Identification of Topological Features in Renal Tumor Microenvironment Associated with Patient Survival

Motivation As a highly heterogeneous disease, the progression of tumor is not only achieved by unlimited growth of the tumor cells, but also supported, stimulated, and nurtured by the microenvironment around it. However, traditional qualitative and/or semi-quantitative parameters obtained by pathologist’s visual examination have very limited capability to capture this interaction between tumor and its microenvironment. With the advent of digital pathology, computerized image analysis may provide a better tumor characterization and give new insights into this problem. Results We propose a novel bioimage informatics pipeline for automatically characterizing the topological organization of different cell patterns in the tumor microenvironment. We apply this pipeline to the only publicly available large histopathology image dataset for a cohort of 190 patients with papillary renal cell carcinoma obtained from The Cancer Genome Atlas project. Experimental results show that the proposed topological features can successfully stratify early- and middle-stage patients with distinct survival, and show superior performance to traditional clinical features and cellular morphological and intensity features. The proposed features not only provide new insights into the topological organizations of cancers, but also can be integrated with genomic data in future studies to develop new integrative biomarkers

Momentum Benefits Non-IID Federated Learning Simply and Provably

Federated learning is a powerful paradigm for large-scale machine learning, but it faces significant challenges due to unreliable network connections, slow communication, and substantial data heterogeneity across clients. FedAvg and SCAFFOLD are two fundamental algorithms to address these challenges. In particular, FedAvg employs multiple local updates before communicating with a central server, while SCAFFOLD maintains a control variable on each client to compensate for "client drift" in its local updates. Various methods have been proposed in literature to enhance the convergence of these two algorithms, but they either make impractical adjustments to algorithmic structure, or rely on the assumption of bounded data heterogeneity. This paper explores the utilization of momentum to enhance the performance of FedAvg and SCAFFOLD. When all clients participate in the training process, we demonstrate that incorporating momentum allows FedAvg to converge without relying on the assumption of bounded data heterogeneity even using a constant local learning rate. This is a novel result since existing analyses for FedAvg require bounded data heterogeneity even with diminishing local learning rates. In the case of partial client participation, we show that momentum enables SCAFFOLD to converge provably faster without imposing any additional assumptions. Furthermore, we use momentum to develop new variance-reduced extensions of FedAvg and SCAFFOLD, which exhibit state-of-the-art convergence rates. Our experimental results support all theoretical findings

Exploring Evaluation Factors and Framework for the Object of Automated Trading System

Automated trading system (ATS) is a computer program that combines different trading rules to find optimal trading opportunities. The objects of ATS, which are financial assets, need evaluation because that is of great significance for stakeholders and market orders. From the perspectives of dealers, agents, external environment, and objects themselves, this study explored factors in evaluating and choosing the object of ATS. Based on design science research (DSR), we presented a preliminary evaluation framework and conducted semi-structured interviews with twelve trading participants engaged in different occupations. By analyzing the data collected, we validated eight factors from literatures and found four new factors and fifty-four sub-factors. Additionally, this paper developed a relationship model of factors. The results could be used in future work to explore and validate more evaluation factors by using data mining

Complete genome sequence of a Megalocytivirus (family Iridoviridae) associated with turbot mortality in China

<p>Abstract</p> <p>Background</p> <p>Turbot reddish body iridovirus (TRBIV) causes serious systemic diseases with high mortality in the cultured turbot, <it>Scophthalmus maximus</it>. We here sequenced and analyzed the complete genome of TRBIV, which was identified in Shandong province, China.</p> <p>Results</p> <p>The genome of TRBIV is a linear double-stranded DNA of 110,104 base pairs, comprising 55% G + C. Total 115 open reading frames were identified, encoding polypeptides ranging from 40 to 1168 amino acids. Amino acid sequences analysis revealed that 39 of the 115 potential gene products of TRBIV show significant homology to other iridovirus proteins. Phylogenetic analysis of conserved genes indicated that TRBIV is closely related to infectious spleen and kidney necrosis virus (ISKNV), rock bream iridovirus (RBIV), orange-spotted grouper iridovirus (OSGIV), and large yellow croaker iridovirus (LYCIV). The results indicated that TRBIV belongs to the genus <it>Megalocytivirus </it>(family Iridoviridae).</p> <p>Conclusions</p> <p>The determination of the genome of TRBIV will provide useful information for comparative study of Megalocytivirus and developing strategies to control outbreaks of TRBIV-induced disease.</p

