Parallel numerical simulation for a super large-scale compositional reservoir

 A compositional reservoir simulation model with ten-million grids is successfully computed using parallel processing techniques. The load balance optimization principle for parallel calculation is developed, which improves the calculation speed and accuracy, and provides a reliable basis for the design of reservoir development plan. Taking M reservoir as an example, the parallel numerical simulation study of compositional model with ten million grids is carried out. When the number of computational nodes increases, message passing processes and data exchange take much time, the proportion time of solving equation is reduced. When the CPU number increases, the creation of Jacobian matrix process has the higher acceleration ratio, and the acceleration ratio of I/O process become lower. Therefore, the I/O process is the key to improve the acceleration ratio. Finally, we study the use of GPU and CPU parallel acceleration technology to increase the calculation speed. The results show that the technology is 2.4 ∼ 5.4 times faster than CPU parallel technology. The more grids there are, the better GPU acceleration effect it has. The technology of parallel numerical simulation for compositional model with ten-million grids presented in this paper has provided the foundation for fine simulation of complex reservoirs.Cited as: Lian, P., Ji, B., Duan, T., Zhao, H., Shang, X. Parallel numerical simulation for a super large-scale compositional reservoir. Advances in Geo-Energy Research, 2019, 3(4): 381-386, doi: 10.26804/ager.2019.04.0

Robotics Dexterous Grasping: The Methods Based on Point Cloud and Deep Learning

Dexterous manipulation, especially dexterous grasping, is a primitive and crucial ability of robots that allows the implementation of performing human-like behaviors. Deploying the ability on robots enables them to assist and substitute human to accomplish more complex tasks in daily life and industrial production. A comprehensive review of the methods based on point cloud and deep learning for robotics dexterous grasping from three perspectives is given in this paper. As a new category schemes of the mainstream methods, the proposed generation-evaluation framework is the core concept of the classification. The other two classifications based on learning modes and applications are also briefly described afterwards. This review aims to afford a guideline for robotics dexterous grasping researchers and developers

Network pharma cology and GEO chip based elucidation of mechanisms underlying the use of Yi Tieqing for prevention and treatment of postoperative nausea and vomiting

Purpose: To investigate the mechanism(s) involved in the use of Yi Tieqing for the prevention and treatment of postoperative nausea and vomiting (PONV), using network pharmacology and GEO chip. Methods: The chemical constituents and functional targets of five traditional Chinese medicines in Yi Tieqing were obtained by searching TCMSP database. The PONV disease targets were identified through DisGeNET, GeneCards and DrugBank databases, and differential expression genes of the GEO database chip (GSE7762) were mined. From the intersections of the component targets and disease targets, the core targets of drugs and diseases were obtained. The core targets were investigated in R language using GO-biological process and KEGG enrichment analyses, and their biological activities were verified via molecular docking. Finally, the severity and incidence of PONV in control and treatment groups were determined and compared. Results: A total of 254 bioactive components and 301 related potential targets were obtained from the TCMSP database. There were 2092 related targets in PONV, and 6 intersecting targets were obtained from Venn diagram. The results of GO biological process and KEGG enrichment analysis showed that the incidence of PONV was strongly correlated with the negative regulation of response to wounding and nervous system. Clinical results showed that from 24 – 48 h (T2) after operation, the severity and incidence of PONV in the treatment group were significantly lower than those in the control group (p < 0.05). Conclusion: Yi Tieqing alleviates PONV through multi-components, multi-targets, and multi-pathways

Aqueous electrosynthesis of an electrochromic material based water-soluble EDOT-MeNH2 hydrochloride

2\u27-Aminomethyl-3,4-ethylenedioxythiophene (EDOT-MeNH2) showed unsatisfactory results when its polymerization occurred in organic solvent in our previous report. Therefore, a water-soluble EDOT derivative was designed by using hydrochloric modified EDOT-MeNH2 (EDOT-MeNH2·HCl) and electropolymerized in aqueous solution to form the corresponding polymer with excellent electrochromic properties. Moreover, the polymer was systematically explored, including electrochemical, optical properties and structure characterization. Cyclic voltammetry showed low oxidation potential of EDOT-MeNH2·HCl (0.85 V) in aqueous solution, leading to the facile electrodeposition of uniform the polymer film with outstanding electroactivity. Compared with poly(2′-aminomethyl- 3,4-ethylenedioxythiophene) (PEDOT-MeNH2), poly(2′-aminomethyl-3,4-ethylenedioxythiophene salt) (PEDOT-MeNH3 +A-) revealed higher efficiencies (156 cm2 C-1), lower bandgap (1.68 eV), and faster response time (1.4 s). Satisfactory results implied that salinization can not only change the polymerization system, but also adjust the optical absorption, thereby increase the electrochromic properties

