Volume 13 | Issue 12 |

 Abstract

In today's competitive job market, possessing technical knowledge alone is insufficient for securing employment through campus interviews. Employers increasingly emphasize soft skills--such as communication, teamwork, problem-solving, adaptability, and emotional intelligence--as essential indicators of a candidate's workplace readiness. This article explores the significance of soft skills for college students, highlighting the gap between academic learning and industry expectations. It examines key soft skills required during campus interviews, the challenges students face in developing them, and effective strategies for refinement, including self-assessment, workshops, extracurricular involvement, and mentorship. The role of colleges in integrating soft skill development into the curriculum and providing practical exposure is also discussed. Through case studies and practical examples, the article demonstrates how focused efforts on soft skill enhancement improve employability and interview performance. Finally, recommendations are provided for students to systematically cultivate these skills, ensuring success not only in campus interviews but also in long-term career growth.

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 Keywords

Soft Skills, Campus Interviews, Employability, Communication, Teamwork, Professional Development

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Creative Commons Attribution 4.0 and The Open Definition

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: Migraine, referred to as Shaqiqa in the Unani system of medicine, is a chronic, episodic headache disorder that predominantly affects one side of the head and has been documented since ancient times. Classical Unani scholars described Shaqiqa within the framework of humoral imbalance and deranged temperament (miz?j), emphasizing the influence of dietary habits, emotional states, lifestyle factors, and environmental exposures. In contrast, modern medicine characterizes migraine as a complex neurovascular disorder involving genetic predisposition, altered cortical excitability, trigeminovascular activation, and neurogenic inflammation. This narrative review explores the historical development of migraine concepts in Unani and modern medical literature and critically examines etiological factors and triggering mechanisms described in both systems. Classical Unani texts identify prolonged fasting, excessive exertion, menstrual irregularities, emotional stress, sleep deprivation, gastrointestinal disturbances, sensory overload, and specific dietary factors as major precipitants of Shaqiqa. Contemporary biomedical research reports remarkably similar triggers, including psychological stress, hormonal fluctuations, irregular sleep patterns, dietary components, sensory stimuli, and environmental changes. Despite differences in theoretical explanations, both traditions demonstrate striking convergence in clinical observations and preventive strategies. Integrating Unani and modern perspectives may therefore provide a more comprehensive understanding of migraine and support the development of patient-centered, integrative management approaches.

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; Migraine, Shaqiqa,, Sudae Nisfi, Adhasisi (Hemicrania), Sudae Ghasyani (Sick Headache), Akhlat -e- Arbaa ,,Humours ,Mizaj

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Earthquake-induced structural damage remains one of the most significant challenges in structural engineering, with recent seismic events highlighting the limitations of traditional force-based design approaches. This research paper examines the evolution from conventional force-based seismic design to performance-based design methodologies, exploring advanced structural systems that enhance building resilience and minimize post-earthquake damage. The paper investigates innovative technologies including base isolation systems, buckling-restrained braces, self-centering structures, and fiber-reinforced polymer retrofitting techniques. Through comprehensive analysis of recent case studies and emerging trends, this research demonstrates how performance-based seismic design combined with advanced materials and structural health monitoring can significantly reduce life-cycle costs while improving structural safety and post-earthquake functionality. The integration of machine learning and artificial intelligence in structural analysis further enhances predictive capabilities and optimization of seismic design parameters. The findings indicate that displacement-based design approaches provide more consistent and economical solutions compared to traditional methods, particularly in moderate seismic regions, while self-centering systems offer superior resilience through damage concentration in replaceable components and elimination of residual deformations.

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Creative Commons Attribution 4.0 and The Open Definition

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Performance-based seismic design, base isolation, buckling-restrained braces, self-centering systems, structural resilience, displacement-based design, fiber-reinforced polymers

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Rotheca serrata, Phytochemical screening, Antioxidant activity, Phenolic content, DPPH assay, Manipur

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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The existing model of pharmaceutical research and development (R&D) is marked by lengthy timelines, exponentially rising expenses, and a clinical trial failure rate surpassing 90%, leading to considerable uncertainty in the portfolio. This review explores the revolutionary use of Artificial Intelligence (AI) and Machine Learning (ML) in forecasting the chances of regulatory approval for pharmaceutical candidates. AI models provide a robust decision-support system by combining various datasets, such as molecular properties, preclinical findings, clinical trial information, and past regulatory results. Essential processes include Natural Language Processing (NLP) for deriving insights from unstructured documents and the application of predictive modeling to estimate success chances. We examine the strategic effects of R&D prioritization, as well as the significant issues concerning data bias, the opaque characteristics of algorithms, and the need to create Explainable AI (XAI) frameworks to build regulatory confidence and expedite the provision of safe and effective treatments.

