Sunil Kumar

A sexy, slim and shaped belly is something most of us lust after. Unfortunately, most of us fail to find out the proper exercises and cannot get the results we want. Our belly is the core and the center of your body. It is necessary to maintain it, and have all movements extend from it.

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Author(s) Dr. Akshay Bhardwaj Dr Rajesh Chauhan Mr. Sunil Kumar Ms. Minakshi Bhardwaj Country India Abstract

M K Sunil Kumar Jul 05, 2026, 23:52 IST

M K Sunil Kumar Jul 06, 2026, 13:15 IST

Author(s) Dr. Manish Kumar Bairwa Prof. Dr. Rajesh Kumar Dr. Sunil Kumar M.V, Dr. Rakshit Sureka Country India Abstract

High-entropy shape memory alloys (HESMAs) are considered promising materials for advanced engineering applications due to their unique properties, including the shape-memory effect, corrosion resistance, superelasticity, bioadaptability, and wear resistance. This study presents a modeling-based approach to optimize powder metallurgy process parameters for HESMA synthesis using a hybrid framework that integrates Response Surface Methodology (RSM), Box–Behnken Design (BBD), Artificial Neural Networks (ANN), and Genetic Algorithms (GA). The optimization processes were designed through RSM to evaluate the influence of key process factors, with theoretical density calculated via the Rule of Mixture serving as the primary response variable. The RSM model achieved a high coefficient of determination (R2 = 0.9660), while the ANN–GA model demonstrated superior predictive accuracy with R2 values of 0.97858 (training), 0.96096 (testing), and 0.98611 (validation). The overall regression coefficient (R2 = 0.9693) confirmed the improved fit of the ANN–GA framework compared to conventional RSM. These results highlight the capability of the hybrid ANN–GA approach to model complex, nonlinear relationships between process parameters and theoretical density, thereby providing a systematic and data-driven methodology for process optimization in HESMA synthesis.

Midgut volvulus is a life-threatening surgical emergency that most commonly presents during infancy, whereas delayed presentation in older children is uncommon and can be diagnostically challenging. An 11-year-old boy presented with acute abdominal pain, bilious vomiting, abdominal distension, and obstipation of two days’ duration after four prior episodes of subacute intestinal obstruction over three years that had been managed conservatively. Contrast-enhanced computed tomography of the abdomen demonstrated the classical whirlpool sign, suggestive of midgut volvulus secondary to intestinal malrotation. Emergency exploratory laparotomy confirmed incomplete intestinal malrotation with a 180-degree clockwise midgut volvulus around a narrow mesenteric base. The bowel was congested but fully viable, without ischemia or necrosis. The patient underwent Ladd’s procedure with counterclockwise derotation, division of Ladd’s bands, widening of the mesenteric base, and bowel repositioning. Caecopexy and sigmoidopexy were also performed because of marked intraoperative mobility of the caecum and redundant sigmoid colon. Recovery was uneventful, and the patient was discharged on postoperative day 7. This case highlights the need to consider malrotation with volvulus beyond infancy in children with recurrent bilious vomiting or episodic intestinal obstruction, because early imaging and timely surgery can preserve bowel viability.

Glaucoma is a primary cause of permanent vision loss, and it often gets worse without anybody noticing. This makes it very important to find it early to stop vision loss. Manually evaluating retinal fundus images frequently necessitates considerable effort and is prone to observer-dependent discrepancies. To address these constraints, a new automated method for detecting glaucoma is presented. It combines fractal-inspired Sierpinski triangle spatial decomposition with multi-scale triangular segmentation to reliably identify clinically important areas of the retina. Handcrafted descriptors that include statistical, frequency-domain, wavelet, morphological, and texture-uniformity data are taken from small areas, giving a detailed and unique picture of the structures in the retina. A hybrid deep learning system that combines bidirectional LSTM, bidirectional GRU, and CNN with Bi-LSTM models that have attention layers captures spatial-temporal connections while highlighting essential visual cues for diagnosis. The Harris Hawks Optimizer, Grey Wolf Optimizer, Red Fox Optimizer, and Social Feature Optimizer are all examples of meta-heuristic algorithms that improve the feature subset. The HHO-based version gives the best results. A thorough examination using benchmark datasets shows that the system works very well, with 98.48% accuracy on Drishti-GS, 98.99% on Origa, 97.44% on RimOne-V2, 97.80% on HVD Binary-Class, 99.02% on HVD-Advance, 98.05% on HVD-Early, and 97.11% on HVD Multi-Class trials. The proposed system shows high reliability and stability in glaucoma diagnosis, delivering consistent performance across multiple datasets. It provides a scalable, non-invasive, and efficient solution for automatic detection, supporting doctors in early treatment and improving patients chances of recovery.

Spicy Organic, a McKinney, Texas-based USDA Certified Organic spice brand, highlights the growing industry gap between organic certification and heavy metal testing of finished spice products.