Comprehensive Analysis Research Articles

Two-cylinder Synchronous Electro-hydraulic Servo System and its Control Technology Development

Background: Electro-hydraulic servo control system synchronous control in industrial application is very extensive because the application of electro-hydraulic servo control system is mostly in a poor working environment, there are a variety of complex external factors. Objective: Improve the comprehensive performance indicators such as accuracy, speed, and stability of synchronous control of hydraulic cylinders Methods: In the process of synchronous movement, the typical hardware structure and control methods and algorithm strategies of the double hydraulic cylinder are analyzed in detail, and the basic principle of common hydraulic double cylinder synchronous control is summarized. Results: Through the comprehensive analysis of papers and patent documents related to the synchronous control of hydraulic twin cylinders, these papers and patented technologies study the control algorithm, and apply the new technology to the synchronous control of electro-hydraulic servo hydraulic cylinders to improve its comprehensive performance indicators such as work accuracy, speed and stability. Conclusion: Referring to the development trajectory of control algorithms in this regard, combined with new control theory and new technology, many achievements can be applied and researched in hydraulic cylinder synchronous control, and better develop the synchronous control system when double hydraulic cylinders and more hydraulic cylinders work together. By collating and analyzing the relevant research results, the two-cylinder synchronous control technology is comprehensively evaluated and prospected, which provides a valuable reference for the research and application in this field.

Utilization of papermaking black liquor as liquid phase for hydrothermal carbonization of corn stalks: The unique role of alkali for production of hydrochar

Papermaking black liquor (BL) contains a large amount of organic matter, alkali, and salt, which has high value in industrial and agricultural production. In the present paper, hydrothermal carbonization (HTC) technology has been employed to deal with BL and corn stalk (CS) under various conditions. A variety of analytical technologies, including Fourier Transform Infrared Spectrometer, X-Ray Diffraction, element analyzer, comprehensive thermal analyzer, scanning electron microscope, chromatography/mass spectrometry, TOC analyzer, and density functional theory (DFT), were used to characterize the physicochemical properties of hydrochar and aqueous phase product. The effects of experimental parameters (temperature, solid-liquid ratio, and time) on the HTC of BL and CS were systematically investigated. The higher energy yield and densification of hydrochar prepared by our HTC technology were obtained at 260 ℃ in 30 min with a solid-liquid ratio of 1:3. Mechanism study indicates that NaOH, which comes from the original BL, could effectively facilitate the cleavage of β–O–4 bond in lignin and β–1–4 glycosidic bond in cellulose and hemicellulose molecules. Hemicellulose and cellulose are more susceptible to degradation relevant to the lignin in the presence of NaOH. Elementary analysis shows that the dosage of BL is important for improving energy densification of hydrochar. The combustion characteristics show that hydrochar presents a thermochemical behavior, which is close to bituminous coal. Owing to hydroxyl ion in NaOH ion pair was consumed in the series of dehydrogenation reactions, pH of HTC aqueous phase product significantly decreases from 11 to 13 in original BL to 4.8–5. Such results indicate that a completely change for the components of BL could be obtained by our HTC technology, which provide a novel idea for the treatment of Papermaking BL without concentration.

Comprehensive Analysis of a Japanese Pedigree with Biallelic ACAGG Expansions in RFC1 Manifesting Motor Neuronopathy with Painful Muscle Cramps.

Cerebellar ataxia, neuropathy, and vestibular areflexia syndrome (CANVAS) is an autosomal recessive multisystem neurologic disorder caused by biallelic intronic repeats in RFC1. Although the phenotype of CANVAS has been expanding via diagnostic case accumulation, there are scant pedigree analyses to reveal disease penetrance, intergenerational fluctuations in repeat length, or clinical phenomena (including heterozygous carriers). We identified biallelic RFC1 ACAGG expansions of 1000 ~ repeats in three affected siblings having sensorimotor neuronopathy with spinocerebellar atrophy initially presenting with painful muscle cramps and paroxysmal dry cough. They exhibit almost homogeneous clinical and histopathological features, indicating motor neuronopathy. Over 10years of follow-up, painful intractable muscle cramps ascended from legs to trunks and hands, followed by amyotrophy and subsequent leg pyramidal signs. The disease course combined with the electrophysical and imagery data suggest initial and prolonged hyperexcitability and the ensuing spinal motor neuron loss, which may progress from the lumbar to the rostral anterior horns and later expand to the corticospinal tract. Genetically, heterozygous ACAGG expansions of similar length were transmitted in unaffected family members of three successive generations, and some of them experienced muscle cramps. Leukocyte telomere length assays revealed comparatively shorter telomeres in affected individuals. This comprehensive pedigree analysis demonstrated a non-anticipating ACAGG transmission and high penetrance of manifestations with a biallelic state, especially motor neuronopathy in which muscle cramps serve as a prodromal and disease progress marker. CANVAS and RFC1 spectrum disorder should be considered when diagnosing lower dominant motor neuron disease, idiopathic muscle cramps, or neuromuscular hyperexcitability syndromes.

