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Abstract In India, the spatial coverage of air pollution data is not homogeneous due to the regionally restricted number of monitoring stations. In a such situation, utilising satellite data might greatly influence choices aimed at enhancing the environment. It is essential to estimate significant air contaminants, comprehend their health impacts, and anticipate air quality to safeguard public health from dangerous pollutants. The current study intends to investigate the spatial and temporal heterogeneity of important air pollutants, such as sulphur dioxide, nitrogen dioxide, carbon monoxide, and ozone, utilising Sentinel-5P TROPOMI satellite images. A comprehensive spatiotemporal analysis of air quality was conducted for the entire country with a special focus on five metro cities from 2019 to 2022, encompassing the pre-COVID-19, during-COVID-19, and current scenarios. Seasonal research revealed that air pollutant concentrations are highest in the winter, followed by the summer and monsoon, with the exception of ozone. Ozone had the greatest concentrations throughout the summer season. The analysis has revealed that NO2 hotspots are predominantly located in megacities, while SO2 hotspots are associated with industrial clusters. Delhi exhibits high levels of NO2 pollution, while Kolkata is highly affected by SO2 pollution compared to other major cities. Notably, there was an 11% increase in SO2 concentrations in Kolkata and a 20% increase in NO2 concentrations in Delhi from 2019 to 2022. The COVID-19 lockdown saw significant drops in NO2 concentrations in 2020; specifically, − 20% in Mumbai, − 18% in Delhi, − 14% in Kolkata, − 12% in Chennai, and − 15% in Hyderabad. This study provides valuable insights into the seasonal, monthly, and yearly behaviour of pollutants and offers a novel approach for hotspot analysis, aiding in the identification of major air pollution sources. The results offer valuable insights for developing effective strategies to tackle air pollution, safeguard public health, and improve the overall environmental quality in India. The study underscores the importance of satellite data analysis and presents a comprehensive assessment of the impact of the shutdown on air quality, laying the groundwork for evidence-based decision-making and long-term pollution mitigation efforts.

Objective. To compare the adequacy, agreement, and acceptability of Papanicolaou testing (cytology) for cervical cancer screening using self-collected samples compared to physician-collected samples in Grenada in the Caribbean. Furthermore, the study identifies the human papillomavirus (HPV) genotypes present among asymptomatic women testing positive for HPV, the etiologic cause of cervical cancer. Methods. Participants were divided into two groups and two cervical samples were collected from the women in each group: a self-collected sample and a physician-collected sample. Cervical specimens were tested for cytology and HPV. HPV genotyping was performed on positive specimens. Results. Self-collected samples were adequate and in agreement with physician-collected samples, showing no difference between the two sampling methods. Oncogenic high-risk HPV genotypes were identified in cervical samples which were positive for atypical squamous cells and low-grade squamous intraepithelial lesions. The high-risk HPV genotypes found, notably HPV 45 and 53, differed from those most commonly reported. Although the commonly reported high-risk genotypes HPV 16 and 18 were found, so were 31, 33, 35, 52, 66, 68, and 82. Conclusions. Using self-collection facilitated the discovery of unexpected HPV genotypes among asymptomatic women in Grenada. These findings add new information to the literature regarding cervical cancer and neoplasia screening and HPV genotypes in the Caribbean. This genotype information may impact surveillance of women with low-grade lesions, HPV vaccine selection, and possibly further vaccine research. Research regarding HPV in Caribbean pathology samples of cervical neoplasia and cancer is needed.

Background: Inflammatory bowel diseases (IBD) require effective colon-targeted drug delivery for improved therapeutic efficacy and minimized systemic side effects. Objectives: The objective of this research was to develop and evaluate novel colon-targeted matrix tablet formulations of mesalamine (5-aminosalicylic acid) for the treatment of IBD. Materials and Methods: Mesalamine matrix tablets were prepared by wet granulation technique using pH-sensitive polymers (HPMC K4M) and biodegradable natural polysaccharides (pectin, chitosan, and guar gum). Tablets were characterized for physicochemical properties, drug content, and in vitro drug release. Compatibility studies using FTIR and DSC confirmed no interaction between mesalamine and polymers. The optimized formulations were enteric-coated with Eudragit S100 and ethyl cellulose. Drug release kinetics and stability studies were conducted. Results and Discussion: The uncoated formulations (M3, M6, M7) showed adequate protection against drug release in simulated gastric (0-2 h) and intestinal (2-5 h) fluids. The enteric-coated formulations (ME3, ME6, ME7) exhibited a lag time of around 2 hours and restricted drug release (

