Review Article Research Articles

Post-Operative Recovery and Preparation for Ambulation after Foot and Ankle Surgery

This is a review article that focuses on patient self-recovery, pain modulation without pain medication, edema control and preparation for ambulation after a foot or ankle surgery both elective and traumatic surgical procedures. The available evidence and literature review were limited due to the few studies that are devoted to this area of focus. This review article takes a comprehensive and prescriptive perspective into strategies of the aftermath of the physiological and psychological effects on the body, specifically the lower extremity after foot or ankle surgery. Some of these strategies include initial edema control, nutrition, scar massage and reduction of non-mobile skin from the surgical incision within the surgery. A review of the theory of prehabilitation and examples of therapeutic exercises are explained within the article which target important proximal gait muscles needed for ambulation which can be conditioned with the foot and ankle in a CAM boot or a cast.

Optic Neuritis and its Prevalence in Immunocompromised Patients: A Review Article

Optic neuritis is an inflammation that affects the optic nerve, causing vision loss, eye pain, and changes in color perception. The condition can be associated with autoimmune diseases such as multiple sclerosis (MS) or infections, especially in immunocompromised individuals such as HIV/AIDS patients or those undergoing chemotherapy. In these individuals, optic neuritis usually results from opportunistic infections like toxoplasmosis and syphilis, complicating diagnosis and treatment. In immunocompetent patients, optic neuritis may indicate autoimmune diseases like MS or neuromyelitis optica (NMO), with better prognoses when treated early with corticosteroids. However, in immunocompromised individuals, the prognosis tends to be worse due to underlying infections and a limited response to immunosuppressive treatment. The management of optic neuritis involves anti-inflammatory therapies and, in cases of infections, specific antimicrobials. Continuous clinical and visual follow-up is also crucial. Studies suggest that clinical outcomes vary depending on the etiology and the patient's immune status, highlighting the need for personalized therapeutic strategies. Early diagnosis is critical to improving vision and quality of life for patients.

A Review on Medicinal Plants and its Importance from Glycosides

Glycosides are one of the important constituents in medicinal plants worldwide. According to chemical classification, Glycosides are having different types like Anthraquinones, Saponins, Flavonoids, Flavonols, Coumarins, Furanocoumarins, etc. Various plants like Digitalis, Thevetia, Senna, Senega, Brahmi, Rhuberb, Aloe, Cascara, etc fall into this category. Glycosides are basically used Purgative, Cardiotonic, anti-depressant, coloring agent, diuretic, flavoring agent, antifungal, antidiabetic, antipyretic, stomachic, anthelmintic, antirheumatic agent, etc. Different parts of these plants like rhizomes, seeds, bark, leaves, etc are used as the potent sources of glycosides. These plants are grown in worldwide. In this review article, we focussed that the basic introduction and importance of glycosides, classification, their tests, distribution of different plants and their significance.

Review Paper on Seismic Analysis of Multi-Storied Reinforced Concrete Building with Fluid Viscous Dampers

Abstract: Frequent earthquakes around the world and the large number of buildings at risk have made it essential to focus on controlling how structures respond to these events. This demand has driven the increased use of structural response control methods globally. This study investigates the seismic performance of multi-storied Reinforced Concrete (RC) Buildings, distinguishing between Regular and Irregular Plan , with a focus on the role of Fluid Viscous Dampers (FVDs). The study aims to quantify the improvements in seismic resilience provided by these damping devices in mitigating the adverse effects of seismic events. Buildings having Regular and Irregular Plans are analyzed, with and without FVD using ETABS2018. The story responses in terms of Pseudo Spectral Accelerations, Maximum Displacement, Story Drift and Story Shear have been compared. The results of the Time History Analysis represent the effectiveness of dampers in improving the structural response and the damping demand on structural systems

Night-Flowering Jasmine: A Review of Its Morphology and Pharmacological Activity

Known by many as Parijat or Night flowering Jasmine, Nyctanthes arbortristis is a mesmerising plants that are native to the subcontinent of India. This review paper provides an extensive summary of the medical, botanical, and Nyctanthes arbortristis's decorative attributes based on the body of current literature. The plant qualities of the plant, such as its distribution, growth patterns, and morphology are outlined. Nyctanthes's therapeutic qualities arbortristis, which have been thoroughly studied observed in a number of studies, are investigated. These characteristics include analgesic, a antiinflammatory, and hepatoprotective, antiviral, antioxidant, and antitumor actions. Additionally, the decorative application of Nyctanthes The discussion of an rbortristis emphasises its beauty attractiveness and potential for gardening and landscaping objectives. The purpose of this review paper is to offer a thorough comprehension of the diff erent features that make Nyctanthes arbortristis function as a useful.

