污水处理PPP项目收益风险云模型综合评价

为了准确评价污水处理PPP(public private partnership)项目收益风险,解决单一方法评价的局限性,提出了一种收益风险云模型综合评价模型.首先建立了污水处理P P P项目收益风险评价指标体系,并提出了改进FSE-SD二次加权模型,在风险指标传统主客观赋权的基础上,对风险指标进行二次加权得到最终权重...     

基于在线神经网络的自适应控制器的设计与应用

针对线性控制系统自适应性较弱的缺点,在其基础上设计了一种基于在线神经网络的自适应控制器．该控制器根据被控对象和参考模型之间的误差调整网络权值,在线抵消被控对象的未建模动态特性和不确定因素．文中以某小卫星姿态控制系统为例,对所提出的自适应控制器进行设计和仿真．结果表明,神经网络以很高的精度跟踪和在线补偿不确定项,改善了线性控制系统的动态性能．     

激光标刻的复杂区域填充算法

为减少填充线段和提高激光加工效率,对复杂区域的填充算法进行了研究．采用延长某些岛屿边界将包含岛屿的区域变为单连通域;然后用最长边延长法和最长边平行截取法将单连通域分解为简单凸多边形,简单凸多边形填充方法是先找到凸多边形所有边对应的高最小的那条边,平行该边进行填充,最后对填充线段的连接顺序进行优化处理．与传统的固定方向扫描填充相比,采用本算法可使复杂区域和实心文字的激光标刻效率提高20％～40％．     

分年龄段的互惠模型的行波解

讨论了一类分年龄段的生物种群互惠模型的行波解存在性问题．在一般带时滞的互惠Lotka—Volterra模型基础上,考虑了年龄段和空间非局部等因素对反应扩散方程行波解存在性的影响．构造了一对合适的上下解,利用单调迭代方法证明了模型的两个平衡点之间行波解的存在性,进一步丰富了单调方法的内容．     

晶格失配对超晶格法向导热系数影响的分子动力学模拟

采用非平衡态分子动力学方法模拟了超晶格的法向导热系数随周期长度的变化关系.模拟结果表明,在晶格匹配的超晶格中,当周期长度同声子平均自由程相当时,超晶格导热系数将出现最小值.而对于具有4%晶格失配的超晶格模拟结果却表明,超晶格导热系数随周期长度的增大而单调上升.这一研究结果表明,材料的晶格失配是大多数实验研究中没有发现超晶格最小导热系数的主要原因.     

氧化铁纳米颗粒固定化溶藻菌的除藻作用

为了探讨氧化铁纳米颗粒固定化溶藻菌后对铜绿微囊藻的溶藻作用和降解微囊藻毒素LR(MC-LR)的作用,从太湖水体中分离获得一株属于芽孢杆菌属的溶藻菌,将其与氧化铁纳米颗粒固定化后,以普通Fe2O3作为实验对照,测定其溶藻作用和降解MC-LR作用.以激光粒度仪测定氧化铁纳米颗粒与溶藻菌两者单独和同时存在时的粒径大小及粒径分布,以获得氧化铁纳米颗粒固定化溶藻菌的证据.分析结果表明:在太湖水体中分离获得的一株芽孢杆菌具有较强的溶藻和降解MC-LR的作用,作用24 h后的溶藻率和MC-LR降解率分别达到44.3%和20.5%.同时加入氧化铁纳米颗粒后,溶藻率达到53.0%,MC-LR的降解率达到33.0%.激光粒度仪检测发现,氧化铁纳米颗粒与细菌混合后的颗粒物的平均直径增加到氧化铁纳米颗粒的12.3倍,同时氧化铁纳米颗粒和细菌单独存在时的粒径分布峰消失.氧化铁纳米颗粒是一种具有良好性能的生物固定化材料,可能通过其特有的途径有效地固定化溶藻菌,并增强溶藻菌的溶藻和降解藻毒素作用.     

Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

Financial distress prediction (FDP) has been widely considered as a promising approach to reducing financial losses. While financial information comprises the traditional factors involved in FDP, nonfinancial factors have also been examined in recent studies. In light of this, the purpose of this study is to explore the integrated factors and multiple models that can improve the predictive performance of FDP models. This study proposes an FDP framework to reveal the financial distress features of listed Chinese companies, incorporating financial, management, and textual factors, and evaluating the prediction performance of multiple models in different time spans. To develop this framework, this study employs the wrapper-based feature selection method to extract valuable features, and then constructs multiple single classifiers, ensemble classifiers, and deep learning models in order to predict financial distress. The experiment results indicate that management and textual factors can supplement traditional financial factors in FDP, especially textual ones. This study also discovers that integrated factors collected 4 years prior to the predicted benchmark year enable a more accurate prediction, and the ensemble classifiers and deep learning models developed can achieve satisfactory FDP performance. This study makes a novel contribution as it expands the predictive factors of financial distress and provides new findings that can have important implications for providing early warning signals of financial risk.     

An eicosanoid-centric view of atherothrombotic risk factors

Cardiovascular disease is the foremost cause of morbidity and mortality in the Western world. Atherosclerosis followed by thrombosis (atherothrombosis) is the pathological process underlying most myocardial, cerebral, and peripheral vascular events. Atherothrombosis is a complex and heterogeneous inflammatory process that involves interactions between many cell types (including vascular smooth muscle cells, endothelial cells, macrophages, and platelets) and processes (including migration, proliferation, and activation). Despite a wealth of knowledge from many recent studies using knockout mouse and human genetic studies (GWAS and candidate approach) identifying genes and proteins directly involved in these processes, traditional cardiovascular risk factors (hyperlipidemia, hypertension, smoking, diabetes mellitus, sex, and age) remain the most useful predictor of disease. Eicosanoids (20 carbon polyunsaturated fatty acid derivatives of arachidonic acid and other essential fatty acids) are emerging as important regulators of cardiovascular disease processes. Drugs indirectly modulating these signals, including COX-1/COX-2 inhibitors, have proven to play major roles in the atherothrombotic process. However, the complexity of their roles and regulation by opposing eicosanoid signaling, have contributed to the lack of therapies directed at the eicosanoid receptors themselves. This is likely to change, as our understanding of the structure, signaling, and function of the eicosanoid receptors improves. Indeed, a major advance is emerging from the characterization of dysfunctional naturally occurring mutations of the eicosanoid receptors. In light of the proven and continuing importance of risk factors, we have elected to focus on the relationship between eicosanoids and cardiovascular risk factors.     

Histone deacetylase inhibitors augment doxorubicin-induced DNA damage in cardiomyocytes

Histone deacetylase inhibitors have emerged as a new class of anticancer therapeutics with suberoylanilide hydroxamic acid (Vorinostat) and depsipeptide (Romidepsin) already being approved for clinical use. Numerous studies have identified that histone deacetylase inhibitors will be most effective in the clinic when used in combination with conventional cancer therapies such as ionizing radiation and chemotherapeutic agents. One promising combination, particularly for hematologic malignancies, involves the use of histone deacetylase inhibitors with the anthracycline, doxorubicin. However, we previously identified that trichostatin A can potentiate doxorubicin-induced hypertrophy, the dose-limiting side-effect of the anthracycline, in cardiac myocytes. Here we have the extended the earlier studies and evaluated the effects of combinations of the histone deacetylase inhibitors, trichostatin A, valproic acid and sodium butyrate on doxorubicin-induced DNA double-strand breaks in cardiomyocytes. Using γH2AX as a molecular marker for the DNA lesions, we identified that all of the broad-spectrum histone deacetylase inhibitors tested augment doxorubicin-induced DNA damage. Furthermore, it is evident from the fluorescence photomicrographs of stained nuclei that the histone deacetylase inhibitors also augment doxorubicin-induced hypertrophy. These observations highlight the importance of investigating potential side-effects, in relevant model systems, which may be associated with emerging combination therapies for cancer.     

Frequent mutations of chromatin remodeling genes in transitional cell carcinoma of the bladder

Transitional cell carcinoma (TCC) is the most common type of bladder cancer. Here we sequenced the exomes of nine individuals with TCC and screened all the somatically mutated genes in a prevalence set of 88 additional individuals with TCC with different tumor stages and grades. In our study, we discovered a variety of genes previously unknown to be mutated in TCC. Notably, we identified genetic aberrations of the chromatin remodeling genes (UTX, MLL-MLL3, CREBBP-EP300, NCOR1, ARID1A and CHD6) in 59% of our 97 subjects with TCC. Of these genes, we showed UTX to be altered substantially more frequently in tumors of low stages and grades, highlighting its potential role in the classification and diagnosis of bladder cancer. Our results provide an overview of the genetic basis of TCC and suggest that aberration of chromatin regulation might be a hallmark of bladder cancer.