Long-term Effects of Land Reform on Human Capital Accumulation: Evidence from West Bengal

We use data on inter-generational gains in educational attainment by some 500,000 individuals in 200 West Bengal villages to explore gender-differentiated impacts of land reform on human capital accumulation at the individual level. While there are significant gains (of about 0.3 years for males) in the immediate post-reform generation, their magnitude pales in comparison to second-generation effects of between 0.85 and 1.2 years that appear irrespectively of the land reform modality. Moreover, there are possibly significant spillover benefits on villagers who did not directly benefit from reform. Placebo tests and alternative specifications support robustness of the results. By contrast, levels of beneficiary productivity and welfare remain far below average, something that could likely be avoided if land reform beneficiaries would receive full ownership rights.rather than being recognized as permanent share tenants and if restrictions on transferability of land were abandoned.India, land reform, long-term effects, human capital

Hybrid recommendation system using product reviews

Abstract. Several businesses/smart applications rely on personalizing their services to adapt to the user’s preferences. Personalized services are developed using recommendation systems based on user’s feedback on products/services, needs, habits and social or demographic characteristics. Several businesses from e-commerce (suggesting users what to buy) to hospitality services (suggesting which hotel to book) focus on using recommendation systems to achieve a personalized experience for their users. Majority of recommendation systems make use of only product ratings shared by the users, this may pose challenges like sparsity of ratings. The wide availability of other attributes of products or users like textual product reviews provided by users or product descriptions in e-commerce and hospitality domains present a gold mine of additional personalising information with which to supplement their ratings based recommendation system. Recommendation systems majorly involves two tasks: rating (predict ratings that user might assign to a product) and ranking (recommend products based on predicted rank scores) prediction tasks. In this thesis, we propose a novel hybrid recommendation system using the state-of-the-art DeepFM model which makes use of multiple textual features derived from product reviews particularly contextual sentence embedding vectors, average sentiment scores and linguistic cues such as presence/absence of negation in the product reviews in combination with ratings shared by users to enhance the prediction of the desired ratings or rank scores. We evaluated our system with commercial datasets from Amazon and Datafiniti for both tasks: predicting rating and recommendations based on predicted rank scores. We utilised different metrics for both types of tasks. From our evaluation we infer that using contextual sentence embedding vectors extracted using BERT, average sentiment scores and presence/absence of negation in the product reviews obtained from VADER, does impact the prediction of ratings and recommendations based on predicted scores of the recommendation system which only utilises product ratings as user preferences. Furthermore, we can conclude from our evaluation that (A) contextual embedding vectors and average sentiment scores together along with ratings in the proposed hybrid system improves prediction of desired ratings, (B) contextual embedding vectors, average sentiment scores and presence/absence of negation in the product reviews together along with ratings in the proposed hybrid system improves prediction of desired ratings as well, (C) contextual embedding vectors and average sentiment scores together along with ratings in the proposed hybrid system improves recommendations based on rank scores

Impact of Land Reform on Productivity, Land Value and Human Capital Investment: Household Level Evidence from West Bengal

While land reform has been the subject of considerable scholarly debate, most of the analyses have been at the aggregate level and focused on rather short-term effects. We use a listing of more than 90,000 households in some 200 villages in West Bengal to highlight the impact of the state's 1978 land reform program on human capital accumulation and current productivity of land use. While we ascertain a highly significant positive effect on long-term accumulation of human capital, our analysis also suggests that, partly because land that had been received through land reform is still operated under share tenancy arrangements, productivity on such land is significantly lower than the average. The combination of lower productivity of reform land relative to own land and land rental and sale's restriction of reform land is associated with significantly lower purchase and sale's price of reform land compared to own land. Programs to allow land reform beneficiaries to acquire full ownership could thus have significant benefits.Agricultural and Food Policy, Land Economics/Use,

Complete the Incompleteness of Land Reform: Household Level Evidence from West Bengal

Replaced with revised version of paper 06/22/11.Labor and Human Capital, Land Economics/Use, Productivity Analysis,

