Volume 14 | Issue 6 |

 Abstract

Background: Plantar fasciitis is a common musculoskeletal disorder characterized by heel pain and functional limitations. Several biomechanical and lifestyle-related factors have been implicated in its development and progression. Understanding the relationship between these factors and plantar fasciitis severity may assist in identifying individuals at risk and planning appropriate interventions. Aim: To explore the relationship between plantar fasciitis and its associated risk factors, including body mass index (BMI), standing duration, ankle dorsiflexion range, pain intensity, and foot arch type. Methods: A cross-sectional observational study was conducted among 100 participants diagnosed with plantar fasciitis. Data were collected using the Plantar Fasciitis Pain and Disability Scale (PFPS), Visual Analogue Scale (VAS), body mass index measurements, goniometric assessment of ankle dorsiflexion, and foot arch evaluation. Correlation analyses were performed to determine the association between PFPS scores and the selected risk factors. Results: Significant associations were identified between plantar fasciitis severity and all measured variables. Positive correlations were observed between PFPS scores and BMI (r = 0.69), standing duration (r = 0.59), pain intensity (r = 0.77), and foot arch type (? = 0.68). A significant negative correlation was found between ankle dorsiflexion range and PFPS scores (r = -0.61). All findings were statistically significant (p < 0.001). Conclusion: Plantar fasciitis severity is significantly associated with increased BMI, prolonged standing, higher pain intensity, reduced ankle dorsiflexion, and abnormal foot arch posture. Addressing these modifiable factors may help reduce symptom severity and improve functional outcomes in individuals with plantar fasciitis.

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 Keywords

Plantar Fasciitis, Body Mass Index, Dorsiflexion Range, Foot Arch Type, Standing Duration, Pain Intensity, PFPS.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rise of the data-driven economy has led to downtime becoming a concern for organizations' operations with regard to data processing and analytical activities. Traditional methods of debugging and remedying manually that have been utilized to date will no longer be able to handle the ever-growing complexity of the data sets being processed. In this paper, we will look at the concept of a self-healing data pipeline, which are automated systems capable of diagnosing themselves and self-repairing. For this research project, we have analyzed Scripted Automation, ML-Based Monitoring, and Advanced Agentic AI as three architectural models.

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 Keywords

Self-Healing Data Pipelines, Data Engineering, Autonomous Remediation, Data Observability, Agentic AI, Schema Drift, Anomaly Detection, Fault Tolerance, MTTR

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In recent years the recruitment process has changed significantly because organizations receive very large numbers of job applications through online platforms making manual resume screening difficult and time consuming. To handle this problem many companies use Applicant Tracking Systems (ATS) that automatically filter resumes using keyword-based techniques. Although these systems reduce manual effort and improve processing speed they often fail to understand the actual meaning and context of resumes which can lead to rejection of qualified candidates because of different wording or resume formats. To overcome these limitations researchers introduced Artificial Intelligence (AI), Natural Language Processing (NLP), Machine Learning (ML) and transformer-based models into recruitment systems for better semantic analysis and candidate evaluation. Recent developments in Large Language Models (LLMs) such as BERT, GPT, LLaMA and Mixtral have further improved contextual understanding and resume job matching accuracy. This survey paper presents a comparative study of traditional and AI based resume screening and recruitment systems. The paper reviews keyword based ATS, NLP driven approaches, transformer architectures and LLM based recruitment models. It compares these systems based on contextual understanding, matching accuracy, scalability, recommendation capability and user experience. The survey also discusses major challenges in existing systems such as lack of personalization, fragmented career guidance, limited contextual analysis and bias in AI models. From the overall analysis it is observed that AI driven recruitment systems provide more accurate and intelligent candidate evaluation compared to traditional methods and systems.

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 Keywords

Component, Artificial Intelligence (AI), Resume Screening, Recruitment Systems, Applicant Tracking Systems (ATS), Natural Language Processing (NLP), Large Language Models (LLMs), Resume Analysis, Job Matching, Semantic Analysis, Machine Learning (ML), Transformer Models, Career Guidance Systems.

