels and BMI in managing hypertension and suggest that interventions targeting these factors could be beneficial in reducing cardiovascular risk.

There is trend towards increased caesarean deliveries in the modern era. One of the most common negative effects of caesarean births is post-operative infectious morbidity. In addition to antibiotic prophylaxis, it has long been advised to prepare the surgical site with povidone-iodine to reduce presence of bacterial and fungal organisms near the skin or vagina. We thus concentrated on researching use of 1

Artificial intelligence (AI) is an emerging field of computer science which is currently being used in many sophisticated applications such as e-commerce, military, education, industry, and healthcare. AI has several subfields like machine learning, neural network, Deep Learning, Natural Language Processing (NLP), and computer vision. In the medical domain, AI with deep learning model plays a crucial role to predict the symptoms of various kinds of disease and clinicians to make decision about analysis critical medical report provided by radiologists and pathologists. However, the adoption of many AI model in healthcare face challenges related to transparency, interpretability, and trustworthiness, due to their “Black-Box” in nature. Usually, it is essential for humans to understand the reasoning behind an AI model’s decision-making. To make a better decision-making, Explainable AI (XAI) is a useful technique that aims to explain the information inside the black-box model of AI algorithms that reveals how the decisions are made. The aim of this paper is to provide a survey of the most novel XAI techniques used in healthcare and related medical imaging applica- tions. In addition, this paper provides the study of various applications of XAI in healthcare and focuses on challenges related to black-box AI models, emphasizing the requirement for interpretable arrangements in healthcare. Furthermore, this paper presents different XAI strategies, including Local Interpretable Model-Agnostic Explanations (LIME), Shapley Additive Explanations (SHAP), and rule-based frameworks, which are displayed and assessed for their viability in making AI models interpretable. Finally, this survey paper provides future direction to help developers and researchers for future prospective investigations in healthcare and discusses future research possibilities in the area of XAI.

ObjectiveThis study aimed to investigate the incidence of and risk factors for stillbirth in an Indian population.MethodsWe conducted a secondary data analysis of a hospital-based cohort from the Maternal and Perinatal Health Research collaboration, India (MaatHRI), including pregnant women who gave birth between October 2018-September 2023. Data from 9823 singleton pregnancies recruited from 13 hospitals across six Indian states were included. Univariable and multivariable Poisson regression analysis were performed to examine the relationship between stillbirth and potential risk factors. Model prediction was assessed using the area under the receiver-operating characteristic (AUROC) curve.ResultsThere were 216 stillbirths (48 antepartum and 168 intrapartum) in the study population, representing an overall stillbirth rate of 22.0 per 1000 total births (95% confidence interval [CI]: 19.2-25.1). Modifiable risk factors for stillbirth were: receiving less than four antenatal check-ups (adjusted relative risk [aRR]: 1.75, 95% CI: 1.25-2.47), not taking any iron and folic acid supplementation during pregnancy (aRR: 7.23, 95% CI: 2.12-45.33) and having severe anemia in the third trimester (aRR: 3.37, 95% CI: 1.97-6.11). Having pregnancy/fetal complications such as hypertensive disorders of pregnancy (aRR: 1.59, 95% CI: 1.03-2.36), preterm birth (aRR: 4.41, 95% CI: 3.21-6.08) and birth weight below the 10th percentile for gestational age (aRR: 1.35, 95% CI: 1.02-1.79) were also associated with an increased risk of stillbirth. Identified risk factors explained 78.2% (95% CI: 75.0%-81.4%) of the risk of stillbirth in the population.ConclusionAddressing potentially modifiable antenatal factors could reduce the risk of stillbirths in India. Major risk factors are amenable to interventions; providing high-quality antenatal care and improving the availability of emergency obstetric care could reduce the risk of stillbirths in India.

