OpenGCD: Assisting Open World Recognition with Generalized Category Discovery

A desirable open world recognition (OWR) system requires performing three tasks: (1) Open set recognition (OSR), i.e., classifying the known (classes seen during training) and rejecting the unknown (unseen$/$novel classes) online; (2) Grouping and labeling these unknown as novel known classes; (3) Incremental learning (IL), i.e., continual learning these novel classes and retaining the memory of old classes. Ideally, all of these steps should be automated. However, existing methods mostly assume that the second task is completely done manually. To bridge this gap, we propose OpenGCD that combines three key ideas to solve the above problems sequentially: (a) We score the origin of instances (unknown or specifically known) based on the uncertainty of the classifier's prediction; (b) For the first time, we introduce generalized category discovery (GCD) techniques in OWR to assist humans in grouping unlabeled data; (c) For the smooth execution of IL and GCD, we retain an equal number of informative exemplars for each class with diversity as the goal. Moreover, we present a new performance evaluation metric for GCD called harmonic clustering accuracy. Experiments on two standard classification benchmarks and a challenging dataset demonstrate that OpenGCD not only offers excellent compatibility but also substantially outperforms other baselines. Code: https://github.com/Fulin-Gao/OpenGCD

Role of extracellular signal-regulated kinase 1/2 signaling underlying cardiac hypertrophy

Cardiac hypertrophy is the result of increased myocardial cell size responding to an increased workload and developmental signals. These extrinsic and intrinsic stimuli as key drivers of cardiac hypertrophy have spurred efforts to target their associated signaling pathways. The extracellular signal-regulated kinases 1/2 (ERK1/2), as an essential member of mitogen-activated protein kinases (MAPKs), has been widely recognized for promoting cardiac growth. Several modified transgenic mouse models have been generated through either affecting the upstream kinase to change ERK1/2 activity, manipulating the direct role of ERK1/2 in the heart, or targeting phosphatases or MAPK scaffold proteins to alter total ERK1/2 activity in response to an increased workload. Using these models, both regulation of the upstream events and modulation of each isoform and indirect effector could provide important insights into how ERK1/2 modulates cardiomyocyte biology. Furthermore, a plethora of compounds, inhibitors, and regulators have emerged in consideration of ERK, or its MAPK kinases, are possible therapeutic targets against cardiac hypertrophic diseases. Herein, is a review of the available evidence regarding the exact role of ERK1/2 in regulating cardiac hypertrophy and a discussion of pharmacological strategy for treatment of cardiac hypertrophy

Requirements-driven self-repairing against environmental failures

Self-repairing approaches have been proposed to alleviate the runtime requirements satisfaction problem by switching to appropriate alternative solutions according to the feedback monitored. However, little has been done formally on analyzing the relations between specific environmental failures and corresponding repairing decisions, making it a challenge to derive a set of alternative solutions to withstand possible environmental failures at runtime. To address these challenges, we propose a requirements-driven self-repairing approach against environmental failures, which combines both development-time and runtime techniques. At the development phase, in a stepwise manner, we formally analyze the issue of self-repairing against environmental failures with the support of the model checking technique, and then design a sufficient and necessary set of alternative solutions to withstand possible environmental failures. The runtime part is a runtime self-repairing mechanism that monitors the operating environment for unsatisfiable situations, and makes self-repairing decisions among alternative solutions in response to the detected environmental failures

Mapping quantitative trait loci for T lymphocyte subpopulations in peripheral blood in swine

<p>Abstract</p> <p>Background</p> <p>Increased disease resistance through improved general immune capacity would be beneficial for the welfare and productivity of farm animals. T lymphocyte subpopulations in peripheral blood play an important role in immune capacity and disease resistance in animals. However, very little research to date has focused on quantitative trait loci (QTL) for T lymphocyte subpopulations in peripheral blood in swine.</p> <p>Results</p> <p>In the study, experimental animals consist of 446 piglets from three different breed populations. To identify QTL for T lymphocyte subpopulations in peripheral blood in swine, the proportions of CD4+, CD8+, CD4+CD8+, CD4+CD8-, CD4-CD8+, and CD4-CD8- T cells and the ratio of CD4+:CD8+ T cells were measured for all individuals before and after challenge with modified live CSF (classical swine fever) vaccine. Based on the combined data of individuals from three breed populations, genome-wide scanning of QTL for these traits was performed based on a variance component model, and the genome wide significance level for declaring QTL was determined via permutation tests as well as FDR (false discovery rate) correction. A total of 27 QTL (two for CD4+CD8+, one for CD4+CD8-, three for CD4-CD8+, two for CD4-CD8-, nine for CD4+, two for CD8+, and eight for CD4+:CD8+ ratio) were identified with significance level of <it>FDR </it>< 0.10, of which 11 were significant at the level of <it>FDR </it>< 0.05, including the five significant at <it>FDR </it>< 0.01.</p> <p>Conclusions</p> <p>Within these QTL regions, a number of known genes having potential relationships with the studied traits may serve as candidate genes for these traits. Our findings herein are helpful for identification of the causal genes underlying these immune-related trait and selection for immune capacity of individuals in swine breeding in the future.</p