Serum zinc levels in children with simple febrile seizure

Background: It has been postulated that children with low serum zinc level are more prone to febrile seizures. Objectives: The objectives of this study were to compare the serum zinc levels in children suffering from febrile seizures with the children with febrile illness without seizures and children with no seizure and fever. Materials and Methods: A prospective case–control study was conducted in the Department of Pediatrics, in a Medical Institution of Meerut, over a period of 2 years (March 2015–May 2017). A total of 150 candidates of age 6 months–60 months were recruited from the pediatric wards and were divided into three subgroups. Group A consisted of 50 children who neither had fever nor seizures. Group B consisted of 50 children who had fever but no seizures. Group C consisted of 50 children who suffered from simple febrile seizure. Here, the Groups A and B served as control while Group C was taken as case. Serum zinc level was assessed in each child after taking written consent from parents. Further, the value of serum zinc was compared among the group. The results were statistically analyzed using the Statistical Package for the Social Sciences Version 21.0 statistical analysis Software. Results: Of 50 children with febrile seizures, 29 (58%) were male. Mean serum zinc levels of all the children included in the study were low (55.42 μg/dl) as compared to the reference values. There was no significant difference in the serum zinc levels in the febrile seizure group and control groups. Conclusion: We found that the serum zinc level was not associated with febrile seizures

Identification of Fast Radio Bursts using Transfer Learning Approach with Data Augmentation

The universe has many mysteries, such as pulsars, dying stars, supernovae, and fast radio bursts (FRBs), FRBs are millisecond long radio signals, detected as a spike in radio-telescope data. Identification of Fast Radio Bursts from available data involves manual inspection of exhaustive data/plots. Radio Frequency Interference in pose a major challenge in identification of Fast Radio Bursts due to their abundance in the observatory data. We present a machine-learning-aided system, which screens telescope-generated data and identifies potential Fast Radio Burst candidates in it. Proposed system employs Convolutional Neural Networks and Transfer Learning to classify potential Fast Radio Bursts from Radio Frequency Interference from data recorded by the uGMRT. We have used data simulation tools to synthesize additional samples in order to make up for the paucity of data. The VGG16-based model displayed the best receiver operating characteristics curve with the area under curve being 0.90 along with an accuracy of 90.67%

A Novel Approach of Development of Web Pattern by Focusing on Web Structure Mining Techniques

The World Wide Web is a very useful and interactive resource of information like hypertext, multimedia etc. When we search any information on the Google, there are many URL’s has been opened. The bulk amount of information becomes very difficult for the users to find, extract and filter the relevant information, so that some techniques are used to solve these problems. The objective of current manuscript is focus on processing of structured and unstructured data mining. With the tremendous growth in website, web portal to provide downloaded data to the user. The semantic web is about machine-understandable web pages to make the web more intelligent and able to provide useful services to the users. The data structure definition and recognition is to estimate the accurate page ranking and to produce better result while searching operation with web data

भा कृ अनु प - केंद्रीय समुद्री मात्स्यिकी अनुसंधान संस्थान, कोच्ची में वर्ष 2017 के दौरान आयोजित राजभाषा हिंदी के कार्यक्रम

भा कृ अनु प - केंद्रीय समुद्री मात्स्यिकी अनुसंधान संस्थान, कोच्ची में वर्ष 2017 के दौरान आयोजित राजभाषा हिंदी के कार्यक्र

In-vitro analysis of potential antibacterial activity of three medicinal plants

The present study was aimed to examine and compare the antibacterial activity of hot methanolic extract of medicinal plants viz. Portulaca oleracea (purslane), Syzygium cumini (L.) (jamun), Psidium guajava (L.) (guava). Antibacterial activity was carried by using agar well diffusion method, against Gram-positive bacteria (Staphylococcus aureus and Bacillus subtilis) and Gram-negative bacteria (Escherichia coli). Results indicated that all the three plant extracts possess antibacterial property against Gram-positive bacteria and no activity was found against Gram-negative bacteria. Moderate zone of inhibition against Staphylococcus aureus and Bacillus subtilis was exhibited by S. cumini (L.) (11mm and 12mm) and P. guajava (L.) (10mm and 11mm) and weak zone of inhibition was exhibited by P. oleracea (5 mm and 6mm). In conclusion, S. cumini (L.) and P. guajava (L.) possess bettercapabilities of being a good candidate in search for natural antibacterial agent against infections and diseases causing Gram-positive bacteria as compared to P. oleracea