A susceptibility locus rs7099208 is associated with non-obstructive azoospermia via reduction in the expression of FAM160B1

Non-obstructive azoospermia （NOA） is a severe defect in male reproductive health that occurs in 1% of adult men. In a previous study, we identified that rs7099208 is located within the last intron of FAM160B1 at 10q25.3. In this study, we analysed expression Quantitative Trait Loci （eQTL） of FAM16OB1, ABLIM1 and TRUB1, the three genes surrounding rs7099208. Only the expression level of FAM16OB1 was reduced for the homozygous alternate genotype （GG） of rs7099208, but not for the homozygous reference or heterozygous geno- types. FAM160B1 is predominantly expressed in human testes, where it is found in spermatocytes and round sper- matids. From 17 patients with NOA and five with obstructive azoospermia （OA）, immunohistochemistry revealed that expression of FAM160B1 is reduced, or undetectable in NOA patients, but not in OA cases or normal men. We conclude that rs7099208 is associated with NOA via a reduction in the expression of FAM160B1.

Textual Content Prediction via Fuzzy Attention Neural Network Model without Predefined Knowledge

Text analysis is a popular technique for finding the most significant information from texts including semantic,emotional,and other hidden features,which became a research hotspot in the last few years.Specially,there are some text analysis tasks with judgment reports,such as analyzing the criminal process and predicting prison terms.Traditional researches on text analysis are generally based on special feature selection and ontology model generation or require legal experts to provide external knowledge.All these methods require a lot of time and labor costs.Therefore,in this paper,we use textual data such as judgment reports creatively to perform prison term prediction without external legal knowledge.We propose a framework that combines value-based rules and a fuzzy text to predict the target prison term.The procedure in our framework includes information extraction,term fuzzification,and document vector regression.We carry out experiments with real-world judgment reports and compare our model’s performance with those of ten traditional classification and regression models and two deep learning models.The results show that our model achieves competitive results compared with other models as evaluated by the RMSE and R-squared metrics.Finally,we implement a prototype system with a user-friendly GUI that can be used to predict prison terms according to the legal text inputted by the user.

An Arthrobacter strain isolated from desert soils in the region of Shule River (China) can convert cellulose to potential biofuels

In this study, an Arthrobacter strain from desert soils in the Shule River Valley was isolated, China, which has a strong ability to convert cellulose to potential biofuel. In total, from five soil sample sites, six strains were isolated that grew well on CMC-Agar medium, with colony diameters ranging from 3~4 mm, among them, one strain had a strong ability to produce biofuels. Based on morphological and phylogenetic analyses, the isolate was identified as Arthrobacter nitroguajacolicus strain SLP1. The chemical properties of the biofuel extracted from the fermentation broth of strain SLP1 were analysed by gas chromatography and mass spectrometry. A total of 41 kinds of carbon compounds were identified, of those,five were detected at peak concentration and the carbon numbers ranged from C16–C22, which can be classified as alkanes,alkenes, and alcohols. Furthermore, biofuel-producing ability of strain SLP1 was enhanced using NTG mutagen. In a total of 94 mutant strains, four show the most enhanced biofuel production relative to the original strain. Biofuel production conditions were optimized by growing the four mutant strains on LB-Agar and SS-Agar medium.

Linkages between soil microbial stability and carbon storage in the active layer under permafrost degradation

The Qinghai-Tibet Plateau(QTP)distributes the largest extent of high-altitude mountain permafrost in the world(Zou et al.,2017),which has different characteristics from high-latitude permafrost(Yang et al.,2010)and stores massive soil carbon.

On-Surface Synthesis of Electron-Deficient Bisanthene Tetraimide

Imide-based conjugated molecules have emerged as a highly promising class of building blocks for constructing n-type semiconducting materials with lowlying lowest unoccupied molecular orbitals and exceptional stability.Although imides,such as naphthalene diimides,perylene diimides and their lateral fused analogs,have been synthesized extensively,the design and synthesis of largerπ-extended molecules incorporating more than two imide groups are desirable but still very challenging.Herein,we report the synthesis of an unprecedented electron-deficient bisanthene tetraimide(ATI)containing a bisantheneconjugated core and four five-membered imide groups,which was successfully achieved via a combined approach of solution and on-surface synthesis.The chemical structures,electronic states,formation mechanism and aromaticity of ATI were systematically investigated by scanning tunneling microscopy,noncontact atomic force microscopy,scanning tunneling spectroscopy,and density functional theory calculations.

Strong in-plane optical anisotropy in 2D van der Waals antiferromagnet VOCl

Two-dimensional(2D)van der Waals(vdW)magnetic materials with strong in-plane anisotropy can make possible novel applications such as optospintronics and strain sensors.In this work,the strong in-plane optical anisotropy in 2D vdW antiferromagnet VOCl has been systematically investigated.The optical brightness and absorption coefficient exhibit evident periodic variation with the change of incident polarization,unveiling the strong in-plane anisotropic optical absorption.The Raman intensity in this material shows obvious dependence on the polarization angle of incident laser,demonstrating that the phonon properties possess strong in-plane anisotropy.Besides,we have also realized in-situ visualization of in-plane optical reflection anisotropy in this material.Moreover,the strong second harmonic generation(SHG)signal can only be detected when the incident polarization is along specific in-plane crystal orientations,illustrating the presence of strong in-plane nonlinear optical anisotropy.These findings will benefit the applications of VOCl in the field of polarization-dependent electronics and spintronics.

Highly-anisotropic optical and electrical properties in layered SnSe

Anisotropic materials are of considerable interest because of their unique combination of polarization- or direction-dependent electrical, optical, and thermoelectric properties. Low-symmetry two-dimensional （2D） materials formed by van der Waals stacking of covalently bonded atomic layers are inherently anisotropic. Layered SnSe exhibits a low degree of lattice symmetry, with a distorted NaC1 structure and an in-plane anisotropy. Here we report a systematic study of the in-plane anisotropic properties in layered SnSe, using angle-resolved Raman scattering, optical absorption, and electrical transport studies. The optical and electrical characterization was direction-dependent, and successfully identified the crystalline orientation in the layered SnSe. Furthermore, the dependence of Raman-intensity anisotropy on the SnSe flake thickness and the excitation wavelength were investigated by both experiments and theoretical calculations. Finally, the electrical transport studies demonstrated that few-layer SnSe field- effect transistors （FETs） have a large anisotropic ratio of carrier mobility （N 5.8） bet- ween the armchair and zigzag directions, which is a record high value reported for 2D anisotropic materials. The highly-anisotropic properties of layered SnSe indicate considerable promise for anisotropic optics, electronics, and optoelectronics.

A Variational Binary Level Set Method for Structural Topology Optimization

This paper proposes a variational binary level set method for shape and topology optimization of structural.First,a topology optimization problem is presented based on the level set method and an algorithm based on binary level set method is proposed to solve such problem.Considering the difficulties of coordination between the various parameters and efficient implementation of the proposed method,we present a fast algorithm by reducing several parameters to only one parameter,which would substantially reduce the complexity of computation and make it easily and quickly to get the optimal solution.The algorithm we constructed does not need to re-initialize and can produce many new holes automatically.Furthermore,the fast algorithm allows us to avoid the update of Lagrange multiplier and easily deal with constraints,such as piecewise constant,volume and length of the interfaces.Finally,we show several optimum design examples to confirm the validity and efficiency of our method.