Explosive Remnants of War: A War after the War?

Explosive Remnants of War (ERW) pose significant humanitarian problems to the civilians as well as to the governments in post conflict situations. People continue to be at risk even after the war due to the presence of ERW. The issue of ERW has in fact shifted the focus of the international community from the immediate impacts of the weapons to their long term effects. In response to this, states concluded a landmark agreement, Protocol V to the UN Convention on Certain Conventional Weapons in 2003 (CCW). This Protocol aims at providing a proper mechanism to deal with ERW threat. Meanwhile, with the beginning of the new century and the emergence of newly sophisticated weapons the debate over the ERW got shifted to one of the most menacing category of weapons called cluster munitions. Again, responding to the problem, the state parties adopted the Convention of Cluster Munitions 2003 which bans the use and development of these deadly weapons. Both these instruments suffer from certain inherent limitations. Despite these limitations they still serve as the last resort for the civilians as well as for the governments of the war torn communities in dealing with the catastrophic effects of ERW

Speed Control of DC Motor using Pid Controller Based on Matlab

This paper is to design PID controller to supervise and control the speed response of the DC motor and MATLAB program is used for calculation and simulation PID controllers are widely used in a industrial plants because of their simplicity and robustness. Industrial processes are subjected to variation in parameters and parameter perturbations. We are choosing PID parameters and discussed Key words: DC motor, PID controller, MATLAB representatio

Right sided infective endocarditis: a forgotten complication of septic abortion

Right-sided native valve infective endocarditis (IE) refers to IE involving the tricuspid or pulmonic valve. In developing countries, septic abortion is still prevalent due to instrumental delivery by untrained personnel. We report a case of a 22-year-old lady with right-sided IE and pulmonary septic embolization complicating septic abortion. The patient was treated with IV antibiotics, however, she succumbed to the illness following worsening respiratory distress and cardiac arrest

An unusual case of hypopituitarism

Lymphocytic hypophysitis represents a difficult diagnostic and therapeutic challenge. The clinical presentation of this inflammatory condition may mimic that of a pituitary adenoma with apoplexy. We report a case of a 45 years old male patient with acute adrenal crisis complicating chronic hypopituitarism secondary to lymphocytic hypophysitis. The patient was managed acutely with high dose steroids and supportive measures, and is currently doing well

Influence of welding parameters on mechanical property during friction stir welded joint on aluminium alloys: a review

The friction stir welding (FSW) is widely used in the fabrication of Aluminium alloy and other non-ferrous alloy. It has good potential to be used in major industries such as automobiles, aerospace, shipbuilding and can be used in the joining of high strength alloys. The FSW process low distortion and heat affected zone (HAZ) with fine recrystallized microstructure which leads to better mechanical properties at the weld zone and produces great stability. In this study, the different FSW parameters such as weld speed, tool rotation speed, tool tilt angle, feed per min has been discussed. The different types of tool pin profile and shoulder have also been discussed and their impacts on mechanical and microstructural properties at welded joints. Among various welding parameters the rotational speed is the most influencing parameter in FSW. Increasing the rotational speed exhibits the increase at tensile strength and is supposed to improve the mechanical properties. The most affected tool pin profile would be considered to be tapered threaded cylindrical pin profile which makes the adequate mixing of material with better flow ability and provide the fine grains at nugget zone. Comparing the FSW with other arc welding processes, it shows a wide range of environmental benefits which are noticeable such as saving in consumable materials, decrease in consumption of filler material and reduction in grinding wastes. Harmful emissions created from arc welding causes a health hazard to the welder. For achieving the high joint-strength for aerospace aluminium alloys and high temperature sustainable metallic alloys, friction stir welding will be preferred

Secondary Metabolites of <em>Brassica juncea</em> (L.) Czern and Coss: Occurence, Variations and Importance

There are numerous secondary plant metabolites found in the crop B. juncea, especially glucosinolates. Isothiocyanates, the by-products of glycosinolate breakdown, are beneficial to human health. A number of studies have also called attention to phenolic compounds and carotenoids, both well known for their anti-oxidant properties. A notable feature is that the profiles and concentrations of secondary plant metabolites vary greatly between varieties and that genetic factors are thought to be the most significant factors. In addition, environmental and agronomic factors have also been noted to change the concentrations of secondary plant metabolites. Secondary plant metabolites are primarily produced for defense purposes. Consequently, the intrinsic quality of Indian mustard, including color, aroma, taste, and medicinal properties, is profoundly influenced by its secondary metabolite profile. The health benefits of glycosinolates and the cancer prevention properties of their breakdown products make them of specific interest. Plant cells that have been injured undergo enzymatic decomposition of glucosinolate by endogenous enzymes such as myrosinase, which releases degradation products such as nitriles, epithionitriles, or isothiocyanates. The main phenolic compounds found in B. juncea are flavonoids and hydroxycinnamic acid derivatives. A diverse secondary metabolite pool is also essential for plant-environment interactions

