Volume 14 | Issue 7 |

 Abstract

Aluminium-copper (Al-Cu) alloys are widely used in aerospace, automotive, defence, and structural engineering applications because of their high specific strength, excellent machinability, and favourable strength-to-weight ratio. However, under rigorous service circumstances, wear, residual stresses, and microstructural instability frequently restrict their mechanical performance. Through grain refinement, precipitation strengthening, and residual stress reduction, deep cryogenic treatment (DCT) has become a successful post-processing method for enhancing the mechanical and tribological performance of Al-Cu alloys. The mechanical characterization of cryogenically treated Al-Cu alloys based on experimental studies and finite element analysis (FEA) is thoroughly reviewed in this work. The review critically investigates how microstructural evolution and mechanical properties are affected by cryogenic treatment factors such as cooling rate, soaking temperature, soaking duration, and post-aging. In addition to microstructural characterization using optical microscopy, scanning electron microscopy (SEM), and X-ray diffraction (XRD), experimental studies on hardness, tensile strength, yield strength, ductility, fatigue performance, wear resistance, and impact behavior are systematically analyzed. Recent developments in finite element analysis for predicting stress distribution, strain behavior, deformation characteristics, and residual stresses are reviewed, with an emphasis on the role of constitutive material models and experimental validation. Finite element analysis successfully predicts the mechanical response of cryogenically treated Al-Cu alloys while cutting development time and experimental expenses, according to a comparison of experimental results with numerical simulations. Multistate modeling, machine learning-assisted material optimization, digital twin technology, and integrated experimental-computational techniques for the design of high-performance Al-Cu alloys are only a few of the future prospects and research gaps identified by the review. For researchers and engineers working on cryogenic processing, mechanical characterization, and computational modeling of advanced aluminum alloys, this review offers a thorough resource.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hardfacing, Deep Cryogenic Treatment, Finite Element Analysis

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Background Oral diseases remain among the most prevalent chronic conditions affecting children worldwide and continue to represent a significant public health challenge. Early diagnosis is essential for preventing disease progression and reducing long-term morbidity. Saliva has emerged as a promising diagnostic medium because it contains a wide range of proteins, inflammatory mediators, microbial constituents, nucleic acids, and metabolites associated with oral and systemic health. Recent advances in artificial intelligence (AI) and machine-learning technologies have enabled rapid analysis of complex biological datasets, facilitating disease prediction and personalized healthcare. The present study aimed to evaluate the role of AI-assisted salivary biomarker analysis in the early detection of oral diseases among children aged 6-12 years. Materials and Methods A cross-sectional analytical study was conducted among 120 children aged 6-12 years. Participants were categorized into healthy and oral disease groups based on clinical findings. Unstimulated saliva samples were collected and analyzed for interleukin-6 (IL-6), matrix metalloproteinase-8 (MMP-8), C-reactive protein (CRP), salivary pH, and Streptococcus mutans counts. Machine-learning algorithms including logistic regression, decision tree analysis, support vector machine, and random forest classification were employed to evaluate biomarker-based disease prediction. Statistical analysis included Student's t-test, Chi-square test, Spearman correlation, and receiver operating characteristic curve analysis. Results Children with oral disease demonstrated significantly elevated salivary IL-6, MMP-8, CRP, and Streptococcus mutans levels compared with healthy participants. Salivary pH was significantly lower in the disease group. Among the machine-learning models evaluated, the random forest classifier demonstrated the highest predictive accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve. Significant positive correlations were observed between inflammatory biomarkers and disease severity. Conclusion Artificial intelligence-assisted salivary biomarker profiling demonstrated promising potential for early identification of pediatric oral diseases. Integration of salivary diagnostics with machine-learning algorithms may provide a rapid, noninvasive, and cost-effective screening approach in pediatric dentistry. Clinical Significance AI-driven salivary diagnostics may facilitate early disease detection, individualized preventive strategies, and improved clinical decision-making in pediatric oral healthcare.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial intelligence, Biomarkers, Early diagnosis, Machine learning, Oral diseases, Pediatric dentistry, Saliva