Study of Injection Molding Warpage Using Analytic Hierarchy Process and Taguchi Method

This study integrated Analytic Hierarchy Process and Taguchi method to investigate into injection molding warpage. The warpage important factor will be elected by Analytic Hierarchy Process (AHP), the AHP hierarchy analysis factor from documents collected and aggregate out data, then through the expert questionnaire delete low weight factor. Finally, we used Taguchi quality engineering method to decide injection molding optimized combination factors. Furthermore, the paper used injection pressure, holding pressure, holding time, mold temperature to analyze four factors, three levels Taguchi design data. Moreover, the paper discussed the reaction of each factor on the S / N ratio and analysis of variance to obtain the best combination of minimal warpage

ANALYSIS OF ANGULAR MOMENTUM THE WHOLE BODY DURING GLIDE HITTING AND KICK HITTING IN BASEBALL

The purpose of this study were to analyze the biomechanical characteristics of glide and kick hitting in baseball which exerted by professional baseball players in Taiwan. Five professional baseball players were selected as the subjects. The experiment used two JVC-DV 9800 high-speed digital cameras(120 Hz).The video data was treated by Kwon3D 3.0 motion analysis system. The following are the main results: The kick hitting could get better rotation benefit and optimum. In the stride phase, angUlar momentum of the body is increasing by body inertia. In the rotation phase, the velocity increasing of the body center of gravity makes the angUlar momentum increase. The largest angular momentum appears right before the ball hi!. Because the body inertia in ball hitting moment was very small, the angUlar momentum was mainly affected by angular velocity. In the phase, the average value, largest value and hitting moment value of angular momentum with kick hitting are larger than those with glide hitting. Therefore, the kick hitting could get larger linear and angular momentum

Habitat adaptation drives speciation of a Streptomyces species with distinct habitats and disparate geographic origins

Microbial diversification is driven by geographic and ecological factors, but how the relative importance of these factors varies among species, geographic scales, and habitats remains unclear. Streptomyces, a genus of antibiotic-producing, spore-forming, and widespread bacteria, offers a robust model for identifying the processes underlying population differentiation. We examined the population structure of 37 Streptomyces olivaceus strains isolated from various sources, showing that they diverged into two habitat-associated (free-living and insect-associated) and geographically disparate lineages. More frequent gene flow within than between the lineages confirmed genetic isolation in S. olivaceus. Geographic isolation could not explain the genetic isolation; instead, habitat type was a strong predictor of genetic distance when controlling for geographic distance. The identification of habitat-specific genetic variations, including genes involved in regulation, resource use, and secondary metabolism, suggested a significant role of habitat adaptation in the diversification process. Physiological assays revealed fitness trade-offs under different environmental conditions in the two lineages. Notably, insect-associated isolates could outcompete free-living isolates in a free-iron-deficient environment. Furthermore, substrate (e.g., sialic acid and glycogen) utilization but not thermal traits differentiated the two lineages. Overall, our results argue that adaptive processes drove ecological divergence among closely related streptomycetes, eventually leading to dispersal limitation and gene flow barriers between the lineages. S. olivaceus may best be considered a species complex consisting of two cryptic species.China Ocean Mineral Resources R&D Association/[DY135-B2-02]/CONRA/ChinaNational Natural Science Foundation of China/[32070001 and 91751118]/NSFC/ChinaRV KEXUE/[KEXUE2019GZ05]//ChinaChinese Academy of Sciences/[KEXUE2019GZ05]/CAS/ChinaUniversidad de Costa Rica/[801-B0-530]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Estructuras Microscópicas (CIEMIC)UCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ciencias de la Computación e Informátic

Stability Assessment of the PET-Based Distributed Grid

The penetration of renewables has been increasing nowadays. The traditional transformer can no longer meet the requirements of utilities. For this reason, a power electronic transformer (PET) is proposed as one of the promising alternatives. However, there are coupling issues between the PET and the connected converters in the low-voltage grid. To study the issues effectively, this article developed impedance models of the PQ node, PV node, and PET. Based on the models, the system stability under different scenarios is assessed by the generalized Nyquist criterion. The effects of the line impedance and control parameters on system stability are studied. Moreover, a comprehensive parameter sensitivity analysis was carried out to reveal the coupling mechanism between converters. Simulations are given to validate the effectiveness of the theoretical analyses