Past Issues

Enhanced Efficiency and Stability of Solar Cells Using Graphene Oxide-TiO₂-Polymer Hybrid Nanomaterials

Abstract

This paper investigates the effect of reduced graphene oxide–zinc oxide (rGO–ZnO) polymer hybrid nanomaterials on the efficiency and environmental stability of organic solar cells (OSCs) and perovskite solar cells (PSCs). The hybrid films were prepared by incorporating rGO and ZnO into PTB7- and PVDF-based matrices and were characterized using UV–Vis spectroscopy, photoluminescence (PL), X-ray diffraction (XRD), scanning electron microscopy (SEM), current–voltage analysis, and accelerated aging tests. The results showed that the rGO–ZnO–PTB7 films exhibited about 25% higher visible-light absorption, while the rGO–ZnO–PVDF films showed about 22% improvement compared with the pure polymer films. PL intensity decreased by about 30% in PTB7-based films and 28% in PVDF-based films, indicating enhanced charge separation and reduced recombination. XRD analysis confirmed improved crystallinity through sharper and more intense diffraction peaks, while SEM images revealed smoother, denser, and more uniform morphologies with fewer voids and reduced agglomeration. In OSCs, the power conversion efficiency increased from 15.2% for pure PTB7 devices to 19.3–20.5% for rGO–ZnO–PTB7 devices. In PSCs, the efficiency increased from 14.3% for pure PVDF devices to 18.5–19.6% for rGO–ZnO–PVDF devices. Stability tests conducted at 85°C and 85% relative humidity for 500 hours showed that the hybrid OSCs and PSCs retained over 88% and 83% of their initial efficiencies, respectively. These findings confirm that rGO–ZnO hybrid nanomaterials are highly effective for improving both photovoltaic performance and long-term durability of next-generation solar cells.

प्रथम एवं द्वितीय विश्वयुद्धों में हरियाणा के सैनिकों की भर्ती, संख्या, क्षेत्रीय वितरण एवं योगदान का मात्रात्मक एवं गुणात्मक विश्लेषण तथा ब्रिटिश “मार्शल रेस” नीति का प्रभाव

Abstract

प्रथम विश्वयुद्ध (1914–1918) और द्वितीय विश्वयुद्ध (1939–1945) के दौरान वर्तमान हरियाणा क्षेत्र ने ब्रिटिश भारतीय सेना को सैनिक, संसाधन और युद्ध-संस्कृति—तीनों स्तरों पर उल्लेखनीय योगदान दिया। यद्यपि उस समय हरियाणा एक पृथक राज्य के रूप में अस्तित्व में नहीं था, बल्कि औपनिवेशिक पंजाब प्रांत तथा उससे संबद्ध रियासती संरचनाओं का हिस्सा था, फिर भी हिसार, रोहतक, गुड़गांव, करनाल और अम्बाला जैसे जिलों से सैनिक भर्ती का पैटर्न स्पष्ट रूप से दिखाई देता है। प्रथम विश्वयुद्ध के लिए उपलब्ध सांख्यिकीय सामग्री से ज्ञात होता है कि वर्तमान हरियाणा क्षेत्र से भर्ती का स्तर अत्यंत ऊँचा था और विभिन्न जिलों में इसमें पर्याप्त असमानता थी। इस असमानता का कारण केवल जनसंख्या नहीं, बल्कि ब्रिटिश “मार्शल रेस” नीति, भूमि-स्वामी कृषक समुदायों की सामाजिक स्थिति, स्थानीय अभिजन नेतृत्व, सैन्य परंपरा और ग्रामीण अर्थव्यवस्था भी थे। द्वितीय विश्वयुद्ध में भारतीय सेना का अभूतपूर्व विस्तार हुआ और भर्ती की परंपरागत सीमाएँ कुछ हद तक शिथिल हुईं, फिर भी पंजाब-हरियाणा क्षेत्र ब्रिटिश सैन्य भर्ती का एक केन्द्रीय आधार बना रहा। यह शोध-पत्र प्रतिपादित करता है कि हरियाणा की सैनिक परंपरा कोई उत्तर-स्वतंत्रता निर्मित घटना नहीं थी, बल्कि उसका औपनिवेशिक काल में ही एक मजबूत संस्थागत, सामाजिक और सांस्कृतिक आधार तैयार हो चुका था।

