Diabetes during Pregnancy: A Maternal Disease Complicating the Course of Pregnancy with Long-Term Deleterious Effects on the Offspring. A Clinical Review

In spite of the huge progress in the treatment of diabetes mellitus, we are still in the situation that both pregestational (PGDM) and gestational diabetes (GDM) impose an additional risk to the embryo, fetus, and course of pregnancy. PGDM may increase the rate of congenital malformations, especially cardiac, nervous system, musculoskeletal system, and limbs. PGDM may interfere with fetal growth, often causing macrosomia, but in the presence of severe maternal complications, especially nephropathy, it may inhibit fetal growth. PGDM may also induce a variety of perinatal complications such as stillbirth and perinatal death, cardiomyopathy, respiratory morbidity, and perinatal asphyxia. GDM that generally develops in the second half of pregnancy induces similar but generally less severe complications. Their severity is higher with earlier onset of GDM and inversely correlated with the degree of glycemic control. Early initiation of GDM might even cause some increase in the rate of congenital malformations. Both PGDM and GDM may cause various motor and behavioral neurodevelopmental problems, including an increased incidence of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Most complications are reduced in incidence and severity with the improvement in diabetic control. Mechanisms of diabetic-induced damage in pregnancy are related to maternal and fetal hyperglycemia, enhanced oxidative stress, epigenetic changes, and other, less defined, pathogenic mechanisms.     

Networked Estimation of Multi‐Agent Systems Subject to Faults and Unreliable Information

In this paper, a novel framework for networked estimation of multi‐agent systems subject to presence of actuator faults is proposed. This framework is developed based on the notion of sub‐observers where within a group of sub‐observers each sub‐observer estimates certain states that are conditioned on a given input, output, and other state information. We model the overall estimation process by a weighted estimation (WE) digraph. By selecting an appropriate path in the WE digraph, an assigned supervisor can select and configure a set of sub‐observers to successfully estimate all the system states. In the presence of large intermittent disturbances, noise, and faults certain sub‐observers may become invalid, and consequently the supervisor reconfigures the set of sub‐observers by selecting a new path in the estimation digraph such that the impacts of these uncertainties are confined to only the local estimators. This will prevent the propagation of uncertainties on the estimation performance of the entire multi‐agent system. Simulation results provided for a five satellite formation flight system in deep space confirm the validity and applicability of our proposed analytical work.     

基于滑动窗口的直升机序列异常检测算法

无标签的序列在异常检测算法中往往存在着对数据的信息掌握不全面、不能合理使用的情况,而采用深度学习的技术实现检测时往往对其计算的解释性欠佳;对于攻克这些难题,以直升机飞行数据为例对时间序列的反常检测问题展开了深入研究,并利用Iforest技术和PCA算法,给出了一个采用滑动窗口的时间序列异常检测方法,利用从滑动窗口采集信息的时间变化状态等数据信息,将序列异常检测问题转换为点异常检测问题;同时以auc评分为衡量标准,从带有时刻特殊标志的多个信息集上检验了检测效率的提高;在无标签的直升机飞行数据集上进行实验,验证了算法的有效性,并通过对比检测过程中不同特征变量的变化情况,从算法层面和现实层面上阐述了算法的可解释性。     

Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations and Future Projections

Based on observations and Coupled Model Intercomparison Project Phase 5 (CMIP5) results, multidecadal variations and trends in annual mean surface air temperature anomalies (SATa) at global, hemispheric, and hemispheric land and ocean scales in the past and under the future scenarios of two representative concentration pathways (RCPs) are analyzed. Fifteen models are selected based on their performances in capturing the temporal variability, long-term trend, multidecadal variations, and trends in global annual mean SATa. Observational data analysis shows that the multidecadal variations in annual mean SATa of the land and ocean in the northern hemisphere (NH) and of the ocean in the southern hemisphere (SH) are similar to those of the global mean, showing an increase during the 1900–1944 and 1971–2000 periods, and flattening or even cooling during the 1945–1970 and 2001–2013 periods. These observed characteristics are basically reproduced by the models. However, SATa over SH land show an increase during the 1945–1970 period, which differs from the other hemispheric scales, and this feature is not captured well by the models. For the recent hiatus period (2001–2013), the projected trends of BCC-CSM1-1-m, CMCC-CM, GFDL-ESM2M, and NorESM1-ME at the global and hemispheric scales are closest to the observations based on RCP4.5 and RCP8.5 scenarios, suggesting that these four models have better projection capability in SATa. Because these four models are better at simulating and projecting the multidecadal trends of SATa, they are selected to analyze future SATa variations at the global and hemispheric scales during the 2006–2099 period. The selected multi-model ensemble (MME) projected trends in annual mean SATa for the globe, NH, and SH under RCP4.5 (RCP8.5) are 0.17 (0.29) °C, 0.22 (0.36) °C, and 0.11 (0.23) °C·decade⁻¹ in the 21st century, respectively. These values are significantly lower than the projections of CMIP5 MME without model selection.     

