Longitudinal and Transverse Rolls in a Triangular Cavity

AbstractNatural convection in a triangular cavity is present in many domestic and industrial systems. Increasing investigators have been devoted to the study of natural convection and heat transfer in the triangular cavity due to its application in the attic design. In this study, the three dimensional (3D) numerical simulation of natural convection in the triangular cavity with the top cooling and the bottom heating has been carried out. The onset and development of natural convection flows in the cavity are investigated for various Rayleigh numbers and aspect ratios. The results show that the 3D structures of convection rolls in the cavity such as transversal rolls and longitudinal rolls, similar to the Rayleigh-Bénard-Poiseuille flow, are clear. The scenario of the roll formation is described

LY294002 induces differentiation and inhibits invasion of glioblastoma cells by targeting GSK-3β and MMP

Glioblastomas are the most common and devastating primary tumors of the central nervous system, with high proliferative capacity, aggressive invasion, and resistance to conventional therapies. Differentiation therapy has emerged as a promising candidate modality. Here we show that the traditional phosphatidylinositol 3 kinase (PI3K) inhibitor LY294002 is capable of inducing differentiation of C6 glioblastoma cells characterized by morphological changes to astrocytic phenotype, increase in differentiation marker protein glial fibrillary acidic pro-tein and inhibition of proliferation. Small interfering RNA against glycogen synthase kinase-3β (GSK-3β) suppresses the induced-differentiation and invasiveness in C6 cells. LY294002 also inhibits MMP-9 expression and invasion of C6 cells, assembling the role of metalloprotease (MMP) inhibitor AG3340. Taken together, these findings suggest differentiation-inducing and invasion-inhibitory effectiveness of LY294002 in glioblastomas, most likely involving inhibition of GSK-3β and MMP respectively

One-Pot Synthesis of Bi/Fe3O4 and Its Catalytic Performances for 4-Nitrophenol Reduction

A novel approach was successfully developed for the catalyst Bi-deposited Fe3O4 magnetic nanoparticles, which was used in the degradation of 4-nitrophenol (4-NP). The Bi/Fe3O4 composite was prepared via a one-pot process from ferrous sulfate and bismuth chloride using hydrazine hydrate as a reducing agent. The catalyst was characterized by X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. In the composite pure Fe3O4 particles were synthesized and bismuth particles were well dispersed. The catalytic performances were investigated for the reduction of 4-NP with sodium borohydride. The catalyst has higher activity when Bi/Fe molar ratio is 1:4 in the composite and the rate constant k is about 0.611 min-1. The catalyst has good reusability which can be used 10 cycles without obvious deactivation. Furthermore, the catalyst can be easily separated by an external magnetic field.

A Customized Text Sanitization Mechanism with Differential Privacy

As privacy issues are receiving increasing attention within the Natural Language Processing (NLP) community, numerous methods have been proposed to sanitize texts subject to differential privacy. However, the state-of-the-art text sanitization mechanisms based on metric local differential privacy (MLDP) do not apply to non-metric semantic similarity measures and cannot achieve good trade-offs between privacy and utility. To address the above limitations, we propose a novel Customized Text (CusText) sanitization mechanism based on the original $\epsilon$-differential privacy (DP) definition, which is compatible with any similarity measure. Furthermore, CusText assigns each input token a customized output set of tokens to provide more advanced privacy protection at the token level. Extensive experiments on several benchmark datasets show that CusText achieves a better trade-off between privacy and utility than existing mechanisms. The code is available at https://github.com/sai4july/CusText.Comment: This work has been accepted to the Findings of ACL 202

National Natural Science Foundation of China

Abstract The advent of multi-core/many-core chip technology offers both an extraordinary opportunity and a profound challenge. In particular, computer architects and system software designers are faced with a unique opportunity to introducing new architecture features as well as adequate compiler technologytogether they may have profound impact. This paper presents a case study (using the 1D Stencil computation) of compiler-amendable performance optimization techniques on a many-core architecture Godson-T. Godson-T architecture has several unique features that are chosen for this study: (1) chip-level global addressable memory -in particular the scratchpad memories (SPM) local to the processing cores; (2) fine-grain memory based synchronization (e.g. full-empty bit for fine-grain synchronization). Leveraging state-of-the-art performance optimization methods for 1-D stencil parallelization (e.g. timed tiling and variants), we developed and implement a number many-core based optimization for Godson-T. Our experimental study show good performance improvements in both execution time speedups and scalability, validated the value of globally accessed SPM and fine-grain synchronization mechanism (full-empty bits) under the Godson-T, and provide some useful guidelines for future compiler technology of many-core chip architectures