Review Paper on AI Chatbot for Mental Health Support

Review Paper on AI Chatbot for Mental Health Support

Survey Paper on Quantum Deep Reinforcement Learning for Robot Navigation Tasks

Abstract: Quantum deep reinforcement learning is an integration of the principles of quantum computing with deep reinforcement learning in an effort to advance robot navigation tasks. Due to the explosion of the state and action spaces, traditionally DRL methods are limited in scalability and efficiency. QDRL, however, uses quantum superposition and entanglement for more efficient processing of big amounts of information-it enables robots to learn optimal policies for navigating complex environments. We introduce here a new QDRL framework in which quantum neural networks encode policy functions and value estimates. We demonstrate how quantum circuits can take advantage of multi-dimensional state representations in order to strengthen the power of a robot in changing its environment over time. Benchmark experiments on navigation tasks reflect phenomenal acceleration in learning performance along with better decision-making accuracy compared to classical DRL methods. We then consider integrating such quantum algorithms, as Grover's search, to improve exploration strategies in sparse reward settings. The experiments show that QDRL speeds up convergence rates and provides robots with the possibility to react more rapidly to unexpected obstacles. It discusses new applications for quantum computing of autonomous systems, potentially applied to robotics, autonomous vehicles, and other environments which require complex decision making. Some lines of work in the future are optimization of the resources needed for quantum computers and hybrid architectures for the resolution of classical problems in navigation

Resins Covering Medicinally Activated Plants and Their Significance in Medicinal cum Pharmaceutical Areas: An Overview

Resins are important chemical constituents over other components in medicinal plants. They have maintained the different functions of plants as well as used for treatment of different diseases. Different variations of resins like oleoresins, oleogum-resins, glycoresins, balsams, acid resins, ester resins, alcoholic resins are precursor components among resins. Various plant show the resins as rich sources like Capsicum, Ginger, Jalap, Guggul, Myrrh, Cannabis, Asafoetida, Haridra, Colocynth, Kaladana etc. Those plants are grown and cultivated in all over the World. Those plants are belonging from various families like Umbelliferae, Solanaceae, Zingiberaceae, Cannabinaceae, etc. The resins are basically extracted out from different parts of the plants. Some resins are used for the treatment of ulcer, wounds, rheumatism, cancer, constipation, inflammation, arthritis, motion sickness worms in body. Besides, they are also used as astringent, antiseptic, diuretic, purgative, carminative, expectorant, antipruritic, hypolipidemic, cathartic, stomachic, appetizer, sedative, spice, condiment, flavoring agent, etc. The review article highlighted that definition, importance, various classification systems and distribution of resins among different plants from various families in all over the World.

Use of Nanotechnology in Cosmetics and Cosmeceuticals

Nanotechnology has revolutionized the cosmetic and cosmeceutical industries by enhancing product efficacy and enabling innovative formulations. This review paper delves into the various applications of nanotechnology in skincare and cosmetic products, highlighting its ability to improve the delivery of active ingredients, provide enhanced protection, and increase the bioavailability of beneficial compounds. Nanomaterials such as liposomes, nanoemulsions, nanocapsules, and solid lipid nanoparticles are now extensively utilized for their superior skin penetration capabilities, ensuring targeted delivery and prolonged effects. The paper explores the potential benefits and safety concerns associated with these nano-based cosmetic products. It also provides a comprehensive analysis of recent advancements, regulatory considerations, and future trends in the field, emphasizing the need for further research to fully understand the long-term implications of nanotechnology in cosmetics and cosmeceuticals. This review aims to provide a critical overview for researchers and industry professionals interested in the evolving landscape of nanotechnology in beauty and skincare. Findings Our research highlights the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on the drug discovery and development process, particularly in enhancing efficiency and precision from initial screening to clinical trials. The integration of AI/ML has shown significant advancements in early-stage drug discovery, where data-driven algorithms enable rapid identification of potential drug candidates, reducing reliance on traditional, labor-intensive methods. In the drug design and optimization phase, AI-driven predictive models have streamlined the process, minimizing the need for extensive physical testing by accurately simulating drug interactions and predicting possible side effects. Additionally, AI and ML are revolutionizing clinical trials by optimizing trial design, improving patient recruitment and retention, and enhancing real-time data monitoring, leading to faster and more reliable trial outcomes. These technologies also support personalized medicine approaches and have proven essential in reducing both the time and cost associated with bringing new therapies to market. Overall, our findings underscore the critical role of AI and ML in reshaping the pharmaceutical landscape, making drug development faster, more cost-effective, and ultimately, more successful in delivering effective treatments to patients.