Despite facing many challenges, the exploration of using natural forces and mechanisms besides gravity to enhance particle settling has never ceased. A novel particle separator design, which utilizes multiple vortexes to enhance particle settling, was proposed in this study. The basic principle is using the fluid's energy to generate small swirling currents in a specially designed vortex claw generator. These currents bring suspended particles from the rapid and turbulent inflow to relatively quiet water regions, separating them from the main flows and reducing their travel distance to the wall. To verify the new separator design's performance, comparison studies were carried out in the laboratory using physical models. The results showed that the new design had much higher particle capture rates for the same inflow rates and tested particle sizes. Most importantly, it was able to effectively remove small particles, and particle capture rates were much less affected by fluctuations in inflow rates. Since most existing particle separators failed to perform well under large inflow rates, these characteristics make the new design stand out from other separators. Due to its special structure, its treatment capacity can also be easily increased without changing its horizontal separator size. HIGHLIGHTS Enhance solid–liquid separation with a novel method.; Utilizing vortexes generated by inflows to collect suspended particles.; In contrast to most solid–liquid separators, it can remove small particles more effectively at high flow rates.; Particle capture rates are much less affected by fluctuations in inflow rates.; With the same footprint, treatment capacity can be easily increased.;

Abstract Invasive alien species (IAS) pose a severe threat to global agriculture, with their impact projected to escalate due to climate change and expanding international trade. The fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), a native of the Americas, has rapidly spread across various continents, causing significant damage to several food crops, especially maize. Integrated pest management (IPM) programs are vital for sustainable FAW control, combining multiple strategies for sustainable results. Over three consecutive years, 2019–20, 2020–21 and 2021–22, the field demonstrations were conducted in semiarid regions of India, testing a four-component IPM approach viz., pheromone traps, microbial, botanicals and ETL based applications of insecticides against farmers' practices (sole insecticide application). IPM implementation led to substantial reductions in FAW infestation. Furthermore, egg mass and larvae infestations were significantly lower in IPM-adopted villages compared to conventional practices. Pheromone-based monitoring demonstrated a consistent reduction in adult moth populations. The lowest technology gap (10.42), extension gap (8.33) and technology index (12.25) was recorded during 2020–21. The adoption of IPM led to increased maize yields (17.49, 12.62 and 24.87% over control), higher net returns (919, 906.20 and 992.93 USD), and favourable benefit–cost ratios (2.74, 2.39 and 2.33) compared to conventional practices respectively during 2019–20, 2020–21 and 2021–22. The economic viability of IPM strategies was evident across three consecutive years, confirming their potential for sustainable FAW management in the semiarid region of India. These strategies hold promise for adoption in other parts of the world sharing similar climatic conditions.

Introduction: Temporomandibular Joint Disorders (TMDs) are considered multifactorial, and several treatment approaches have been proposed for their effective management. The use of non invasive treatment modalities is recommended, which includes Transcutaneous Electric Nerve Stimulation (TENS), Low-Level Laser Therapy (LLLT), acupuncture, ultrasound, and manual therapies. Aim: To evaluate the effectiveness of TENS, LLLT, and ultrasound therapy in patients suffering from TMDs. Materials and Methods: This prospective, randomised clinical trial was conducted on thirty patients (11 males, 19 females) clinically diagnosed with TMD associated with Temporomandibular Joint (TMJ) pain, clicking joint sound, pain in the muscles of mastication, and limited mouth opening. Patients were sequentially randomised into three groups to be treated with TENS, laser beam, and ultrasound therapies, respectively. The Visual Analog Scale (VAS) Score and pain-free mouth opening were recorded before, during, and after treatment. Data were analysed using Statistical Package for Social Sciences(SPSS) version 16.0 statistical software. Statistical tests such as the paired sample t-test, Analysis of Variance (ANOVA), and post-hoc Tukey test were performed. Results: There was a significant reduction in the VAS score in the TENS group (3.15), LLLT group (5.75), and ultrasound group (5.50) post-treatment (p