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Creative Commons Attribution 4.0 and The Open Definition

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The replacement of the Planning Commission with NITI Aayog, on Jan 1, 2015, marks one of the major consequential institutional shifts in post - independence federal structure of India. Officially framed as a shift from "command & control" centralized planning towards "cooperative federalism" , this transition basically altered the Center-State relations by reshaping fiscal federalism, resource allocation mechanisms, and inter- governmental consultation processes. However, the ground reality diverges significantly from the rhetoric. While states Apparently received a higher share of tax devolution [jumping from 32% to 42% under the 14th Finance Commission], they simultaneously lost critical institutional forums for negotiation, faced increased political discretion in fund allocation, and witnessed an erosion of fiscal autonomy through the implementation of GST and a sudden increase in the non- shareable cesses. This paper presents the comprehensive evidence from state government testimonies , primary government documents, and scholarly analysis, to argue that this transition does not represent genuine federalization. Instead, it signals a shift from institutional centralization to political centralization, where "cooperative federalism" remains largely aspirational rather than operational.

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 Keywords

Cooperative Federalism, Planning Commission, NITI Aayog, Super Cabinet

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Background: Hamstring tightness is common among young adults and may be influenced by biomechanical and lifestyle factors. Aim: To assess the prevalence of hamstring tightness and its correlation with body mass index (BMI), daily sitting duration, and foot posture among college students. Methods: A cross-sectional study was conducted among 100 college students. Hamstring flexibility was assessed using the Active Knee Extension (AKE) test. BMI, sitting duration using the Multi-Context Sitting Questionnaire, and foot posture using the Foot Posture Index-6 were recorded. Pearson correlation was used for BMI and sitting duration; Spearman correlation was used for foot posture. Results: Hamstring tightness was prevalent among participants. BMI showed a strong positive correlation with hamstring tightness (r = 0.73, p < .001), sitting duration showed a positive correlation (r = 0.37, p = .001), and foot posture showed a very strong positive correlation (? = 0.84, p < .001). Conclusion: BMI, sitting duration, and foot posture were significantly associated with hamstring tightness. Preventive strategies should address body weight, posture, and prolonged sitting. Index Terms--Hamstring tightness, body mass index, sitting duration, foot posture, college students, cross-sectional study.

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Hamstring tightness, body mass index, sitting duration, foot posture, college students, cross-sectional study.

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Creative Commons Attribution 4.0 and The Open Definition

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If we look at today's time, the lending activities sector plays a very crucial role in economic development because financial institutions provide financial support to individuals, businesses or companies so that they can fulfil their financial needs. This study is titled "Borrowers Experience vs Borrowers Perception in Lending: A comparative study between SBI and BAJAJ finance customers in Ranchi", in this we examined the lending experience of borrowers or according to them we evaluated whether any significant gap exists between borrowers' expectations and actual lending experiences. This study is conducted among customers of SBI and Bajaj finance which are Ranchi based branches. Primary data is collected through proper questionnaire among total 100 respondents. Study is of quantitative research approach, and some statistical tools were used like descriptive statistics, reliability analysis and independent sample t-test and pair sample t-test for data analysis was used by using IBM SPSS. Hypothesis testing was performed to compare borrowers experience between SBI and BAJAJ finance and examine whether any significant perception gap. The findings show the need to give importance to transparency, customer centric service delivery or digital convenience which enhances customer satisfaction. The study recommends that there is a need to improve transparency in loan related charges and there should be simplified documentation process, there is a need to critically develop borrowers experience and lending perception index so that customers can monitor which institutions can meet their actual satisfaction.

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 Keywords

borrowers experience, perception gap, lending services, SBI, Bajaj Finance.

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Creative Commons Attribution 4.0 and The Open Definition

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Digital journaling has become a popular medium for recording personal experiences, emotions, and daily reflections. Despite generating valuable longitudinal data, most journaling platforms primarily serve as storage systems and provide limited support for understanding emotional trends, behavioral patterns, or personal growth opportunities. This paper presents an AI-powered framework that transforms journal entries into actionable insights through the integration of emotion recognition, behavioral insight generation, and personalized recommendation mechanisms. The proposed framework analyzes journal content to identify emotional states, extract meaningful contextual information, and generate structured insights related to behavioral patterns, recurring challenges, strengths, and goal-oriented actions. To further enhance user engagement and self-improvement, the framework delivers personalized recommendations by combining emotional context, semantic understanding, and user preferences. A feedback-driven adaptation mechanism continuously refines user representations, enabling recommendations and insights to evolve with changing user behavior. By converting unstructured journal data into meaningful and personalized guidance, the proposed framework extends digital journaling beyond passive reflection and supports continuous self-awareness, decision-making, and personal development.