Inhibitory Kinetics of Cyanidin-3-O-glucoside against α-Amylase and α-Glucosidase

The inhibitory mechanism of α-amylase and α-glucosidase by cyanidin-3-O-glucoside was investigated by ultrafiltration, high performance liquid chromatography (HPLC), enzyme kinetics, and molecular docking. The results indicated that cyanidin-3-O-glucoside inhibited α-amylase and α-glucosidase in a reversible and non-competitive manner. Besides, the fluorescence quenching analysis indicated that cyanidin-3-O-glucoside combined with the two enzymes by hydrogen bonds to form a complex. Molecular docking analysis showed that cyanidin-3-O-glucoside interacted with the key amino acid residues of α-amylase and α-glucosidase through hydrogen bonds and hydrophobic forces, and the binding energies were −7.8 and −9.8 kcal/mol, respectively. Our research suggests that cyanidin-3-O-glucoside has the potential to be used as an inhibitor of α-amylase and α-glucosidase in the development of functional foods

Study on the evaluation of the clinical effects of traditional chinese medicine in heart failure by complex intervention: protocol of SECETCM-HF

<p>Abstract</p> <p>Background</p> <p>Experts in Traditional Chinese Medicine (TCM) have studied the TCM subject of the pathogenesis of heart failure (HF) for several decades. As a result, the general idea is <it>ben </it>deficiency and <it>biao </it>excess. However, the clinical evaluation system which combined the TCM and western medicine in HF has not been developed yet. The objective is to establish the evaluation index system for the integration of TCM and western medicine. The evaluation indexes which include TCM items will specify the research design and methods.</p> <p>Methods</p> <p>Nine medical centers in different cities in China will participate in the trial. A population of 340 patients with HF will be enrolled through a central randomized system for different test groups. Group A will be treated with only western medicine, while group B with western and Chinese medicine together. The study will last for 12 months from the date of enrollment. The cardiovascular death will be the primary outcome.</p> <p>Discussion</p> <p>By putting the protocol into practice, the clinical effects of TCM for HF will be identified scientifically, objectively as well as rationally. The proper index system which built in the study will be helpful for the clinical effect expression of HF by integrated medicine in future.</p> <p>Trial Registration</p> <p>ChiCTR-TRC-00000059</p

Optimizing Deep Learning Inference via Global Analysis and Tensor Expressions

We thank our shepherd, Vinod Grover, and the anonymous reviewers for their constructive feedback. For the purpose of open access, the authors have applied a Creative Commons Attribution (CCBY) license to any Author Accepted Manuscript versionarising from this submission

Advancing LLM Reasoning Generalists with Preference Trees

We introduce Eurus, a suite of large language models (LLMs) optimized for reasoning. Finetuned from Mistral-7B and CodeLlama-70B, Eurus models achieve state-of-the-art results among open-source models on a diverse set of benchmarks covering mathematics, code generation, and logical reasoning problems. Notably, Eurus-70B beats GPT-3.5 Turbo in reasoning through a comprehensive benchmarking across 12 tests covering five tasks, and achieves a 33.3% pass@1 accuracy on LeetCode and 32.6% on TheoremQA, two challenging benchmarks, substantially outperforming existing open-source models by margins more than 13.3%. The strong performance of Eurus can be primarily attributed to UltraInteract, our newly-curated large-scale, high-quality alignment dataset specifically designed for complex reasoning tasks. UltraInteract can be used in both supervised fine-tuning and preference learning. For each instruction, it includes a preference tree consisting of (1) reasoning chains with diverse planning strategies in a unified format, (2) multi-turn interaction trajectories with the environment and the critique, and (3) pairwise data to facilitate preference learning. UltraInteract allows us to conduct an in-depth exploration of preference learning for reasoning tasks. Our investigation reveals that some well-established preference learning algorithms may be less suitable for reasoning tasks compared to their effectiveness in general conversations. Inspired by this, we derive a novel reward modeling objective which, together with UltraInteract, leads to a strong reward model.Comment: Models and data are available at https://github.com/OpenBMB/Euru