Intimate Partner Violence Risk Factors: A Vulnerability-Adaptation Stress Model Approach.

Intimate partner violence (IPV) disproportionally affects women. Using the vulnerability-adaptation stress model, we examined adverse childhood experiences (ACEs), self-esteem, and hope as vulnerability indicators and relationship status and length, positive and negative affect, and socioeconomic status (SES) as stressors to ascertain the risk for IPV. Women (N = 491, M = 37.15, standard deviation = 12.51) completed an online survey comprised of the Positive and Negative Affect Scale, Rosenberg's Self-esteem Scale, Snyder's Hope Scale, ACE questionnaire, Composite Abuse Scale Revised-Short Form, and demographic questions. Factor analysis identified four ACE factors of sexual abuse, physical or psychological abuse, witnessing domestic violence, and household dysfunction. A five-step hierarchical multiple regression identified that greater exposure to physical or psychological child abuse was associated with an increased risk of IPV (Step 2), B = 0.73 [0.16, 1.34]. Lower self-esteem, B = -0.30 [-0.47, -0.14] predicted IPV (Step 3). Age B = 0.07 [0.01, 0.13], negative affect, B = 0.39 [0.19, 0.59], and relationship length, B = -1.24 [-2.16, 0.41] were associated with a higher risk of IPV (Step 4). In Step 5, previous variables attenuated to non-significance while age, B = 0.07 [0.01, 0.13], negative affect, B = 0.39 [0.19, 0.59], and relationship length B = -1.25 [-2.16, 0.41] remained significant. While the key findings of this study were inconsistent with some commonly reported findings (e.g., ACEs, self-esteem, hope, relationship status, SES, age), these inconsistencies are important to highlight given the factorial approach to examining ACEs, the comprehensive analyses conducted, and our examination of these variables' direct relationship to IPV. The study was limited by its cross-sectional nature, higher prevalence of IPV victims, and not examining IPV sub-types. Similar studies need to be conducted for other relationship types and victimized individuals (e.g., same-sex relationships and male victims) to provide a complete picture of risk factors for IPV.

Open-Ended Online Learning for Autonomous Visual Perception.

The visual perception systems aim to autonomously collect consecutive visual data and perceive the relevant information online like human beings. In comparison with the classical static visual systems focusing on fixed tasks (e.g., face recognition for visual surveillance), the real-world visual systems (e.g., the robot visual system) often need to handle unpredicted tasks and dynamically changed environments, which need to imitate human-like intelligence with open-ended online learning ability. Therefore, we provide a comprehensive analysis of open-ended online learning problems for autonomous visual perception in this survey. Based on "what to online learn" among visual perception scenarios, we classify the open-ended online learning methods into five categories: instance incremental learning to handle data attributes changing, feature evolution learning for incremental and decremental features with the feature dimension changed dynamically, class incremental learning and task incremental learning aiming at online adding new coming classes/tasks, and parallel and distributed learning for large-scale data to reveal the computational and storage advantages. We discuss the characteristic of each method and introduce several representative works as well. Finally, we introduce some representative visual perception applications to show the enhanced performance when using various open-ended online learning models, followed by a discussion of several future directions.

Comprehensive Analysis for Predicting Prognoses and Immune Responses of m6A-Related lncRNAs in Women with Lung Adenocarcinoma.