CPSAA: Accelerating Sparse Attention using Crossbar-based Processing-In-Memory Architecture

The attention mechanism requires huge computational efforts to process unnecessary calculations, significantly limiting the system's performance. Researchers propose sparse attention to convert some DDMM operations to SDDMM and SpMM operations. However, current sparse attention solutions introduce massive off-chip random memory access. We propose CPSAA, a novel crossbar-based PIM-featured sparse attention accelerator. First, we present a novel attention calculation mode. Second, we design a novel PIM-based sparsity pruning architecture. Finally, we present novel crossbar-based methods. Experimental results show that CPSAA has an average of 89.6X, 32.2X, 17.8X, 3.39X, and 3.84X performance improvement and 755.6X, 55.3X, 21.3X, 5.7X, and 4.9X energy-saving when compare with GPU, FPGA, SANGER, ReBERT, and ReTransformer.Comment: 14 pages, 19 figure

HSPA12A Unstabilizes CD147 to Inhibit Lactate Export and Migration in Human Renal Cell Carcinoma

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. Background: Metastasis accounts for 90% of cancer-associated mortality in patients with renal cell carcinoma (RCC). However, the clinical management of RCC metastasis is challenging. Lactate export is known to play an important role in cancer cell migration. This study investigated the role of heat shock protein A12A (HSPA12A) in RCC migration. Methods: HSPA12A expression was examined in 82 pairs of matched RCC tumors and corresponding normal kidney tissues from patients by immunoblotting and immunofluorescence analyses. The proliferation of RCC cells was analyzed using MTT and EdU incorporation assays. The migration of RCC cells was evaluated by wound healing and Transwell migration assays. Extracellular acidification was examined using Seahorse technology. Protein stability was determined following treatment with protein synthesis inhibitor cycloheximide and proteasome inhibitor MG132. Mass spectrometry, immunoprecipitation, and immunoblotting were employed to examine protein-protein interactions. Results: RCC tumors from patients showed downregulation of HSPA12A, which was associated with advanced tumor node metastasis stage. Intriguingly, overexpression of HSPA12A in RCC cells inhibited migration, whereas HSPA12A knockdown had the opposite effect. Lactate export, glycolysis rate, and CD147 protein abundance were also inhibited by HSPA12A overexpression but promoted by HSPA12A knockdown. An interaction of HSPA12A with HRD1 ubiquitin E3 ligase was detected in RCC cells. Further studies demonstrated that CD147 ubiquitination and proteasomal degradation were promoted by HSPA12A overexpression whereas inhibited by HSPA12A knockdown. Notably, the HSPA12A overexpression-induced inhibition of lactate export and migration were abolished by CD147 overexpression. Conclusion: Human RCC shows downregulation of HSPA12A. Overexpression of HSPA12A in RCC cells unstabilizes CD147 through increasing its ubiquitin-proteasome degradation, thereby inhibits lactate export and glycolysis, and ultimately suppresses RCC cell migration. Our results demonstrate that overexpression of HSPA12A might represent a viable strategy for managing RCC metastasis

Understanding Local Bonding Structures of Ni-Doped Chromium Nitride Coatings through Synchrotron Radiation NEXAFS Spectroscopy

CrN has widespread applications as protective coatings, for example, in aircraft jet engines whereby their high hardness and good oxidation resistance render metal components resistant to harsh operating conditions. Alloying elements are commonly incorporated (doped) into the coatings to further enhance their thermomechanical properties. However, the effect of dopants on the electronic properties and their roles in modifying the grain boundary configurations remain unclear. Lack of such critical knowledge has hindered the development of design strategies for high performance CrN-based coatings. To address this challenging issue, in the present study near-edge X-ray absorption fine structure (NEXAFS) investigations of Cr1-yNiyN coatings at the Cr L3,2-edge (570-610 eV), Ni L3,2-edge (840-890 eV), and N K-edge (380-450 eV) regions were conducted using synchrotron radiation soft X-ray (SXR) spectroscopy in both Auger electron yield (AEY) and total fluorescence yield (TFY) modes. The chemical states in CrNiN were found to change with the increase of Ni content, manifested as a small chemical shift and moderate change of shapes of various absorption edges. The CrN grain size also became smaller with increasing Ni concentration. These findings help improve our understanding of local bonding structures, which could potentially lead to improved coating designs for highly demanding applications