Leveraging Artificial Intelligence to Reduce Human-Animal Conflict in India

The case focuses on the use of artificial intelligence (AI) and computer vision (CV) technologies to solve a socially complex issue of human-animal conflict in the geographical regions surrounding the Tadoba Andhari Tiger Reserve (TATR) in Maharashtra state in central India. Due to an increasing tiger population, the villages surrounding the TATR often encountered tigers that strayed outside the reserve, sometimes leading to injuries or fatalities either to the humans or the wild animals involved. Valiance, a technology company, collaborated with the Forest department and other local stakeholders to create a computer vision based AI virtual wall system as a pilot project. The technology solution monitored the location 24hrs a day 7 days a week and had the capability of identifying tigers, leopards, and other predators, and sending out automated, real time alerts to help prevent human-animal conflict situations. Based on the outcome of the pilot, the solution could be refined and then a wider rollout could be planned

Nano-vectors for efficient liver specific gene transfer

Recent progress in nanotechnology has triggered the site specific drug/gene delivery research and gained wide acknowledgment in contemporary DNA therapeutics. Amongst various organs, liver plays a crucial role in various body functions and in addition, the site is a primary location of metastatic tumor growth. In past few years, a plethora of nano-vectors have been developed and investigated to target liver associated cells through receptor mediated endocytosis. This emerging paradigm in cellular drug/gene delivery provides promising approach to eradicate genetic as well as acquired diseases affecting the liver. The present review provides a comprehensive overview of potential of various delivery systems, viz., lipoplexes, liposomes, polyplexes, nanoparticles and so forth to selectively relocate foreign therapeutic DNA into liver specific cell type via the receptor mediated endocytosis. Various receptors like asialoglycoprotein receptors (ASGP-R) provide unique opportunity to target liver parenchymal cells. The results obtained so far reveal tremendous promise and offer enormous options to develop novel DNA-based pharmaceuticals for liver disorders in near future

Garud Survey: A Case of Improving Safety and Transparency in Mining Operations Using Drone Technology

SAI Minerals Pvt. Limited (SAI Minerals), a renowned company engaged in mining cement-grade limestone and manufacturing cement in Rajasthan, India, has been grappling with recurring survey reconciliation and safety issues across its mining operations. Additionally, in compliance with new government regulations, they are now required to conduct aerial surveys and submit digital images and survey reports to the Indian Bureau of Mines (IBM). SAI Minerals sought a permanent solution to these challenges and approached Garud Survey Private Limited (Garud Survey), a technology-driven surveying agency. SAI Minerals recognized that these issues not only impacted their production but also tarnished the company\u27s reputation in the mining industry due to frequent accidents. Garud Survey recommended that the best approach to address the problem was to make the survey process faster and more accurate, enabling all stakeholders to have a clear and up-to-date view of the operational status. Garud Survey proposed the implementation of cutting-edge technology to identify and address the root cause of the problem. This case further explores the application of system analysis and design to the adoption and implementation of the latest technology in a real-world use case, as well as the challenges associated with managing change

Efficacy of vijaysar, aloevera alone and their combination in the treatment of newly diagnosed cases of type 2 diabetes mellitus: a randomized single blind prospective study

Background: Diabetes mellitus is a disease was known since ancient time and all system of medicine over world were tried to cure this disease. Unfortunately the numbers of diabetes patients are increasing day by day due to many risk factors such as sedentary life, obesity etc.Methods: A total of 120 patients with newly diagnosed type 2 diabetes mellitus attending OPD of UPUMS, Saifai, Etawah, Uttar Pradesh, India, were included in the study. Patients were divided into 4 groups. Group-1, 2, 3 and 4 received Aloevera, Vijaysar, Aloevera + Vijaysar and Glimepiride respectively for thirteen weeks. Sample for fasting blood sugar and postprandial blood sugar were measured at baseline, 1st, 2nd, 3rd, 5th, 8th and at 13th week. HbA1c and Lipid profile were measured at baseline and at thirteen week.Results: Significant decrease in FPG, 2hPG, and HbA1c level were achieved in all groups but effects was maximum in Glimepiride group. Vijaysar had shown better glucose control than Aloevera as well as Aloevera + Vijaysar group. Synergism was shown by both herbal drugs for FPG control but not for 2hPG. The Effect of Vijaysar alone on 2hPG was similar to Glimepiride.Conclusions: Vijaysar could be a promising herbal drug for the treatment of mild uncomplicated cases of type-2 diabetes mellitus; however both drugs have shown synergism for FPG control. Both herbal drugs were safe during our study, only one patient of Vijaysar group had complaint of diarrhoea, which was subsided one week later

Evaluation of antidepressant and analgesic activity of tapentadol with mirtazapine: an experimental study

