Superfluid Density in Conventional Superconductors: From Clean to Strongly Disordered

We reexpress the superfluid density of a disordered superconductor obtained by two of us earlier [Phys. Rev. B 102, 024514 (2020)] in a new highly convergent form, and use the results to make an extensive and successful comparison with experiment in the dirty limit for all temperatures. We point out that there is a regime (conventional superconductor with low, but increasing disorder) where theoretical predictions need to be confronted with accurate experiment.Comment: 9 pages, 3 figure

An Investigation of Suicidal Ideation from Social Media Using Machine Learning Approach

  Despite improvements in the detection and treatment of severe mental disorders, suicide remains a significant public health concern. Suicide prevention and control initiatives can benefit greatly from a thorough comprehension and foreseeability of suicide patterns. Understanding suicide patterns, especially through social media data analysis, can help in suicide prevention and control efforts. The objective of this study is to evaluate predictors of suicidal behavior in humans using machine learning. It is crucial to create a machine learning model for detection of suicide thoughts by monitoring a user's social media posts to identify warning signs of mental health issues. Through the analysis of social media posts, our research intends to develop a machine learning model for identifying suicide ideation and probable mental health problems. This study will help immensely to comprehend the environmental risk factors that influence suicidal thoughts and conduct across time. In this research the use of machine learning on social media data is an exciting new direction for understanding the environmental risk factors that impact an individual's susceptibility to suicide ideation and conduct over time. The machine learning algorithms showed high accuracy, precision, recall, and F1-score in detecting suicide patterns on social media data whereas SVM has the highest performance with an accuracy of 0.886.    

Transport signatures of fragile glass dynamics in the melting of the two-dimensional vortex lattice

In a two-dimensional superconducting vortex lattice, the melting from the solid to the isotropic liquid can occur via an intermediate phase that retains orientational correlations. The effect of such correlations on transport and their interplay with the quenched disorder remain open questions. We perform magnetotransport measurements in a wide range of temperatures and magnetic fields on a weakly pinned two-dimensional vortex system in amorphous MoGe films. While at high fields, where quenched disorder dominates, we recover the typical strong-glass behavior of a vortex liquid, at low fields the resistivity shows a clear crossover to a fragile vortex glass. Our findings, supported by numerical simulations, suggest that this is a signature of heterogeneous dynamics that arises from the presence of orientational correlations

Melting of the vortex lattice through intermediate hexatic fluid in a-MoGe thin film

The hexatic fluid refers to a phase in between a solid and a liquid which has short range positional order but quasi-long range orientational order. In the celebrated theory of Berezinskii, Kosterlitz and Thouless and subsequently refined by Halperin, Nelson and Young, it was predicted that a 2-dimensional hexagonal solid can melt in two steps: first, through a transformation from a solid to a hexatic fluid which retains quasi long range orientational order and then from a hexatic fluid to an isotropic liquid. In this paper, using a combination of real space imaging and transport measurements we show that the 2-dimensional vortex lattice in a-MoGe thin film follows this sequence of melting as the magnetic field is increased. Identifying the signatures of various transitions on the bulk transport properties of the superconductor, we construct a vortex phase diagram for a two dimensional superconductor.Comment: New Data added in this versio

A novel copper complex induces ROS generation in doxorubicin resistant Ehrlich ascitis carcinoma cells and increases activity of antioxidant enzymes in vital organs in vivo

BACKGROUND: In search of a suitable GSH-depleting agent, a novel copper complex viz., copper N-(2-hydroxyacetophenone) glycinate (CuNG) has been synthesized, which was initially found to be a potential resistance modifying agent and later found to be an immunomodulator in mice model in different doses. The objective of the present work was to decipher the effect of CuNG on reactive oxygen species (ROS) generation and antioxidant enzymes in normal and doxorubicin-resistant Ehrlich ascites carcinoma (EAC/Dox)-bearing Swiss albino mice. METHODS: The effect of CuNG has been studied on ROS generation, multidrug resistance-associated protein1 (MRP1) expression and on activities of superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx). RESULTS: CuNG increased ROS generation and reduced MRP1 expression in EAC/Dox cells while only temporarily depleted glutathione (GSH) within 2 h in heart, kidney, liver and lung of EAC/Dox bearing mice, which were restored within 24 h. The level of liver Cu was observed to be inversely proportional to the level of GSH. Moreover, CuNG modulated SOD, CAT and GPx in different organs and thereby reduced oxidative stress. Thus nontoxic dose of CuNG may be utilized to reduce MRP1 expression and thus sensitize EAC/Dox cells to standard chemotherapy. Moreover, CuNG modulated SOD, CAT and and GPx activities to reduce oxidative stress in some vital organs of EAC/Dox bearing mice. CuNG treatment also helped to recover liver and renal function in EAC/Dox bearing mice. CONCLUSION: Based on our studies, we conclude that CuNG may be a promising candidate to sensitize drug resistant cancers in the clinic

Fine Grained Authorization Through Predicated Grants

Authorization in SQL is currently at the level of tables or columns. Many applications need a finer level of control. We propose a model for fine-grained authorization based on adding predicates to authorization grants. Our model supports predicated authorization to specific columns, cell-level authorization with nullification, authorization for function/procedure execution, and grants with grant option. Our model also incorporates other novel features, such as query defined user groups, and authorization groups, which are designed to simplify administration of authorizations. Our model is designed to be a strict generalization of the current SQL authorization mechanism. 1