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 Keywords

Emotion Recognition, Behavioral Insight Generation, Personalized Recommendation, Digital Journaling, Natural Language Processing, User Modeling, Artificial Intelligence

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Creative Commons Attribution 4.0 and The Open Definition

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The cabin floor of a vehicle plays a critical role in structural integrity, NVH (Noise, Vibration, Harshness) performance, and crashworthiness. Optimization of the cabin floor can significantly improve stiffness, modal frequencies, and durability without substantially increasing mass. Topography optimization is a subset of structural optimization techniques where design features such as ribs, beads, and surface reinforcements are intelligently placed on a base surface to improve stiffness, reduce stress concentrations, and control deformation modes under given loading conditions. Unlike topology or shape optimization, which can drastically alter geometry, topography optimization maintains the overall shape but refines the surface features, making it especially useful for components like floor panels in automotive or aerospace applications. The floor panel under study is subjected to real-world loading scenarios such as distributed loads, point loads, and boundary conditions and support regions. The primary objectives are to maximize stiffness (minimize compliance), reduce mass, and maintain acceptable vibration and NVH (Noise, Vibration, Harshness) performance. Commercial CAE tools such as Altair Optistruct are used to carry out the finite element analysis and optimization process. A baseline design is first analyzed to understand its deformation and stress distribution. Then, topography optimization is performed to introduce bead patterns that improve stiffness with minimal material addition. Design constraints include manufacturing feasibility, such as draw directions for stamping and limits on bead height and spacing. The optimized design is then evaluated against the baseline in terms of weight, stiffness, natural frequency, and stress distribution.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Optistruct, Hypermesh, Catia, Topography Optimization

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cyberbullying is a growing concern among adolescents due to increased digital technology use. This study evaluated the effectiveness of a Structured Teaching Programme (STP) on cyberbullying knowledge among 60 adolescents in selected schools of Mehsana City. A pre-experimental one-group pretest-posttest design was used. The findings showed a significant improvement in knowledge scores after the intervention. The study concludes that STP is an effective strategy for enhancing cyberbullying awareness among adolescents.

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A STUDY TO ASSESS THE EFFECTIVENESS OF A STRUCTURED TEACHING PROGRAMME ON KNOWLEDGE REGARDING CYBERBULLYING AMONG ADOLESCENTS IN SELECTED SCHOOLS OF MEHSANA CITY, GUJRAT

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The global rise of multidrug-resistant bacterial and fungal pathogens poses a critical challenge to clinical medicine, driving the demand for novel pharmacophores. Pyrazole heterocycles represent a privileged scaffold capable of bypassing established resistance mechanisms. Here, we report the design, synthesis, structural characterization, and in vitro antimicrobial evaluation of a novel clubbed bis-pyrazole entity: 2'-(4-chlorophenyl)-1-(2,4-dinitrophenyl)-5'-methyl-5-phenyl-2',4,4',5-tetrahydro-1H,3'H-[3,4'-bipyrazol]-3'-one. Synthesized via a multi-step condensation approach, the target compound was structurally elucidated using FTIR, 1H NMR, 13C NMR and Mass Spectral elemental analysis. In vitro screening against standard bacterial (Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa) and fungal (Candida albicans, Aspergillus niger) strains was performed using agar-well diffusion and microdilution assays. The compound demonstrated potent antimicrobial efficacy, characterized by significant zones of inhibition and low minimum inhibitory concentration (MIC) values. These results highlight the synergistic potential of integrating a halogenated phenyl moiety with a formylated bipyrazole core to develop potent, broad-spectrum antimicrobial agents.

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 Keywords

Pyrazole, oxobutyrates, Antimicrobial activity, MIC

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