(1R*,5S*)-8-(2-Fluoro-4-nitro­phen­yl)-8-aza­bicyclo­[3.2.1]octan-3-one

In the title compound, C13H13FN2O3, the fused piperidine ring is in a chair conformation. The fused pyrrolidine ring shows an envelope conformation with the N atom displaced by 0.661 (3) Å out of the plane formed by the four C atoms of the pyrrolidine ring. The dihedral angle between this plane and the plane formed by the four attached C atoms of the piperidine ring (not including the carbonyl C atom) is 67.63 (10)°. The F atom is disordered and was refined using a split model with an occupancy ratio of 0.910 (3): 0.080 (3)

No-Reference Quality Assessment for Colored Point Cloud and Mesh Based on Natural Scene Statistics

To improve the viewer's quality of experience and optimize processing systems in computer graphics applications, the 3D quality assessment (3D-QA) has become an important task in the multimedia area. Point cloud and mesh are the two most widely used electronic representation formats of 3D models, the quality of which is quite sensitive to operations like simplification and compression. Therefore, many studies concerning point cloud quality assessment (PCQA) and mesh quality assessment (MQA) have been carried out to measure the visual quality degradations caused by lossy operations. However, a large part of previous studies utilizes full-reference (FR) metrics, which means they may fail to predict the accurate quality level of 3D models when the reference 3D model is not available. Furthermore, limited numbers of 3D-QA metrics are carried out to take color features into consideration, which significantly restricts the effectiveness and scope of application. In many quality assessment studies, natural scene statistics (NSS) have shown a good ability to quantify the distortion of natural scenes to statistical parameters. Therefore, we propose an NSS-based no-reference quality assessment metric for colored 3D models. In this paper, quality-aware features are extracted from the aspects of color and geometry directly from the 3D models. Then the statistic parameters are estimated using different distribution models to describe the characteristic of the 3D models. Our method is mainly validated on the colored point cloud quality assessment database (SJTU-PCQA) and the colored mesh quality assessment database (CMDM). The experimental results show that the proposed method outperforms all the state-of-art NR 3D-QA metrics and obtains an acceptable gap with the state-of-art FR 3D-QA metrics

Phase-Modulated Elastic Properties of Two-Dimensional Magnetic FeTe: Hexagonal and Tetragonal Polymorphs

Two-dimensional (2D) layered magnets, such as iron chalcogenides, have emerged these years as a new family of unconventional superconductor and provided the key insights to understand the phonon-electron interaction and pairing mechanism. Their mechanical properties are of strategic importance for the potential applications in spintronics and optoelectronics. However, there is still lack of efficient approach to tune the elastic modulus despite the extensive studies. Herein, we report the modulated elastic modulus of 2D magnetic FeTe and its thickness-dependence via phase engineering. The grown 2D FeTe by chemical vapor deposition can present various polymorphs, i.e. tetragonal FeTe (t-FeTe, antiferromagnetic) and hexagonal FeTe (h-FeTe, ferromagnetic). The measured Young's modulus of t-FeTe by nanoindentation method showed an obvious thickness-dependence, from 290.9+-9.2 to 113.0+-8.7 GPa when the thicknesses increased from 13.2 to 42.5 nm, respectively. In comparison, the elastic modulus of h-FeTe remains unchanged. Our results could shed light on the efficient modulation of mechanical properties of 2D magnetic materials and pave the avenues for their practical applications in nanodevices.Comment: 19 pages, 4 figure

Subjective and Objective Quality Assessment for in-the-Wild Computer Graphics Images

Computer graphics images (CGIs) are artificially generated by means of computer programs and are widely perceived under various scenarios, such as games, streaming media, etc. In practical, the quality of CGIs consistently suffers from poor rendering during the production and inevitable compression artifacts during the transmission of multimedia applications. However, few works have been dedicated to dealing with the challenge of computer graphics images quality assessment (CGIQA). Most image quality assessment (IQA) metrics are developed for natural scene images (NSIs) and validated on the databases consisting of NSIs with synthetic distortions, which are not suitable for in-the-wild CGIs. To bridge the gap between evaluating the quality of NSIs and CGIs, we construct a large-scale in-the-wild CGIQA database consisting of 6,000 CGIs (CGIQA-6k) and carry out the subjective experiment in a well-controlled laboratory environment to obtain the accurate perceptual ratings of the CGIs. Then, we propose an effective deep learning-based no-reference (NR) IQA model by utilizing multi-stage feature fusion strategy and multi-stage channel attention mechanism. The major motivation of the proposed model is to make full use of inter-channel information from low-level to high-level since CGIs have apparent patterns as well as rich interactive semantic content. Experimental results show that the proposed method outperforms all other state-of-the-art NR IQA methods on the constructed CGIQA-6k database and other CGIQA-related databases. The database along with the code will be released to facilitate further research

Kagome surface states and weak electronic correlation in vanadium-kagome metals

RV6Sn6 (R = Y and lanthanides) with two-dimensional vanadium-kagome surface states is an ideal platform to investigate kagome physics and manipulate the kagome features to realize novel phenomena. Utilizing the micron-scale spatially resolved angle-resolved photoemission spectroscopy and first-principles calculations, we report a systematical study of the electronic structures of RV6Sn6 (R = Gd, Tb, and Lu) on the two cleaved surfaces, i.e., the V- and RSn1-terminated (001) surfaces. The calculated bands without any renormalization match well with the main ARPES dispersive features, indicating the weak electronic correlation in this system. We observe 'W'-like kagome surface states around the Brillouin zone corners showing R-element-dependent intensities, which is probably due to various coupling strengths between V and RSn1 layers. Our finding suggests an avenue for tuning electronic states by interlayer coupling based on two-dimensional kagome lattices

