Aliah University

Within Indian Education, Teacher Education constitutes of fundamental ethical concern as it shapes not just pedagogical competence but also the ethical and communal aspect of society. In the Indian context, declining ethical standards, government failures and exclusion are frequently addressed through policy reforms and nonsupervisory mechanisms. Such approaches remain insufficient without a deeper philosophical explanation. From a philosophical reflection, this paper argues that the crisis of teacher education in India is fundamentally moral in nature. Persistent exclusion, weak responsibility structures and immorally deficient government reflect a deeper normative failure rather than mere administrative shortcomings. Drawing upon normative ethics and political philosophy, particularly the ideas of Kant, Plato, John Rawls and B.R Ambedkar, the study examines ethics, government, and inclusion as interrelated moral categories. It is contended that inclusive education is not a procedural ideal but a normative demand grounded in justice, dignity, and moral responsibility. This paper argues that the genuine reform in Teacher Education requires moral responsibility and reconstruction rather than solely technocratic intervention.

To be absolutely honest, it has not been that simple on my part to grasp the impact that Artificial Intelligence is having on the world of law, as it seems everything is evolving at a pace, way too swift, to keep up with. My understanding of law has recently changed because I believe that most of it relies on human judgment and hours reading cases but now the AI actually participates in it in a manner that I did not believe. It is not only to accelerate the process or to perform repetitive tedious work. It as a matter of fact appears to be transforming the way lawyers think and the manner in which they could possibly make decisions, which appears to be overwhelming in my view. I was forced to read about what AI translates to specific to the field of law since it was something I did not fully understand initially. It is not like regular computers; machine learning or natural language processing systems can learn data rather than simply act on some set rules. Systems like the TAXMAN which were used many years ago were extremely rudimentary in comparison to the current systems such as scanning large stacks of legal documents, case prediction or assisting in legal research. People criticize that this is a great improvement being done, but I am yet to be convinced. I also have issues that persistently annoy me. As an illustration, imagine a misjudgment of an AI tool due to the biased data? Or what when no one can tell how the system was determined to its ending owing to the presence of those black box models? Whom do you accuse at that, the lawyer or the machine? These questions seem to have no definite answers to them and that is scary in terms of justice. Admittedly, I think there is no way that AI can substitute real lawyers or judges. Emotions and fairness are something that cannot be perceived by technology, yet at least by real people. I believe that probably the most appropriate solution is to use AI, not to rule people but rather to assist them. Perhaps in this way out of balance we can make the legal system more efficient and yet retain the human element.

Serotonin is one of the crucial neurotransmitters that plays a vital role in human physiology and normally exists in human serum in the 200 nM to 1.1 μM range along with a wide variety of interfering agents. This makes it a quite challenging task to detect serotonin in an efficient, electrochemical way at ambient temperature in a relatively low concentration (nanomolar) of abundance. So, this work is focused on developing an enzyme-less electrochemical sensing platform that can detect serotonin with a very low limit of detection (LOD) in a highly sensitive and selective way. For this purpose, carbon quantum dots (CQDs), one of the advanced carbonaceous materials, were prepared from a natural source (corn seeds) and applied to make a nanocomposite sensing platform with an electrochemically deposited NiWO4 thin film on FTO-coated glass substrate. The prepared materials were thoroughly characterized by using sophisticated instrumentation techniques. The fabricated NiWO4/CQD nanocomposite thin film was then subjected to detailed electrochemical probing toward serotonin sensing. Fascinatingly, the developed sensor prototype yielded an LOD of 134.0 nM without compromising the sensitivity (16.9 μA μM–1 cm–2), which makes it well capable for detecting serotonin that is present in human serum in the nM to μM order.

Agriculture is a major source of livelihood and economic activity in Nadia District, West Bengal, yet block-level variations in productivity and land use are evident. This study evaluates agricultural performance across blocks using secondary data from District Statistical Handbooks, Agriculture Department records, and Census reports. Analytical methods include land-use assessment, crop area computation, and comparative productivity analysis through spatial statistical techniques, with performance summarized using a composite Z-score index. Out of 390,660 hectares of agricultural and horticultural land, 288,090 hectares (74%) constitute net sown area. The analysis reveals that Krishnaganj, Nabadwip, Ranaghat-I, Karimpur-II, and Chakdaha exhibit the highest agricultural efficiency, while Karimpur-I (0.018), Chapra, and Krishnanagar-I show the lowest efficiency. These results indicate substantial intra-district disparities, highlighting the need for targeted interventions, optimized resource allocation, and policies to improve agricultural efficiency, strengthen rural livelihoods, and ensure regional food security.

Background: Assessment of physical factors such as Body Mass Index (BMI) and Waist Hip Ratio (WHR) and their association with Physical Activity Levels (PAL) is essential among college student population for assessing their health risk & creating a healthy environment through the implementation of effective strategies by educational institutions.Methods: A cross sectional study was conducted on 202 adult college students (male:105 & female: 97) of Kolkata, West Bengal, India, under the age group 18-23 years. They were randomly selected through Convenient sampling method and their PAL(MET-Min/Week) was estimated and classified using the guideline of International Physical Activity Questionnaire (IPAQ) Short. Their BMI & WHR were also measured and categorized as per WHO guideline. Co-relation of the BMI & WHR with their PAL has been analysed and the risk of chronic disease was observed. The study wasapproved by the Institutional Human Ethical Committee.Conclusions: Majority (82.18%) of students had ‘High’ physical activity levels, with males showing significantly higher total mean PAL & WHR than females (p < 0.05). Physically inactive were (4.46%) &Obese were 10.40% yet 25.25% of students were found at high cardiovascular & other health risk. While physical activity is crucial for overall health, its impact on BMI & WHR can be inconsistent as individual variability in response to exercise, dietary habits, metabolic rate and genetic predispositions etc. and also some other health matrices or hidden factors which should be explored through further research. While PAL had no significant correlation with BMI or WHR, the PAL-WHR correlation (Beta coefficient = 0.034) was comparatively stronger than PAL-BMI (Beta coefficient = 0.006), suggesting WHR is a more significant health indicator than BMI. This study thus highlighted the need for targeted health interventions in college student’s populationspecially the females to address obesity and the associated risks of cardiovascular and other chronic diseases