Volume 13 | Issue 7 |

 Abstract

Unemployment in India has been persistent issue. The Indian economy is facing a major slowdown due to increasing rate of unemployment. Unemployment has resulted in under-utilization of human resources. The ever-growing population of India requires great employment opportunities. Moreover, there are not enough number of jobs to absorb the bulging workforce. In this regard the Prime Minister Employment Generation Programme (PMEGP) is playing a crucial role in promoting self-employment opportunities through micro and small industries development by encouraging the first-generation new entrepreneurs. The study aims to evaluate the performance of the scheme among various category of beneficiaries. The paper focuses to study the growth of small and medium enterprises under the PMEGP scheme in Simdega district of Jharkhand and also analyses the importance of this scheme in employment generation.

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 Keywords

Unemployment, Self-employment, employment generation, PMEGP scheme

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This study investigates the key drivers behind elevated fund inflows into the Indian financial market. Employing a mixed-method approach that combines quantitative time-series analysis of macroeconomic, foreign, and domestic data (2023-2025) with qualitative insights from interviews, this paper identifies four primary determinants: (1) global macroeconomic dynamics, particularly U.S. monetary policy and currency trends; (2) robust domestic retail participation via systematic investment plans (SIPs) and domestic institutions; (3) ease of regulations governing foreign investments; and (4) relative valuation and sectoral attractiveness. Regression results reveal significant correlations between fund inflows and U.S. rate differentials as well as SIP growth. The findings underscore the interplay between external and internal factors, highlighting implications for policymakers and investors.

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Fund Infusion, Inflows, Indian Financial Market, Foreign and domestic data, Currency trends.

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Abstract: Trapezius spasm can be well-defined as "an inflammation of the neck and upper back muscle" named trapezius, which involves myofascial pain syndrome. This muscle helps in actions like shrugging shoulders and neck movements such as neck extension, which is produced by the bilateral contraction of descending trapezius fibers, while lateral flexion of the neck is produced by the unilateral contraction of descending fibers. Its prevalence is highest in females of middle age and less common in males, with a fluctuating mean point prevalence of 13%, and neck pain usually occurs in the upper trapezius muscle [1] This study follows a randomized controlled trial (RCT) design to compare the effectiveness of Myofascial Release (MFR) Technique and Cryotherapy in relieving pain and improving cervical range of motion (ROM) in patients with upper trapezius spasm. In conclusion, both Myofascial Release and Cryotherapy are effective in reducing pain and improving cervical range of motion in patients with upper trapezius spasm.

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 Keywords

Muscle Energy Techniques (MET), positional release therapy (PRT), myofascial release technique (MFR), Trapezius spasm

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Anthony Doerr's Cloud Cuckoo Land offers a posthuman narrative that reimagines libraries and literature as dynamic, multispecies ecosystems. The paper aims to explore how Doerr's novel transcends traditional anthropocentric storytelling by portraying interspecies and intertemporal connections that highlight the resilience of both human and non-human actors. Through posthuman theory, particularly the works of Donna Haraway, Rosi Braidotti, and Bruno Latour, the paper attempts to examine the novel's treatment of libraries as living, ecological networks that persist across time, geography, and species boundaries. Central to the novel is an ancient Greek text that weaves through multiple timelines, from 15th-century Constantinople to a dystopian future in space, connecting disparate characters and settings through its preservation and transformation. The novel's journey is not merely a human endeavour but one shaped by non-human forces such as animals, plants, fungi, and digital systems. The library is reimagined as a space where knowledge and survival are co-produced by humans, the environment, and technology. The novel's treatment of resilience moves beyond individual endurance to a collective, ecological form of survival, where literature itself becomes a collaborative, life-sustaining force. The paper argues that Cloud Cuckoo Land presents a vision of literature and knowledge as interconnected, evolving entities, offering an ecological and posthuman reconfiguration of identity, agency, and memory.

