Topology hierarchy of transition metal dichalcogenides built from quantum spin Hall layers

The evolution of the physical properties of two-dimensional material from monolayer limit to the bulk reveals unique consequences from dimension confinement and provides a distinct tuning knob for applications. Monolayer 1T'-phase transition metal dichalcogenides (1T'-TMDs) with ubiquitous quantum spin Hall (QSH) states are ideal two-dimensional building blocks of various three-dimensional topological phases. However, the stacking geometry was previously limited to the bulk 1T'-WTe2 type. Here, we introduce the novel 2M-TMDs consisting of translationally stacked 1T'-monolayers as promising material platforms with tunable inverted bandgaps and interlayer coupling. By performing advanced polarization-dependent angle-resolved photoemission spectroscopy as well as first-principles calculations on the electronic structure of 2M-TMDs, we revealed a topology hierarchy: 2M-WSe2, MoS2, and MoSe2 are weak topological insulators (WTIs), whereas 2M-WS2 is a strong topological insulator (STI). Further demonstration of topological phase transitions by tunning interlayer distance indicates that band inversion amplitude and interlayer coupling jointly determine different topological states in 2M-TMDs. We propose that 2M-TMDs are parent compounds of various exotic phases including topological superconductors and promise great application potentials in quantum electronics due to their flexibility in patterning with two-dimensional materials

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Using millimeter-wave radar to evaluate the performance of dummy models for advanced driving assistance systems test

Abstract With the rapid development of intelligent and connected vehicles, the experimental road test for the advanced driving assistance system (ADAS) is dramatically increasing around the world. Considering its high cost and hazardous situations, simulation test based on a dummy model is becoming a promising way for ADAS road test practice to reduce the experiment expanses. This study proposed a methodology for the evaluation of the performance of human and dummies with distinct designed materials based on the data extracted from the Doppler effect of millimeter-wave radar. Echo data of 8 different angles from 0 to 360 degrees, with the an interval of 45 degrees, at the same distance between the test object and the signal source is collected. Meanwhile, the echo energy is collected for correlation modeling and analysis among groups. By evaluating the performance of humans and dummies via statistical analysis, a close correlation was found which results verified the substitutability of the dummy for the ADAS experiment test. The correlation coefficient between human and dummies ranges from 0.75 to 0.93. The support vector machine (SVM) model was developed and fitted to predict the echo energy in diverse environments. The mean average error (MAE) is 5.42–11.42 in the training and testing datasets while root mean square error (RMSE) is 0.43–0.90. The methods developed in the study can simulate the real ADAS road test environment and support future experimental research

Design and Test of a Straw-Clearing-Depth Self-Adaptive Control System of a Front-Mounted Seedbed-Preparation Device

In northeast China, most seedbed-preparation devices use the ground-wheel profiling method to ensure their operational stability. However, during the wide-width operation of the front-mounted seedbed-preparation device, the poor trafficability characteristics and the low profiling accuracy of the ground-wheel profiling mechanism result in unstable straw clearing depth, poor straw clearing quality, and the low operational efficiency of the seedbed-preparation device. In order to solve the above problems, a straw-clearing-depth self-adaptive control system of a front-mounted seedbed-preparation device was designed. The key structural design of the self-adaptive control system was completed through theoretical analysis. The performance test results of the self-adaptive control system showed that the lifting speed of the front-suspension mechanism was greater than 0.2 m/s in the manual button control mode, and the relative error between the target value and the actual value of the straw clearing depth was 10.8% under the self-adaptive profiling control mode. The three-factor and five-level quadratic regression orthogonal rotation center combination test method was adopted to conduct a parameter combination optimization test, with the machine operation speed, the operation depth of the straw clearing knife, and the straw covering amount as test factors, and the straw clearing rate, the qualified rate of operation depth, and the consistency of straw clearing between rows as evaluation indices. The results indicated that when the machine operation speed was 5~8.8 km/h, the operation depth of the straw clearing knife was 50 mm, the straw covering amount was 0.9~1.44 kg/m2, the straw clearing rate was ≥86%, the qualified rate of operation depth was ≥86%, and the consistency of straw clearing between rows was ≥83%. Field tests were carried out on the machine using operation speeds of 5 km/h, 6 km/h, 7 km/h, and 8 km/h under the conditions of an operation depth of the straw clearing knife of 50 mm and a straw covering amount of 1.2 kg/m2. The results showed that the straw clearing rate, the qualified rate of operation depth, and the consistency of straw clearing between rows were all within the optimized range under different machine operation speeds, which was basically consistent with the optimized results

