Kakatiya University

Herbal medicines from traditional medical systems function as valuable resources which contain diverse medicinal compounds that can treat multiple medical conditions. The complex multi-component system of these products hinders their ability to meet conventional drug testing standards which focus on single drug and single target methods thus delaying their acceptance as modern clinical treatment methods. Multi-omics technologies which include genomics and transcriptomics and proteomics and metabolomics and systems biology have created a new scientific approach in phytomedicine research. This review examines how multi-omics research methods reveal the complex medicinal functions which herbal bioactive compounds possess. The research shows that genomic and transcriptomic analysis methods enable scientists to understand how phytochemicals control blood sugar levels through their impact on host gene networks and biological processes. The research investigates how the plant metabolomic profile which identifies all its phytochemicals interacts with herbal treatment to show metabolic changes in the host organism. This article demonstrates how systems biology and network pharmacology combine different high-throughput datasets into a unified system. Research scientists create detailed compound-target-disease networks which enable them to visualize how botanical extracts produce combined effects through multiple biological pathways. The development of standardized bioinformatic pipelines and data integration algorithms and the establishment of valid methods to measure the natural biological variability of herbal preparations continue to present major difficulties. The path from multi-omics data collection to the development of practical drug discovery solutions stands as the most important challenge which must be overcome to update herbal medicine practices while creating new network-based treatment methods.

Grinding is a critical machining process used to achieve superior dimensional accuracy and surface integrity in precision components across the automotive, aerospace, and manufacturing industries. This study introduces a hybrid framework that integrates Taguchi-based empirical modeling with Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization to assess and improve grinding performance while considering dressing parameters within the limitations of practical experimental settings. The parameters studied were dresser depth of cut, dresser cross-feed rate, and grinding feed rate. Experiments were designed using a Taguchi L9 orthogonal array with two replicates per run, yielding 18 trials in total. Surface roughness, grinding power, and grinding ratio were selected as performance objectives. By focusing on the simultaneous optimization of surface roughness, power consumption, and grinding ratio, this framework distinguishes itself by including dressing effects in a multi-objective evolutionary model. The hybrid framework successfully generated Pareto-optimal solutions for conflicting objectives. The best result achieved a surface roughness of 0.2795 μm, with 1.696 kW grinding power and a grinding ratio of 11.1621. The use of a resource-efficient experimental design further enhances its practical applicability, offering sustainable and effective solutions for industrial-grinding processes.

This study investigated the development of ambient-cured self-compacting geopolymer concrete ((SCGC)) using a neutral-grade sodium silicate solution as the sole activator. The binder system comprised ground granulated blast furnace slag (GGBFS), fly ash (FA), and micro silica (MS), with partial substitution of MS by rice husk ash (RHA) at 5–15% to improve sustainability and pozzolanic reactivity. Mixes were evaluated at two binder contents (500 and 600 kg/m³) and two solution-to-binder (S/B) ratios (0.6 and 0.5), with assessments of fresh properties, mechanical performance, and microstructural characteristics. All formulations demonstrated satisfactory workability and cohesive rheological behavior. The early age strength development was significant, with selected RHA-based mixes achieving over 50% of their 28-day compressive strength within 3 days and exceeding 85% by 7 days. The optimal mix, incorporating 600 kg/m³ binder and 15% RHA at 0.5 S/B, exhibited a 26% strength gain over the control mix, with corresponding improvements in tensile and flexural strengths. The SEM analysis revealed dense gel matrices with interpenetrating N–A–S–H and C–A–S–H phases, reduced porosity, and improved gel continuity. The results demonstrate that ambient-cured SCGC based on a hybrid industrial-waste binder constitutes a promising, lower-clinker geopolymer binder system with enhanced fresh, mechanical, and microstructural performance, while long-term durability and structural behavior require further investigation.

ABSTRACT This paper presents a linearly polarized, ground‐defected 2 × 2 rectangular patch antenna array with microstrip inset feeding. A simple structure is realized by placing the rectangular patches and the feeding network on the same layer. The proposed microstrip inset‐fed configuration facilitates proper impedance matching and easy array formation. This work provides an in‐depth examination of the antenna array's characteristics and performance. The antenna array is fabricated on an RT Duroid substrate and integrates a dumbbell‐shaped defected ground structure (DGS) in a triangular form with four radiating elements. The primary objective of incorporating the DGS is to improve the return loss. The proposed compact antenna array has overall dimensions of 106.3 × 112 × 1.575 mm 3 and is intended for wireless communication applications. The designed array operates over the desired frequency band of 3.52–3.61 GHz, achieving a reflection coefficient better than −10 dB and an impedance bandwidth of 25.09%. The antenna exhibits stable radiation characteristics with a peak gain of approximately 13.08 dBi across the operating band. The array is analyzed using HFSS, and fabrication and measurements are carried out to validate the simulated results. The measured outcomes show good agreement with the simulations, demonstrating the suitability of the proposed antenna for 5G midband mobile broadband wireless communication applications.

