Academic stress has become a concern among secondary students and higher education students in today’s educational environment. Various study habits and patterns like study session length, break frequency, structured study techniques, multitasking behaviours and mainly social media usage during studying time affects the overall well-being as there is massive usage of social media among students. This study investigates the relationship between the study habits and student stress among secondary school and higher education students in India and USA. Study is descriptive in nature, primary data is collected using a structured questionnaire, data were collected from respondents aged 14–25 years from India and USA. Findings reveal significant cross-country differences in study duration, structured scheduling, and stress levels. Multitasking and poor break management significantly increase stress and burnout risk. The moderating role of country highlights cultural variations in stress pathways.

The rapid advancement of quantum computing poses a fundamental challenge to existing consensus protocols in distributed systems, particularly those underpinning blockchain technologies. Classical Byzantine fault-tolerant mechanisms rely on computational hardness assumptions, which are vulnerable to quantum algorithms such as Shor’s and Grover’s. This study proposes a Quantum Entanglement Swapping Consensus (QESC) framework. This novel model uses entanglement swapping and Bell state measurements to enable secure, tamper-evident agree- ments among distributed quantum nodes. Building on quantum key distribution protocols (BB84 and E91) and experimental demonstrations of long-distance entanglement over 103 km of optical fibre [11], we present a theoretical model in which consensus arises from verifiable entangled correlations rather than computational puzzles. We compared QESC with Practical Byzantine Fault Tolerance (PBFT) and evaluated it across latency, fault tolerance, and eavesdropping resistance. The results show that QESC can achieve consensus finality with unconditional security guarantees. The study concludes with a discussion of the hardware limitations and a roadmap for experimental validation.

This study examines cryptocurrency market behaviour during crash conditions and evaluates the extent to which structured risk management techniques and behavioural biases affected financial losses. The study employs a quantitative design that is bolstered by qualitative observations. A structured questionnaire was used to gather primary data from (111) retail cryptocurrency traders. In order to obtain a deeper understanding of behaviour, (12) active cryptocurrency market traders were interviewed for qualitative analysis. The relationships between behavioural biases, social media influence, risk management techniques, and financial losses were examined using one-way ANOVA and Pearson correlation analysis. The results show that emotional biases like panic selling, overconfidence, FOMO, and frequent short-term trading greatly increase financial losses. A majority of respondent groups’ trading decisions were found to be influenced by social media sentiment. Most significantly, correlation analysis confirms that disciplined strategies significantly lower the magnitude of losses during times of high volatility by showing a strong negative relationship between structured risk management practices and financial losses.

In years startups have become a popular career choice for students. However, many students are still hesitant to start their businesses. One of the reasons for this is the fear of failure and the perceived risk of starting a business. Student’s views on startup failure are influenced by factors, including financial risk, lack of knowledge and experience social and family pressure and concerns about future career stability. These views play a role in shaping their entrepreneurial intentions and decision-making. This study aims to examine the students’ perceptions of startup failure and risk factors and how these perceptions affect their attitudes towards entrepreneurship. By identifying whether fear of failure and perceived risk act as barriers or motivators the research seeks to understand the mindset among students. The findings are expected to provide insights for academic institutions and policymakers in developing effective entrepreneurship education and support systems.

Startups have an important role in promoting innovations, employment and economic development. However, they have to overcome various challenges during their early growth stage. Thus, this study aims to explore the major key challenges faced by startups during their initial phase. The major challenges may include funding issues, competition in the market, managerial inexperience, regulatory hurdles and technological hurdles. This research is based on descriptive research and uses primary and secondary data. In this paper the findings of the study show that funding issues, lack of awareness among customers and operational inefficiency are the major hurdles for the growth of startups. Thus, this paper concludes that with good financial planning, guidance, support of the government and effective business planning, startups can overcome their challenges during their early growth phase.

As the global financial landscape is transitioning from a traditional ecosystem to digitally based transactions rapidly, AI models for scam detection have turned into an indispensable pillar for proactive defence. The opaqueness of automated decision-making has however caused the Human Trust conundrum that cannot be addressed by algorithmic models alone. To find out the levels of trust among the users, this paper involves comparison of consumer trust in human-in-the-loop systems versus that of completely independent systems. The mean trust score of AI systems of the survey was calculated using inferential statistics and a 5-point Likert scale, the measure of trust, and provided a mean of 3.04 and a standard deviation of 0.30, compared to the average score of a human-led systems at 2.97 and a standard deviation of 0.32. The t-test of paired samples gave a value of 0.5984, that is, there is no considerable difference between the levels of trust between the two interventions. Moreover, ANOVA tests confirmed that trust level do not differ based on age group. Chi-square provided a p-value of 0.0529, that is, there is a strong marginal tendency preferring age- based preference, although 53.45% of the participants chose instantaneous AI blocking as opposed to human verification (46.55%). The result of these findings is a situation where trust is balanced, where users perceive that the respective systems are equally reliable, despite the possibility that functional preferences for speed may be directed towards a gradual shift to automated solutions.

Present research is conducted with the objective of measuring the impact of work values of school of teachers of senior secondary level on Leadership Behavior (LB). For this work value is considered as independent variable and leadership behaviour is considered as dependent variable. Also work value is divided into 4 sub independent variables: Professionalism and Work Environment (PWE), Collaboration and Teamwork (CT), Personal and Professional Growth (PPG), Work Engagement and Motivation (WEM). Further a tool is developed on which data is collected from the respondents. For development of tool, pilot testing is done 100 sample set on 40 items which was initially narrowed to 23 after statistical analysis. Methods including principal component analysis, varimax rotation with kaiser normalization, explained percentage of variance, and Cronbach's alpha were used to determine the tool's validity and reliability. Finally, regression analysis was used on a larger sample size of 528 to look at how factors including professionalism and work environment, cooperation and collaboration, personal and professional development, and work engagement and motivation affected leadership behavior. Final findings of the research show that, work values have significant impact on leadership behavior.