In recent years, there has been a growing interest in using artificial intelligence (AI) for rainfall-runoff modelling, as it has shown promising adaptability in this context. The current study involved the use of six distinct AI models to simulate monthly rainfall-runoff modelling in the Bardha watershed, India. These models included the artificial neural network (ANN), k-nearest neighbour regression model (KNN), extreme gradient boosting (XGBoost) regression model, random forest regression model (RF), convolutional neural network (CNN), and CNN-RNN (convolutional recurrent neural network). The years 2003–2007 are classified as the calibration or training period, while the years 2008–2009 are classified as the validation or testing period for the span of time 2003 to 2009. The available rainfall, maximum and minimum temperatures, and discharge data were collected and utilized in the models. To compare the performance of the models, five criteria were employed: R2, NSE, MAE, RMSE, and PBIAS. The CNN-RNN model simulates the rainfall-runoff model in the Bardha watershed best in both the training and testing periods (training: R2 is 0.99, NSE is 0.99, MAE is 1.76, RMSE is 3.11, and PBIAS is −1.45; testing: R2 is 0.97, NSE is 0.97, MAE is 2.05, RMSE is 3.60, and PBIAS is −3.94). These results demonstrate the superior performance of the CNN-RNN model in simulating monthly rainfall-runoff modelling when compared to the other models used in the study. The findings suggest that the CNN-RNN model could be a valuable tool for various applications related to sustainable water resource management, flood control, and environmental planning.

In light of the adverse prognosis related to severe mitral regurgitation, heart failure, or sudden cardiac death in a subset of patients with mitral valve prolapse (MVP), identifying those at higher risk is key. For the first time in decades, researchers have the means to rapidly advance discovery in the field of MVP thanks to state-of-the-art imaging techniques, novel omics methodologies, and the potential for large-scale collaborations using web-based platforms. The National Heart, Lung, and Blood Institute recently initiated a webinar-based workshop to identify contemporary research opportunities in the treatment of MVP. This report summarizes 3 specific areas in the treatment of MVP that were the focus of the workshop: 1) improving management of degenerative mitral regurgitation and associated left ventricular systolic dysfunction; 2) preventing sudden cardiac death in MVP; and 3) understanding the mechanisms and progression of MVP through genetic studies and small and large animal models, with the potential of developing medical therapies.

Introduction: A common surgical technique for gallbladder disorders is laparoscopic cholecystectomy (LC), which has the benefits of less postoperative discomfort and quicker recovery. The purpose of this retrospective research was to assess postoperative outcomes and complications in patients having laparoscopic correction. Methods: In total, 200 patients who had LC at the tertiary care center between 2017 and 2022 were the subjects of a retrospective investigation. We gathered and examined data on preoperative conditions, surgical specifics, postoperative results, and demographics. Results: Notable findings from the study were as follows: (1) The average age of the patients was 47.5 years (±12.3), and there were strong correlations (P < 0.001) between age and problems. (2) Significant correlations were found between many covariates and postoperative outcomes, such as a 10% readmission rate and a mean hospital stay of 3.6 days (±1.2) (P < 0.05). (3) Different relationships were seen between the complications (P values ranging from 0.021 to

IntroductionAI technologies have the potential to transform patient care. AI has been used to aid in differential diagnosis and treatment planning for psychiatric disorders, administer therapeutic protocols, assist with interpretation of cognitive testing, and patient treatment planning. Despite advancements, AI has notable limitations and remains understudied and further research on its strengths and limitations in patient care is required. This study explored the responses of AI (Chat-GPT 3.5) and trained clinicians to commonly asked patient questions.MethodsThree clinicians and AI provided responses to five dementia/geriatric healthcare-related questions. Responses were analyzed by a fourth, blinded clinician for clarity, accuracy, relevance, depth, and ease of understanding and to determine which response was AI generated.ResultsAI responses were rated highest in ease of understanding and depth across all responses and tied for first for clarity, accuracy, and relevance. The rating for AI generated responses was 4.6/5 (SD = 0.26); the clinician s' responses were 4.3 (SD = 0.67), 4.2 (SD = 0.52), and 3.9 (SD = 0.59), respectively. The AI generated answers were identified in 4/5 instances.ConclusionsAI responses were rated more highly and consistently on each question individually and overall than clinician answers demonstrating that AI could produce good responses to potential patient questions. However, AI responses were easily distinguishable from those of clinicians. Although AI has the potential to positively impact healthcare, concerns are raised regarding difficulties discerning AI from human generated material, the increased potential for proliferation of misinformation, data security concerns, and more.