Background:There is trend towards increased caesarean deliveries in the modern era. One of the most common negative effects of caesarean births is post-operative infectious morbidity. In addition to antibiotic prophylaxis, it has long been advised to prepare the surgical site with povidone-iodine to reduce presence of bacterial and fungal organisms near the skin or vagina. We thus concentrated on researching use of 1% povidone iodine vaginally preoperatively to prevent post-caesarean section endometritis in our hospital. Methods:This was a prospective, observational, case-control study. All pregnant women undergoing LSCS fulfilling the inclusion criterion were recruited and divided into two groups. All characteristics were recorded in specially designed Case Report Form, and patients were reviewed for 6 weeks for outcome measures. The data were analysed using Excel sheets, and Chi-square test and independent sample t-test were applied to analyse the statistical significance. Results:The cases were found to have undergone significantly greater mean number of pelvic examinations than the controls (p value < 0.0001). Greater proportion of controls developed endometritis and fever than the cases, and this value was statistically significant (p < 0.05). Wound infection and post-LSCS CRP levels were greater among controls as compared to cases, but this was not statistically significant. Conclusion:Incidence of post-caesarean endometritis and fever was significantly lower among cases as compared to controls. Application of povidone iodine is a simple and cost-effective method which can be implemented on a larger scale in order to reduce caesarean related morbidity.

Background: Treatment of Post partum haemorrhage relies primarily on uterotonics, but early use of Tranexamic Acid (TXA) has become part of several recommended algorithms. Recent data has demonstrated that Tranexamic Acid (TXA), an antifibrinolytic agent, reduces death due to bleeding when used as a treatment for PPH. This study was conducted with an objective to see the role of tranexamic acid along with uterotonic agent (oxytocin) in prevention of postpartum hemorrhage. Materials and Methods: The present prospective observational study carried out at the Maternal and Child Health (MCH) wing Department of a rural tertiary care hospital and medical college situated in the central India during January 2021 to December 2022. A total sample size of 1640 patients attending labour room for vaginal birth or caesarean section in 3rd stage of labour were included in the study. Total 1640 women were further divided into two groups, Group A (receiving both tranexamic acid along with oxytocin) and Group B (receiving only oxytocin). Blood loss in each group was measured by visual method and Gravimetric (measurement by weight) method. They were followed till delivery; maternal and neonatal outcome was studied. Statistical analysis was done by using SPSS 27.0 version and GraphPad Prism 7.0 version and p<0.05 considered as level of significance. Results: The majority of patients in Group A and Group B were between 26-30 years of age group. There was no significant difference between the groups in terms of maternal age, gestational age, gravida and booking status. The mean foetal birth weight among Group A was 2421.28 ± 626.91 and Group B was 2381.38 ± 721.20 with no significant difference between the groups. There was significant reduction in blood loss in study group A as compared to control group in both vaginal and LSCS birth with statistically significant difference. Conclusion: Tranexamic acid injection, an antifibrinolytic agent when given prophylactically after delivery of placenta along with oxytocin appears to reduce the blood loss during normal labour as well as caesarean sections effectively.

Background Coronavirus disease has affected the entire population worldwide in terms of physical and environmental consequences. Therefore, the current study demonstrates the changes in the concentration of gaseous pollutants and their health effects during the COVID-19 pandemic in Delhi, the national capital city of India. Methodology In the present study, secondary data on gaseous pollutants such as nitrogen dioxide (NO 2 ), carbon monoxide (CO), sulfur dioxide (SO 2 ), ammonia (NH 3 ), and ozone (O 3 ) were collected from the Central Pollution Control Board (CPCB) on a daily basis. Data were collected from January 1, 2020, to September 30, 2020, to determine the relative changes (%) in gaseous pollutants for pre-lockdown, lockdown, and unlockdown stages of COVID-19. Results The current findings for gaseous pollutants reveal that concentration declined in the range of 51%–83% (NO), 40%–69% (NOx), 31%–60% (NO 2 ), and 25%–40% (NH 3 ) during the lockdown compared to pre-lockdown period, respectively. The drastic decrease in gaseous pollutants was observed due to restricted measures during lockdown periods. The level of ozone was observed to be higher during the lockdown periods as compared to the pre-lockdown period. These gaseous pollutants are linked between the health risk assessment and hazard identification for non-carcinogenic. However, in infants (0–1 yr), Health Quotient (HQ) for daily and annual groups was found to be higher than the rest of the exposed group (toddlers, children, and adults) in all the periods. Conclusion The air quality values for pre-lockdown were calculated to be “poor category to “very poor” category in all zones of Delhi, whereas, during the lockdown period, the air quality levels for all zones were calculated as “satisfactory,” except for Northeast Delhi, which displayed the “moderate” category. The computed HQ for daily chronic exposure for each pollutant across the child and adult groups was more than 1 (HQ > 1), which indicated a high probability to induce adverse health outcomes.