Background: Data comparing tapentadol with an antidepressant is limited. A comparison of tapentadol with mirtazapine at different dose has not been performed, the other antidepressant in the same therapeutic class with a significant market share, has been undertaken. In the absence of relevant data to assess the place that tapentadol should occupy in the therapeutic arsenal, indirect comparisons are the most rigorous way to go. We conducted a study evaluate antidepressant and analgesic activity of tapentadol with mirtazapine at different doses in Swiss albino mice.Methods: Tapentadol was administered at 10, 20 and 40 mg/kg (i.p) once daily for 14 days to swiss albino mice of either sex. The immobility period for antidepressant activity of mice were recorded in forced swim test and reaction time for analgesic activity of mice were recorded in tail flick test of the control and drug treated group. The antidepressant and analgesic activity of tapentadol (10, 20, 40 mg/kg i.p) was compared with that of mirtazapine (3, 5, 7 mg/kg i.p), administered for 14 days.Results: Tapentadol produced better antidepressant at (20, 40 mg/kg), but less at 10 mg/kg and significant analgesic activity at all the three doses, as indicated by reduction in immobility times and increase in reaction time as compared to control. Mirtazapine produced no antinociceptive activity at 3 mg/kg, but significant at 5, 7 mg/kg and showed better antidepressant activity at all the three doses in mice. The result of this study indicates the better analgesic activity of tapentadol at all the doses and least antidepressant activity at 10 mg/kg, as compared to mirtazapine which has shown better antidepressant activity at all the three doses but no analgesic activity at 3 mg/kg.Conclusion: It can be concluded that tapentadol is a better drug in case of depression associated with pain compared to mirtazapine in mice

Cefuroxime axetil induced glossitis: a case report

Cefuroxime axetil is a semi synthetic cephalosporin antibiotic, which is prescribed for different types of infections such as lung, ear, throat, urinary tract, and skin. This is the drug of choice in the treatment and prevention of streptococcal infections. In this case, the patient was prescribed cefuroxime axetil, diclofenac, and paracetamol for pharyngitis. The patient developed glossitis 3 hrs after ingestion of above drugs which improved after withdrawing the offending drug. Glossitis is an uncommon, but serious adverse drug effect of cefuroxime axetil. It is important to recognize and manage it to prevent fatality. The case has been reported to the Pharmacovigilance Center Uttar Pradesh Rural Institute of Medical Sciences and Research Saifai, Etawah

Early detection and prediction of cardiotoxicity after radiation therapy for breast cancer: the BACCARAT prospective cohort study

International audienceBackground Radiotherapy (RT) for breast cancer presents a benefit in terms of reducing local recurrence and deaths resulting from breast cancer but it can lead to secondary effects due to the presence of neighboring cardiac normal tissues within the irradiation field. Breast RT has been shown to be associated with long-term increased risk of heart failure, coronary artery disease, myocardial infarction and finally cardiovascular death more than 10 years after RT. However, there is still a lack of knowledge for early cardiotoxicity induced by breast RT that can appear long before the onset of clinically significant cardiac events. Based on a 2-year follow-up prospective cohort of patients treated with breast RT, the BACCARAT (BreAst Cancer and CArdiotoxicity Induced by RAdioTherapy) study aims to enhance knowledge on detection and prediction of early subclinical cardiac dysfunction and lesions induced by breast RT and on biological mechanisms potentially involved, based on functional and anatomical cardiac imaging combined with simultaneous assessment of multiple circulating biomarkers and accurate heart dosimetry. Methods/Design BACCARAT study consists in a monocentric prospective cohort study that will finally include 120 women treated with adjuvant 3D CRT for breast cancer, and followed for 2 years after RT. Women aged 50 to 70 years, treated for breast cancer and for whom adjuvant 3D CRT is indicated, without chemotherapy are eligible for the study. Baseline (before RT) and follow-up data include measurements of functional myocardial dysfunction including strain and strain rate based on 2D-speckle tracking echocardiography, anatomical coronary lesions including description of plaques in segments of coronary arteries based on Coronary computed tomography angiography, and a wide panel of circulating biomarkers. The absorbed dose is evaluated for the whole heart and its substructures, in particular the coronary arteries. Analysis on occurrence and evolution of subclinical cardiac lesions and biomarkers will be performed and completed with dose-response relationship. Multivariate model of normal tissue complication probability (NTCP) will also be proposed. Discussion Tools and results developed in the BACCARAT study should allow improving prediction and prevention of potential lesions to cardiac normal tissues surrounding tumors and ultimately enhance patients' care and quality of life. Trial registration ClinicalTrials.gov NCT02605512. © 2016 Jacob et al

Enhancing Financial Management Efficiency through Advanced Prediction Modeling and Data-Driven Decision-Making Strategies

Efficient financial management depends on the ability to precisely forecast financial risks, frequently insolvency, which directly impacts strategic planning and resource allocation. However, many existing prediction models struggle to process complex, multivariate financial data, which limits their efficiency in presenting actionable understanding for proactive decision-making. To address this challenge, this research offers an advanced predictive modeling framework based on the Intelligent Grey Wolf Optimized Deep Residual Neural Network (IGWO-DRNN), which incorporates deep learning (DL) with nature-inspired optimization to improve insolvency prediction and financial management efficacy. The research initiates with comprehensive data preprocessing, including normalization. Independent Component Analysis (ICA) is working for feature extraction, modifying complex financial variables into numerically independent components to uncover hidden patterns within the data. The predictive core is the IGWO-DRNN, incorporating the learning ability of deep residual networks with the global optimization strength of the Intelligent Grey Wolf Optimizer (IGWO) to efficiently model nonlinear relationships within financial datasets and avoid local minima during training. The entire implementation is created in Python and its machine-learning (ML) libraries, certifying computational flexibility and scalability. The proposed IGWO-DRNN model achieves a high R² (0.498) with reduced MSE (0.014), MAE (0.078), and RMSE (0.120). The IGWO-DRNN cruciallyimproves both predictive accuracy and computational efficiency. This intelligent framework contributes modern financial management by enabling timely, reliable, and data-driven forecasts, supporting proactive risk mitigation and strategic decision-making