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Parking space management has become a critical challenge in urban areas due to increasing vehicle numbers and limited parking infrastructure. This paper presents a comprehensive study of machine learning (ML) models in IoT-enabled environments focusing on proposing an ML-based model for predicting available parking space. The study evaluates the performance of various models including K-nearest neighbors (KNNs), support vector machines (SVMs), random forest (RF), decision tree (DT), logistic regression (LR), and Naïve Bayes (NB) based on “precision, recall, accuracy, and F1-score performance metrics”. The results obtained by implementing ML models on the data with 65% and 85% threshold values are compared to draw meaningful conclusions regarding their performance in predicting parking space availability. Among the evaluated models, random forest (RF) demonstrates superior performance with high precision, recall, accuracy, and F1-score values. It showcases its effectiveness in accurately predicting parking space availability in the IoT-enabled environment. On the other hand, models such as K-nearest neighbors (KNNs), decision tree (DT), logistic regression (LR), and Naïve Bayes (NB) show relatively lower performance in complex parking scenarios. The paper concludes that the use of advanced predictive models, particularly random forest, significantly enhances the accuracy and reliability of IoT-enabled parking management systems and also reduces the waiting time of the vehicles, leading to more efficient resource utilization, reduced traffic congestion in real-time scenarios, and better user satisfaction in the IoT-enabled environment., Author(s): Anchal Dahiya [1]; Pooja Mittal [1]; Yogesh Kumar Sharma [2]; Umesh Kumar Lilhore (corresponding author) [3,4]; Sarita Simaiya [4]; Ehab Ghith [5]; Mehdi Tlija [6] 1. Introduction As more [...]

Simple Summary: Colorectal cancer is a major health concern globally, and finding ways to improve treatment outcomes is crucial. This review explores the role of biomarkers—biological indicators that can predict how a patient will respond to treatment or indicate the likely course of the disease—in managing colorectal cancer. By examining both well-established and emerging biomarkers, we hope to provide a clearer understanding of how these markers can guide personalized treatment plans. The findings from this research could help doctors make more informed decisions, ultimately improving patient care and outcomes in colorectal cancer. Colorectal cancer (CRC) remains the second leading cause of cancer-related mortality worldwide. While immune checkpoint inhibitors have significantly improved patient outcomes, their effectiveness is mostly limited to tumors with microsatellite instability (MSI-H/dMMR) or an increased tumor mutational burden, which comprise 10% of cases. Advancing personalized medicine in CRC hinges on identifying predictive biomarkers to guide treatment decisions. This comprehensive review examines established tissue markers such as KRAS and HER2, highlighting their roles in resistance to anti-EGFR agents and discussing advances in targeted therapies for these markers. Additionally, this review summarizes encouraging data on promising therapeutic targets and highlights the clinical utility of liquid biopsies. By synthesizing current evidence and identifying knowledge gaps, this review provides clinicians and researchers with a contemporary understanding of the biomarker landscape in CRC. Finally, the review examines future directions and challenges in translating promising biomarkers into clinical practice, with the goal of enhancing personalized medicine approaches for colorectal cancer patients. [ABSTRACT FROM AUTHOR]

Objective: To propose a theoretical formulation of engeletin-nanostructured lipid nanocarriers for improved delivery and increased bioavailability in treating Huntington's disease (HD). Methods: We conducted a literature review of the pathophysiology of HD and the limitations of currently available medications. We also reviewed the potential therapeutic benefits of engeletin, a flavanol glycoside, in treating HD through the Keap1/nrf2 pathway. We then proposed a theoretical formulation of engeletinnanostructured lipid nanocarriers for improved delivery across the blood-brain barrier (BBB) and increased bioavailability. Results: HD is an autosomal dominant neurological illness caused by a repetition of the cytosine-adenine-guanine trinucleotide, producing a mutant protein called Huntingtin, which degenerates the brain's motor and cognitive functions. Excitotoxicity, mitochondrial dysfunction, oxidative stress, elevated concentration of ROS and RNS, neuroinflammation, and protein aggregation significantly impact HD development. Current therapeutic medications can postpone HD symptoms but have long-term adverse effects when used regularly. Herbal medications such as engeletin have drawn attention due to their minimal side effects. Engeletin has been shown to reduce mitochondrial dysfunction and suppress inflammation through the Keap1/NRF2 pathway. However, its limited solubility and permeability hinder it from reaching the target site. A theoretical formulation of engeletin-nanostructured lipid nanocarriers may allow for free transit over the BBB due to offering a similar composition to the natural lipids present in the body a lipid solubility and increase bioavailability, potentially leading to a cure or prevention of HD. Conclusion: The theoretical formulation of engeletin-nanostructured lipid nanocarriers has the potential to improve delivery and increase the bioavailability of engeletin in the treatment of HD, which may lead to a cure or prevention of this fatal illness. [ABSTRACT FROM AUTHOR]