The major problems in an underwater wireless optical communication (UWOC) link are turbulence induced fading and pointing errors. In this paper, we have investigated the bit error rate (BER) performance of spatially coupled low-density parity-check (SC-LDPC) coded horizontal UWOC link over a strong turbulent channel model with pointing errors. The performance of this link for different channel and code parameters has been studied using simulations. It has been observed that a rate 1/2 ARJA protograph based SC-LDPC code with graph lifting factor of 256 gives a coding gain of 47 dB at a BER of ${10}^{-4}$ for strong turbulence channel model with pointing errors. An analytical BER expression for an uncoded UWOC link under strong turbulence with pointing errors for the On-Off Keying modulation technique has been derived. A multidimensional protograph based extrinsic information transfer algorithm has been developed to obtain the decoding thresholds for different channel parameters and code rates. We have also studied the SC-LDPC coded vertical UWOC link performance for some specific strong turbulence channel parameters with pointing errors and observed that as the link length increases from $20 m$ to $40 m$ , the performance gap between the hypothetical and cascaded channel models increases from $1.1 dB$ to $5.5 dB$ .

Introduction: Studies investigating the alterations of serum irisin and its change with metformin therapy in patients with polycystic ovary syndrome (PCOS) are conflicting. Our aim is to study serum irisin in PCOS patients and the change of irisin levels with metformin therapy over 6 months. Methods: This is a randomized control study conducted in 187 PCOS cases and 94 age-matched controls aged 18–40 years. Detailed evaluation of anthropometric, biochemical, and hormonal parameters was performed. A subset of 99 overweight/obese patients with body mass index (BMI) ≥23 kg/m2 were stratified into a metformin group (n = 67) receiving 500 mg thrice daily and a lifestyle intervention-only group (n = 32). The effect of metformin therapy on serum irisin levels was measured at the end of 6 months. Statistical analyses were performed with SPSS version 26.0 Software. Results: Serum irisin was higher in PCOS patients than in controls [12.47 (8.1–17.7) vs 8.3 (7.0–9.6) ng/ml, P < 0.001], independent of BMI. Serum irisin showed a significant positive association with BMI (β =0.168), waist-to-hip ratio (β =0.166), leutinizing hormone (β =0.225), TG (β =0.305), FAI (β =0.151), and testosterone (β =0.135). Serum irisin showed a significant positive association with homeostatic model assessment of insulin resistance (HOMA-IR) (β =0.14, P = 0.04) in overweight/obese PCOS patients only (n = 146) but not in the whole PCOS cohort (n = 187). Metformin reduced the median serum irisin levels significantly (13.9 to 12.1 ng/ml, P < 0.001), and the delta change in irisin levels was associated with HOMA-IR in the metformin group. Conclusion: Serum irisin is increased in PCOS patients independent of BMI. Metformin therapy reduced serum irisin levels in overweight/obese PCOS patients by improving insulin resistance.

The analysis of morphometric parameters plays a crucial role in understanding and managing watersheds, making it a fundamental component of hydrological investigations. This review paper talks about how important it is to objectively evaluate morphometric parameters, with a focus on the evaluation of basins' relief, linear, and areal parameters. However, it is noted that there is a lack of a distinct standard classification and implication for each parameter in some research publications. Furthermore, the range and categories of values for each morphometric parameter have not been adequately addressed in previous studies. Many papers state whether a particular parameter's resultant value is high or low without providing specific value ranges or associated implications. Also, it is emphasised that the accuracy and sources of digital elevation models (DEMs) affect how well morphometric parameter analysis works, even when DEMs with the same resolution are used. The existing literature demonstrates that determining the value of each morphometric parameter poses significant challenges. Moreover, verifying the first and second Horton's laws and assessing the correlations between morphometric parameters have been lacking in some articles. The main objective of this review article is to address these gaps by providing an in-depth study of each parameter's categorization, including the range of values, the level of input data quality, the data products generated, and the applicability of the fundamental Horton's laws. By doing so, this review aims to enhance the understanding of morphometric parameters, their value ranges, and the significance of their application in watershed analysis and management.

