Dinesh Kumar

Mohammed Nazish Quasmi Jiten Singh Rachna Yadav Dinesh Kumar Talat Azam Mary K. Ekka Dinesh Dhingra

Author(s) Ms. Garima Singh Prof. Dinesh Kumar Country India Abstract Abstract

Young, AZ, October 7, 2026 — Moderate, Compassionate Republican and former independent candidate for Arizona Congressional District 2 announces his candidacy for President of The United States of America in 2028.

Phytic acid (PA) is the major phosphorus-storage compound in maize kernels, but its strong mineral-chelating capacity limits the bioavailability of essential nutrients in humans and monogastric animals. Although classical low-phytic-acid mutants have demonstrated the feasibility of phytate reduction, their use in breeding has been constrained by pleiotropic effects on seed viability, germination, and agronomic performance. Therefore, identifying natural allelic variation for kernel PA content in elite nutritional backgrounds such as Quality Protein Maize (QPM) is important for biofortification breeding. To our knowledge, no genome-wide association study has yet been reported for kernel PA content in maize. Here, we evaluated 249 QPM inbred lines across two environments and conducted genome-wide association analysis using sequencing-derived SNP markers. Kernel PA content showed substantial phenotypic variation, highly significant genotypic effects, and high broad-sense heritability in both environments, indicating strong genetic control. Of 11,525,180 variants initially called, 115,416 chromosomal biallelic SNPs passed initial filtering, and 26,074 high-quality SNPs were retained for population structure, linkage disequilibrium, and association analyses. Multi-model GWAS identified five high-confidence marker-trait associations on chromosomes 1, 3, 4, and 7. The strongest locus, chr3:236714544, was consistently detected across environments and analytical models and explained up to 17.7% of phenotypic variation. Allelic effect analysis confirmed significant differences among genotype classes at all five loci, with the clearest differentiation observed at chr3:236714544. LD-based haplotype analysis identified a three-SNP chromosome four haplotype block associated with kernel PA variation, with Hap2/GAC showing lower PA content. Integrated candidate-gene analysis prioritized seven putative candidate genes involved in transcriptional regulation, phosphate transport, phosphorylation-dependent signaling, seed development, and lipid/protein storage-related processes.

Professional identity formation (PIF) is the process through which medical students integrate professional values, norms, and behaviours into their developing professional identity. Although PIF is increasingly recognised as an educational goal in undergraduate medical education (UGME), intervention research remains heterogeneous in educational approaches, theoretical foundations, outcome measurement, and geographic distribution. This scoping review mapped educational interventions designed to support PIF in UGME, their theoretical foundations, outcome and measurement approaches, and geographic and income-group distribution. PubMed, Embase, Scopus, and ERIC were searched for English-language studies published from 2010 to 2025, supplemented by grey literature and citation searching. Studies addressing PIF-focused educational interventions among undergraduate medical students were eligible. Two reviewers independently screened records, with disagreements resolved through discussion or adjudication by a third reviewer. Data were charted using a piloted form and narratively synthesised using an inductively derived seven-category intervention taxonomy. Fifty-two studies from 21 countries were included. Interventions comprised clinical exposure (n=13, 25.0%), humanities/arts (n=11, 21.2%), reflective/narrative approaches (n=9, 17.3%), mentorship (n=7, 13.5%), mixed interventions (n=5, 9.6%), simulation (n=4, 7.7%), and peer learning (n=3, 5.8%). Identity development was the predominant outcome (n=32, 61.5%). Theoretical or conceptual frameworks were reported in 44 studies (84.6%), whereas eight (15.4%) reported none. Validated instruments were used in only three studies (5.8%). Forty-nine studies (94.2%) originated from high-income countries, two (3.8%) from lower-middle-income countries, and one (1.9%) from an upper-middle-income country. Four studies reported null or near-null effects. PIF intervention research remains theoretically heterogeneous, measurement-limited, and geographically concentrated. Greater use of validated, culturally responsive measures and longitudinal, context-sensitive research, particularly in low- and middle-income settings, is needed.

Abstract Wound healing is a complex biological process that can be severely impaired by persistent inflammation, oxidative stress, microbial

Biometric models are used for identifying the legitimate user to provide security. Biometrics refers to a technology designed to evaluate physical characteristics and has become an essential tool for human authentication. Although existing biometric authentication methods provide several advantages, they often face challenges such as limited accuracy and robustness. Integrating multiple biometric modalities helps overcome these issues and enhances overall authentication performance. Thus, this research outlines a novel multimodal biometric recognition approach based on the Ant Lion Border Collie Optimization (ALBCO) and Generative Adversarial Network (GAN). Here, palm print images, fingerprint images, finger knuckle, iris, and finger vein images are acquired and fed to pre-processing. The produced pre-processed image undergoes feature extraction. Features like LOOP, Daugman’s rubber sheet model, LGP, minutiae points, and grid features are extracted and given to the feature fusion phase. The optimally weighted coefficients are generated using the devised ALBCO in fusion. The proposed ALBCO combines Ant Lion Optimizer (ALO) and Border Collie Optimization (BCO). The fused features are further given to the GAN for multimodal biometric recognition. The proposed ALBCO-based GAN offered improved performance with the highest accuracy of 0.945, the lowest FAR of 0.064, and the lowest FRR of 0.109.

Author(s) Ms. Pragya Singh Prof. Dinesh Kumar Country India Abstract

Market: New York, NY, — Scientists have identified two threats with the potential to bring about human extinction: nuclear conflict and the

In low-inertia AC microgrids, voltage formation, frequency support, power sharing, and disturbance rejection are performed by grid-forming (GFM) converters.