Free standing layer of PA6 nanofibers was prepared using electrospinning method on the multilayered composite nonwoven fabrics for better control over the elimination of metal ions in contaminated water. Electrospun nanofiber membranes showed superior performance due to their controlled porosity, better modular design and flexibility. Recently, increasing attention has been given to hydrophilic membranes such as PA6 which resulted decreased bio and organic fouling. We have developed a strategy to generate the composite nanofibers-based membrane over polyester/leno multilayer to produce a hierarchical structure for efficient elimination of metal ions at various concentration of feed stock solution. The functionalized carbon nanotube-graphene hybrid nanofillers have been introduced in the nanofiber morphology using electrospinning to further increase the hydrophilicity and selectivity towards elimination of toxic metal ions. A series of high-resolution microscopic studies and BET analysis have been carried out to illustrate the resultant composite nanofibrous web uniformly deposited over nonwoven fabrics where the mean fiber diameter was ranging from 190-350 nm. It has been found that the flux rate critically depends upon the porosity of the hierarchical multilayer fabrics which in turn established the importance of the percentage loading of nanofibers on the membrane.

Aim: To evaluate the ability of four types of the risk of malignance indices (RMI) based on serum levels of Ca-125, ultrasound score and menopausal status to discriminate between benign and malignant ovarian tumours.Methods: it was a Prospective cross sectional Study conducted in the Department of Obstetrics and Gynecology.During this study 300 women were enrolled in the study over a period of 1 1/2 years (December 2015-July 2017).The RMI was evaluated for sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) with reference to the actual presence of a malignant or benign pelvic tumour.Results: In this study out of 300 patients with clinically suspected ovarian tumours were included.RMI 1,2,3,4 was calculated according to their formula.Sensitivity of RMI-1, 2, 3 and 4 was calculated to be 63.43%, 77.61%, 63.43% and 76.49% respectively.Specificity of RMI-1, 2, 3 and 4 was calculated to be 68.75%,65.62%, 65.62% and 62.50% respectively.RMI-2 and RMI-4 had maximum sensitivity while RMI-1 had maximum specificity.Overall RMI-2 appears to be the most accurate of all the four RMI.Conclusions: Overall RMI 2 appears to be more accurate of all.it may be concluded that, the RMI is a simple scoring system with higher accuracy in differentiating benign from malignant ovarian masses, it can be easily introduced in clinical practice and can be the test of choice in the preoperative evaluation of the adnexal mass under primary settings.Based on our study, RMI 2 use with ultrasound findings can be a useful and applicable method for initial assessment of patients with pelvic masses.

