Functional Dysregulations in CA1 Hippocampal Networks of a 3-Hit Mouse Model of Schizophrenia

For a better translation from treatment designs of schizophrenia to clinical efficiency, there is a crucial need to refine preclinical animal models. In order to consider the multifactorial nature of the disorder, a new mouse model associating three factors (genetic susceptibility—partial deletion of the MAP6 gene, early-life stress—maternal separation, and pharmacological treatment—chronic Δ-9-tetrahydrocannabinol during adolescence) has recently been described. While this model depicts a schizophrenia-like phenotype, the neurobiological correlates remain unknown. Synaptic transmission and functional plasticity of the CA1 hippocampal region of male and female 3-hit mice were therefore investigated using electrophysiological recordings on the hippocampus slice. While basal excitatory transmission remained unaffected, NMDA receptor (NMDAr)-mediated long-term potentiation (LTP) triggered by theta-burst (TBS) but not by high-frequency (HFS) stimulation was impaired in 3-hit mice. Isolated NMDAr activation was not affected or even increased in female 3-hit mice, revealing a sexual dimorphism. Considering that the regulation of LTP is more prone to inhibitory tone if triggered by TBS than by HFS, the weaker potentiation in 3-hit mice suggests a deficiency of intrinsic GABA regulatory mechanisms. Indeed, NMDAr activation was increased by GABA_A receptor blockade in wild-type but not in 3-hit mice. This electrophysiological study highlights dysregulations of functional properties and plasticity in hippocampal networks of 3-hit mice, one of the mechanisms suspected to contribute to the pathophysiology of schizophrenia. It also shows differences between males and females, supporting the sexual dimorphism observed in the disorder. Combined with the previously reported study, the present data reinforce the face validity of the 3-hit model that will help to consider new therapeutic strategies for psychosis.     

Multiple Empirical Kernel Learning with Majority Projection for imbalanced problems

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To make MEKL suit for the imbalanced problems, this paper introduces a weight matrix and a regularization term into MEKL. The weight matrix assigns high misclassification cost to the minority samples to balanced misclassification cost between minority and majority class. The regularization term named Majority Projection (MP) is used to make the classification hyperplane fit the distribution shape of majority samples and enlarge the between-class distance of minority and majority class. The contributions of this work are: (i) assigning high cost to minority samples to deal with imbalanced problems, (ii) introducing a new regularization term to concern the property of data distribution, (iii) and modifying the original PAC-Bayes bound to test the error upper bound of MEKL-MP. Through analyzing the experimental results, the proposed MEKL-MP is well suited to the imbalanced problems and has lower generalization risk in accordance with the value of PAC-Bayes bound.     

基于降噪时序深度学习网络的风电功率短期预测方法

利用风电场历史功率数据预测未来一段时间内的风功率,对保障电网安全稳定运行具有重要的意义。本文提出一种基于奇异谱分析SSA(singular spectrum analysis)和长短时记忆LSTM(long-short term memory net⁃work)网络的时序特征预测框架用于短期风功率的预测。首先通过SSA对历史风功率原始数据进行降噪处理,然后经过数据转换之后,以LSTM网络为基础进行预测模型的训练,最后通过某风电场提供的两个风机的历史功率数据进行验证。实验结果表明,奇异谱分析对风电场的历史数据具有良好的降噪性,SSA+LSTM模型在测试数据上取得了较好的预测性能,能够有效进行短期风功率的预测。     

NNI-1型C_5/C_6烷烃异构化催化剂长周期运行分析及建议

中国石化海南炼油化工有限公司0.2 Mt/a C5/C6烷烃异构化装置以连续重整装置的拔头油为原料,使用NNI-1催化剂,采用一次通过流程,不设脱异戊烷塔和稳定塔,经设在连续重整装置内的脱丁烷塔稳定处理后作为汽油调合组分。该装置于2006年9月开工投产,截至2015年3月已连续运行3个周期。长周期运行分析结果表明:前两个周期中NNI-1催化剂具有较高的异构化活性及选择性,C5异构化率为60%左右,C6异构化率为80%左右,C6选择性为15%左右,产品辛烷值基本达到技术指标要求(RON≥78);而在第三周期运行中,催化剂积炭增加等原因导致其异构化活性及选择性降低,异构化产品辛烷值提升能力呈现逐步衰减的趋势,提高反应苛刻度已不能弥补催化剂活性下降造成的产品辛烷值降低。为保证装置长周期运行,建议择机停工对催化剂进行再生,或是直接换用与装置原料性质匹配的异构化催化剂。     

