Volume 14 | Issue 5 |

 Abstract

The B-pillar is a critical automotive structural member that significantly influences side-impact safety, roof crush resistance, and overall occupant protection. Increasing regulatory pressure and the transition toward lightweight electric vehicles have intensified research into advanced B-pillar materials and structural optimization. This review summarizes recent developments in crashworthiness analysis, lightweight materials, thickness optimization, structural reinforcement, and finite element simulation methods for B-pillar design. High-strength steels, aluminum alloys, and fiber-reinforced composites are compared in terms of stiffness, energy absorption, manufacturability, and mass efficiency. Emerging directions including topology optimization, hybrid joining, and AI-assisted design are discussed. The review identifies major research gaps and proposes future pathways for safer and lighter vehicle body structures

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B-Pillar , side impact, CAE, FEA , Vehicle

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Wound Although the biological process of healing is intricate and tightly controlled, chronic and non-healing wounds continue to pose a significant clinical challenge, impacting millions of patients globally and putting a significant financial strain on healthcare systems. Prolonged inflammation, poor angiogenesis, oxidative stress, microbial colonization, and dysregulated protease activity are some of the factors that lead to delayed wound healing, especially in older and diabetic populations. Because of its strong anti-inflammatory, antibacterial, antioxidant, and pro-angiogenic qualities, velutin, a naturally occurring flavonoid, has garnered more and more interest for use in wound healing applications. Poor aqueous solubility, low absorption, and insufficient retention at the wound site hinder velutin's clinical translation despite its therapeutic potential. Thermosensitive hydrogels have emerged as an advanced drug delivery platform capable of overcoming these limitations by providing in situ gelation, sustained drug release, enhanced wound residence time, and a moist, protective healing environment. This review highlights the pathophysiology of chronic wounds, the pharmacological potential of velutin in wound repair, and the advantages of thermosensitive hydrogel systems as wound dressings. Emphasis is placed on the synergistic integration of velutin with thermoresponsive hydrogels as a promising strategy to improve therapeutic efficacy, patient compliance, and overall wound healing outcomes.

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Wound healing; Chronic wounds; Velutin; Flavonoids; Thermosensitive hydrogel; Drug delivery system; Controlled release; Tissue regeneration

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 Abstract

bastar jile ke janjatiya vidyarthiyon ki samasya samadhan yogyata par shaley vatavaran ke prabhav ka adhyayan

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bastar jile ke janjatiya vidyarthiyon ki samasya samadhan yogyata par shaley vatavaran ke prabhav ka adhyayan

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Dalit Literature, Subaltern, Intersectionality, Double Marginalization, Purity and Pollution, Othering, S.K. Bhanwara.

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The connection between Enterprise Resource Planning (ERP) systems with Human Resource (HR) analytics has become a major shift for companies wanting to manage their workforce using data. In today's fast-paced and digital world, decisions about people need to be backed by up to date information and smart strategies. ERP systems gather all the important data from an organization, while HR analytics turns that data into useful insights that help improve how well the workforce performs, how productive they are and how well the company plans for the future. This study looks at the difficulties, possibilities and advantages of combining ERP systems with HR analytics. It shows how new technology, connecting different data sources, using predictions to guide decisions and working together across the organization all help make HR decisions better. The paper also points out how changes in technology, using automation and the use of AI are helping areas like hiring, keeping employees happy, managing their performance and making sure they stay with the company. The results show that companies that use ERP and HR analytics together get more efficient operations, better forecasts for their workforce, a better experience for employees and a lasting edge over competitors. However, there are still big challenges like keeping data private, the cost of setting it up, resistance from employees and the complexity of the systems. The study ends by saying that aligning the company's strategy, being ready for new technology and managing changes within the organization are key to making this integration work. Keywords: ERP Systems, HR Analytics, Digital Transformation, Workforce Management, Data-Driven HR, Decision Making

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Human Resource Information Systems (HRIS) Predictive Analytics Workforce Analytics Talent Management Employee Engagement Performance Management Artificial Intelligence (AI) in HR Business Intelligence Organizational Efficiency Data Integration Strategic Human Resource Management (SHRM) Cloud-Based ERP

