Use of calcium carbide for artificial ripening of fruits : its application and hazards

A review of different articles related to artificial ripening was done. Focus was given on the hazards and applications of calcium carbide for artificial ripening, being a very common practice in Nepalese Market. Litterateurs showed many hazardous aspects of carbide use and also standard procedures of safety handling aspects. But being banned by regulation, due to its hazardous aspects and lack of proper handling methods among users, it was concluded that the use of calcium carbide is to be strictly monitored and controlled

Preparation of Lapsi (Choerospondias axillaries roxb.) pulp using IMF technology and study on storage stability

The work was carried out to study the storage stability and food safety aspects of lapsi (Choerospondias axillaries roxb.) pulp stock prepared using Intermediate Moisture Food Technology. Three recipes were designed with the TSS of 55, 60 and 65 oBx and the TSS/Acidity ratio of 20, 25 and 30 respectively so as to achieve the theoretical water activity level of 0.86 to 0.90. Further three treatments using no preservative, potassium sorbate (0.3%) as preservative and pasteurisation with hot filling were done to those recipes. All samples were found to be safe from the food poisoning organism Staphylococcus aureus. All preservative added and pasteurised samples as well as 65 oBx sample with no preservative were stable up to 5 months storage and no Mold growth were observed. Mold observed after 2 month in 55 oBx sample and after 69th day in 60 oBx sample with no preservative. Preservative added samples were faint in colour while pasteurised samples were dark due to browning reaction during heating. No preservative used sample was best in appearance. 65 oBx with no preservative sample was good design but protection from air to prevent browning and use of sorbate to further extend shelf life was found necessary

BUCKLING OF THIN CYLINDRICAL SHELLS: IMPERFECTION SENSITIVITY, NON-DESTRUCTIVE TECHNIQUE FOR CAPACITY PREDICTION AND APPLICATION FOR WIND TURBINE TOWERS

The presence of imperfections significantly reduces the load-carrying capacity of thin cylindrical shells and the reduction depends on the shape and the size of the imperfections. As a result, the prediction of the shells\u27 buckling capacity requires a priori knowledge about the imperfections---a difficult, expansive, and time-consuming adventure, if not impossible. Consequently, thin cylindrical shells are designed conservatively using the knockdown factor approach that accommodates the uncertainties associated with the imperfections present in the cylinders; almost all the design codes follow this approach explicitly or implicitly. However, cylindrical shells can be designed more efficiently by making them insensitive to imperfections, or by knowing their exact capacity without the difficult task of measuring the imperfections. This dissertation examines these two approaches for the efficient designing of thin cylindrical shells. In addition, we investigate buckling behavior and imperfection sensitivity of thin cylindrical shells under pure bending along with their applications in tall wind turbine towers. For making thin cylindrical shells insensitive to imperfection, wavy cross-sections are proposed instead of circular cross-sections. Past studies have demonstrated the effectiveness of wavy cylinders to reduce imperfection sensitivity under axial compression assuming linear elastic material behavior and using eigenmode imperfections. In this dissertation, using a realistic dimple-like imperfection, new insights are presented into the response of wavy cylinders under uniform axial compression and bending. We found that thin cylindrical shells can be made imperfection insensitive by manipulating their cross-section geometry. For high-fidelity estimates of the capacity of thin cylindrical shells without measuring the imperfections, a novel procedure is proposed based on the probing of the axially loaded cylinders. Computational implementation of the proposed procedure yields accurate results when the probing is near the imperfection; however, the procedure over-predicts the capacity when the probing is away from the imperfection. It demonstrates the crucial role played by the probing location and shows that the prediction of imperfect cylinders is indeed possible if the probing is at the proper location. The behavior of cylindrical shells under bending and their imperfection sensitivity have not been fully understood for all the range of dimensions. In this dissertation, we investigate the buckling behavior and imperfection sensitivity of thin steel cylindrical shells under pure bending, focusing on a specific range of slenderness, which is found in energy structures such as tall wind turbine towers (60 \u3c R/t \u3c 120). We found that strain-hardening models play an impactful role on the bending behavior; moreover, the presence of imperfections reduces the collapse curvature more than the reduction in peak moment. Further, we propose wavy wind turbine towers to make wind turbine towers efficient. The imperfection sensitivity of the wavy towers is evaluated, and we found that the sensitivity of the wavy towers is small compared to that of the circular towers

Mind Your Language: Abuse and Offense Detection for Code-Switched Languages

In multilingual societies like the Indian subcontinent, use of code-switched languages is much popular and convenient for the users. In this paper, we study offense and abuse detection in the code-switched pair of Hindi and English (i.e. Hinglish), the pair that is the most spoken. The task is made difficult due to non-fixed grammar, vocabulary, semantics and spellings of Hinglish language. We apply transfer learning and make a LSTM based model for hate speech classification. This model surpasses the performance shown by the current best models to establish itself as the state-of-the-art in the unexplored domain of Hinglish offensive text classification.We also release our model and the embeddings trained for research purpose

Ground Water in the City of Varanasi, India: present status and prospects

The city of Varanasi is short of water. The city obtains a total of 270 million litres water from the river Ganga and tubewells. Yet every fifth citizen lacks drinking water. The ground water is polluted due to nitrate and faecal coliform. A further problem is the plan to settle the growing population in a new township nearby under the integrated development plan of Greater Varanasi, a part of the Jawajarlal Nehru Urban Renewal Mission. To fulfill the growing demand of fresh water, new water bearing horizon of the most affected part of the city i.e. southern part is to be identified. This paper reports a study of the variation in the grain size attributes of an aquifer material taken from different depths from the affected region in order to establish the generalized hydrological properties and recommend the depth of the well accordingly. From the grain size analysis and hydrological study it may be concluded that water bearing zones are mainly found in three horizons at the depths 44-56 m; 56-87 m; and 87-165 m. The third water bearing horizon (total thickness being 78 m) can act as a good potential ground water horizon for a new township. Due to its greater depth, the water would be relatively fresh being characterized by very low concentration of dissolved solids. Therefore, this horizon is strongly recommended for utilizing the water resource for the township

Federated Online and Bandit Convex Optimization

We study the problems of distributed online and bandit convex optimization against an adaptive adversary. We aim to minimize the average regret on $M$ machines working in parallel over $T$ rounds with $R$ intermittent communications. Assuming the underlying cost functions are convex and can be generated adaptively, our results show that collaboration is not beneficial when the machines have access to the first-order gradient information at the queried points. This is in contrast to the case for stochastic functions, where each machine samples the cost functions from a fixed distribution. Furthermore, we delve into the more challenging setting of federated online optimization with bandit (zeroth-order) feedback, where the machines can only access values of the cost functions at the queried points. The key finding here is identifying the high-dimensional regime where collaboration is beneficial and may even lead to a linear speedup in the number of machines. We further illustrate our findings through federated adversarial linear bandits by developing novel distributed single and two-point feedback algorithms. Our work is the first attempt towards a systematic understanding of federated online optimization with limited feedback, and it attains tight regret bounds in the intermittent communication setting for both first and zeroth-order feedback. Our results thus bridge the gap between stochastic and adaptive settings in federated online optimization