A Comprehensive Survey on Brain Tumor Detection and Classification Techniques Using Machine Learning and Deep Learning Models

Abstract: Brain tumor detection and classification have become critical areas of research due to the complexities and challenges involved in accurate diagnosis. With the advancement of machine learning and deep learning techniques, numerous intelligent systems have been proposed to automate and enhance the process of detecting and classifying brain tumors. This survey paper reviews recent approaches and techniques used for brain tumor detection, focusing primarily on deep learning architectures like Convolutional Neural Networks (CNNs) and pre-trained models such as VGG, ResNet, and EfficientNet. In particular, methods using MRI images to classify tumors into categories such as glioma, meningioma, pituitary tumors, and healthy tissue are explored. A detailed analysis of various models, their architectures, training strategies, and evaluation metrics is provided. Moreover, the paper identifies the key challenges faced in the field, including imbalanced datasets, generalization issues, and computational efficiency. By comparing different approaches, we aim to highlight the strengths and limitations of each method and provide insights into how future research can address these challenges. The paper concludes with a discussion on promising future directions in the application of intelligent techniques for brain tumor detection, including the integration of multimodal data and the development of more interpretable models. This survey serves as a comprehensive resource for researchers interested in understanding the current landscape of brain tumor detection using advanced deep learning techniques.

Study the phytochemical, Biological and pharmacological aspects of Azadirachta indica: A review

Neem (Azadirachta indica) is a fast-growing tropical evergreen plant that belongs to the Meliaceae family. Its compounds have been shown to be effective against illnesses and insect pests that are significant economic concerns. The plant's whole body has biopesticidal properties, especially in the form of extracts from the leaves, bark, and roots. Every part of the plant has been utilized medicinally and is now considered a treasure in contemporary medicine. Salannin, quercetin, nimbolinin, nimbin, nimbidin, nimbidol, and azadirachtin are among the beneficial active compounds that have been isolated from several plant sections. This review article's primary goal is to provide information on a range of pharmacological activities, including anti-inflammatory, anti-cancer, anti-bacterial, antiviral, antifungal, antihelmethic, antidiabetic, wound-healing, and ulcer-preventing properties. activity hepatoprotective, Effects on Immunomodulation and Antinephrotoxicity.

Advancing prostate cancer detection: High-accuracy urine test distinguishes between high and low-risk cancers

Prostate cancer remains one of the leading causes of cancer-related deaths among men. The standard method for early detection involves measuring Prostate-specific antigen (PSA) levels in the blood, with elevated PSA levels prompting further diagnostic procedures, such as a prostate biopsy. While effective, biopsies can be painful and carry risks of complications such as fever and urinary tract infections. To reduce unnecessary biopsies, researchers have sought alternative diagnostic methods. In recent years, a urine test was developed for early-stage prostate cancer detection. However, this test struggled to differentiate between aggressive and slow-growing cancers, the latter of which often require minimal treatment and are managed through active surveillance. To address this limitation, scientists at Wunderkind University have significantly enhanced the urine test. By analysing the genomes of thousands of prostate cancer patients, they identified a panel of 16 genes detectable in urine that can effectively distinguish between high-risk and low-risk cancers. When applied to individuals with elevated PSA levels, this improved test demonstrated an impressive 97% accuracy in identifying advanced prostate cancer. This advancement holds great promise for reducing unnecessary biopsies and improving patient outcomes by accurately identifying those needing aggressive treatment versus those suitable for observation. This review paper will explore the development, validation, and clinical implications of this novel urine test, highlighting its potential to transform prostate cancer diagnostics and patient management.