Objective: The in utero no flow/no grow hypothesis postulates that reduced inflow of blood into the left ventricle due to a stenotic mitral valve could lead to ventricular hypoplasia and hypoplastic left heart syndrome. This has been demonstrated in chick embryos, but less so in large animals. We investigated the impact of mitral obstruction on left and right ventricular growth in fetal lambs. Methods: Twelve pregnant ewes, most bearing twins, were instrumented at 119 ± 1 days gestational age. Carotid artery and jugular vein catheters, an ascending aorta flow probe, and a left atrial deflated balloon catheter were implanted into 1 fetus (left atrial balloon group), and the twin remained an uninstrumented control. The balloon was inflated gradually over 8 days until net antegrade aortic flow was eliminated. Fetal transesophageal echocardiography was performed at the time of surgery and just before termination in both groups. Results: Terminal fetal body weights were comparable between groups. Terminal heart/body weight ratio was higher in left atrial balloon group fetuses (6.9 ± 0.8 g/kg) compared with controls (5.9 ± 0.6 g, P = .0126). The left ventricular/right ventricular weight ratio was 24% (P = .0077) lower in left atrial balloon group fetuses than in controls. Left ventricular/heart weight (0.24 ± 0.04 g/g vs 0.30 ± 0.04 g/g, P = .0009), left ventricular end-diastolic volume (2.3 ± 0.7 mL vs 7.1 ± 0.8 mL; P = .0012), and left ventricular end-systolic volume (1.01 mL [0.95-1.95 mL] vs 3.38 mL [3.28-3.57 mL], P = .0042) were lower in left atrial balloon group fetuses compared with controls. Right ventricular weight (g/kg), right ventricular end-diastolic volume, and right ventricular end-systolic volume were similar between groups. Conclusions: In this late-gestation fetal lamb model, in utero obstruction of mitral inflow slowed left ventricular growth and caused right ventricular remodeling.

Background/Aims: With the increasing demand for inpatient beds on the NHS, we need to ensure that patients are being admitted only if necessary for long term conditions including rheumatic diseases. We wanted to determine whether the length of inpatient stays for patients could be reduced and whether they could have been managed differently on an outpatient basis.This study's aim is to evaluate the inpatient stay of patients with rheumatic diseases admitted to Basildon University Hospital. Methods: This is a retrospective review of medical records of 94 patients admitted at Basildon Hospital between May 2022 to July 2022. We evaluated patient details, including age, sex, their primary medical and rheumatological diagnoses, care they received, and the circumstances surrounding their hospital admission. We also tried to determine how many of these inpatients could be treated as outpatients. Results: Of 94 patients, 51% were males, their age ranged from 21 to 94 years (median 66 years). Commonest age group was 80–89 years comprising 22% of patients. Maximum number of inpatients stayed equally between 2–7 days and 15 to 30 days occupied 22 % each. The inpatient stay varied from 1 to 149 days with 13% patients staying more than 30 days. Most common indication of long-term hospital stays were social problems 38%. frailty 31% and infections 31%. The primary reason for admission was rheumatological in 42% of patients and medical in 55% of patients. There was no data available for 3%. The rheumatological reasons included GCA 32%, joint Swelling/pain 22%, vasculitis 14%, crystal arthropathy 14%, PMR 13% and drug reactions 5%. Medical reasons included infections 24%, falls 18%, neurology/strokes 14%, respiratory (Non-infectious & SOB) 11%, Oncology (meningioma/frontal lode tumour/RCC) 5% and others. Treatment from rheumatology team during admission was steroids 36%, DMARDS 23%, joint injections 10%, NSAIDS 2%, IVIG 3% etc. Rest of the patients (26%) were under investigation for diagnosis. After evaluation it was felt that 39% of these patients could have been managed on outpatient basis and 58% required inpatient care. Conclusion: This audit shows that 39% of admitted patients with rheumatological complaints can be managed on an outpatient basis. The concept of emergency or hot clinics as outpatient may be an efficient alternative for these patients.