The neurodegenerative condition known as Parkinson's disease (PD) is brought on by the depletion of dopaminergic neurons in the basal ganglia, which is the brain region that controls body movement. PD occurs due to many factors, from which one of the acknowledged effects of oxidative stress is pathogenic pathways that play a role in the development of Parkinson's disease. Antioxidants, including flavonoids, vitamins E and C, and polyphenolic substances, help to reduce the oxidative stress brought on by free radicals. Consequently, this lowers the risk of neurodegenerative disorders in the long term. Although there is currently no cure for neurodegenerative illnesses, these conditions can be controlled. The treatment of this disease lessens its symptoms, which helps to preserve the patient's quality of life. Therefore, the use of naturally occurring antioxidants, such as polyphenols, which may be obtained through food or nutritional supplements and have a variety of positive effects, has emerged as an appealing alternative management strategy. This article will examine the extent of knowledge about antioxidants in the treatment of neurodegenerative illnesses, as well as future directions for research. Additionally, an evaluation of the value of antioxidants as neuroprotective agents will be provided. [ABSTRACT FROM AUTHOR]

Introduction: Black pregnant individuals endure a disproportionate burden of preventable morbidity and mortality due to persistent, racially mediated social and systemic inequities. As patient advocates, Black community‐based doulas help address these disparities via unique services not provided by conventional doulas. However, Black doulas themselves may encounter obstacles when providing care to Black perinatal clients. We characterized the barriers encountered by Black community‐based doulas in Los Angeles, California. Methods: We partnered with a Black community‐based doula program to conduct semistructured interviews with its community doulas and program directors, covering the following topics: motivations for becoming a doula, services provided, and challenges faced as a Black doula in perinatal settings. Interview transcripts were reviewed via directed content analysis, with attention to the influence of systemic racism on service provision. Additionally, our research team used Camara Jones' Levels of Racism, which describes race‐associated differences in health outcomes to code data. Results: We interviewed 5 Black community‐based doulas and 2 program directors, who all shared experiences of inequitable care and bias against Black clients that could be addressed with the support and advocacy of culturally congruent doulas. The community doulas shared experiences of stigma as Black doulas, compounded by racial prejudice. Interviewees noted sources of structural racism affecting program development, instances of interpersonal racism as they interacted with the health care system, and internalized racism that was revealed during culturally based doula trainings. Additionally, the doulas emphasized the importance of cultural concordance, or a shared identity with clients, which they considered integral to providing equitable care. Conclusion: Despite facing institutionalized, interpersonal, and internalized forms of racism, Black community‐based doulas provide avenues for Black birthing individuals to navigate systemic racism experienced during the perinatal process. However, these forms of racism need to be addressed for Black community doulas to flourish. [ABSTRACT FROM AUTHOR]

Activin A receptor type I (ACVR1), a transmembrane serine/threonine kinase, belongs to the transforming growth factor-β superfamily, which signals via phosphorylating the downstream effectors and SMAD transcription factors. Its central role in several biological processes and intracellular signaling is well known. Genetic variation in ACVR1 has been associated with a rare disease, fibrodysplasia ossificans progressive, and its somatic alteration is reported in rare cancer diffuse intrinsic pontine glioma. Furthermore, altered expression or variation of ACVR1 is associated with multiple pathologies such as polycystic ovary syndrome, congenital heart defects, diffuse idiopathic skeletal hyperostosis, posterior fossa ependymoma and other malignancies. Recent advancements have witnessed ACVR1 as a potential pharmacological target, and divergent promising approaches for its therapeutic targeting have been explored. This review highlights the structural and functional characteristics of receptor ACVR1, associated signaling pathways, genetic variants in several diseases and cancers, protein–protein interaction, gene expression, regulatory miRNA prediction and potential therapeutic targeting approaches. The comprehensive knowledge will offer new horizons and insights into future strategies harnessing its therapeutic potential. [ABSTRACT FROM AUTHOR]

Successful implementations of Software Development Methodologies significantly improve software efficiency, collaboration and security. Most companies are moving away from traditional development methodologies towards DevOps for faster and better software delivery. DevOps, which is a primary need of the IT industry, brings development and operation teams together to overcome communication gaps responsible for software failures. It relies on different sets of automation tools to robotize the tasks of software development from continuous integration, to testing, delivery, and deployment. The existence of several automation tools in each development phase raises the need for an integrated set of tools to reduce development time. For this purpose, we used the DevOps-based hybrid model Integrated Tool Chain (ITC), along with three sample java-based projects or code repositories to quantify the results. This paper evaluates and compares measurement metrics of java projects using traditional development methodologies and DevOps, and the results are shown in tabular and graphical format. The latest Google and Stack Overflow Trends have also been included to retrieve the best performer development methodology. This comparative and evaluative performance analysis will be beneficial to young researchers that study the metrics of software development, while also they will be introduced to the automotive environment of DevOps, the latest emerging buzzword in software development. [ABSTRACT FROM AUTHOR]

Software development methodologies have evolved through traditional waterfall model to recent DevOps development culture. This research validates the performance of our previously proposed, implemented and verifed DevOps-based hybrid model of integrated automation tools. For this purpose, underlying work considers random DevOps automation tool chain model based on current market and industry scenario followed by the evaluation of software quality metrics for both models and conclude comparative results in the form of tables. The results confirm that a randomly selected tool chain performs better, but if the tool chain is pre-determined or fixed, DevOps performance improves many folds, which validates the performance of our DevOps-based hybrid model of integrated automation tools. This research will be useful for software developers to select best automation tools that not only speed up the development process but also deliver quality software. [ABSTRACT FROM AUTHOR]