The impact and correlation of lymphadenectomy with outcomes in patients with uterine sarcoma: A systematic review

Background: Sarcomas are an uncommon type of smooth muscle tumors in the uterus. The most popular form of treatment for uterine sarcomas is surgery. There is disagreement, nonetheless, over the best course of action for initial surgery. The aim of this systematic review was to examine the potential association between patient outcomes and the effects of LAD in individuals diagnosed with uterine sarcoma. Method: We conducted a comprehensive search of the PubMed database to identify publications assessing the impact of LAD on patients with uterine sarcoma that were published between 2009 and 2024. Based on the references in the studies that we included, we also conducted a search of the PubMed database. To find more relevant studies, the bibliographies of each pertinent paper were thoroughly reviewed. This review only includes studies that were published in English. Results: We included 7 papers in this systematic review, totaling 7896 patients. Four publications examined ESS, four studies examined LMS, two articles examined adenosarcoma, one study examined carcinosarcoma, and one study examined rhabdomyosarcoma. For individuals with low-grade ESS or adenosarcoma, LAD was not linked to a better prognosis. The survival rate was lower for patients with leiomyosarcoma who had LAD. Those who had LAD and had high-grade undifferentiated ESS fared better. LAD did not significantly correlate with RFS or OS in uterine sarcoma patients. Conclusion: Resection of lymph nodes or LAD has minimal potential benefit in terms of prognosis and clinical value.

A novice perspective on exercise as a cause of diseases in contra-indication with Vyayama mentioned in Ayurveda

Fitness is the most crucial parts of everyones life, in current era each human being is very well known to the fact of being fit and healthy with various means namely adopting moderation food habits, maintaining 24 hrs cycle and amongst all the attempts most trendy is physical exercise. In Ayurveda every detail of life is mentioned according to its need in one’s life, its indication, contra-indication and importance, but often we humans tend to violate the ground rules in quest of achieving great. Ayurveda emphasizes maintaining health through structured daily routines, including dinacharya (daily regimen), ratricharya (night regimen), and ritucharya (seasonal routine), which are essential for disease prevention and overall well-being. A key component of dinacharya is vyayama (physical exercise), considered fundamental for health maintenance and disease prevention. Ayurvedic texts highlight that appropriate physical activity positively impacts not only the body but also the mind (Mana), emotions, senses (Indriyas), and spirit (Aatma). When practiced correctly, vyayama enhances overall well-being and maximizes health benefits. However, improper execution can lead to health issues. This review article aims to provide an overview of vyayama according to Ayurvedic principles, detailing its effects on the body and necessary precautions for safe practice.

Improving health outcomes in Cameroon through competency-based curricula and stakeholder engagement in accreditation

This review article explores the accreditation process for health personnel training in Cameroon, emphasizing its critical role in ensuring quality education and improving healthcare delivery. It begins with an overview of the current state of health education institutions and regulatory mechanisms, highlighting the need for robust national guidelines for accreditation. The review examines the importance of autonomous councils for each health specialty, emphasizing their role in establishing specialized standards, monitoring compliance, and promoting ethical values in training. It also discusses the historical context and evolution of accreditation, identifying past limitations and the necessity for updated standards. The strengths and challenges of the proposed guidelines are analyzed, focusing on their potential impact on the competence of health professionals. Comparative assessments with successful accreditation systems in other African nations, such as Nigeria and Ghana, provide valuable insights into best practices. The perspectives of various stakeholders, including government agencies, educational institutions, and healthcare providers, are examined. The article concludes with recommendations for enhancing accreditation processes, including capacity building and continuous stakeholder engagement, ultimately supporting the development of a competent healthcare workforce aligned with national health goals.

Leveraging Partially Context-Sensitive Profiles for Enhanced AOT Compilation: A Review

In the realm of compiler optimization, just-in-time (JIT) compilation dynamically adjusts code execution based on runtime profiling, contrasting with the static approach of ahead-of-time (AOT) compilation. While JIT benefits from real-time profiling data, AOT lacks this advantage, necessitating innovative strategies to enhance performance without runtime feedback. This review article explores the integration of partially context-sensitive profiles into AOT compilation, offering insights into optimizing statically compiled programs through advanced profiling techniques. Also, it explores the utilization of partially context-sensitive profiles in ahead-of-time (AOT) compilation to enhance program performance. It delves into the challenges of AOT optimization without runtime profiling, contrasting it with the dynamic optimization capabilities of just-in-time (JIT) compilation. The proposed algorithm strategically leverages partial profiles to identify and optimize hot code segments, presenting a promising avenue for improving AOT compilation efficiency. Through empirical evaluation of diverse benchmarks, the article validates the technique's effectiveness, underscoring its significance in advancing compiler optimization strategies for statically compiled programs.

