Inflammation and Oxidative Stress in Obesity-Related Glomerulopathy

Obesity-related glomerulopathy is an increasing cause of end-stage renal disease. Obesity has been considered a state of chronic low-grade systemic inflammation and chronic oxidative stress. Augmented inflammation in adipose and kidney tissues promotes the progression of kidney damage in obesity. Adipose tissue, which is accumulated in obesity, is a key endocrine organ that produces multiple biologically active molecules, including leptin, adiponectin, resistin, that affect inflammation, and subsequent deregulation of cell function in renal glomeruli that leads to pathological changes. Oxidative stress is also associated with obesity-related renal diseases and may trigger the initiation or progression of renal damage in obesity. In this paper, we focus on inflammation and oxidative stress in the progression of obesity-related glomerulopathy and possible interventions to prevent kidney injury in obesity

Significant late Jurassic counterclockwise rotations of the Yanshiping region, east North Qiangtang terrane, implication on Lhasa - Qiangtang initial collision

Abstract HKT-ISTP 2013 A

Facile synthesis of coaxial CNTs/MnOx-carbon hybrid nanofibers and their greatly enhanced lithium storage performance

Carbon nanotubes (CNTs)/MnOx-Carbon hybrid nanofibers have been successfully synthesized by the combination of a liquid chemical redox reaction (LCRR) and a subsequent carbonization heat treatment. The nanostructures exhibit a unique one-dimensional core/shell architecture, with one-dimensional CNTs encapsulated inside and a MnOx-carbon composite nanoparticle layer on the outside. The particular porous characteristics with many meso/micro holes/pores, the highly conductive one-dimensional CNT core, as well as the encapsulating carbon matrix on the outside of the MnOx nanoparticles, lead to excellent electrochemical performance of the electrode. The CNTs/MnOx-Carbon hybrid nanofibers exhibit a high initial reversible capacity of 762.9 mAh-1, a high reversible specific capacity of 560.5 mAh-1 after 100 cycles, and excellent cycling stability and rate capability, with specific capacity of 396.2 mAh-1 when cycled at the current density of 1000 mA-1, indicating that the CNTs/MnOx-Carbon hybrid nanofibers are a promising anode candidate for Li-ion batteries

Quintic trigonometric Bézier curve with two shape parameters

The fifth degree of trigonometric Bézier curve called quintic with two shapes parameter is presented in this paper. Shape parameters provide more control on the shape of the curve compared to the ordinary Bézier curve. This technique is one of the crucial parts in constructing curves and surfaces because the presence of shape parameters will allow the curve to be more flexible without changing its control points. Furthermore, by changing the value of shape parameters, the curve still preserves its geometrical features thus makes it more convenient rather than altering the control points. But, to interpolate curves from one point to another or surface patches, we need to satisfy certain continuity constraints to ensure the smoothness not just parametrically but also geometrically

NL2Formula: Generating Spreadsheet Formulas from Natural Language Queries

Writing formulas on spreadsheets, such as Microsoft Excel and Google Sheets, is a widespread practice among users performing data analysis. However, crafting formulas on spreadsheets remains a tedious and error-prone task for many end-users, particularly when dealing with complex operations. To alleviate the burden associated with writing spreadsheet formulas, this paper introduces a novel benchmark task called NL2Formula, with the aim to generate executable formulas that are grounded on a spreadsheet table, given a Natural Language (NL) query as input. To accomplish this, we construct a comprehensive dataset consisting of 70,799 paired NL queries and corresponding spreadsheet formulas, covering 21,670 tables and 37 types of formula functions. We realize the NL2Formula task by providing a sequence-to-sequence baseline implementation called fCoder. Experimental results validate the effectiveness of fCoder, demonstrating its superior performance compared to the baseline models. Furthermore, we also compare fCoder with an initial GPT-3.5 model (i.e., text-davinci-003). Lastly, through in-depth error analysis, we identify potential challenges in the NL2Formula task and advocate for further investigation.Comment: To appear at EACL 202