Enhancing Consumer Trust in Digital Currency Transactions: The Integration of Biometric Payment Systems and Blockchain Technology

Abstract

Consumer trust is one of the main conditions for the wider adoption of digital currency transactions. Although digital payments promise speed, convenience, and new forms of financial inclusion, many users remain hesitant because they fear fraud, identity theft, privacy loss, operational failure, and weak institutional protection. This paper examines how biometric payment systems and blockchain technology can jointly strengthen consumer trust in digital currency environments. Using a literature-based conceptual approach, the paper synthesizes work on trust theory, technology acceptance, digital identity, biometric authentication, and blockchain-enabled payment design. The argument advanced is that the two technologies support different but complementary layers of trust. Biometric systems mainly improve authentication trust by linking access to a user's embodied identity and by reducing dependence on passwords, cards, or other transferable credentials. Blockchain mainly improves transactional and institutional trust by increasing traceability, auditability, tamper resistance, and confidence in record integrity. However, neither technology creates trust automatically. Biometrics can trigger concerns about surveillance, template theft, bias, and exclusion, while blockchain can create anxiety about privacy, scalability, governance, and irreversibility. The paper therefore proposes an integrated trust model in which secure biometrics, privacy-preserving blockchain architecture, clear governance rules, and user-centred design operate together. It concludes that consumer trust rises most strongly when authentication is simple, fraud controls are visible, privacy protections are credible, and institutional accountability remains clear behind the technology.

Reimagining Employability: Integrating Skill Development and Industry–Academia Synergy in Higher Education

Abstract

Graduate employability has emerged as one of the defining concerns of contemporary higher education as universities face growing pressure to demonstrate economic, social, and professional relevance. At the same time, employers increasingly report persistent gaps between graduates’ academic preparation and workplace expectations, especially in relation to problem-solving, adaptability, communication, digital fluency, and applied professional judgment. This paper examines how employability can be reimagined through the integration of intentional skill development and sustained industry–academia synergy. Drawing on a structured review of scholarship on employability, work-integrated learning, university–industry partnerships, graduate capital, and skills mismatch, the study develops a conceptual synthesis of the mechanisms through which higher education institutions can strengthen graduate outcomes. The review indicates that employability is not reducible to job attainment alone; rather, it is a multidimensional construct shaped by knowledge, skills, identity, social capital, self-efficacy, and access to authentic learning environments. The findings show that fragmented or symbolic collaboration with industry has limited impact, whereas embedded partnerships—such as co-designed curricula, live projects, internships, practitioner teaching, and shared assessment—generate stronger alignment between learning and labor-market needs. The paper further argues that employability should be positioned as a whole-institution responsibility rather than an add-on service delegated to careers offices. A framework is proposed in which curriculum redesign, experiential learning, faculty engagement, employer participation, and inclusive support structures work together to create sustainable employability ecosystems. The study concludes that higher education institutions can enhance graduate employability most effectively when they combine disciplinary rigor with collaborative, practice-oriented, and future-focused models of learning.

Statistical Modelling of Moderate Distribution in Resource Allocation

Abstract

Moderate disparities in resource allocation were often overlooked in favour of extreme inequality, despite their long-term implications for fairness, access, and welfare. In the present study, the factors associated with moderate distribution patterns were examined, statistical models were constructed to predict moderate distribution outcomes, and alternative allocation strategies were evaluated. A simulated cross-sectional dataset of 60 administrative regions was created for illustrative empirical analysis. Resource allocation balance was operationalised through a Moderate Distribution Score (MDS), while explanatory variables included social need, poverty intensity, environmental vulnerability, institutional capacity, and population pressure. Correlation analysis, multiple linear regression, and random forest regression were applied. Allocation strategies were then compared through simulated policy scenarios involving equal-share, population-based, need-based, and hybrid weighted allocation rules. It was found that institutional capacity, social need recognition, and poverty intensity were positively associated with moderate distribution outcomes, whereas population pressure and environmental vulnerability exerted adverse effects. In predictive terms, random forest regression was found to outperform linear regression, although both models demonstrated acceptable forecasting ability. Among the strategy scenarios, the hybrid weighted model was found to produce the strongest balance between equity, sustainability, and efficiency, followed by the need-based model. It was concluded that moderate distribution outcomes were shaped by a combination of socioeconomic and institutional factors and that multi-criteria allocation strategies were better suited than simple equal-share rules for promoting equitable resource allocation.