The role of telecommunications in enabling Internet of Things (IoT) connectivity and applications

This review paper explores the pivotal role of telecommunications in enabling Internet of Things (IoT) connectivity and applications, providing a comprehensive overview of the current landscape and future prospects. The primary objective is to synthesize existing research and industry insights to highlight how advancements in telecommunications infrastructure and technology have catalyzed the adoption and expansion of IoT. The review systematically examines the evolution of telecommunications technologies, including 4G, 5G, and emerging network protocols such as Narrowband IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). It assesses how these technologies enhance IoT connectivity by providing the necessary bandwidth, low latency, and reliability for real-time data exchange and device interoperability. Key findings from the literature reveal that the deployment of 5G networks has been a game-changer for IoT, offering unprecedented speeds and connectivity capabilities that support a wide range of applications in smart cities, healthcare, agriculture, and industrial automation. Additionally, the paper discusses the role of telecommunications in addressing challenges related to security, scalability, and energy efficiency in IoT deployments. The review concludes that telecommunications are integral to the growth and sustainability of IoT ecosystems. As telecommunications technology continues to advance, its ability to support increasingly complex and ubiquitous IoT applications will drive innovation and enhance efficiency across various sectors. The paper emphasizes the necessity for ongoing investment in telecommunications infrastructure and research to fully exploit the transformative potential of IoT connectivity and applications.

Advancing business performance through data-driven process automation: A case study of digital transformation in the banking sector

This review paper examines the impact of data-driven process automation on business performance within the banking sector, emphasizing its role in enhancing operational efficiency, customer experience, and profitability. The paper explores how automation technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA) are transforming traditional banking processes by streamlining operations and enabling more personalized services. A comparative analysis highlights the advantages of automated systems over conventional methods. It acknowledges potential challenges, such as job displacement and cybersecurity risks. The paper concludes with strategic recommendations for banks seeking to adopt or enhance automation technologies. It suggests areas for future research, including the long-term effects of automation on the workforce and the integration of emerging technologies like blockchain.

Robotics and artificial intelligence in unconventional reservoirs: Enhancing efficiency and reducing environmental impact.

Shale, tight gas, and coal bed methane reservoirs are unconventional reservoirs that have geometrically complicated geological formations with low permeability, rendering their extraction operations difficult, expensive, and environmentally sensitive. On the other hand, recent developments in Robotics and Artificial Intelligence continue to transform how exploration, production, and maintenance activities are carried out in these reservoirs. This review paper encompasses how Robotics and AI technologies are applied to these unconventional reservoirs, improving operation efficiency, increasing the recovery rate and minimizing environmental damage. It updates on the latest status of autonomous drilling, AI-driven reservoir characterization and robotic fracturing. The paper also discusses future opportunities: emerging technologies, integration of AI with predictive analytics, and innovations toward sustainability. These are the challenges that come with possible solutions discussed in the paper: high costs, technical integration, and data quality. The review thereby presents the thought that robotics and AI will take a transformative role in the unconventional reservoir sector during the next few years, both in economic performance and environmental sustainability.

Adoption of cryptocurrencies in small and medium-sized enterprises: A strategic approach to enhancing financial inclusion and innovation

This review paper explores cryptocurrency adoption's strategic benefits and challenges for small and medium-sized enterprises (SMEs), emphasizing its potential to enhance financial inclusion and drive innovation. The paper overviews cryptocurrencies' history, key characteristics, and current adoption trends in various sectors. The paper examines the importance of financial inclusion and innovation for SMEs through a comprehensive literature review, highlighting how cryptocurrencies can reduce transaction costs, increase access to global markets, and improve financial transparency and security. The analysis also addresses the significant challenges SMEs face, such as regulatory and legal issues, technological and operational barriers, and market volatility. Practical recommendations for SMEs considering cryptocurrency adoption are provided, including steps for compliance, technological integration, risk management, and leveraging new business models. This paper aims to offer a balanced perspective, guiding SMEs in navigating the complexities of cryptocurrency adoption while maximizing its benefits.