During the past decade, the average 5-year survival rate of patients with Lung adenocarcinoma (LUAD) has remained < 20%, although the targeted therapies and novel immunotherapy approaches have held promise. Epigenetic modifications could provide prognostic value as molecular biomarkers, and we aimed to identify the independent risk of m6A-related lncRNAs to establish a risk model for the clinical prediction of prognoses in women with LUAD. In this study, we first assessed 31 N6-methyladenosine (m6A)-related lncRNAs associated with overall survival. Moreover, we evaluated the expression of the oncogenic driver and the tumor immune microenvironment (TIME) in two female LUAD subtypes (clusters 1 and 2) using consensus clustering. We also found 16 m6A-related lncRNAs as the independent prognostic indicator of women with LUAD and established a risk model developed from these lncRNAs. We comprehensively investigated the correlation between the TIME and m6A-related lncRNA and found that m6A-related lncRNA may significantly affect the immune cell infiltration level in LUAD. In conclusion, our study provides evidence on the prognostic prediction in women with LUAD and may help elucidate the processes and mechanisms of m6A-regulated lncRNAs.

Exploring the Potential Mechanisms of Action of Gentiana Veitchiorum Hemsl. Extract in the Treatment of Cholestasis using UPLC-MS/MS, Systematic Network Pharmacology, and Molecular Docking.

Gentiana veitchiorum Hemsl. (GV) has a long history in Tibetan medicine for treating hepatobiliary disease cholestasis. However, the mechanisms mediating its efficacy in treating cholestasis have yet to be determined. To elucidate the mechanisms of action of GV in the treatment of cholestasis, an integrated approach combining ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis with network pharmacology was established. A comprehensive analysis of the chemical composition of GV was achieved by UPLC-MS/MS. Subsequently, a network pharmacology method that integrated target prediction, a protein-protein interaction (PPI) network, gene set enrichment analysis, and a component- target-pathway network was established, and finally, molecular docking and experiments in vitro were conducted to verify the predicted results. Twenty compounds that were extracted from GV were identified by UPLC-MS/MS analysis. Core proteins such as AKT1, TNF, and IL6 were obtained through screening in the Network pharmacology PPI network. The Kyoto Encyclopedia of the Genome (KEGG) pathway predicted that GV could treat cholestasis by acting on signaling pathways such as TNF/IL-17 / PI3K-Akt. Network pharmacology suggested that GV might exert a therapeutic effect on cholestasis by regulating the expression levels of inflammatory mediators, and the results were further confirmed by the subsequent construction of an LPS-induced RAW 264.7 cell model. In this study, UPLC-MS/MS analysis, network pharmacology, and experiment validation were used to explore potential mechanisms of action of GV in the treatment of cholestasis.

Public Policy Innovation: Analyzing the Implementation and Outcomes of Progressive Initiatives

Public policy innovation plays a pivotal role in addressing contemporary societal challenges, and this journal article scrutinizes the implementation and outcomes of progressive initiatives in the realm of public policy. The study delves into the dynamics of policy innovation, examining the factors influencing successful implementation and evaluating the resultant outcomes. The article begins by elucidating the significance of public policy innovation in responding to the evolving needs of societies. It explores various forms of innovation, including technological, procedural, and institutional innovations, and their impact on the policy landscape. A comprehensive analysis of the implementation process follows, encompassing stakeholder engagement, regulatory frameworks, and the role of leadership in fostering innovation-friendly environments. Case studies and real-world examples illustrate instances of successful policy innovation, highlighting best practices and lessons learned. Furthermore, the study assesses the outcomes of progressive policy initiatives, considering their effectiveness in achieving intended goals and addressing societal challenges. It also explores the potential unintended consequences and challenges associated with policy innovation. The findings underscore the importance of a dynamic and adaptive policy framework that encourages experimentation, learning, and continuous improvement. Recommendations include the establishment of innovation labs, cross-sector collaboration, and mechanisms for ongoing evaluation and feedback. In conclusion, this article contributes to the discourse on public policy innovation, offering insights into the complexities of implementation and the multifaceted outcomes of progressive initiatives. As societies navigate unprecedented challenges, fostering a culture of innovation in public policy emerges as a key strategy for building responsive and effective governance systems.

Prognostic factors of first-onset optic neuritis based on diagnostic criteria and antibody status: a multicentre analysis of 427 eyes

BackgroundOptic neuritis (ON) prognosis is influenced by various factors including attack severity, underlying aetiologies, treatments and consequences of previous episodes. This study, conducted on a large cohort of first ON...

Comprehensive Analyses and Experiments Confirmed IGFBP5 as a Prognostic Predictor Based on an Aging-genomic Landscape Analysis of Ovarian Cancer.

