Social Divisions among the Indian Labouring Masses

Dalits and women in India are denied even minimum representation in policy making and accessing national resources. Highly under-represented in state machinery, media, and all higher wage employments, they are highly over-represented in low wage, highly labour intensive, and hazardous jobs. For them, facing exploitation and discrimination, not only by the state and the employers but also by their fellow workers, is a constant reality. The social, cultural, economic, and political systems in India are built to operate in such a way as to produce and reproduce the social divisions continuously and aggravate the problems of divisions among the labourers. The labour movements, which are supposed to oppose this unjust system, have generally ignored the issue of representation of dalits and women as they operate as part and parcel of the same social system that produces and reproduces ascriptive divisiveness

Temperature dependence of transport spin polarization in NdNi5 measured using Point Contact Andreev reflection

We report a study in which Point contact Andreev reflection (PCAR) spectroscopy using superconducting Nb tip has been carried out on NdNi5, a ferromagnet with a Curie temperature of TC~7.7K. The measurements were carried out over a temperature range of 2-9K which spans across the ferromagnetic transition temperature. From an analysis of the spectra, we show that (i) the temperature dependence of the extracted value of transport spin polarization closely follows the temperature dependence of the spontaneous magnetization; (ii) the superconducting quasiparticle lifetime shows a large decrease close to the Curie temperature of the ferromagnet. We attribute the latter to the presence of strong ferromagnetic spin fluctuations in the ferromagnet close to the ferromagnetic transition temperature.Comment: pdf file including figures-Typographical error and errors in references correcte

Evolutionary trends in the hemoglobins of murine animals

The evolutionary origin of murine line based on a phylogenetic tree made on sequence data of ∞- and β -hemoglobin chains, followed by the diversity spectrum of hemoglobin genes in two wild species of murine rodents: Rattus rattus rufescens (house rat) and Bandicota indica (bandicoot rat) has been reported. Each house rat contains six hemoglobin types involving two infinity-and three β-chains, which suggests a probable gene duplication at the oc chain locus and a gene triplication at the β-chain locus. Each bandicoot rat contains one infinity-and two β -chains suggesting a probable gene duplication at the β-chain locus. Peptide pattern analysis of the polypeptide chains of these murine hemoglobins further indicates that intraspecies differences among duplicated chains of the same kind are less than interspecies differences among corresponding ∞-and β -chains

ANALYSIS ON DEEP LEARNING TO DETECT THE BRAIN MRI TUMOR SEGEMENTATION

In this recent scenario, brain tumour detection system through classification technique helps in the person infected with brain tumour and plays an important role to provide effectiveness in the diagnosis process and proper treatment. The above MRI classification method helps to provide effective and early-stage treatment for identifying the tumour in the brain and determine the level of tumour occurrences. As there are several classification methods related to brain tumour exists in recent days, which is associated with U-Net architecture i.e., deep learning methods related to medical classification. Based on the comparison of the feature information among low-level and high-level, in this paper the propose architecture of Residual U-NET with some enhanced local feature information as it helps to improve the medical image segmentation. Through this, propose work helps to highlight the improvement in the attention module for the segmentation of image tumour, propose the novel attention module based on the Residual U-Net model. In the modified Residual U-Net model, residual module and attention gate is addressed along with dropout and wide context layers. Here the addition of salient feature information, which helps to focus on the large sensitive scaled information but also consider the small-scale images also. In the performance analysis, modified model associated with gate attention outperforms with the existing models like, U-Net and CNN Densely models