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This research presents the design and implementation of a robust mobility and autonomous navigation system for a wheeled robotic platform, focusing on real-time responsiveness and stable obstacle negotiation. Traditional autonomous control systems often suffer from high latency and CPU freezing due to conventional delay-based programming. To address these limitations, this study implements a Reactive Path Planning strategy powered by a Non-Blocking State Machine architecture. By utilizing asynchronous timing control through the millis() function, the system achieves continuous sensor monitoring and parallel task execution, ensuring that the processor remains active during decision-making intervals. The navigation logic is governed by a defined State Transition Table, which facilitates seamless transitions between movement states including forward progression, emergency reversal, and directional pivoting based on immediate environmental stimuli. Experimental evaluation demonstrates that the reactive "Sense-Act" cycle significantly improves the robot's ability to navigate cluttered environments with high temporalprecision and reduced communication interruptions. The findings conclude that the integration of non-blocking control logic provides a scalable and efficient framework for autonomous mobile robots in dynamic industrial and domestic applications .

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Autonomous Navigation, Wheeled Mobile Robots (WMR), Reactive Path Planning,Non-Blocking Control Logic, Finite State Machines (FSM), Obstacle Avoidance, Embedded Systems, Real-time Decision Making .

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Background: Diabetes mellitus (DM) is a global metabolic pandemic with an estimated 451 million people affected worldwide, with this figure being projected to increase to 693 million by 2045. Although effective, conventional antidiabetic pharmacotherapy is plagued by adverse effects, drug resistance, and high cost, fostering renewed scientific interest in plant-derived therapeutics. India contains an abundant source of ethnomedicinal plants with traditional applications in glycaemic management, many of which have not been fully characterized at the molecular level. Purposes: This is a review in which the evidence is systematically consolidated on (i) pharmacology of antidiabetic phytoconstituents, (ii) already established and emerging strategies of extraction and isolation, (iii) already validated pharmacological models of antidiabetic screening, and (iv) spectroscopic methodologies of structural characterization of bioactive compounds. Methods: A thorough literature review was performed in PubMed, Scopus, Web of Science and Google Scholar using the following keywords: antidiabetic plants, phytoconstituents, bioactive compounds, ?-amylase inhibition, ?-glucosidase inhibition, LC-MS, GC-MS, and Indian medicinal plants. After quality appraisal, articles that were published between 2000 and 2024 were included. Findings: More than 400 plant species have been reported to have hypoglycaemic potential, with flavonoids, alkaloids, terpenoids, glycosides and tannins being the major pharmacologically active classes. One of them is the inhibition of carbohydrate-hydrolyzing enzymes (?-amylase and ?-glucosidase), stimulation of pancreatic insulin secretion, upregulation of GLUT4, and AMPK activation. Soxhlet extraction, Maceration, and Ultrasound-assisted extraction have been commonly used for isolation, whereas HR-LC-MS and GC-MS have been employed as gold standards for structural elucidation. The alloxan- and streptozotocin-induced rodent models continue to predominate as in vivo systems for the validation of antidiabetic agents. Conclusion: India harbors a scientifically underexplored phytochemical reservoir with high potential for the discovery of antidiabetic drugs. Fractionation guided by bioactivity, coupled with high-resolution spectroscopic detection, is a strong pipeline for revealing new, safe, and effective lead compounds. Molecular docking, ADMET profiling, and phase I/II clinical trials should be the focus of future research to translate preclinical results into therapeutic applications.

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Antidiabetic; Bioactive compounds; Ethnopharmacology; Extraction; Fractionation; Isolation; LC-MS; GC-MS; Medicinal plants; Phytoconstituents; ?-Amylase inhibition; ?-Glucosidase inhibition