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Posthumanism, Ecological Networks, Resilience, Cloud Cuckoo Land Anthony Doerr, Temporal Networks, Multispecies Ethics

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These sources collectively explore the historical and sociological dimensions of Devi (Goddess) worship in Kerala, South India, with a particular focus on Bhadrakali and Kali. They discuss the evolution of these cults from ancient, possibly non-Aryan, traditions, including the influence of matriarchal societies and folk practices like animal sacrifices. The texts highlight various ritualistic art forms such as Mudiyettu, Theyyam, and Padayani, which often depict the myth of Bhadrakali slaying the demon Darika and feature male performers embodying female deities. Furthermore, the sources examine how these democratic, emotional forms of worship have interacted with and been assimilated into Brahminical and Tantric traditions, while still retaining their non-Brahmin features and community participation.

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Cult,Mother Goddess,Shaktism,traditions,rituals,matriarchy

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The effluent and solid waste of the Chlor-alkali industry contained significant amount of mercury. The effluent after joining the Rushikulya River significantly changes the physico-chemical properties of river water. The river water which is used for irrigation contained significant amount of mercury. Significant variation was recorded in temperature, pH, hardness, chlorinity, dissolved oxygen, BOD, COD, suspended solids, total nitrogen, total phosphorus and mercury content. The mercury concentration significantly varied in all the 5 stations of the effluent canal. The sediments collected from the effluent canal were dumped nearby. It was observed that the solid waste contained significant amount of mercury much more than prescribed limit. The lechate and washings enter into the river during rainy season increasing the mercury level in the river water. This river water was used to irrigate the crop fields at down stream. To study the impact of lechate on seed germination and seedling viability laboratory experiments were conducted taking rice crop seeds. The concentration of mercury was maintained in all the experiments. Solid waste was taken and air dried, powdered. The solid waste powder (1kg) was taken mixed with distilled water (2L) and stirred for 15days at 2hrs interval. After 15 days of stirring the whole content was allowed to sediment and the extract was decanted and kept in the fridge for experiment. The seed germination and seedling establishment decreased with the increase in solid waste extract concentration, when compared to the respective control values. The pigments like total chlorophyll, total pheophytin and carotenoid content significantly decreased in exposed seedling leaves compared to control seedling leaves of rice crop seedlings. The effluent and solid waste of the industry is highly toxic and should not be released into the environment as both the toxicants severely affect the environment and plants.

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Chlor-alkali industry, Effluent, Solid waste, Residual Mercury, Crop plant, Pigment, Chlorophyll, Pheophytin, Carotenoid

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The Bharatiya Nagarik Suraksha Sanhita (BNSS), 2023, replaces the colonial-era Code of Criminal Procedure (CrPC), 1973,with the objective of addressing inefficiencies in the criminal justice system. This paper examines the limitations of Cr.PC in addressing delays and prison healthcare, while analyzing how BNSS introduces systemic reforms to mitigate overcrowding and ensure timely medical intervention for inmates. By introducing stricter timelines for investigations, mandatory case reviews, and digitalized legal procedures , BNSS aims to ensure faster delivery in criminal justice system. The delay in the criminal justice system has a profound impact on the health and well-being of prisoners, particularly under-trial detainees. Through a socio-legal analysis, the researcher evaluates how prolonged trials contribute to physical and mental health deterioration, exacerbated by overcrowding, lack of medical facilities, and procedural inefficiencies .The Bharatiya Nagarik Suraksha Sanhita (BNSS), 2023, introduces key reforms, including speedy trial provisions, bail reforms, and mandatory healthcare measures, to address these challenges. However, the effectiveness of these provisions depends on their proper implementation. By analyzing existing policies and proposing strategic interventions, this study highlights the urgent need for a justice system that safeguards not only legal rights but also the fundamental health needs of prisoners. It argues that ensuring timely justice is essential not just for legal fairness but also for protecting prisoners' dignity, health, and human rights. Furthermore, the study highlights the role of technology-driven legal management in enhancing transparency and accountability, which can lead to improved healthcare services within prisons. This paper critically examines the gaps in Cr.PC,1973 concerning judicial delays and prison healthcare, while analyzing the potential of BNSS,2023 in addressing these systemic issues. The study explores the correlation between prolonged incarceration, deteriorating health conditions, and the need for expedited judicial processes .Through an analysis of the BNSS and its impact on the efficiency of the justice system, this study advocates for a holistic approach that integrates legal, administrative, and healthcare improvements within correctional facilities.