Parameter Combination Optimization of the Lateral Straw Clearing and Throwing Knife Based on Discrete Element Simulation

In order to explore the laws of corn straw lateral moving and throwing, it is necessary to identify the main factors that restrict improvements in the quality of straw clearing and reductions in power consumption and then optimize the knife parameter combinations; in this paper, the kinematic analysis of single-stage lateral moving and throwing of corn straw was carried out, and the mathematical model for the collision process between the knife and straw is established. Key factors affecting the lateral moving and throwing efficiency of straw were determined according to the model analysis. A parameter combination optimization test was conducted with three-factor and five-level quadratic regression orthogonal rotation center combination test methods and discrete element virtual simulation, taking into account the edge angle of cutting, the rotation radius of the knife, and the rotation speed of the knife roller as test factors and the straw clearing rate and power consumption as performance evaluation indexes. The test results showed that at a travel speed of 7.2 km/h when the edge angle of cutting was 65°, the rotation radius of the knife was 420 mm, and the rotation speed of the knife roller was 538~600 rpm, the straw clearing rate was ≥85%, and power consumption was ≤1.5 kW. The field test was carried out to verify the optimized results, and the test results showed that the test values of the performance evaluation indexes were all in the ranges of the optimized interval. These research results lay down the foundation for the design of lateral straw clearing and throwing knives

Theoretical Study on DBU-Catalyzed Insertion of Isatins into Aryl Difluoronitromethyl Ketones: A Case for Predicting Chemoselectivity Using Electrophilic Parr Function

The possible mechanisms of 1,8-diazabicyclo[5.4.0]­undec-7-ene (DBU)-catalyzed chemoselective insertion of <i>N</i>-methyl isatin into aryl difluoronitromethyl ketone to synthesize 3,3-disubstituted and 2,2-disubstituted oxindoles have been studied in this work. As revealed by calculated results, the reaction occurs via two competing paths, including α and β carbonyl paths, and each path contains five steps, that is, nucleophilic addition of DBU to ketone, C–C bond cleavage affording difluoromethylnitrate anion and phenylcarbonyl–DBU cation, nucleophilic addition of difluoromethylnitrate anion to carbonyl carbon of <i>N</i>-methyl isatin, acyl transfer process, and dissociation of DBU and product. The computational results suggest that nucleophilic additions on different carbonyl carbons of <i>N</i>-methyl isatin via α and β carbonyl paths would lead to different products in the third step, and β carbonyl path associated with the main product 3,3-disubstituted oxindole is more energetically favorable, which is consistent with the experimental observations. Noteworthy, electrophilic Parr function can be successfully applied for exactly predicting the activity of reaction site and reasonably explaining the chemoselectivity. In addition, the distortion/interaction and noncovalent interaction analyses show that much more hydrogen bond interactions should be responsible for the lower energy of the transition state associated with β carbonyl path. The obtained insights would be valuable for the rational design of efficient organocatalysts for this kind of reactions with high selectivities

ANTspin: Efficient Absolute Localization Method of RFID Tags via Spinning Antenna

The Global Positioning System (GPS) has been widely applied in outdoor positioning, but it cannot meet the accuracy requirements of indoor positioning. Comprising an important part of the Internet of Things perception layer, Radio Frequency Identification (RFID) plays an important role in indoor positioning. We propose a novel localization scheme aiming at the defects of existing RFID localization technology in localization accuracy and deployment cost, called ANTspin: Efficient Absolute Localization Method of RFID Tags via Spinning Antenna, which introduces a rotary table in the experiment. The reader antenna is fixed on the rotary table to continuously collect dynamic data. When compared with static acquisition, there is more information for localization. After that, the relative incident angle and distance between tags and the antenna can be analyzed for localization with characteristics of Received Signal Strength Indication (RSSI) data. We implement ANTspin using COTS RFID devices and the experimental results show that it achieves a mean accuracy of 9.34 cm in 2D and mean accuracy of 13.01 cm in three-dimensions (3D) with high efficiency and low deployment cost