Ovarian cancer (OC) is one of the malignant diseases of the reproductive system in elderly women. Aging-related genes (ARGs) were involved in tumor malignancy and cellular senescence, but the specifics of these mechanisms in OC remain unknown. ARGs expression and survival data of OC patients were collected from TCGA and CPTAC databases. Subtype classification was used to identify the roles of hub ARGs in OC progression, including function enrichment, immune infiltration, and drug sensitivity. LASSO regression was utilized to confirm the prognosis significance for these hub ARGs. MTT, EdU, Transwell, and wounding healing analysis confirmed the effect of IGFBP5 on the proliferation and migration ability of OC cells. ARGs were ectopically expressed in OC tissues compared to normal ovary tissues. Three molecular subtypes were divided by ARGs for OC patients. There were significant differences in ferroptosis, m6A methylation, prognosis, immune infiltration, angiogenesis, differentiation level, and drug sensitivity among the three groups. LASSO regression indicated that 4 signatures, FOXO4, IGFBP5, OGG1 and TYMS, had important prognosis significance. Moreover, IGFBP5 was significantly correlated with immune infiltration. The hub ARG, IGFBP5, expression was significantly decreased in OC patients compared to normal women. IGFBP5 could also reduce the migration and proliferation ability of OC cells compared to vector and NC groups. IGFBP5 was correlated with OC prognosis and associated with OC migration and proliferation. This gene may serve as potential prognostic biomarkers and therapeutic targets for OC patients.

Anthriscus sylvestris: An overview on Bioactive Compounds and Anticancer Mechanisms from a Traditional Medicinal Plant to Modern Investigation.

Anthriscus sylvestris (L.) Hoffm. Gen. is a biennial or perennial herb commonly found in China. It has a long history of use in traditional Chinese medicine to treat various ailments such as cough, gastric disorders, spleen deficiency, and limb weakness. Recently, its potential as an anticancer agent has gained considerable attention and has been the subject of extensive research focusing on extract efficacy, identification of active compounds, and proposed molecular mechanisms. Nevertheless, further high-quality research is still required to fully evaluate its potential as an anticancer drug. This review aims to comprehensively summarize the anticancer properties exhibited by the active components found in Anthriscus sylvestris. We conducted a comprehensive search, collation, and analysis of published articles on anticancer activity and active compounds of A. sylvestris using various databases that include, but are not limited to, PubMed, Web of Science, Science Direct and Google Scholar. The primary chemical composition of A. sylvestris consists of phenylpropanoids, flavonoids, steroids, fatty acids, and organic acids, showcasing an array of pharmacological activities like anticancer, antioxidant, anti-aging, and immunoregulatory properties. Thus, this review highlights the active compounds isolated from A. sylvestris extracts, which provide potential leads for the development of novel anticancer drugs and a better understanding of the plant's pharmacological effects, particularly its anticancer mechanism of action.

Accurate Registration of Cross-Modality Geometry via Consistent Clustering.

The registration of unitary-modality geometric data has been successfully explored over past decades. However, existing approaches typically struggle to handle cross-modality data due to the intrinsic difference between different models. To address this problem, in this article, we formulate the cross-modality registration problem as a consistent clustering process. First, we study the structure similarity between different modalities based on an adaptive fuzzy shape clustering, from which a coarse alignment is successfully operated. Then, we optimize the result using fuzzy clustering consistently, in which the source and target models are formulated as clustering memberships and centroids, respectively. This optimization casts new insight into point set registration, and substantially improves the robustness against outliers. Additionally, we investigate the effect of fuzzier in fuzzy clustering on the cross-modality registration problem, from which we theoretically prove that the classical Iterative Closest Point (ICP) algorithm is a special case of our newly defined objective function. Comprehensive experiments and analysis are conducted on both synthetic and real-world cross-modality datasets. Qualitative and quantitative results demonstrate that our method outperforms state-of-the-art approaches with higher accuracy and robustness. Our code is publicly available at https://github.com/zikai1/CrossModReg.

Retrospective study on the distribution of hemoglobinopathies in Karnataka-A laboratory experience.

