Thiruthangal Nadar College

Purpose: This study examines the structural, institutional, and socio-economic barriers influencing entrepreneurial outcomes, with particular emphasis on access to finance, institutional awareness, gender bias, digital adoption challenges, mentorship gaps, and market competition. The research seeks to identify the most significant predictors affecting entrepreneurial sustainability and performance.Design/Methodology/Approach: A quantitative research design was adopted using a structured questionnaire administered to 300 entrepreneurs engaged in service and retail sectors. Data were analyzed using frequency analysis, descriptive statistics, and multiple regression techniques. The regression model was employed to determine the relative contribution of identified barriers to entrepreneurial outcomes, with R² and standardized beta coefficients used to assess explanatory power and predictor strength.Findings: Limited information about government schemes and institutional support is the strongest predictor of entrepreneurial outcomes. Gender bias in business networks and challenges in adopting digital technologies also significantly influence performance. Financial constraints, competitive pressure from larger enterprises, work–life balance challenges, and lack of mentorship exhibit moderate effects. The regression model shows moderate explanatory power, indicating that institutional and structural factors shape entrepreneurial success more than individual capabilities alone.Originality/Value: This study contributes to the entrepreneurship literature by providing empirical evidence on the multidimensional barriers affecting entrepreneurial performance within emerging business contexts. It integrates institutional, structural, and socio-economic variables into a single analytical framework, offering a comprehensive understanding of entrepreneurial constraints.Practical Implications: The study recommends strengthening awareness of government schemes, promoting inclusive business networks, enhancing digital capacity-building initiatives, improving financial accessibility, and institutionalizing mentorship programs. Policymakers and support institutions can utilize these findings to design integrated strategies that foster sustainable entrepreneurial ecosystems.

Millennial women are getting of more of a and the more of a crucial jobs in a rapidly evolving of industry of the information technology. Its workplace compatibility, or how the effectively it can fulfil both the organizational and the personal goals, an is very essential when it comes to the its goals for a behavior, such as the being creative, loyal, and the staying on the job. Even though a lot of it companies are working of to the remedy the problem, an it is challenging of for a them to the keep millennial women on staff. The reasons for a this are that there aren't enough possibilities to the advance forward in a your job, there is bias against women, and the there is an imbalance between the work and the life. to the promote employee satisfaction and the long-term organizational advancement, an it is essential to the understand the impact of the work compatibility on behavioral intentions. Structured questionaires and the semi-structured interviews are employed to the collect data from the 200 millennial women employed at leading of information technology firms in a Chennai. The study has used a mixed-methods approach. We has used a Likert scale poll to the judge how well the work fit together. These criteria included, but are not limited to, role clarity, adaptability, support mechanisms, and the professional recognition. We has used regression and the structural equating modeling (SEM) to the analyze the data in a order to the determine the presence of the an associating between the work appropriateness and the individuals with the behavioral intentions. The findings indicate that employees with the intentions to the take acting are significantly have influenced by opportunities for a professional advancement, managerial support, and the enhanced flexibility in a working of conditings. There was a positive link between the higher work compatibility and the greater loyalty to the organization, less desire to the leave, and the more of a willingness to the try new things.

The SecureSustainNet Framework- a novel technique for enhancing security and sustainability in data centers is introduced in this paper. Given the security and sustainability concerns with data centers, this paper tackles the challenge of balancing data center security and energy efficiency. Existing solutions are unable to provide the required security level without large processing and power costs. States existing approaches that combine efficient resource utilization with high security performance is identified as a research gap. The multi-objective optimization of those approaches is designed to incorporate energy, efficient techniques and security functionalities. The approach has 6 main algorithms; Intrusion Detection System with Anomaly Detection; AES, 256 encryptions with virtualization, based key management; Role Based Access Control RBAC with dynamic policy tuning; dynamic resource allocation; energy consumption monitoring and management; and renewable source integration. The framework has been implemented into the network simulator ns, 3. A remarkably high 98.7% Anomaly Detection Rate ADR was elicited through an interpreter Intrusion Detection System IDS against Gaussian Mixture Models GMM, 6.4% above existing approaches, with a mean 0.4% False Positive Rate FPR. It achieved a 2.5% increase in processing time due to its AES, 256 Encryption system through which employ a dynamically managed key management system. It attained a 97.4% Access Control Effectiveness (ACE) and an 8.8% increase against traditional models through its dynamic policy adaptations based on user context. It obtained an 85.2% Resource Utilization Efficiency RUE and a 7% increase over its competitors while reducing the energy consumption by 15.6% through its efficient resource utilization. The power usage effectiveness PUE of the system was calculated as 1.25, a far cry from current models that achieved it as high as 1.47

When it comes to healthcare management driven by the Internet of Things (IoT), a revolutionary solution for safe and effective cloud storage has emerged with the combination of blockchain and machine learning (ML). This article delves into the important issues surrounding the privacy, security, scalability, and real-time processing of data that are intrinsic to healthcare systems that use the Internet of Things. A hybrid framework is proposed, combining blockchain’s decentralized and tamper-proof architecture with ML’s capability for real-time anomaly detection and predictive analytics. The proposed solution ensures robust data security, enhances system scalability, and provides intelligent insights for improved healthcare delivery. Experimental evaluations demonstrate the effectiveness of the framework in mitigating cyber threats, ensuring data integrity, and optimizing performance in IoT healthcare environments. Blockchain and ML have the ability to revolutionise safe cloud storage, according to this research. This might lead to improvements in healthcare IoT systems.

The title compound, C22H16N4O2, crystallizes in the monoclinic space group P21/c with two independent molecules, A and B, in the asymmetric unit. The isoxazole ring is inclined to the pyridine ring system, the indoline ring, and the phenyl ring by 8.00 (10), 70.93 (10), 35.89 (12), respectively, ° for molecule A,and 4.24 (10), 84.62 (9),30.02 (11)° for molecule B. In the crystal, molecules are linked by C—H...O and C—H...N interactions, forming layers parallel to the (100) plane. In addition π–π interactions with centroid-to-centroid distances of 3.8057 (12) Å and a series of C—H...π interactions help to consolidate the packing in a three-dimensional architecture within the crystal. Additional electron density was localized in voids (398 Å3 solvent accessible volume) summing up to 92 electrons, which corresponds to approximately 3.5 molecules of ethanol. The given chemical formula and other crystal data do not take into account the solvent.