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Drug Approval Prediction, Artificial Intelligence, Machine Learning, Clinical Trials, Portfolio Management, Explainable AI (XAI), Regulatory Risk

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A strategic instrument for influencing consumer behavior, integrated marketing communication (IMC) is especially useful for teens, who are particularly sensitive to marketing and media stimuli. Determining the association of different IMC tools--public relations, social media marketing, sales promotion, advertising, and personal selling--on the buying behavior of male and female teenagers is the goal of this study. The study examines 100 teenagers between the ages of 13 and 19 using a structured questionnaire. The results demonstrate a significant association between gender and buying behavior based on Direct marketing, Advertising, Personal selling, and Sales promotion, and an insignificant association with Public relations.

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IMC Tools, Buying behavior, Teens, Gender, Association

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The problem of motorcycle collisions is one of the leading issues of road safety, but the danger is not constant all the time and all day. vehicle characteristics. This paper conducts statistical research into the data on motorcycle crashes to address three useful questions: (1) at what times of the day collisions were concentrated (and are still concentrated) (peak hours), (2) are collisions. more probable on weekends than on weekdays, and (3) patterns of collision varying between vehicle makes and whether make and day type are independent variables. We start with descriptive profiling of collision frequency by car model and time of collision, and a sharp peak in late-afternoon hours. Next, we use Bayes' Rule to compare the conditional likelihood of observing a crash on weekends versus weekdays. Finally, we test the independence of vehicle make and day type using Pearson's Chi-Square test, finding strong evidence of dependence between make and whether a collision occurs on a weekday or weekend. Together, these results suggest that motorcycle collision occurrence varies meaningfully with temporal context and vehicle-make composition, motivating targeted safety messaging and enforcement strategies that align with peak-hour and weekend-driven risk patterns

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Motorcycle collisions; peak hours; weekend effect; Bayes' Rule; chi-square test; independence testing

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Creative Commons Attribution 4.0 and The Open Definition

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This article explores the transformative impact of British colonial educational policies on the Indian subcontinent, specifically the introduction of English as a medium of instruction and its subsequent role in fostering both a new intelligentsia and a linguistic divide. It further examines the reactive rise of regional language movements, culminating in the establishment of the Kerala Bhasha Institute. By analyzing the Institute's fifty-year history, the study evaluates its role in bridging the gap between scholarly knowledge and the vernacular, ensuring that Malayalam remains a vibrant medium for scientific, technological, and academic discourse.

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The Dual Legacy: Colonial Education, Regional Languages, and the Evolution of the Kerala Bhasha Institute

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This conceptual paper outlines a model, rooted deeply in established theory, that aims to decode the relationship between external marketing levers and final consumption results. The model investigates how core stimuli, such as pricing strategies, product availability, promotional deals, quality cues, product packaging, and social influence, directly affect consumer outcomes, including how often products are purchased, whether a brand is adopted, the variety of products bought, and overall spending. The framework is built upon the foundational principles of several key behavioral theories: Stimulus-Organism-Response (S-O-R) Theory, Trait Activation Theory (TAT), Signalling Theory, Social Influence Theory, and Consumer Personality Theory. Crucially, the model proposes that inherent consumer traits specifically perfectionism, brand consciousness, novelty seeking, and price consciousness do not just influence, but act as essential moderating mechanisms. These traits filter and shape the impact of external marketing cues, ultimately translating them into specific consumer buying behaviors. The paper concludes by consolidating these theoretical foundations and formally presenting conceptual propositions that can be tested through future empirical research.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Marketing Stimuli, Consumer Traits, Consumption Outcomes

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Creative Commons Attribution 4.0 and The Open Definition