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Modern engineering platforms increasingly operate under conditions that are difficult to predict using conventional control approaches. Treatment facilities, climate-control installations, and energy-management platforms are often developed as separate technical units with limited interaction between internal processes. While this configuration simplifies deployment and maintenance, it also reduces flexibility under unstable environmental and load conditions. In practical industrial environments, equipment performance is heavily influenced by fluctuations in temperature, humidity, resource quality, and consumption intensity. Industrial facilities, logistics networks, and compact autonomous installations all operate under different environmental constraints, requiring continuous adjustment of working parameters instead of fixed operating regimes. In my work within the intelligent household and environmental-technology sector, I have observed increasing demand for engineering systems capable of coordinating monitoring, regulation, and predictive operational management within a unified infrastructure. In particular, the engineering approaches developed by Aleksandr Mikhalevich demonstrate how adaptive control architectures can improve operational stability under variable environmental and industrial conditions. As technical environments become more dynamic, isolated subsystems are no longer sufficient for maintaining stable long-term performance. Higher efficiency is achieved when monitoring, environmental regulation, resource processing, and energy management operate within a coordinated control structure capable of responding to changing conditions in real time. The expansion of integrated engineering solutions has accelerated due to advances in sensor technologies, automated regulation, and predictive data analysis. These tools allow installations to adjust operating modes according to current system behavior, reducing unnecessary energy consumption and improving stability under variable loads. Under these conditions, engineering infrastructure increasingly functions as a connected control environment in which multiple technical processes operate within a shared regulatory framework rather than as isolated mechanical units.

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adaptive infrastructure, integrated control architectures, environmental regulation, predictive analytics, industrial automation, electrochemical reactors, intelligent monitoring, resource management, telemetry systems, autonomous regulation

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hearing loss there are often major obstacles when trying to share ideas with one another. This project has created an assistive communication system utilizing software to respond to these challenges and make communication more accessible. The proposed solution is a unified software platform utilizing both speech to text and text to speech technologies to provide effective communication between individuals with disabilities who have different methods of communicating. The system works by capturing sound from a user's voice via a microphone (capturing the audio) and converting it into text so that a user who cannot hear can read and understand what was said by the other user. Conversely, when a user who does not have vision inputs text, the system converts the text input into audio (speech) so that the visually impaired user can hear and understand what was said. The software is written in Python and makes use of several Python libraries including Speech Recognition for recognizing speech accurately and pyttsx3 for converting text into speech that sounds as natural as possible. This system is built to be low cost, easy to use and simple to set up without requiring any specialized hardware. This system can provide meaningful communication between individuals with disabilities nearly instantly, supporting fluid, real-time conversations. The performance testing showed the system provides good accuracy and performance under normal conditions and some performance limitations exist when there is significant noise present or the input is unclear. This system supports communication, increases independence and supports inclusive communities for those with visual or auditory impairments. This system also has a high probability of being used in real-world settings in many education, healthcare and daily communication environments, with future development possibilities such as multilingual support and advanced noise handling capabilities.

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Assistive Technology, Speech Recognition, Text-to-Speech, Artificial Intelligence, Accessibility

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The prevalent endocrine and metabolic condition known as Polycystic Ovarian Disease (PCOD), or Polycystic Ovary Syndrome (PCOS), affects women who are of reproductive age. Due to intricate connections between genetic, hormonal, and environmental variables, it is typified by hyperandrogenism, chronic anovulation, and polycystic ovarian morphology. Its pathogenesis is primarily characterized by insulin resistance and dysregulation of the hypothalamic-pituitary-ovarian (HPO) axis, which lead to metabolic disorders like obesity, dyslipidemia, and hyperinsulinemia. Infertility, hirsutism, irregular menstrual periods, and psychological problems including anxiety and depression are among the symptoms that women come with in clinical settings. Based on imaging and biochemical analysis, the diagnosis is made using the Rotterdam, NIH, or AE-PCOS criteria. A comprehensive and customized strategy combining pharmaceutical interventions, lifestyle changes, and nutraceutical support is needed for management. While natural substances like myo-inositol, N-acetylcysteine, alpha-lactalbumin, and Ceylon cinnamon show promise in enhancing insulin sensitivity and lowering oxidative stress, insulin-sensitizing medications like metformin continue to be the mainstay of treatment. In order to enhance long-term metabolic and reproductive results, future developments will prioritize precision medicine, gut microbiota modification, and treatments based on nanotechnology. In order to lower problems and improve the general quality of life for women with PCOD, early diagnosis and multidisciplinary therapy are crucial.

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Polycystic Ovarian Disease (PCOD), Insulin Resistance, Hyperandrogenism, Nutraceutical Therapy, Precision Medicine.

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