The importance of screening for hemoglobinopathies is well-documented in India. However, information on the distribution of hemoglobinopathies in Karnataka is lacking. The present study focuses on determining the spectrum of hemoglobinopathies for various districts of Karnataka. A retrospective analysis of samples registered for hemoglobinopathies for a period of 5 years (2017-2021) was carried out. A total of 17066 records registered only from the Karnataka region, were anonymized and retrieved. The data included gender, age, district, and results of the tests. The results were based on complete blood count, peripheral smear, and capillary electrophoresis (CE) pattern. The data were revalidated by pathologists, and the unambiguous data were analyzed for the study. One-fourth of the records (25%) showed abnormal hematological parameters. The number of female records (66%) was twice that of males and both genders showed higher distribution of thalassemia, followed by variants and double heterozygotes (DH). Several cases of thalassemia major were identified below the age of 17 years. The majority of thalassemia cases were β thal and 93% of them were β thal trait. Among the variants, HbS was more prevalent than HbE. Among the districts, Hassan had a 35.2% thal, Mysuru had a 7.2% variant, and Chitradurga had a 5.5% DH. Thalassemia, variants, and DH were distributed across several districts of Karnataka to various levels. The comprehensive retrospective analysis of the spectrum of hemoglobinopathies in various districts of Karnataka serves as evidence to carry out a prospective study on population screening where the incidence of thalassemia and structural variants is high.

Quantifying Human Gait Symmetry During Blindfolded Treadmill Walking.

Bilateral gait symmetry is an essential requirement for normal walking since asymmetric gait patterns increase the risk of falls and injuries. While human gait control heavily relies on the contribution of sensory inputs, the role of sensory systems in producing symmetric gait has remained unclear. This study evaluated the influence of vision as a dominant sensory system on symmetric gait production. Ten healthy adults performed treadmill walking with and without vision. Twenty-two gait parameters including ground reaction forces, joint range of motion, and other spatial-temporal gait variables were evaluated to quantify gait symmetry and compared between both visual conditions. Visual block caused increased asymmetry in most parameters of ground reaction force, however mainly in the vertical direction. When vision was blocked, symmetry of the ankle and knee joint range of motion decreased, but this change did not occur in the hip joint. Stance and swing time symmetry decreased during no-vision walking while no significant difference was found for step length symmetry between the two conditions. This study provides a comprehensive analysis to reveal how the visual system influences bilateral gait symmetry and highlights the important role of vision in gait control. This approach could be applied to investigate how vision alters gait symmetry in patients with disorders to help better understand the role of vision in pathological gaits.

Deep-Learning-Based Simulation and Inversion of Transient Electromagnetic Sounding Signals in Permafrost Monitoring Problem

Abstract —This article presents a novel approach to addressing the challenges in permafrost monitoring through the integration of deep-learning techniques with conventional electromagnetic sounding methods. Our methodology comprises a forward finite element method (FEM) solver, augmented with the Sumudu transform, and an artificial neural network (ANN) solver trained on FEM-generated data. Remarkably, the ANN solver demonstrates similar accuracy to the FEM solver but operates at a superior speed that is nearly 10,000 times faster. Furthermore, we introduce an inverse problem solution drawing on the PARS algorithm. In addition, we present an ANN-based inverse solver, where the input and output roles are inverted. The ANN inverse solver is trained on the same data, thereby offering an alternative approach to solving the inverse problem. In a computational experiment, we compare the numerical inversion results using the PARS algorithm with those obtained from the ANN forward solver, ANN inversion, and a linear combination of these solutions. This comprehensive analysis sheds light on the effectiveness of our deep-learning-based approach in permafrost monitoring, providing insights for future applications in geophysics and environmental science.

Optimization of Energy Consumption in Formaldehyde Production Process Using Reboiled Absorption Process

Formaldehyde is a crucial chemical building block in various industries, and its production often involves energy-intensive processes. This study focuses on optimizing energy consumption in formaldehyde production, explicitly employing the reboiled absorption process with a production capacity of 27,000 tons per year. The objective of this article is to develop a more energy-efficient process of formaldehyde synthesis by addition or refrigerant cycle stream to preserve the energy, reducing energy consumption and improving the sustainability of the process. The reboiled absorption process involves the absorption of formaldehyde gas into a liquid absorbent, followed by reboiling to release the absorbed formaldehyde. A comprehensive analysis of the entire production system compares unmodified and modified process simulations, heat integration, and energy analysis. Beside the energy consumption of the process, the number of stages within the absorption process contributes to the product mass flow rate of the overall process by increasing the surface area which mass transfer can occur. However, adding too many stages to the process may negatively impact the energy efficiency of the process. Therefore, optimizing energy consumption and absorption processes in formaldehyde production is essential to improve the sustainability of the process and increase the overall profitability of the production process. The results show that the proposed method dramatically improves the sustainability of CH2O synthesis by reducing overall energy consumption and emissions by 93.978%, reducing energy consumption from 153,735,360.4 kJ/h to 9,256,646.618 kJ/h. Copyright © 2024 by Authors, Published by Universitas Diponegoro and BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Conceptual and Theoretical Review of Self-Worth

