Chronic crisis: migrant workers and India's COVID-19 lockdown

India’s nationwide lockdown amidst the coronavirus pandemic has created a severe dislocation in the lives of its migrant population. Based on their research in Noida, a hotspot of the crisis, Ritanjan Das (University of Portsmouth) and Nilotpal Kumar (Azim Premji University, Bangalore) explain how the pandemic exacerbates the ‘chronic crisis’ in the everyday existence of migrants to unprecedented proportions

EVALUATION OF ULCEROPROTECTIVE ACTIVITY OF MUSA SAPIENTUM VAR. PARADISIACA METHANOLIC FRUIT EXTRACT AGAINST ASPIRIN INDUCED GASTRIC ULCERS IN ALBINO RATS

Objective: The objective of the study was to evaluate the ulceroprotective activity of Musa sapientum var. paradisiaca methanolic fruit extract (MSE) against aspirin induced gastric ulcers in albino rats.Methods: Fresh plantain bananas were sliced and air dried at room temperature. The dried slices were ground to a fine powder. The extract was prepared by percolating dried powder with methanol. Twenty four healthy albino rats of 100-200 gms were taken for the study. The animals were divided into four groups of six animals each. Group I or control (3percent gum acacia 5 ml/kg orally for 7 days). Group II or experimental control (aspirin 400 mg/kg orally single dose on the 7th day). Group III or MSE group (MSE 100 mg/kg orally for 7 days and aspirin 400 mg/kg orally single dose on the 7th day). Group IV or standard (ranitidine 150 mg/kg orally for 7 days and aspirin 400 mg/kg orally single dose on the 7th day). On 8th day the stomachs of the sacrificed rats were removed and (1) ulcer index (2) total acidity (3) free acidity (4) gastric mucous secretion were studied.Results: The ulcer index, free and total acidity in group III and IV showed significant decrease in comparison to group II (p <0.01) whereas there was increase in gastric mucus secretion (p <0.01).Conclusion: The study showed significant ulceroprotective activity of Musa sapientum var. paradisiaca methanolic fruit extract (MSE) against aspirin induced gastric ulcers in albino rats.KEYWORDSAspirin, free acidity, gastric mucous, Musa sapientum var. paradisiaca, percolation, peptic ulcer, ranitidine, total acidity, ulcer indexAbbreviation: MSE – Musa sapientum var. paradisiaca extrac

Co-occurrence of arsenic, fluoride and uranium in a fluvial environment

by Nilotpal Das and Manish Kuma

Simultaneous Semi-Coupled Dictionary Learning for Matching RGBD data

Matching with hidden information which is available only during training and not during testing has recently become an important research problem. Matching data from two different modalities, known as cross-modal matching is another challenging problem due to the large variations in the data coming from different modalities. Often, these are treated as two independent problems. But for applications like matching RGBD data, when only one modality is available during testing, it can reduce to either of the two problems. In this work, we propose a framework which can handle both these scenarios seamlessly with applications to matching RGBD data of Lambertian objects. The proposed approach jointly uses the RGB and depth data to learn an illumination invariant canonical version of the objects. Dictionaries are learnt for the RGB, depth and the canonical data, such that the transformed sparse coefficients of the RGB and the depth data is equal to that of the canonical data. Given RGB or depth data, their sparse coefficients corresponding to their canonical version is computed which can be directly used for matching using a Mahalanobis metric. Extensive experiments on three datasets, EURECOM, VAP RGB-D-T and Texas 3D Face Recognition database show the effectiveness of the proposed framework

Vintage Effects and the Diffusion of Time-Saving Technological Innovations: The Adoption of Optical Scanners by U.S. Supermarkets."

The diffusion literature implicitly assumes that a technological innovation remains homogeneous throughout the time period of the study with the sole modification being an assumed reduction in the real price of the technology over time. We argue that the technology can change in significant ways from one vintage to another to alter the nature of the diffusion process. We support this claim with estimates from non-parametric, semi-parametric and parametric duration models for the first generation of optical scanners installed in supermarkets in the U.S. between June 1974 and March 1985.Technological change

"Persistent Adoption of Time-Saving Process Innovations."

This paper is a draft of a chapter in a forthcoming book entitled, The Economics of Persistent Innovators,to be published by Springer. We consider the persistent adoption of innovations by firms that are not directly involved in the innovation process. In addition to a survey of the literature, we offer empirical evidence of persistent adoption for a specific time-saving process innovation: high-speed detachable chairlifts.Innovation, Diffusion, Service, Quality

A comparative health risk assessment due to arsenic contaminated water inthe Ganga and the Brahmaputra floodplain, India

by Arbind Kumar Patel, Nilotpal Das and Manish Kuma

Simultaneous Semi-Coupled Dictionary Learning for Matching in Canonical Space

Cross-modal recognition and matching with privileged information are important challenging problems in the field of computer vision. The cross-modal scenario deals with matching across different modalities and needs to take care of the large variations present across and within each modality. The privileged information scenario deals with the situation that all the information available during training may not be available during the testing stage, and hence, algorithms need to leverage the extra information from the training stage itself. We show that for multi-modal data, either one of the above situations may arise if one modality is absent during testing. Here, we propose a novel framework, which can handle both these scenarios seamlessly with applications to matching multi-modal data. The proposed approach jointly uses data from the two modalities to build a canonical representation, which encompasses information from both the modalities. We explore four different types of canonical representations for different types of data. The algorithm computes dictionaries and canonical representation for data from both the modalities, such that the transformed sparse coefficients of both the modalities are equal to that of the canonical representation. The sparse coefficients are finally matched using Mahalanobis metric. Extensive experiments on different data sets, involving RGBD, text-image, and audio-image data, show the effectiveness of the proposed framework