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Siliguri Corridor, sometimes known as India's "Chicken's Neck," is one of the most perilous regions in South Asia. This land-based chokepoint is the only way for the mainland to access India's Northeastern region, which is rich in resources (Bharali, 2020, p. 1). At its narrowest point, it is only 22 km wide. This essay reevaluates the strategic security of the Siliguri Corridor using Kautilya's Mandala (Circle of States) from the ancient Indian classic, the Artha shastra. This research amalgamates classical realism in statecraft with contemporary multi-domain security issues, situating India as the Viji Gishu (the nucleus, aspiring power) and its bordering nations within concentric circles of intrinsic conflict and potential collaboration. This study suggests that the Ari (China, a natural enemy) is increasing its presence through the Chumbi Valley and the Doklam Plateau. Kautilya's text also describes Madhyama (Middle Ruler) as a state positioned between the aspiring conqueror and the enemy, acting as a conceptual buffer, and Mitra as an ally (Gautam et al., 2015, p. 53). Nepal, Bhutan, and Bangladesh exemplify these states. The results suggest that military defences alone will not be enough to protect the corridor; instead, they require Kautilyan Upayas (diplomatic strategies). This means improving infrastructure, fostering economic interdependence with these buffer countries, and employing a diverse range of diplomatic methods to address both new and enduring challenges.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Siliguri Corridor, Kautilya, Mandala Theory, Chokepoint, Geopolitics, Indian Foreign Policy, Strategic Security

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Digital technologies are changing the way organizations manage their human resources. Tools such as Artificial Intelligence (AI), HR analytics, Human Resource Information Systems (HRIS), automation, and cloud-based platforms have made HR processes faster, more efficient, and more data-driven. However, as organizations become increasingly dependent on technology, there is a growing concern that important human values such as trust, empathy, fairness, transparency, and employee well-being may be overlooked. This study explores how organizations can achieve a balance between digital innovation and human-centered HR practices. It proposes a conceptual framework to examine the relationship between Digital HR Transformation, employee experience, human values, and organizational performance. The study adopts a quantitative research approach, and the proposed model will be tested using Structural Equation Modeling (SEM). The findings are expected to contribute to the growing field of Digital HRM by highlighting the importance of integrating technology with human values to create more sustainable, ethical, and employee-focused workplaces.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital HR Transformation, Artificial Intelligence, HR Analytics, Human Values, Employee Experience, Organizational Performance.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Water is the second most important and essential element on the earth which sustains life. Life cannot be imagined without water. Although the quality of life is improving but it is occurring at the cost of natural resources. Contamination of drinking water due to industrialisation, increase in population, improper utilisation of water, intermixing of sewer and pesticides with fresh water are the most important issues of the country. Presence of various pollutants in water cause severe threat to survival of the human beings and eco system. Drinking water polluted with trace metals and pesticides posess carcinogenic nature.This review examines the major causes and consequences of water pollution in Punjab and solutions.The review also gives insights into government efforts,local responses and the role of technology in mitigating this problem.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pollution, Pollutants, Contamination, Water, Pesticides

