WindGP: Efficient Graph Partitioning on Heterogenous Machines

Graph Partitioning is widely used in many real-world applications such as fraud detection and social network analysis, in order to enable the distributed graph computing on large graphs. However, existing works fail to balance the computation cost and communication cost on machines with different power (including computing capability, network bandwidth and memory size), as they only consider replication factor and neglect the difference of machines in realistic data centers. In this paper, we propose a general graph partitioning algorithm WindGP, which can support fast and high-quality edge partitioning on heterogeneous machines. WindGP designs novel preprocessing techniques to simplify the metric and balance the computation cost according to the characteristics of graphs and machines. Also, best-first search is proposed instead of BFS and DFS, in order to generate clusters with high cohesion. Furthermore, WindGP adaptively tunes the partition results by sophisticated local search methods. Extensive experiments show that WindGP outperforms all state-of-the-art partition methods by 1.35 - 27 times on both dense and sparse distributed graph algorithms, and has good scalability with graph size and machine number.Comment: 19 pages, 15 figures, 18 table

SPARK-NC: A Lead-Bismuth-Cooled Small Modular Fast Reactor with Natural Circulation and Load Following Capabilities

In this study, a conceptual design was developed for a lead-bismuth-cooled small modular fast reactor SPARK-NC with natural circulation and load following capabilities. The nominal rated power was set to 10 MWe, and the power can be manipulated from 5 MWe to 10 MWe during the whole core lifetime. The core of the SPARK-NC can be operated for eight effective full power years (EFPYs) without refueling. The core neutronics and thermal-hydraulics design calculations were performed using the SARAX code and the natural circulation capability of the SPARK-NC was investigated by employing the energy conservation equation, pressure drop equation and quasi-static reactivity balance equation. In order to flatten the radial power distribution, three radial zones were constructed by employing different fuel enrichments and fuel pin diameters. To provide an adequate shutdown margin, two independent systems, i.e., a control system and a scram system, were introduced in the core. The control assemblies were further classified into two types: primary control assemblies used for reactivity control and power flattening and secondary control assemblies (with relatively smaller reactivity worth) used for power regulation. The load following capability of SPARK-NC was assessed using the quasi-static reactivity balance method. By comparing three possible approaches for adjusting the reactor power output, it was shown that the method of adjusting the coolant inlet temperature was viable, practically easy to implement and favored for the load following operation

Class imbalance: A crucial factor affecting the performance of tea plantations mapping by machine learning

Due to disparities in area among various land cover types, class imbalance has always existed in crop mapping research, posing uncertainties in extracting minority classes which occupy a smaller area. In this paper, taking tea plantations mapping in Hangzhou city as an example, we created a series of training datasets with different imbalance-ratios (IRs), compared the accuracy between the extraction models using these datasets, and analyzed the impact of class imbalance on various machine learning algorithms (Artificial Neural Network, Decision Tree, Random Forest and XGBoost), aiming to provide a feasible approach to improve the mapping accuracy of minority classes. The leave-one-out cross validation results showed that in most cases, with the increase of the IR, the model’s F2-score first increased and then decreased, and the increase of F2-scores ranged from 0.2% to 29.2%, suggesting that moderately increasing the number of other samples in the training dataset can improve the tea plantations extraction accuracy. Consistent result can also be obtained by using the whole city’s samples for modeling and random sampling validation. XGBoost performed best among the four algorithms, which yielded the optimal tea plantations map with a PA of 97%, UA of 93% and F2-score of 96% when the IR of the training dataset was 6. The UA was 19% higher than that of the model using a balanced dataset (IR=1) and was 11% higher than that of the model using pseudo-balanced datasets created by the oversampling method. The conclusions of this study offer insights for the identification of minority classes, contributing to achieving higher accuracy in remote sensing crop mapping

MicroRNA-326 attenuates immune escape and prevents metastasis in lung adenocarcinoma by targeting PD-L1 and B7-H3

Abstract Tumor-infiltrating T cells are highly expressive of inhibitory receptor/immune checkpoint molecules that bind to ligand expressed by tumor cells and antigen-presenting cells, and eventually lead to T cell dysfunction. It is a hot topic to restore T cell function by targeting immune checkpoint. In recent years, immunotherapy of blocking immune checkpoint and its receptor, such as PD-L1/PD-1 targeted therapy, has made effective progress, which brings hope for patients with advanced malignant tumor. However, only a few patients benefit from directly targeting these checkpoints or their receptors by small compounds or antibodies. Since the complexity of the regulation of immune checkpoints in tumor cells, further research is needed to identify the novel endogenous regulators of immune checkpoints which can help for developing effective drug target to improve the effect of immunotherapy. Here, we verified that microRNA-326 (miR-326) repressed the gene expression of immune checkpoint molecules PD-L1 and B7-H3 in lung adenocarcinoma (LUAD). We detected that the expression of miR-326 in LUAD tissue was negatively correlated with PD-L1/B7-H3. The repression of PD-L1 and B7-H3 expression through miR-326 overexpression leads to the modification the cytokine profile of CD8+ T cells and decreased migration capability of tumor cells. Meanwhile, the downregulation of miR-326 promoted tumor cell migration. Moreover, blocking PD-L1 and B7-H3 attenuated the tumor-promoting effect induced by miR-326 inhibitor. In tumor-bearing mice, the infiltration of CD8+ T cells was significantly increased and the expression of TNF-α, and IFN-γ was significantly enhanced which contributed to tumor progression after miR-326 overexpression. Collectively, miR-326 restrained tumor progression by downregulating PD-L1 and B7-H3 expression and increasing T cell cytotoxic function in LUAD. Our findings revealed a novel perspective on the complex regulation of immune checkpoint molecules. A new strategy of using miR-326 in tumor immunotherapy is proposed