Facial Recognition is a technique that uses the face and its features to identify/verify a person. It is a Biometric Application, which is playing an integral role in today’s world in a wide variety of areas like Criminal Identification, Visitor Verification, and many other Real Time Identification systems. In this paper, we present a system that does facial matching for deformed faces. The proposed method combines the extraction of high-level feature representations using Deep Learning and the calculation of facial ratios using Image Processing to generate a robust model that can be used to identify/verify deformed faces. Whereas traditional face recognition systems show poor results when there is a face deformation. We use a function that tells us how similar or how different the two input images are. So, for this Siamese network is used. This network takes in an image as input and gives its feature vector. Then, we find the distance between the computed feature vectors of the two images which will give us a similarity score. Next, we use an Image Processing technique to calculate the facial ratios from macro features like eyes, lips, etc. These facial ratios are calculated based on facial landmarks spread across the face. We use multiple facial ratios, so even if deformities occur in a part of the face it will not have much effect on the system rendering it immune to facial changes. Hence, this paper tries to close the gap in the previously devised facial matching methods which were not designed for deformed faces.

Heavy metal pollution, in the aquatic ecosystem, has become an area of concern garnering increasing attention since the past few decades. These metals are introduced into the marine ecosystem mainly due to anthropogenic activities including offshore Oil and Gas exploration and production activities Though rich in aliphatic and aromatic hydrocarbons, crude oil also contains some trace element like vanadium, nickel, iron, aluminium, copper and some heavy metals like lead and cadmium. Poisonous or hazardous components of crude oil are mainly benzene and heavy metals which vary depending on the source of the crude oil. Elements like copper, mercury, lead, cadmium, zinc and chromium are very toxic. Except copper and zinc, others are nonessential and toxic. In fact, all metals are toxic at high concentrations. The heavy metal overload has inhibitory effects on the development of aquatic organisms such as phytoplankton, zooplankton, and fish. The metallic compounds could disturb the oxygen level and mollusc’s development, byssus formation, as well as reproductive processes. Hence, monitoring the heavy metal concentrations in sea water over a period of time is of great help in checking the pollution level and identifying the trend, which in turn will be instrumental in formulating sustainable practices. The paper mainly focuses on the study of the concentration of non-essential heavy metals in sea water around the operational areas of ONGC in western offshore area. The distribution of heavy metals in the seawater of ONGC’s exploratory blocks in Krishna-Godavari Basin, Bay of Bengal was investigated. Fifty four sea water samples collected as per OSPAR guidelines from each blocks (Vasihta G1 PML-65, Yaman PML, Godavari PML-46, DWN M-3, KG OS DW III 62, and KG DWN 98/2-1) of Krishna-Godavari Basin, Bay of Bengal and processed samples were analyzed by ICP-MS for Pb, Cr, As, and Cd. Comparison of average results in studied 6 blocks with various seawater quality guidelines is discussed to assess the present contamination. It reveals that seawater in study area are not contaminated with respect to perceived heavy metals. Generated data will assist in future for proactive measures and minimize the impact of anthropogenic sources.

Abnormal prolonged labour and its effects are important contributors to maternal and perinatal mortality and morbidity worldwide. E-partograph is a modern tool for real-time computerised recording of labour data which improves maternal and neonatal outcome. The aim was to improve the rates of e-partograph plotting in all eligible women in the labour room from existing 30% to achieve 90% in 6 months through a quality improvement (QI) process. A team of nurses, obstetricians, postgraduates and a data entry operator did a root cause analysis to identify the possible reasons for the drop in e-partograph plotting to 30%. The team used process flow mapping and fish bone analysis. Various change ideas were tested through sequential Plan-Do-Study-Act (PDSA) cycles to address the issues identified. The interventions included training labour room staff, identification of eligible women and providing an additional computer and internet facility for plotting and assigning responsibility of plotting e-partographs. We implemented these interventions in five PDSA cycles and observed outcomes by using control charts. A set of process, output and outcome indicators were used to track if the changes made were leading to improvement. The rate of e-partograph plotting increased from 30% to 93% over the study period of 6 months from August 2018 to January 2019. The result has been sustained since the last PDSA cycle. The maternal outcome included a decrease in obstructed and prolonged labour with its associated complications from 6.2% to 2.4%. The neonatal outcomes included a decrease in admissions in the neonatal intensive care unit for birth asphyxia from 8% to 3.4%. It can thus be concluded that a QI approach can help in improving adherence to e-partography plotting resulting in improved maternal health services in a rural maternity hospital in India.

