University of Lorraine

About: University of Lorraine is a education organization based out in Nancy, France. It is known for research contribution in the topics: Population & Nonlinear system. The organization has 11942 authors who have published 25010 publications receiving 425227 citations. The organization is also known as: Lorraine University.

A new record excited state (3)MLCT lifetime for metalorganic iron(ii) complexes.

Abstract: Herein we report the synthesis and time-resolved spectroscopic characterization of a homoleptic Fe(ii) complex exhibiting a record (3)MLCT lifetime of 26 ps promoted by benzimidazolylidene-based ligands. Time dependent density functional molecular modeling of the triplet excited state manifold clearly reveals that, at equilibrium geometries, the lowest (3)MC state lies higher in energy than the lowest (3)MLCT one. This unprecedented energetic reversal in a series of iron complexes, with the stabilization of the charge-transfer state, opens up new perspectives towards iron-made excitonic and photonic devices, hampering the deactivation of the excitation via metal centered channels.

Conséquences psychopathologiques du confinement

Abstract: The psychological effects of isolation have already been described in the literature (polar expeditions, submarines, prison). Nevertheless, the scale of confinement implemented during the COVID-19 pandemic is unprecedented. In addition to reviewing the published studies, we need to anticipate the psychological problems that could arise during or at a distance from confinement. We have gone beyond the COVID-19 literature in order to examine the implications of the known consequences of confinement, like boredom, social isolation, stress, or sleep deprivation. Anxiety, post-traumatic stress disorder, depression, suicidal or addictive behaviours, domestic violence are described effects of confinement, but the mechanisms of emergence of these disorders and their interrelationships remain to be studied. For example, what are the mechanisms of emergence of post-traumatic stress disorders in the context of confinement? We also remind the reader of points of vigilance to be kept in mind with regard to eating disorders and hallucinations. Hallucinations are curiously ignored in the literature on confinement, whereas a vast literature links social isolation and hallucinations. Due to the broad psychopathological consequences, we have to look for these various symptoms to manage them. We quickly summarize the diagnostic and therapeutic approaches already in place, such as telemedicine, which is undergoing rapid development during the COVID-19 crisis.

Association of Polygenic Score for Schizophrenia and HLA Antigen and Inflammation Genes With Response to Lithium in Bipolar Affective Disorder: A Genome-Wide Association Study.

Abstract: Importance Lithium is a first-line mood stabilizer for the treatment of bipolar affective disorder (BPAD). However, the efficacy of lithium varies widely, with a nonresponse rate of up to 30%. Biological response markers are lacking. Genetic factors are thought to mediate treatment response to lithium, and there is a previously reported genetic overlap between BPAD and schizophrenia (SCZ). Objectives To test whether a polygenic score for SCZ is associated with treatment response to lithium in BPAD and to explore the potential molecular underpinnings of this association. Design, Setting, and Participants A total of 2586 patients with BPAD who had undergone lithium treatment were genotyped and assessed for long-term response to treatment between 2008 and 2013. Weighted SCZ polygenic scores were computed at differentPvalue thresholds using summary statistics from an international multicenter genome-wide association study (GWAS) of 36 989 individuals with SCZ and genotype data from patients with BPAD from the Consortium on Lithium Genetics. For functional exploration, a cross-trait meta-GWAS and pathway analysis was performed, combining GWAS summary statistics on SCZ and response to treatment with lithium. Data analysis was performed from September 2016 to February 2017. Main Outcomes and Measures Treatment response to lithium was defined on both the categorical and continuous scales using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. The effect measures include odds ratios and the proportion of variance explained. Results Of the 2586 patients in the study (mean [SD] age, 47.2 [13.9] years), 1478 were women and 1108 were men. The polygenic score for SCZ was inversely associated with lithium treatment response in the categorical outcome, at a thresholdP Conclusions and Relevance This study provides evidence for a negative association between high genetic loading for SCZ and poor response to lithium in patients with BPAD. These results suggest the potential for translational research aimed at personalized prescribing of lithium.

An efficient Harris hawks-inspired image segmentation method

Abstract: Segmentation is a crucial phase in image processing because it simplifies the representation of an image and facilitates its analysis. The multilevel thresholding method is more efficient for segmenting digital mammograms compared to the classic bi-level thresholding since it uses a higher number of intensities to represent different regions in the image. In the literature, there are different techniques for multilevel segmentation; however, most of these approaches do not obtain good segmented images. In addition, they are computationally expensive. Recently, statistical criteria such as Otsu, Kapur, and cross-entropy have been utilized in combination with evolutionary and swarm-based strategies to investigate the optimal threshold values for multilevel segmentation. In this paper, an efficient methodology for multilevel segmentation is proposed using the Harris Hawks Optimization (HHO) algorithm and the minimum cross-entropy as a fitness function. To substantiate the results and effectiveness of the HHO-based method, it has been tested over a benchmark set of reference images, with the Berkeley segmentation database, and with medical images of digital mammography. The proposed HHO-based solver is verified based on other comparable optimizers and two machine learning algorithms K-means and the Fuzzy IterAg. The comparisons were performed based on three groups. This first one is to provide evidence of the optimization capabilities of the HHO using the Wilcoxon test, and the second is to verify segmented image quality using the PSNR, SSIM, and FSIM metrics. Then, the third way is to verify the segmented image comparing it with the ground-truth through the metrics PRI, GCE, and VoI. The experimental results, which are validated by statistical analysis, show that the introduced method produces efficient and reliable results in terms of quality, consistency, and accuracy in comparison with the other methods. This HHO-based method presents an improvement over other segmentation approaches that are currently used in the literature.