Smart Credit Card Approval Prediction System using Machine Learning

This project focuses on automating the credit card application assessment process using advanced machine learning techniques, including Random Forest, Gradient Boosting, SVMs, Logistic Regression, Regularization Methods, and Hyperparameter Tuning. The objective is to improve the efficiency, accuracy, and fairness of credit card approval decisions. Historical credit card application data, comprising applicant demographics, financial history, and employment details, is collected and pre-processed. Feature engineering and exploratory data analysis (EDA) enhance the dataset’s predictive power. Three machine learning algorithms, Random Forest, Logistic Regression, and Gradient Boosting are applied. Regularization techniques (L1 and L2) and hyperparameter tuning are used to prevent overfitting and optimize model performance. The project assesses model performance by employing metrics such as accuracy, precision, recall, F1-score, and ROC-AUC metrics, and conducts feature importance analysis to identify key factors influencing approval decisions. The project aims to deliver robust, accurate, and fair credit card approval models, benefitting both financial institutions and applicant

Remote Sensing for Agricultural Applications

The application of remote sensing in quantifying the crop health status is trending. Sensors can serve as early warning systems for countering climatic or biological aberrations before having negative impacts on crop yield. Remote sensing applications have been playing a significant role in agriculture sector for evaluating plant health, yield and crop loss (%) estimation, irrigation management, identification of crop stress, weed and pest detection, weather forecasting, gathering crop phenological informations etc. Forecast of crop yields by using remote sensing inputs in conjunction with crop simulation models is getting popular day by day for its potential benefits. Remote sensing reduces the amount of field data collection and improves the precision of the estimates. Crop stress caused by biotic and abiotic factors can be monitored and quantified with remote sensing. Monitoring of vegetation cover for acreage estimation, mapping and monitoring drought condition and maintenance of vegetation health, assessment of crop condition under stress prone environment, checking of nutrient and moisture status of field, measurement of crop evapotranspiration, weed management through precision agriculture, gathering and transferring predictions of atmospheric dynamics through different observational satellites are the major agricultural applications of remote sensing technologies. Normalized difference vegetation index (NDVI), vegetation condition index (VCI), leaf area index (LAI), and General Yield Unified Reference Index (GYURI) are some of the indices which have been used for mapping and monitoring drought and assessing vegetation health and productivity. Remote sensing with other advanced technologies like geographical information systems (GIS) are playing a massive role in assessment and management of several agricultural activities. State or district level information systems based on available remote sensing information are required to be utilized efficiently for improving the economy coming from agriculture

Breeding for Enhancing Legumovirus Resistance in Mungbean: Current Understanding and Future Directions

Yellow mosaic disease (YMD) affects several types of leguminous crops, including the Vigna species, which comprises a number of commercially important pulse crops. YMD is characterized by the formation of a bright yellow mosaic pattern on the leaves; in severe forms, this pattern can also be seen on stems and pods. This disease leads to tremendous yield losses, even up to 100%, in addition to deterioration in seed quality. Symptoms of this disease are similar among affected plants; YMD is not limited to mungbean (Vigna radiata L. Wilczek) and also affects other collateral and alternate hosts. In the last decade, rapid advancements in molecular detection techniques have been made, leading to an improved understanding of YMD-causing viruses. Three distinct bipartite begomoviruses, namely, Mungbean Yellow Mosaic India Virus (MYMIV), Mungbean Yellow Mosaic Virus (MYMV), and Horsegram Yellow Mosaic Virus (HgYMV), are known to cause YMD in Vigna spp. Vigna crops serve as an excellent protein source for vegetarians worldwide; moreover, they aid in improving soil health by fixing atmospheric nitrogen through a symbiotic association with Rhizobium bacteria. The loss in the yield of these short-duration crops due to YMD, thus, needs to be checked. This review highlights the discoveries that have been made regarding various aspects of YMD affecting mungbean, including the determination of YMD-causing viruses and strategies used to develop high-yielding YMD-resistant mungbean varieties that harness the potential of related Vigna species through the use of different omics approaches