DGI: Easy and Efficient Inference for GNNs

While many systems have been developed to train Graph Neural Networks (GNNs), efficient model inference and evaluation remain to be addressed. For instance, using the widely adopted node-wise approach, model evaluation can account for up to 94% of the time in the end-to-end training process due to neighbor explosion, which means that a node accesses its multi-hop neighbors. On the other hand, layer-wise inference avoids the neighbor explosion problem by conducting inference layer by layer such that the nodes only need their one-hop neighbors in each layer. However, implementing layer-wise inference requires substantial engineering efforts because users need to manually decompose a GNN model into layers for computation and split workload into batches to fit into device memory. In this paper, we develop Deep Graph Inference (DGI) -- a system for easy and efficient GNN model inference, which automatically translates the training code of a GNN model for layer-wise execution. DGI is general for various GNN models and different kinds of inference requests, and supports out-of-core execution on large graphs that cannot fit in CPU memory. Experimental results show that DGI consistently outperforms layer-wise inference across different datasets and hardware settings, and the speedup can be over 1,000x.Comment: 10 pages, 10 figure

10Be和26Ai揭示的合黎山西南部侵蚀速率初步研究

地表侵蚀速率是衡量地貌演化的一个重要因子。本研究利用原地宇宙成因核素 10Be 和 26Al 对合黎山西南部地表岩石侵蚀速率进行了首次测定。结果显示：约 30 ka 以来，合黎山西南部的地表岩石侵速率约为 24 mm∙ka-1。这一结果与已见报道的其他基岩侵蚀速率值一致。这一结果与 Small et al 获得的非干旱地区的基岩侵蚀速率也基本一致，但是显著高于干旱的南极地区和半干旱的澳大利亚。10Be 和26Al 获得的侵蚀速率的良好一致性表明本研究中所用侵蚀模式的有效性。所得的侵蚀速率小于 Palumbo et al 测定的合黎山平均流域侵蚀速率（99 mm∙ka-1），原因解释尚待更多地点和样品的研究。<br style="line-height: normal; text-align: -webkit-auto; text-size-adjust: auto;" /

A multi-objective control strategy for three phase grid-connected inverter during unbalanced voltage sag

This paper presents a new multi-objective control strategy for inverter-interfaced distributed generation (IIDG) to ensure its safe and continuous operation under unbalanced voltage sags. The proposed control strategy can effectively improve the low voltage ride through (LVRT) capability, reduce active power oscillations, and limit overcurrent simultaneously, which are marked as the most important control objectives of IIDG during unbalanced voltage sags. The advanced voltage support scheme, which utilizes positive sequence component, is firstly proposed to maximize the LVRT capability of IIDG during unbalanced voltage sags. Then, to ensure the safety of IIDG, the active power oscillation suppression and current limitation algorithm are designed individually. Based on the control algorithms of such objectives, the multi-objective control method, including scenario classification and reference current determination, is then presented to achieve such three objectives under various system conditions simultaneously. Finally, case studies and evaluations based on MATLAB/Simulink are carried out to illustrate the effectiveness of the proposed method

An improved inverse-time over-current protection method for microgrid with optimized acceleration and coordination

This paper presents an improved inverse-time over-current protection method based on the compound fault acceleration factor and the beetle antennae search (BAS) optimization method for microgrid. The proposed method can not only significantly increase the operation speed of inverse-time over-current protection but also improve the protection coordination by considering possible influential factors, in terms of microgrid operation modes, distributed generation (DG) integration status, fault types, and positions, which are marked as the most challenging problems for over-current protection of microgrid. In this paper, a new Time Dial Setting (TDS) of inverse-time protection is developed by applying a compound fault acceleration factor, which can notably accelerate the speed of protection by using low-voltage and short-circuit impedance during the fault. In order to improve protection coordination, the BAS algorithm is then used to optimize the protection parameters of pick up current, TDS and the inverse time curve shape coefficient. Finally, the case studies and various evaluations based on DIgSILENT/Power Factory are carried out to illustrate the effectiveness of the proposed method

Association of CD40 Gene Polymorphisms with Sporadic Breast Cancer in Chinese Han Women of Northeast China