Introduction: This study aimed to distinguish isolated hypogonadotropic hypogonadism (IHH) from constitutional delay in growth and puberty (CDGP) by various hormonal tests in both sexes. Methods: Boys with testicular volume (TV)

Rainfall–runoff (R–R) analysis is essential for sustainable water resource management. In the present study focusing on the Peddavagu River Basin, various modelling approaches were explored, including the widely used Soil and Water Assessment Tool (SWAT) model, as well as seven artificial intelligence (AI) models. The AI models consisted of seven data-driven models, namely support vector regression, artificial neural network, multiple linear regression, Extreme Gradient Boosting (XGBoost) regression, k-nearest neighbour regression, and random forest regression, along with one deep learning model called long short-term memory (LSTM). To evaluate the performance of these models, a calibration period from 1990 to 2005 and a validation period from 2006 to 2010 were considered. The evaluation metrics used were R2 (coefficient of determination) and NSE (Nash–Sutcliffe Efficiency). The study's findings revealed that all eight models yielded generally acceptable results for modelling the R–R process in the Peddavagu River Basin. Specifically, the LSTM demonstrated very good performance in simulating R–R during both the calibration period (R2 is 0.88 and NSE is 0.88) and the validation period (R2 is 0.88 and NSE is 0.85). In conclusion, the study highlighted the growing trend of adopting AI techniques, particularly the LSTM model, for R–R analysis. HIGHLIGHTS The study used SWAT and seven AI models for the Peddavagu River Basin.; LSTM performed well in simulating R–R during calibration (R2 is 0.88 and NSE is 0.88) and validation (R2 is 0.88 and NSE is 0.85).; These models are valuable for sustainable water management in the Peddavagu River Basin.;

Despite controversy about the efficacy and safety of aducanumab, the FDA's fast-tracking of this medicine is truly historic. However, structural problems leading to socioeconomic disparities and systemic racism in science, healthcare, and society have left out under-represented populations. This perspective outlines the racial and socioeconomic health disparities in aducanumab treatment: 1) Disparities in the risk of Alzheimer's disease (AD), 2) Limited participation from under-represented groups in AD trials raising concerns about the generalizability of the results, 3) Questionable applicability of the amyloid hypothesis in groups under-represented in AD research, and 4) Aducanumab's initial sticker price that unfairly singled out those with lower socioeconomic backgrounds. Potential solutions are discussed.

The sustainable management of groundwater resources is crucial for ecological diversity, human health, and economic growth. This study employs scientific concepts and advanced techniques, including the analytic hierarchy process (AHP) and Fuzzy-AHP, to identify groundwater potential zones (GWPZs). Thematic maps representing drainage density, elevation, soil, geomorphology, slope, land use and land cover, and rainfall are used to delineate the GWPZs. Both techniques are employed to assign weights to these thematic maps based on their characteristics and water potential. The study revealed that in the investigated area, 17.76 and 18.27% of the final GWPZs (AHP and Fuzzy-AHP) can be classified as having poor potential, while 72.79 and 71.07% are categorized as having moderate potential. Moreover, 9.45 and 10.69% of the final GWPZs are identified as having high potential using the AHP and Fuzzy-AHP models, respectively. Receiver operating characteristics (ROCs) analysis is employed to validate these findings, demonstrating that the Fuzzy-AHP technique achieves an accuracy of 74% in identifying GWPZs in the region. This study utilizes the best method derived from both models to identify 26 suitable locations for artificial recharge sites. The reliable findings of this research offer valuable insights into decision-makers and water users in the Kinnerasani Watershed. HIGHLIGHTS The novel Fuzzy-AHP method for identifying GWPZs.; Suitable locations for artificial recharge sites were determined by selecting the best model between AHP and Fuzzy-AHP.; The obtained results are valuable for making informed decisions and facilitating sustainable groundwater management planning.;