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Calotropis procera (family: Apocynaceae) is a medicinal plant widely recognized for its significant pharmacological properties, particularly its anti-inflammatory potential. The present study aimed to evaluate the phytochemical constituents, investigate the anti-inflammatory activity of C. procera leaf extract, and develop a stable topical cream formulation for therapeutic use. Leaves of C. procera were collected, authenticated, shade-dried, and powdered. The extraction was carried out using methanol by cold maceration (1:10) for 48 hours with intermittent shaking, followed by filtration and concentration. Preliminary phytochemical screening of the extract revealed the presence of important secondary metabolites such as flavonoids, alkaloids, tannins, and phenolic compounds, which are known to contribute to anti-inflammatory activity.The mechanism of action was associated with the inhibition of pro-inflammatory mediators, including TNF-?, IL-1?, IL-6, and INF-?, indicating suppression of inflammatory pathways linked to cyclooxygenase and lipoxygenase enzymes. A topical cream formulation was prepared using beeswax, liquid paraffin, methyl paraben, and triethanolamine through emulsification at controlled temperature. The formulation was evaluated for physicochemical parameters such as pH, spreadability, homogeneity, washability, and irritability. The cream exhibited a pH of 6.9, smooth texture, good spreadability (0.66 cm/sec), and non-irritant nature, indicating its suitability for dermal application. The anti-inflammatory activity of the formulation was further confirmed by the albumin denaturation assay, demonstrating significant inhibition of protein denaturation. These findings highlight the therapeutic potential of Calotropis procera extract in topical formulations for the management of inflammatory conditions.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Calotropis Procera, Crude Extract, Anti-inflammatory Cream Formulation, Evaluation.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Digital technology now shapes almost every part of daily life, from learning and work to communication, banking, and access to public services. While this shift has opened new opportunities, it has also increased people's exposure to cyber risks such as phishing, identity theft, cyberstalking, online harassment, misinformation, data leaks, and financial fraud. Women often face these risks more sharply because digital access, confidence, social freedom, and support systems are still unequal in many contexts. This paper explores how cyber security awareness and education can help women become safer, more confident, and more resilient in digital spaces. It argues that women's cyber security should not be treated only as a technical matter, but also as an issue connected to education, social justice, and public policy. Drawing on existing research and current practice, the paper examines how digital literacy, safe online habits, awareness training, and legal knowledge contribute to women's empowerment. It also proposes a practical framework based on inclusive education, community support, and institutional cooperation. Overall, the study shows that improving cyber security awareness among women is essential for building a safer and more balanced digital society.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cyber security awareness, women's digital safety, digital resilience, cyber hygiene, digital literacy, gender and technology, online harassment, information age, cyber education, women empowerment.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Occupational health risks among Indian infrastructure workers are pronounced, and there have been no docu-mented wellness interventions for this segment till date. This quasi-experimental research examined the impact of a 12-week Ayur-Yoga intervention - comprising of Ayurveda prakriti determination, lifestyle counselling and structured yoga practice - on 120 infrastructure workers in Gurugram (60 intervention and 60 waitlist control), measuring outcomes at baseline, week 12 and three months later. Significant improvement was witnessed in all outcome categories, including decrease in perceived stress levels (PSS-10 scale; d = 0.83; p < .001), where progress was fully maintained at three-month follow up. Reduction in blood pressure, musculoskeletal issues (36% decrease; p < .001) and absenteeism, along with increase in work engagement and productivity (d = 1.25; p < .001) were also observed. Program adherence was very high (attendance rate of 87%) and participant satisfaction level was positive. Efficacy of the intervention was comparable among all three prakriti types (F = 0.26; p = .769), suggesting suitability of implementation without constitution-based assessment. This study provides groundbreaking evidence for effectiveness of an Ayur-Yoga intervention in occupational environment, and has immediate policy implications for the Ministry of AYUSH and Viksit Bharat 2047.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ayurveda; occupational health; prakriti; perceived stress; workplace wellness; infrastructure workers

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper reads Ankush Saikia's Remember Death as an epistemic inquiry into how detective fiction constructs, mediates, and socializes truth. The study contends that the novel fragments testimony, privileges mediated records, and tailors a resolution that functions as a simulacrum rather than a transparent recovery of fact. The paper first situates the book against the classical Holmesian model and the genre contract that promises verifiable closure. It then offers close readings of key scenes that includes testimonies, documents and media-centred sequences. In the end, the detective's account consolidates competing fragments into a persuasive story. The analysis draws selectively on Baudrillard's notion of simulation. The analysis shows how Saikia's narrative produces social acceptance of a constructed truth. The paper treats knowledge itself as a contested terrain and concludes that Remember Death reconceives the whodunit.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Detective fiction, Simulacra, Simulation, Ankush Saikia, Thriller

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Funambulus pennantii,wildlife;ecosystem,anthropogenic pressure

  License

Creative Commons Attribution 4.0 and The Open Definition