Amyloidosis is increasingly recognized as a contributor to heart failure, particularly among older adults and patients with heart failure with preserved ejection fraction (HFpEF). Despite advances in diagnostic imaging and disease-modifying therapies, amyloidosis remains underdiagnosed in many settings, and population-level data examining its co-occurrence with cardiovascular disease on death certificates are limited. This study examined two decades of national mortality data to evaluate deaths co-coded with amyloidosis and cardiovascular disease (CVD) in the United States and to assess temporal trends and demographic disparities in age-adjusted mortality rates. A retrospective analysis was conducted using mortality data from the CDC WONDER database spanning 1999-2020. Age-adjusted mortality rates (AAMRs) per 1,000,000 persons were calculated, and trends were assessed using Average Annual Percentage Change (AAPC) and Annual Percent Change (APC) using Joinpoint 5.0.2. Between 1999 and 2020, 26,391 amyloidosis and CVD-related deaths occurred among adults aged 25 years and older in the United States. The overall AAMR for deaths co-coded with amyloidosis and CVD increased from 4.40 in 1999 to 9.31 in 2020, with an AAPC of 3.49 (p < 0.001). The most pronounced increase occurred between 2018 and 2020 (APC: 13.60). Rates were higher among men than women, with both sexes showing a marked increase in the last decade. African American or Black individuals had the highest rates (11.40), followed by White (5.11) and Hispanic (3.86) individuals. Rates were highest in the Northeast region (6.71). Metropolitan areas had higher rates than non-metropolitan areas (5.73 vs. 4.76), with a more pronounced increase in metropolitan regions. Age-adjusted mortality rates for deaths co-coded with amyloidosis and cardiovascular disease have increased over time, likely reflecting improved recognition and documentation. Higher rates of co-coded deaths were noted among men, African Americans, and individuals in the Northeast region, highlighting potential disparities in diagnostic access and recognition.

Indigenous ethical traditions offer powerful ways to address modern challenges, including peace, justice, and sustainability. Sant Sri Sevalal, a respected spiritual leader among the Banjara people, established moral principles to promote peace, equality, self-control, environmental stewardship, and respect for everyone. This study examines the principles underpinning Sevalal’s vision for peaceful coexistence and how they can advance gender equality, environmental protection, and moral leadership. It examines Sevalal’s 21 precepts of moral principles with respect to honesty, nonviolence, acceptance of others, respect for women, care for nature, clear thinking, and social duty. The article employs a qualitative, interpretive approach, drawing on secondary sources and academic literature, to situate Sevalal’s teachings within broader discussions of indigenous ethics, peace, and sustainability. The research suggests that Sevalal’s ideas provide a comprehensive and practical moral framework for addressing today’s conflicts, inequalities, environmental damage, and moral decline.

Aim: Diabetes mellitus is one of the most common diseases and a continueing global epidemic, with over 1 to 9 adults living with the diabetes. It exacerbates multiorgan damages including the liver. Our previous study shows potent antioxidant and anti-inflammatory activity in the ethanolic leaf extract of B. grandiflora (BGEE). The present study was designed to evaluate the antidiabetic and hepatoprotective activity of BGEE against diabetic rats. Study Design: BGEE was subjected to evaluate antidiabetic and hepatoprotective activity against STZ-induced diabetic rats. Place and Duration of Study: “Shri Shankaracharya College of Pharmaceutical Sciences, Shri Shankaracharya Professional University, Bhilai-490020, Chhattisgarh, India”, over the period of 4 months. Methodology: For the study, Wistar albino rats (150-180 g) were randomly divided into different groups (n = 6 animals per group). Diabetes was induced in animals by administration of a single dose of STZ (50 mg/kg, i.p.). BGEE at two dose levels, 100 and 200 mg/kg/day, p.o., were administered in their respective groups (BGEE-100 and BGEE-200) for consecutive ten weeks and assessed against the STZ control group. The normal group was also included in the study. Results: BGEE treatments significantly (P &lt; 0.05) reduced blood glucose levels compared to the STZ control group. Moreover, BGEE treatments significantly (P &lt; 0.05) restored the serum hepatic enzymes (SGOT, SGPT, and ALP), hepatic antioxidants (CAT, SOD, and GSH), and lipid peroxidation (MDA) compared to the STZ control group. The beneficial effect of BGEE against diabetic hepatopathy was also reflected in histopathological studies. Conclusion: According to these findings, B. grandiflora is a very promising natural resource for the creation of potent, multi-target phytotherapeutics that can treat glycemic dysregulation and related diabetic hepatopathy.

Quantum computing and generative artificial intelligence are two areas that can be associated with two of the revolutionary concepts in the recent past. Quantum computation is a technique that uses quantum mechanics principles to solve computational problems with much higher efficiency than other computational systems. On the other hand, supervised computing intelligence utilizes AI computations to produce new information such as pictures, text, and tones that resemble the foreseen example sets that the computations were prepared on. Thus, this section aims to evaluate the combination of two modern technologies and their possibilities in employing both in the context of data security and protection. This will look at how the expansion of speed from quantum computers can be used when combined with the ability to generate useful and rich data through generative simulated intelligence. As these innovations develop, people start wondering about their sinister motives as far as cracking ensembles or creating fake images using deepfakes. It is necessary to regulate the risk-free and ethical applications of quantum computing and generative computer-based intelligence to guarantee the continued belief in enhanced frameworks and to protect important data. In other words, the goal of this chapter is to give an all-inclusive account of the security threats brought to bear by quantum computing and generative artificial intelligence. The publication under discussion is designed to outline possible risks and threats, viable options for avoiding them, and principles for ensuring information security in the age of such complicated stages. In this section, there are brief explanations of the current examinations as well as the status of security in quantum computing and generative AI in light of real case scenarios presented. It quite objectively says something about it, even though there is terror potential in these innovations, and some doubts regarding trustworthy advancement and implementation.