ParisTech

About: ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Residual stress & Finite element method. The organization has 1888 authors who have published 1965 publications receiving 55532 citations. The organization is also known as: Paris Institute of Technology & ParisTech Développement.

Does complex hydrology require complex water quality policy

Abstract: Nonpoint-source water pollution is frequently considered intractable because it is hard to regulate large numbers of small sources and because the science associated with assessing the impact of each source is complex. New Zealand has demonstrated that it is possible to implement a simple cap-and-trade system to help reduce nitrogen leaching from many small farms and thereby protect water quality. This paper relates to the second challenge: are complex regulatory systems worthwhile when nitrogen delivery is complex? When nitrogen moves through groundwater to a lake, leaching from different farms reaches the lake at different times and the damage caused is temporally differentiated. Policy that regulates farmers according to the timing of their nitrogen delivery will be more complex than policy that does not. Whether the gain in efficiency justifies this additional complexity can be assessed through modelling. We use an integrated model to estimate the gains from complex nitrogen regulation that incorporates groundwater delivery times relative to simple nitrogen regulation that does not. We find that the gains from more complex regulation are small in the catchment we study and cannot justify the additional complexity required. A sensitivity analysis enables us to identify the types of catchments where complex regulation may be worthwhile.

A new comprehensive possibilistic group decision approach for resilient supplier selection with mean–variance–skewness–kurtosis and asymmetric information under interval-valued fuzzy uncertainty

Abstract: Since resilient supplier selection problems (RSSPs) are regarded vague, uncertain and complex, interval-valued fuzzy sets (IVFSs) and possibilistic statistical theories can assist to deal with preferences and experience of group of experts into meaningful results to appraise the potential suppliers. This research presents a novel comprehensive possibilistic statistical group decision approach with IVFSs and asymmetric information to solve RSSPs in the supply chain networks (SCNs). Possibilistic statistical concepts, including mean, variance, skewness and kurtosis, are proposed for the first time in the literature of SCNs for the group decision process. Also, asymmetric information with IVFSs is provided in the presented approach along with introducing two new extensions of weighting methods for experts as well as evaluation criteria. In addition, new relations, new separation measures and novel distinguish indices are introduced regarding to the preference by similarity to ideal solutions with mean–variance–skewness–kurtosis modeling. Then, the proposed comprehensive decision approach is implemented to an application in automobile industry for the RSSPs to assess the resilience strategy in the SCNs under uncertain conditions.

Towards a Pragmatic Approach to a Psychophysiological Unit of Analysis for Mental and Brain Disorders: An EEG-Copeia for Neurofeedback.

Abstract: This article proposes what we call an “EEG-Copeia” for neurofeedback, like the “Pharmacopeia” for psychopharmacology. This paper proposes to define an “EEG-Copeia” as an organized list of scientifically validated EEG markers, characterized by a specific association with an identified cognitive process, that define a psychophysiological unit of analysis useful for mental or brain disorder evaluation and treatment. A characteristic of EEG neurofeedback for mental and brain disorders is that it targets a EEG markers related to a supposed cognitive process, whereas conventional treatments target clinical manifestations. This could explain why EEG neurofeedback studies encounter difficulty in achieving reproducibility and validation. The present paper suggests that a first step to optimize EEG neurofeedback protocols and future research is to target a valid EEG marker. The specificity of the cognitive skills trained and learned during real time feedback of the EEG marker could be enhanced and both the reliability of neurofeedback training and the therapeutic impact optimized. However, several of the most well-known EEG markers have seldom been applied for neurofeedback. Moreover, we lack a reliable and valid EEG targets library for further RCT to evaluate the efficacy of neurofeedback in mental and brain disorders. With the present manuscript, our aim is to foster dialogues between cognitive neuroscience and EEG neurofeedback according to a psychophysiological perspective. The primary objective of this review was to identify the most robust EEG target. EEG markers linked with one or several clearly identified cognitive-related processes will be identified. The secondary objective was to organize these EEG markers and related cognitive process in a psychophysiological unit of analysis matrix inspired by the Research Domain Criteria (RDoC) project.

Diastereoselective synthesis of the C17–C30 fragment of amphidinol 3

Abstract: The diastereoselective synthesis of the C17–C30 fragment of amphidinol 3 (AM3) 1 was achieved from the enantio-enriched aldehyde 20, Weinreb amide 14 and 2-bromo-3-(trimethylsilyl)propene, which was used as a bifunctional conjunctive reagent. The absolute configuration of the stereogenic centers, in both aldehyde 20 and Weinreb amide 14, were efficiently controlled by using (+)-(R)-methyl-p-tolylsulfoxide as the unique source of chirality.