“站票坐票同价销售”背后的法学思考——兼评“丁昌祥诉北京铁路局无座车票价格案”

据不完全统计,从1998年葛锐诉郑州铁路分局至今10余年,铁路部门因公益诉讼站在被告席的次数已不少于10次。这些诉讼在一定程度上推动了中国法治建设的进程。但深究诉讼中原、被告博弈的过程,其中折射出的经济学、社会学及法学问题不容小觑。随着我国改革的全面深化,培育法治信仰、优化法治环境,方能实现法治"中国梦"、促进经济社会和谐发展。     

Influence of Si-Doping on the Performance of InGaN/GaN Multiple Quantum Well Solar Cells

Semiconductors - The performance of InGaN/GaN multiple quantum well (MQW) solar cells with five different Si-doping concentrations, namely 0, 4 × 1017 cm–3, 1 × 1018 cm–3, 3...     

空气预热器实时监控系统堵塞可视化性能研究

针对电站锅炉回转式空气预热器运行时上下表面不可见的问题，本文提出了一种视频监控与故障分析系统，可直接监测转子表面情况。该系统通过视频监控获取图像，结合改进的Retinex算法对其进行处理，实现了以下2个功能:1）能分析积灰程度以判断转子堵塞 情况；2）与温度场融合实时显示转子表面热点分布以预防二次燃烧。该系统已应用于某600 MW机组，实现了在热态环境下对空气预热器转子积灰程度、热点分布、堵塞程度的估算与可视化，大大提高了空气预热器运行的可靠性。     

从7-ADCA生产过程中环境友好的回收苯乙酸

采用新工艺回收7-氨基-3-脱乙酰氧基头孢烷酸(7-ADCA)生产中产生的苯乙酸,并对苯乙酸回收过程中产生的废硫酸进行处理。采用硫酸(9 8%)洗涤二氯甲烷,硫酸与二氯甲烷适宜的体积比为1∶50,洗涤好的二氯甲烷中含苯乙酸4%。蒸馏出二氯甲烷,趁热向熔融苯乙酸中加入母液,降温析出苯乙酸。晾干的苯乙酸为白色鳞片状,含量大于99%,苯乙酸母液补充部分清水套用到下一批析出苯乙酸。废浓硫酸用芬顿试剂氧化,控制80℃氧化4h,双氧水和七水硫酸亚铁重量比为6∶1,废浓硫酸COD下降85%以上。氧化结束后向废硫酸中加入铁粉和双氧水,制得聚合硫酸铁。     

火电机组负荷分配中多源不确定性因素影响分析

不确定性因素存在于火电机组负荷分配中，影响机组负荷分配、节能环保目标。本文综合考虑负荷预测不确定性、机组煤耗率不确定性与其CO2排放系数不确定性，分别构建火电机组一次能源消耗成本与CO2排放量最小目标下的火电机组负荷优化分配模型；以此为基础，引入析因分析方差分解方法，量化多源不确定性因素单独与交互作用下对节能、环保目标的影响程度。结果表明:负荷预测不确定性对火电机组节能、环保目标影响最为显著，相对影响程度分别为51.13%、62.70%；机组煤耗特性及其CO2排放系数影响次之，相对影响程度分别为47.58%、34.95%。此研究结果对不确定性条件下电力系统负荷分配具有借鉴价值。     

低剂量抑制剂Inhibex501存在下的甲烷水合物相平衡研究

含动力学抑制剂的天然气水合物相平衡研究对新型低剂量抑制剂的开发具有指导作用。在283.6 ~ 290.9 K和7.51 MPa ~ 15.97 MPa的温压范围内研究了抑制剂Inhibex501及其溶剂2-乙二醇单丁醚对甲烷水合物相平衡条件的影响。实验结果显示，0.5wt%和2.0wt%浓度的Inhibex501对甲烷水合物形成的热力学条件具有促进作用，能使甲烷水合物形成移向更高的温度或者更低的压力，而2-乙二醇单丁醚在浓度0.2wt% ~ 1.0wt%范围几乎不改变甲烷水合物形成的热力学条件，N-乙烯基己内酰胺与N-乙烯基吡咯烷酮的共聚物对水合物形成热力学条件的改变起主要作用。     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.