Effects of Low-Level Autonomic Stimulation on Prevention of Atrial Fibrillation Induced by Acute Electrical Remodeling

Background. Rapid atrial pacing (RAP) can induce electrical and autonomic remodeling and facilitate atrial fibrillation (AF). Recent reports showed that low-level vagosympathetic nerve stimulation (LLVNS) can suppress AF, as an antiarrhythmic effect. We hypothesized that LLVNS can reverse substrate heterogeneity induced by RAP. Methods and Results. Mongrel dogs were divided into (LLVNS+RAP) and RAP groups. Electrode catheters were sutured to multiple atrial sites, and LLVNS was applied to cervical vagosympathetic trunks with voltage 50% below the threshold slowing sinus rate by ⩽30 msec. RAP induced a significant decrease in effective refractory period (ERP) and increase in the window of vulnerability at all sites, characterized by descending and elevated gradient differences towards the ganglionic plexi (GP) sites, respectively. The ERP dispersion was obviously enlarged by RAP and more significant when the ERP of GP-related sites was considered. Recovery time from AF was also prolonged significantly as a result of RAP. LLVNS could reverse all these changes induced by RAP and recover the heterogeneous substrate to baseline. Conclusions. LLVNS can reverse the electrical and autonomic remodeling and abolish the GP-central gradient differences induced by RAP, and thus it can recover the homogeneous substrate, which may be the underlying mechanism of its antiarrhythmic effect

Updated Prediction of Air Quality Based on Kalman-Attention-LSTM Network

The WRF-CMAQ (Weather research and forecast-community multiscale air quality) simulation system is commonly used as the first prediction model of air pollutant concentration, but its prediction accuracy is not ideal. Considering the complexity of air quality prediction and the high-performance advantages of deep learning methods, this paper proposes a second prediction method of air pollutant concentration based on the Kalman-attention-LSTM (Kalman filter, attention and long short-term memory) model. Firstly, an exploratory analysis is made between the actual environmental measurement data from the monitoring site and the first forecast data from the WRF-CMAQ model. An air quality index (AQI) was used as a measure of air pollution degree. Then, the Kalman filter (KF) is used to fuse the actual environmental measurement data from the monitoring site and the first forecast results from the WRF-CMAQ model. Finally, the long short-term memory (LSTM) model with the attention mechanism is used as a single factor prediction model for an AQI prediction. In the prediction of O3 which is the main pollutant affecting the AQI, the results show that the second prediction based on the Kalman-attention-LSTM model features a better fitting effect, compared with the six models. In the first prediction (from the WRF-CMAQ model), for the RNN, GRU, LSTM, attention-LSTM and Kalman-LSTM, SE improved by 83.26%, 51.64%, 43.58%, 45%, 26% and 29%, respectively, RMSE improved by 83.16%, 51.52%, 43.21%, 44.59%, 26.07% and 28.32%, respectively, MAE improved by 80.49%, 56.96%, 46.75%, 49.97%, 26.04% and 27.36%, respectively, and R-Square improved by 85.3%, 16.4%, 10.3%, 11.5%, 2.7% and 3.3%, respectively. However, the prediction results for the Kalman-attention-LSTM model proposed in this paper for other five different pollutants (SO2, NO2, PM10, PM2.5 and CO) all have smaller SE, RMSE and MAE, and better R-square. The accuracy improvement is significant and has good application prospects

Fractional order sliding mode control based on single parameter adaptive law for nano‐positioning of piezoelectric actuators

Abstract A fractional order sliding mode control (FOSMC) based on single parameter adaptive law for nano‐positioning of Piezoelectric Actuators (PEAs) is proposed. First, the Bouc–Wen (B–W) model is used to describe the hysteresis of the nano‐position platform based on PEAs, which provides a mathematical model for the subsequent controller design. Then, theoretical support is provided to design the FOSMC based on adaptive law of different parameters, which are proposed for the displacement tracking problem of PEAs, and the position error convergence is also proved. Moreover, the core parameters of FOSMC based on single parameter adaptive law are identified by hybrid differential evolution (HDE) and adaptive differential evolution (ADE), which require considering the relationship between the scaling factor and the cross‐probability factor. Finally, experiments have been conducted with the displacement signals mixed with multiple frequencies and multiple amplitudes and the results obtained from them show that the proposed control scheme can produce a faster response and smaller tracking errors in PEAs system as compared to traditional control algorithms

Research on safety and efficiency warranted vessel scheduling in unidirectional multi-junction waterways of port waters

Traffic management in port waters is a complicated task considering vessels with various characteristics and the specific layout of waterways. Optimal management is needed to reduce vessel waiting time and guarantee adequate safety, which in turn could enhance port competitiveness, and is conducive to port development. In this paper, a key collision avoidance point precomputation model is proposed to assess the safety level of each vessel scheduling plan and the consequent efficiency in unidirectional multi-junction waterways of port waters. An integrated vessel scheduling approach (IVSA) is proposed and developed to obtain the safety-enabled optimal vessel scheduling with the purpose to minimize the total delay under the premise of adequate safety. A series of experiments has been conducted by employing data of an empirical port in northern China. It is found that, in addition to improving traffic environment and reducing unnecessary behavior of vessels, IVSA could substantially reduce the total delay, from 6.04% to 27.75%. Result of this research can provide a guidance for port seaside management under complex situations and provide the decision-making support for the assessment of vessel traffic on future port waterway expansion