Z-Selectivity in Olefin Metathesis with Chelated Ru Catalysts: Computational Studies of Mechanism and Selectivity

The mechanism and origins of Z-selectivity in olefin metathesis with chelated Ru catalysts were explored using density functional theory. The olefin approaches from the “side” position of the chelated Ru catalysts, in contrast to reactions with previous unchelated Ru catalysts that favor the bottom-bound pathway. Steric repulsions between the substituents on the olefin and the N-substituent on the N-heterocyclic carbene ligand lead to highly selective formation of the Z product

Finite-temperature violation of the anomalous transverse Wiedemann-Franz law

The Wiedemann-Franz (WF) law links the ratio of electronic charge and heat conductivity to fundamental constants. It has been tested in numerous solids, but the extent of its relevance to the anomalous transverse transport, which represents the topological nature of the wave function, remains an open question. Here we present a study of anomalous transverse response in the noncollinear antiferromagnet Mn$_{3}$Ge extended from room temperature down to sub-Kelvin temperature and find that the anomalous Lorenz ratio remains close to the Sommerfeld value up to 100 K, but not above. The finite-temperature violation of the WF correlation is caused by a mismatch between the thermal and electrical summations of the Berry curvature, rather than the inelastic scattering as observed in ordinary metals. This interpretation is backed by our theoretical calculations, which reveals a competition between the temperature and the Berry curvature distribution. The accuracy of the experiment is supported by the verification of the Bridgman relation between the anomalous Ettingshausen and Nernst effects. Our results identify the anomalous Lorenz ratio as an extremely sensitive probe of Berry spectrum near the chemical potential.Comment: 9 pages,6 figures, Supplemental Material include

Semi-supervised Complex-valued GAN for Polarimetric SAR Image Classification

Polarimetric synthetic aperture radar (PolSAR) images are widely used in disaster detection and military reconnaissance and so on. However, their interpretation faces some challenges, e.g., deficiency of labeled data, inadequate utilization of data information and so on. In this paper, a complex-valued generative adversarial network (GAN) is proposed for the first time to address these issues. The complex number form of model complies with the physical mechanism of PolSAR data and in favor of utilizing and retaining amplitude and phase information of PolSAR data. GAN architecture and semi-supervised learning are combined to handle deficiency of labeled data. GAN expands training data and semi-supervised learning is used to train network with generated, labeled and unlabeled data. Experimental results on two benchmark data sets show that our model outperforms existing state-of-the-art models, especially for conditions with fewer labeled data

A temporal Convolutional Network for EMG compressed sensing reconstruction

Electromyography (EMG) plays a vital role in detecting medical abnormalities and analyzing the biomechanics of human or animal movements. However, long-term EMG signal monitoring will increase the bandwidth requirements and transmission system burden. Compressed sensing (CS) is attractive for resource-limited EMG signal monitoring. However, traditional CS reconstruction algorithms require prior knowledge of the signal, and the reconstruction process is inefficient. To solve this problem, this paper proposed a reconstruction algorithm based on deep learning, which combines the Temporal Convolutional Network (TCN) and the fully connected layer to learn the mapping relationship between the compressed measurement value and the original signal, and it has been verified in the Ninapro database. The results show that, for the same subject, compared with the traditional reconstruction algorithms orthogonal matching pursuit (OMP), basis pursuit (BP), and Modified Compressive Sampling Matching Pursuit (MCo), the reconstruction quality and efficiency of the proposed method is significantly improved under various compression ratios (CR)

Association between iscR-based phylogeny, serovars and potential virulence markers of Haemophilus parasuis

Haemophilus parasuis is an economically important bacterial pathogen of swine. Extensive genetic and phenotypic heterogeneity among H. parasuis strains have been observed, which hinders the deciphering of the population structure and its association with clinical virulence. In this study, two highly divergent clades were defined according to iron–sulphur cluster regulator (iscR)-based phylogeny analysis of 148 isolates. Clear separation of serovars and potential virulence markers (PVMs) were observed between the two clades, which are indicative of independent evolution of the two lineages. Previously suggested virulence factors showed no correlation with clinical virulence, and were probably clade or serovar specific genes emerged during different stage of evolution. PVMs profiles varied widely among isolates in the same serovar. Higher strain diversity in respect of PVMs was found for isolates from multi-strain infected farms than those from single strain infected ones, which indicates that multi-strain infection in one farm may increase the frequency of gene transfer in H. parasuis. Systemic isolates were more frequently found in serovar 13 and serovar 12, while no correlation between clinical virulence and iscR-based phylogeny was observed. It shows that iscR is a reliable marker for studying population structure of H. parasuis, while other factors should be included to avoid the interference of gene exchange of iscR between isolates. The two lineages of H. parasuis may have undergone independent evolution, but show no difference in clinical virulence. Wide distribution of systemic isolates across the entire population poses new challenge for development of vaccine with better cross-protection. Our study provides new information for better deciphering the population structure of H. parasuis, which helps understanding the extreme diversity within this pathogenic bacterium

The clinical value of progestin-primed ovarian stimulation protocol for women with diminished ovarian reserve undergoing IVF/ICSI: a systematic review and meta-analysis

BackgroundTo determine whether progestin-primed ovarian stimulation (PPOS) is more effective for women with diminished ovarian reserve (DOR) than clomiphene citrate (CC)/letrozole (LE) plus gonadotropin in IVF or ICSI treatment.MethodsNine databases were searched until May 24, 2023, to identify relevant studies. Forest plots were used to present the results of this meta-analysis. Begg’s and Egger’s tests were applied to estimate publication bias. Subgroup and sensitivity analysis were performed to check the potential sources of heterogeneity and verify the robustness of the pooled results, respectively.ResultsA total of 14 studies with 4182 participants were included for meta-analysis. There was evidence of a statistically notable increase in clinical pregnancy rate (OR = 1.39, 95%CI [1.01, 1.91], p = 0.05), optimal embryos rate (OR = 1.50, 95%CI [1.20, 1.88], p = 0.0004), and cumulative pregnancy rate (OR = 1.73, 95%CI [1.14, 2.60], p = 0.009), the duration and the amount of gonadotropin required (MD = 1.56, 95%CI [0.47, 2.66], p = 0.005; SMD = 1.51, 95%CI [0.90, 2.12], p < 0.00001), along with decrease cycle cancellation rate (OR = 0.78, 95%CI [0.64, 0.95], p = 0.02), luteinizing hormone (LH) level on the day of hCG (SMD = -0.81, 95%CI [-1.10, -0.53], p < 0.00001), and premature LH surge rate (OR = 0.10, 95%CI [0.07, 0.15], p < 0.00001) when PPOS was used. No evidence for publication bias within results was revealed.ConclusionsBased on evidence-based results, PPOS protocol seems to improve IVF/ICSI outcomes for women with DOR. More research with larger sample sizes and rigorous designs are required to further explore the value of PPOS among women diagnosed with DOR.Systematic review registrationwww.crd.york.ac.uk, identifier CRD42023430202