This study examined the significance of self-worth as a crucial factor in human mental health and psychosocial development. The study explores self-worth interventions, mental disorders, and available resources. A comprehensive analysis of the conceptual and theoretical aspects of self-worth is undertaken. To begin with, the study offers conceptual justifications drawn from the self-worth literature, elucidating theoretical perspectives on the formation of self-worth in individuals. It elaborates on related concepts and their interconnections with self-worth. Furthermore, the examination extends to the influence of culture on self-worth development and emotions. Theoretical discussions on self-worth are approached through Psychoanalytic theory, Psychosocial development theory, Transactional analysis theory, and Attachment theory. The research scrutinizes the association between various mental disorders and self-worth, investigating how a lack of self-worth may exacerbate or precipitate certain psychopathologies. Previous interventions aimed at enhancing self-worth are outlined, accompanied by an exploration of methods for measuring self-worth. The study emphasizes the pivotal role of self-worth in individuals' mental health, considering the implications of concepts like unconditional self-worth and contingencies of self-worth. Recommendations are provided for individuals, parents, and mental health professionals based on the findings.

Comprehensive analyses reveal molecular and clinical characteristics of RNA modification writers across 32 cancer types

&lt;p class="MsoNormal" style="text-align: justify;"&gt;&lt;span lang="EN-US" style="font-size: 12pt; font-family: Nunito;"&gt;Adenosine alterations to RNA, which are largely determined by RNA modification writers (RMWs), are critical for cancer growth and progression. These RMWs can catalyze different types of adenosine modifications, such as N6-methyladenosine (m6A), N1-methyladenosine (m1A), alternative polyadenylation (APA), and adenosine-to-inosine (A-to-I) RNA editing. These modifications have profound effects on gene expression and function, such as immune response, cell development. Despite this, the clinical effects of RMW interactive genes on these cancers remain largely unclear. A comprehensive analysis of the clinical impact of these epigenetic regulators in pan-cancer requires further comprehensive exploration. Here, we systematically profiled the molecular and clinical characteristics of 26 RMWs across 33 cancer types using multi-omics datasets and validated the expression level of some RMWs in various cancer lines. Our findings indicated that a majority of RMWs exhibited high expression in diverse cancer types, and this expression was found to be significantly associated with poor patient outcomes. In the genetic alterations, the amplification and mutation of RMWs were the dominant alteration events. Consequently, the RNA Modification Writer Score (RMW score) was established as a means to assess the risk of RMWs in pan-cancer. We found that 27 of 33 cancers had significantly higher scores compared with normal tissues, and it was significantly correlated with prognosis. We also evaluated their impact on the tumor microenvironment and the response to immunotherapy and targeted therapy. These findings verified the important role of RMWs in different aspects of cancer biology, and provided biomarkers and personalized therapeutic targets for cancer.&lt;/span&gt;&lt;/p&gt;

Comprehensive analysis of environmental exposure to hazardous trace elements and lung function: a national cross-sectional study

BackgroundThere is growing interest in the joint effects of hazardous trace elements (HTEs) on lung function deficits, but the data are limited. This is a critical research gap given increased...

Geometric features and traffic dynamic analysis on 4-leg intersections

AbstractWith the escalating density of vehicles converging at road intersections, the surge in road accidents, traffic conflicts, and traffic congestion has emerged as a pressing concern. This research paper addresses these challenges by employing MC (manual control) techniques to mitigate encroachment issues at three selected intersections. These intersections were identified through a comprehensive analysis of the Ranking-based Instance Selection (RIS), enabling the design of suitable measures to facilitate smooth traffic flow and minimize the occurrence of crashes. In order to gather pertinent data, the study incorporates various parameters such as traffic volume, peak flow rate (PFR), traffic conflicts, accidents, and intersection inventory. Through the implementation of our proposed approaches, which involve both MC techniques and signalized operation, a supreme level of service (LOS) is attainable. Notably, our findings demonstrate a remarkable reduction in the volume-to-capacity ratio (v/c ratio) of up to 0.62. This paper thus serves as a significant contribution to the field of traffic management, offering practical insights for optimizing intersection design and effectively addressing the challenges posed by increased traffic density.