A Markovian–Bayesian Network for Risk Analysis of High Speed and Conventional Railway Lines Integrating Human Errors

The article provides a new Markovian–Bayesian network model to evaluate the probability of accident associated with the circulation of trains along a given high speed or conventional railway line with special consideration to human error. This probability increases as trains pass throughout the different elements encountered along the line. A Bayesian network, made up of a sequence of several connected Bayesian subnetworks, is used. A subnetwork is associated with each element in the line that implies a concentrated risk of accident or produces a change in the driver's attention, such as signals, tunnel, or viaduct entries or exits, etc. Bayesian subnetworks are also used to reproduce segments without signals where some elements add continuous risks, such as rolling stock failures, falling materials, slope slides in cuttings and embankments, etc. All subnetworks are connected with the previous one and some of them are multi‐connected because some consequences are dependent on previous errors. Because driver's attention plays a crucial role, its degradation with driving time and the changes due to seeing light signals or receiving acoustic signals is taken into consideration. The model updates the driver's attention level and accumulates the probability of accident associated with the different elements encountered along the line. This permits us to generate a continuously increasing risk graph that includes continuous and sudden changes indicating where the main risks appear and whether or not an action must be taken by the infrastructure manager. Sensitivity analysis allows the relevant and irrelevant parameters to be identified avoiding wastes of time and money by concentrating safety improvement actions only on the relevant ones. Finally, some examples are used to illustrate the model. In particular, the case of the Orense–Santiago de Compostela line, where a terrible accident took place in 2013.     

GutSelf: Interindividual Variability in the Processing of Dietary Compounds by the Human Gastrointestinal Tract

Nutritional research is currently entering the field of personalized nutrition, to a large extent driven by major technological breakthroughs in analytical sciences and biocomputing. An efficient launching of the personalized approach depends on the ability of researchers to comprehensively monitor and characterize interindividual variability in the activity of the human gastrointestinal tract. This information is currently not available in such a form. This review therefore aims at identifying and discussing published data, providing evidence on interindividual variability in the processing of the major nutrients, i.e., protein, fat, carbohydrates, vitamins, and minerals, along the gastrointestinal tract, including oral processing, intestinal digestion, and absorption. Although interindividual variability is not a primary endpoint of most studies identified, a significant number of publications provides a wealth of information on this topic for each category of nutrients. This knowledge remains fragmented, however, and understanding the clinical relevance of most of the interindividual responses to food ingestion described in this review remains unclear. In that regard, this review has identified a gap and sets the base for future research addressing the issue of the interindividual variability in the response of the human organism to the ingestion of foods.     

A four year study to determine the optimal harvesting period for Tunisian Chemlali olives

Due to the importance of the stage of maturity on several olive pomological parameters and oil quality indices, and to the interest that Tunisian olive oil production has recently received, the optimal harvesting period for the main Tunisian olive cultivar, Chemlali, was assessed. For the first time, a four‐season crops study, carried out in three representative geographical areas, was focused on both olive fruit pomological parameters and oil chemical composition at different stages of maturity. The stage of maturity was the factor showing the highest influence on the major part of these parameters, followed by the crop year. To guarantee a reasonable fat content and a good chemical quality of oil, in particular a harmonious acidic composition, acceptable UV absorbance, and a content high of antioxidants, unsaponifiable matter and sterols, the optimal harvesting period for Chemlali olives would appears to be between the end of November to the middle of December, which corresponds to a maturity index between 2.5 and 3.5.     

The sprayed ZnO films: nanostructures and physical parameters

We synthesized the pure and indium-doped (IZO) ZnO films with a facile composition control spray pyrolysis route. The substrate temperature (T_s) and In-doping effects on the properties of as-grown films are investigated. The X-ray pattern confirms that the as-synthesized ZnO phase is grown along a (002) preferential plane. It is revealed that the crystalline structure is improved with a substrate temperature of 350 ℃. Moreover, the morphology of as-grown films, analyzed by AFM, shows nanostructures that have grown along the c-axis. The (3 × 3μm²) area scanned AFM surface studies give the smooth film surface RMS < 40 nm. The UV-VIS-IR measurements reveal that the sprayed films are highly transparent in the visible and IR bands. The photoluminescence analysis shows that the strong blue and yellow luminescences of 2.11 and 2.81 eV are emitted from ZnO and IZO films with a slight shift in photon energy caused by In-doping. The band gap is a bit widened by In-doping, 3.21 eV (ZnO) and 3.31 eV (IZO) and the resistivity is reduced from 385 to 8 Ω ·m. An interesting result is the resistivity linear dependence on the substrate temperature of pure ZnO films.     

热轧低密度钢Fe-1.80Mn-1.05Al-0.09C的高温热塑性

采用Gleeble 3500热模拟试验机对一种低合金系热轧低密度钢进行了高温(760～1200℃)热塑性研究,并结合光学显微镜、体视显微镜以及扫描电镜对拉断后的断口附近组织和断口形貌进行了表征。结果表明,随着拉伸温度升高,断口面积逐渐缩小,韧窝也逐渐变大变深,断面收缩率总体表现良好,均达到80%以上,表现出了良好的高温热塑性。但是试验钢在900～1000℃进行拉伸时,出现了多处颈缩现象,900～1000℃时存在理论塑性低谷区,应避免在900～1000℃进行铸坯矫直或轧制。     

残余元素对涟钢CSP热冷轧卷质量的影响

钢中的残余元素问题是钢铁冶金面临的重要问题之一,高性能新钢种必须考虑残余元素的有害影响.涟钢矿石来源多而杂,导致铁水中As,Cu,Pb,Sn,Sb等残余元素增加.从残余元素(As,Cu,Pb,Sn,Sb等)对涟钢热轧卷、冷轧卷表面质量和力学性能的影响进行分析.分析结果表明:送检的热轧卷发现表面氧化铁与试样基体的界面有铜的富集;晶界处铜的富集会成为热轧卷产生裂纹的原因之一;冷轧卷酸洗后表面有黑点,黑点处发现有Cu,As,Sn,Sb等残余元素的富集;对特定时期的热轧卷力学性能进行多次逐步回归分析发现Sb对屈服强度有显著的负相关.