Prioritizing the elective surgery patient admission in a Chinese public tertiary hospital using the hesitant fuzzy linguistic ORESTE method

In public health systems around the world, there are not enough medical resources to provide elective (e.g., scheduled or non-emergency) services for all patients immediately. One feasible solution is to prioritize patients by taking into account a variety of factors, such as disease severity, waiting time, and disease types. This is a typical Multiple Criteria Decision Making (MCDM) problem. To solve this problem, in this paper, we first conduct an investigation on the admission process, and obtain 16 indicators affecting patients’ admission, which form a criteria system. Since there is much vague and uncertain information which can be depicted by the hesitant fuzzy linguistic term set effectively for these indicators, we then apply a powerful MCDM method, named the hesitant fuzzy linguistic ORESTE, to prioritize the elective surgery patient admission in a Chinese public tertiary hospital, the West China Hospital. Robust results are obtained by performing a sensitivity analysis with six scenarios. We also compare the results with those derived by other HFL-MCDM methods. It is illustrated that the hesitant fuzzy linguistic ORESTE can help hospitals flexibly manage the patient admissions.     

考虑新能源的梯级水电中长期调度策略研究

研究风光水中长期互补协调调度对探索风光的接入对水电运行的影响有重要意义。以流域Y下游两库五级梯级水电站及其周边的风光资源为例，建立了计及发电量最大化和时段最小出力最大化的双目标模型，在求解时将时段最小出力最大化目标转化为约束条件，在约束破坏时对目标函数加以惩罚，以达到简化求解的目的。最后通过分析互补协调调度的效果及风光对水库蓄泄水的影响提取了互补运行中梯级水电的调度策略，即互补运行中，水库群蓄水时期的调度策略以水资源最优化为原则，供水时期需重点关注，应根据风光总发电特性进行策略调整。     

Learning keyword phrases from query logs of USPTO patent examiners for automatic query scope limitation in patent searching

Professional search in patent repositories poses several unique challenges. One key requirement is to search the entire affected space of concepts, following well-defined procedures to ensure traceability of results obtained. Several techniques have been introduced to enhance query generation, preferably via automated query term expansion, to improve retrieval effectiveness. Currently, these approaches are mostly limited to computing additional query terms from patent documents based on statistical measures. For conceptual search to solve the limitation of traditional keyword search standard dictionaries are used to provide synonyms and keyword phrases for query refinement. Studies show that these are insufficient in such highly specialized domains. In this paper, we present an approach to extract keyword phrases from query logs created during the validation procedure of the patent applications. This creates valuable domain-specific lexical databases for several specific patent classes that can be used to both expand as well as limit the scope of a patent search. This provides a more powerful means to guide a professional searcher through the search process. We evaluate the lexical databases based on real query sessions of patent examiners.     

Analysis on hydrogen risk mitigation in severe accidents for Pressurized Heavy Water Reactor

Hydrogen source term and hydrogen mitigation under severe accidents is evaluated for most nuclear power plants (NPPs) after Fukushima Daiichi accident. Two units of Pressurized Heavy Water Reactor (PHWR) are under operating in China, and hydrogen risk control should be evaluated in detail for the existing design. The distinguish feature of PHWR, compared with PWR, is the horizontal reactor core surrounded by moderator in calandria vessel (CV), which may influence the hydrogen source term. Based on integral system analysis code of PHWR, the plant model including primary heat transfer system (PHTS), calandria, end shield system, reactor cavity and containment has been developed. Two severe accident sequences have been selected to study hydrogen generation characteristic and the effectiveness of hydrogen mitigation with igniters. The one is Station Blackout (SBO) which represents high-pressure core melt accident, and the other is Large Break Loss of Coolant Accident (LLOCA) at reactor outlet header (ROH) which represents low-pressure core melt accident. Results show that under severe accident sequences, core oxidation of zirconium–steam reaction will produce hydrogen with deterioration of core cooling and the water in CV and reactor cavity can inhibits hydrogen generation for a relatively long time. However, as the water dries out, creep failure happens on CV. As a result, molten core falls into cavity and molten core concrete interaction (MCCI) occurs, releasing a large mass of hydrogen. When hydrogen igniters fail, volume fraction of hydrogen in the containment is more than 15% while equivalent amount of hydrogen generate from a 100% fuel clad-coolant reaction. As a result, hydrogen risk lies in the deflagration–detonation transition area. When igniters start at the beginning of large hydrogen generation, hydrogen mixtures ignite at low concentration in the compartments and the combustion mode locates at the edge of flammable area. However, the power supply to igniters should be ensured.