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Human rights, Judicial delays, Prisoners' wellbeing, Access to justice.

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The present study investigates the teacher effectiveness of secondary school teachers in Guntur district, Andhra Pradesh, with a focus on demographic variables such as gender, marital status, locality, and educational qualification. A total of 300 teachers were selected using stratified random sampling. The Teacher Effectiveness Scale (KTES) developed by Umme Kulsum (2000) was employed to measure teacher effectiveness across five domains: preparation and planning, classroom management, subject knowledge and delivery, teacher characteristics, and interpersonal relations. The data were analyzed using Mean, Standard Deviation, and t-tests. The results revealed that female teachers, married teachers, and urban teachers had significantly higher levels of teacher effectiveness compared to their counterparts. However, no significant difference was found between graduate and post-graduate teachers. These findings highlight the role of demographic and contextual factors in influencing teaching effectiveness and underscore the importance of supportive environments and continuous professional development to enhance educational quality at the secondary level.

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Teacher Effectiveness, Secondary School Teachers, Preparation and Planning, Classroom Management, Subject Knowledge and Delivery, Teacher Characteristics, And Interpersonal Relations.

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Environmental, Social, and Governance (ESG) factors have emerged as critical dimensions of corporate accountability and long-term value creation. As global stakeholders demand greater transparency, firms increasingly adopt ESG disclosure practices. This paper examines how industry peer effects influence ESG disclosure behavior, highlighting how companies benchmark peers to align with industry norms. Drawing on institutional theory and panel data analysis, the study confirms that firms mimic peer ESG practices to maintain legitimacy and competitive advantage. While peer effects can improve overall reporting standards, they also present challenges such as inconsistent disclosures and greenwashing risks. The paper concludes with recommendations for corporate leaders and policymakers to harness peer effects for more credible and comparable ESG reporting.

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ESG Disclosure, Peer Effects, Institutional Theory, Corporate Governance, Sustainability Reporting

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Artificial Intelligence (AI) is transforming many fields, and plant digital phenomics is no exception. The intersection of AI and plant phenomics-- the study of plant traits and their variation-- is paving the way for significant advancements in agriculture, ecology, and plant sciences. Here's a primer on how AI is shaping this field, focusing on the journey from data to insights: Plant digital phenomics involves the collection and analysis of detailed, quantitative data on plant traits using digital tools. These traits can include growth rates, leaf shape, flower color, and stress responses. The goal is to understand the genetic, environmental, and physiological factors that influence plant development and performance. Efficient image recognition is important in crop and forest management. However, it faces many challenges, such as the large number of plant species and diseases, the variability of plant appearance, and the scarcity of labeled data for training. To address this issue, we modified a SOTA Cross-Domain Few-shot Learning (CDFSL) method based on prototypical networks and attention mechanisms. We employed attention mechanisms to perform feature extraction and prototype generation by focusing on the most relevant parts of the images, then used prototypical networks to learn the prototype of each category and classify new instances. Finally, we demonstrated the effectiveness of the modified CDFSL method on several plant and disease recognition datasets. The results showed that the modified pipeline was able to recognize several cross-domain datasets using generic representations, and achieved up to 97.85% and 95.06% classification accuracy on datasets with the same and different domains, respectively. In addition, we visualized the experimental results, demonstrating the model's stable transfer capability between datasets and the model's high visual correlation with plant and disease biological characteristics. Moreover, by extending the classes ofdifferent semantics within the training dataset, our model can be generalized to other domains, which implies broad applicability.

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 Keywords

AI, image characteristics ;ML, CDFL; learning transformation; bark images database.

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