A novel three-tiered visualization approach for firewall rule validation

Firewall is one of the most critical elements of the current Internet, which can protect the entire network against attacks and threats. While configuring the firewalls, rule configuration has to conform to, or say be consistent with, the demands of the network security policies such that the network security would not be flawed. For the security consistency, firewall rule editing, ordering, and distribution must be done very carefully on each of the cooperative firewalls, especially in a large-scale and multifirewall-equipped network. Nevertheless, a network operator is prone to incorrectly configure the firewalls because there are typically thousands or hundreds of filtering/admission rules (i.e., rules in the Access Control List file, or ACL for short), which could be set up in a firewall; not mentioning these rules among firewalls affect mutually and can make the matter worse. Under this situation, the network operator would hardly know his/her misconfiguration until the network functions beyond the expectation. For this reason, our work is to build a visualized validation system for facilitating the check of security consistency between the rule configuration of firewalls and the demands of network security policies. To do so, the developed validation system utilizes a three-tiered visualization hierarchy along with different compound viewpoints to provide users with a complete picture of firewalls and relationships among them for error debugging and anomaly removal. In addition, in this paper, we also enumerate the source of security inconsistency while setting ACLs and make use of it as a basis of the design of our visualization model. Currently, part of the firewall configuration of our campus network has been used as our system's input to demonstrate our system's implementation.     

综合物探方法在河南济源疙瘩深隐伏铁矿床勘查中的应用

河南省济源市疙瘩铁矿床深隐伏沉积变质型磁铁矿床,地面磁异常呈弱缓特征。常规的单一磁法辅助地质对确定矿体埋深尚显不足。矿区岩矿石的电阻率特征具备采用电法来推断赋矿地层的大致埋深和起伏形态,又基于地质体埋藏较深,因而布设了可控源音频大地电磁测深方法,推断出地质体的大致深度。在此基础上,对弱缓磁异常再进行反演。这样通过对可控源音频大地电磁测深(CSAMT)异常和弱磁异常进行综合研究,推断出的磁铁矿体产状及埋深为地质优化钻孔提供了较可靠的依据。这种综合物探方法对解决深隐伏磁铁矿地质问题具有借鉴意义。     

军事电子网络对抗中网络流量异常识别

由于军事电子网络对抗中的流量具有海量、高速的特征,且异常流量具有较强的特征隐蔽性,因此,采用传统算法进行异常流量识别往往均有耗时大、有效识别率低的缺陷.为此,提出基于主分量分析与多时间序列数据挖掘算法相结合的军事电子网络对抗中网络流量异常识别方法.针对各维熵值时间序列之间具有关联性的特点,利用支持向量机算法进行多维流量数据分类,为异常流量的识别提供数据支持,依据主分量分析法对维数进行缩减,对信息熵值异常子空间与正常子空间进行有效分离,实现军事电子网络对抗中网络异常流量的有效识别.实验结果表明,采用改进算法进行军事电子网络对抗中网络流量异常识别,能够有效提高异常流量识别率及识别准确性,有效的保障了军事电子网络的安全性,具有显著的优越性.     

刚果（布）Mpassa-Moubiri铜多金属矿区多源遥感蚀变矿化异常提取

刚果(布)Mpassa-Moubiri矿区铜、铅、锌等矿种找矿前景良好,运用多源遥感数据可提供丰富的找矿地质信息。本文选取Aster、Sentinel-2A、Worldview-2影像,采用主成分分析法分别提取白铅矿化、菱锌矿化、硅化、铁染、蓝铜矿化、孔雀石化等蚀变矿化异常信息,光谱角监督分类方法提取浅表含矿黑土异常信息。运用GIS密度分割挖掘各类蚀变矿化信息空间分布规律,并将其作为评价指标构建层次分析模型,最终圈定异常强度阈值高于0.8、面积17.18 km²的遥感综合异常区域。结果表明：遥感综合异常主要呈北东向展布,富集在碳酸盐岩与碎屑岩接触带的有利成矿部位,与地表调查、化探异常吻合较好,表明多源数据组合能有效提取该矿区蚀变矿化信息,可为后续大比例尺勘查工作部署提供依据。     

供电企业基于三层分析模型的线损异常分析及处理研究

线损精益化管理一直都是国家电网公司一项重点工作,近几年线损数据获取技术日趋成熟,但是分析方法依旧匮乏,严重影响了高损治理的效果。为解决电网运行中高损治理不佳的问题,我们提出了用大数据分析方法来解决传统线损管理问题——供电企业基于三层分析模型的线损异常分析及处理研究。首先,搭建了一个由Hampel抗差算法、加权皮尔逊算法和随机森林算法三种不同算法构成的三层线损异常分析模型;通过该模型,可以结合不同用户用电量大小不一的特点,自上而下的分析大电量异常用户和小电量异常用户。然后将该模型嵌入公司已有的线损监控平台中,可以实现对全省线损数据的实时监测、有效挖掘、深度分析、精准定位和工单管控,形成基于三层分析模型的线损异常分析及处理新方法。该方法对分析处理10kV高损线路和0.4kV高损台区中效果显著。