Dependability analysis like reliability, safety, performability etc. of safety-critical systems (SCS) have been modeled using various modeling techniques such as unified modeling language (UML), fault tree, failure mode effect analysis, and reliability block diagrams (RBDs). These techniques are capable to model all the system requirements, and the developed replica is implicitly accepted by all the stakeholders. These techniques demonstrate the static properties of a system and fail while capturing the dynamic behavior. Dynamic reliability block diagrams (DRBDs), which are extension to RBDs provide a framework for modeling the dynamic behavior of SCS. However, the analysis of a DRBD model in order to locate and identify the critical aspects of reliability and safety such as nonliveness, deadlock, design errors, or faulty state, is not trivial when done manually. This paper presents a novel approach for model based verification for digital feedwater control system (DFWCS) of a nuclear power plant (NPP) by developing its formal model using DRBD and then analyzing it using colored Petri nets for full proof design. The techniques to improve the faulty design are also proposed. Finally this model is proved to be bounded and deadlock-free.

Background: The SARS-CoV-2 pandemic in India has adversely affected many aspects of population health. We need detailed evidence of the impact on reproductive health in India so that lessons can be learnt.Methods: Hospital-based repeated monthly survey of nine severe maternal complications and death in 15 hospitals across five states in India covering a total of 202,986 hospital births, December-2018 through to May-2021. We calculated incidence rates (with 95% Confidence Intervals (CIs)) per 1000 hospital births, case-fatality and rate ratios (RR) with 95% CIs. Linear regression was used to examine the association between the Government Response Stringency Index (GRSI) for India and changes in hospital births, incidence and case-fatality.Results: There was a significant decrease in hospital births per month during the pandemic period with a 4.8% decrease per 10% increase in the GRSI scores (p<0.001). The overall incidence of severe complications in the pandemic period was not significantly different from the pre-pandemic period, but hospital admissions from septic abortion was 56% higher (RR=1.56; 95% CI=1.22–1.99; p<0.001). The overall case-fatality of complications increased by 23% (RR=1.23; 95% CI=1.03–1.46; p=0.022) and remained high across the different phases of the pandemic with a notable significant increase in deaths from heart failure in pregnancy.Conclusion: Our study supports the legitimacy of the calls made to maintain sexual and reproductive health services as essential services during the pandemic. Lessons learnt should be used to avert the ongoing reproductive health crisis while India plans to manage a third wave of the pandemic.Funding Information: The MaatHRI platform and this study was funded by a Medical Research Council Career Development Award to MN (Ref:MR/P022030/1).Declaration of Interests: The authors declare that they have no competing interests.Ethics Approval Statement: The MaatHRI platform and the repeated monthly survey have been approved by the institutional review boards (IRB) of each coordinating Indian institution, namely: Srimanta Sankaradeva University of Health Sciences, Guwahati, Assam (No.MC/190/2007/Pt-1/126); Nazareth hospital, Shillong, Meghalaya (Ref No. NH/CMO/IEC/COMMUNICATIONS/18-01); Emmanuel Hospital Association, New Delhi (Ref. Protocol No.167); Mahatma Gandhi Institute of Medical Sciences, Sevagram, Maharashtra (Ref No. MGIMS/IEC/OBGY/118/2017); and the Institute of Medical Sciences, Banaras Hindu University, Varanasi, Uttar Pradesh (No.Dean/2018/EC/290). The project has also been approved by the Government of India's Health Ministry's Screening Committee, the Indian Council of Medical Research, New Delhi (ID number 2018-0152) and by the Oxford Tropical Research Ethics Committee (OxTREC), University of Oxford, UK (OxTREC Ref: 7-18).