BACKGROUND: Breast cancer is a polygenetic disorder with a complex inheritance pattern. Single nucleotide polymorphisms (SNPs), the most common genetic variations, influence not only phenotypic traits, but also interindividual predisposition to disease, treatment outcomes with drugs and disease prognosis. The co-stimulatory molecule CD40 plays a prominent role in immune regulation and homeostasis. Accumulating evidence suggests that CD40 contributes to the pathogenesis of cancer. Here, we set out to test the association between polymorphisms in the CD40 gene and breast carcinogenesis and tumor pathology. METHODOLOGY AND PRINCIPAL FINDINGS: Four SNPs (rs1800686, rs1883832, rs4810485 and rs3765459) were genotyped by the polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) method in a case-control study including 591 breast cancer patients and 600 age-matched healthy controls. Differences in the genotypic distribution between breast cancer patients and healthy controls were analyzed by the Chi-square test for trends. Our preliminary data showed a statistically significant association between the four CD40 gene SNPs and sporadic breast cancer risk (additive P = 0.0223, 0.0012, 0.0013 and 0.0279, respectively). A strong association was also found using the dominant, recessive and homozygote comparison genetic models. In the clinical features analysis, significant associations were observed between CD40 SNPs and lymph node metastasis, human epidermal growth factor receptor 2 (C-erbB2), estrogen receptor (ER), progesterone receptor (PR) and tumor protein 53 (P53) statuses. In addition, our haplotype analysis indicated that the haplotype C(rs1883832)G(rs4810485), which was located within the only linkage disequilibrium (LD) block identified, was a protective haplotype for breast cancer, whereas T(rs1883832)T(rs4810485) increased the risk in the studied population, even after correcting the P value for multiple testing (P = 0.0337 and 0.0430, respectively). CONCLUSIONS AND SIGNIFICANCE: Our findings primarily show that CD40 gene polymorphisms contribute to sporadic breast cancer risk and have a significant association with clinicopathological features among Chinese Han women from the Heilongjiang Province

B7-H4 gene polymorphisms are associated with sporadic breast cancer in a Chinese Han population

© 2009 Zhang et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Practical Research of Electronic Transformer Based on Interpolation Algorithm

As a result of the adoption of new photovoltaic technology, electronic transformers have great advantages compared with traditional electromagnetic type, such as anti-saturated, high linearity, compact and lightweight etc. The working principle of sensing head of electronic current/voltage transformers is introduced in the paper. The causes of phase error in electronic transformer are analyzed. And a set of phase compensation methods based on the signal transfer principle of electronic transformer is presented. The phase-difference caused by Rogowski coil and time-delay in signal transferring from high voltage side to merging unit are analyzed, and the higher sampling rate and the method of linear interpolation is used to solve the problem. In the simulation test the phase error compensation effect is very good, and the simulation result shows that the integrated error after compensation is able to meet the requirements of the measurement and protection, and demonstrates the validity of the method. DOI: http://dx.doi.org/10.11591/telkomnika.v11i2.198

Energy supply reliability assessment of the integrated energy system considering complementary and optimal operation during failure

Integrated energy system (IES) is an effective solution for energy and environment problems. In view of the difficulty of traditional reliability assessment methods to reasonably and effectively assess the reliability of the IES, an energy supply reliability assessment method based on sequential Monte Carlo simulation is proposed in this study. The optimal operation of the system is realised by mobilising the multi-energy complementary characteristics during device failure. The reliability of the system under three different operation objectives is compared and analysed. Three new reliability indices are proposed, which take into account the supply of multiple energy loads and the differences among different energy. Finally, through the analysis of energy supply reliability under different objectives, the reasonability of the proposed indices and the flexible scheduling of energy flow under different objectives are verified; therefore, the IES can realise adaptive and targeted operation strategy during device failure. Also, the influence of different device faults on the system's energy supply reliability is ranked, which is of great significance to find the weak parts of the system and provide a reference for the system to improve energy supply reliability

Optimal operation of multiple integrated energy systems based on a hybrid Taguchi‐compact salp swarm algorithm

Abstract With the rapid development of integrated energy system (IES), it has become a trend to form multiple integrated energy systems (MIESs) in a certain region. However, there is a lack of coordination and cooperation among MIESs. This paper proposes an optimal operation model of MIESs with four cost objectives, which focuses on energy interaction among MIESs. As a non‐linear and large optimization problem, it is difficult for conventional mathematical methods to solve. Hence, this paper proposes a hybrid Taguchi‐compact salp swarm algorithm (TCSSA). The compact technique can save the operation memory of model. Taguchi method can improve the convergence speed and solution accuracy of model. The proposed algorithm is tested on 28 benchmark functions and applied to optimal operation of MIESs. Results demonstrate that: (1) compared with other famous algorithms, TCSSA can provide more efficient execution and better solutions. (2) The optimal operation of MIESs based on TCSSA can achieve the complementary of energy advantages, which effectively reduces the total cost of MIESs (up to 9.67%)