Butterfly and Nest-Shaped Tp*-W-Cu-S Cluster Monomers and Dimers with Hexamethylenetetramine as Ligand: Anion-Dependent Structures and Nonlinear Optical Properties

The assembly of[Et4N][Tp*WS3](1) with CuX (Tp* =hydridotris(3,5-dimethylpyrazol-1-yl)borate;X =Cl,Br,and I) or[Cu(MeCN)4][PF6]in the presence of tetratopic liga...     

Speckle characteristics of simulated deep Fresnel region under shadowing effect

After the three-dimensional self-affine fractal random surface simulation, we use the optical scattering theory to calculate the deep Fresnel region speckle(DFRS) under consideration of the more strict shadowing effect. The evolution of DFRS with the scattering distance and the intensity probability distribution are studied. It is found that the morphology of the scatterer has an antisymmetric relationship with the intensity distribution of DFRS, and the effect of micro-lenses on the scattering surface causes the intensity probability distribution of DFRS to deviate from the Gaussian speckle in the high light intensity area.     

Space-Air-Ground Integrated Mobile Crowdsensing for Partially Observable Data Collection by Multi-Scale Convolutional Graph Reinforcement Learning

Mobile crowdsensing (MCS) is attracting considerable attention in the past few years as a new paradigm for large-scale information sensing. Unmanned aerial vehicles (UAVs) have played a significant role in MCS tasks and served as crucial nodes in the newly-proposed space-air-ground integrated network (SAGIN). In this paper, we incorporate SAGIN into MCS task and present a Space-Air-Ground integrated Mobile CrowdSensing (SAG-MCS) problem. Based on multi-source observations from embedded sensors and satellites, an aerial UAV swarm is required to carry out energy-efficient data collection and recharging tasks. Up to date, few studies have explored such multi-task MCS problem with the cooperation of UAV swarm and satellites. To address this multi-agent problem, we propose a novel deep reinforcement learning (DRL) based method called Multi-Scale Soft Deep Recurrent Graph Network (ms-SDRGN). Our ms-SDRGN approach incorporates a multi-scale convolutional encoder to process multi-source raw observations for better feature exploitation. We also use a graph attention mechanism to model inter-UAV communications and aggregate extra neighboring information, and utilize a gated recurrent unit for long-term performance. In addition, a stochastic policy can be learned through a maximum-entropy method with an adjustable temperature parameter. Specifically, we design a heuristic reward function to encourage the agents to achieve global cooperation under partial observability. We train the model to convergence and conduct a series of case studies. Evaluation results show statistical significance and that ms-SDRGN outperforms three state-of-the-art DRL baselines in SAG-MCS. Compared with the best-performing baseline, ms-SDRGN improves 29.0% reward and 3.8% CFE score. We also investigate the scalability and robustness of ms-SDRGN towards DRL environments with diverse observation scales or demanding communication conditions.     

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher

In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption. The parallel compressed sensing method is adopted to ensure the encryption and decryption efficiency. The ZUC stream cipher is used to sample the one-dimensional chaotic map to reduce the correlation between elements and improve the randomness of the chaotic sequence. The compressed sensing measurement matrix is constructed by using the sampled chaotic sequence to improve the image restoration effect. In order to reduce the block effect after the parallel compressed sensing operation, we also propose a method of a random block of images. Simulation analysis shows that the algorithm demonstrated better encryption and compression performance.     

Simultaneous Determination of Six Immunosuppressants in Human Whole Blood by HPLC-MS/MS Using a Modified QuEChERS Method

A high-performance liquid chromatography-tandem mass spectrometry method was established for the simultaneous determination of mycophenolic acid, mycophenolate mofetil, tacrolimus, rapamycin, everolimus and pimecrolimus in human whole blood by optimizing the QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) preparation method. Whole blood was extracted into ethyl acetate, salted out with anhydrous magnesium sulfate, and purified with ethylenediamine-N-propyl silane adsorbent. The supernatant was evaporated under nitrogen until dry and finally reconstituted in methanol. Chromatographic separation was performed on an Agilent Poroshell 120 EC-C18 column in methanol (mobile phase A)-water (optimized for 0.1% acetic acid and 10 mM ammonium acetate, mobile phase B) at a 0.3 mL·min⁻¹ flow rate. Electrospray ionization and positive ion multiple reaction monitoring were used for detection. The time for of analysis was 13 min. The calibration curves range of tacrolimus, rapamycin, everolimus and pimecrolimus were in the range of 1–100 ng·mL⁻¹, mycophenolate mofetil in the range of 0.1–10 ng·mL⁻¹ and mycophenolic acid at 10–1000 ng·mL⁻¹. All correlation coefficients were >0.993. The coefficients of variation (CV, %) for inter-day and intra-day precision were less than 10%, while the spiked recoveries were in the range of 92.1% to 116%. Our method was rapid, sensitive, specific, and reproducible for the simultaneous determination of six immunosuppressants in human whole blood. Importantly, our approach can be used to monitor drug concentrations in the blood to facilitate disease treatment.     

Cardiac-specific overexpression of Ndufs1 ameliorates cardiac dysfunction after myocardial infarction by alleviating mitochondrial dysfunction and apoptosis

Myocardial infarction (MI) is the leading cause of premature death among adults. Cardiomyocyte death and dysfunction of the remaining viable cardiomyocytes are the main pathological factors of heart failure after MI. Mitochondrial complexes are emerging as critical mediators for the regulation of cardiomyocyte function. However, the precise roles of mitochondrial complex subunits in heart failure after MI remain unclear. Here, we show that NADH:ubiquinone oxidoreductase core subunit S1 (Ndufs1) expression is decreased in the hearts of heart failure patients and mice with myocardial infarction. Furthermore, we found that cardiac-specific Ndufs1 overexpression alleviates cardiac dysfunction and myocardial fibrosis in the healing phase of MI. Our results demonstrated that Ndufs1 overexpression alleviates MI/hypoxia-induced ROS production and ROS-related apoptosis. Moreover, upregulation of Ndufs1 expression improved the reduced activity of complex I and impaired mitochondrial respiratory function caused by MI/hypoxia. Given that mitochondrial function and cardiomyocyte apoptosis are closely related to heart failure after MI, the results of this study suggest that targeting Ndufs1 may be a potential therapeutic strategy to improve cardiac function in patients with heart failure.Subject terms: Heart failure, Myocardial infarction, Myocardial infarction     

生物芯片扫描仪研究进展

简要介绍生物芯片的基本概念以及生物芯片检测装置的国内外发展动态;分别介绍了本文设计的CCD系统生物芯片检测仪和激光共聚焦生物芯片扫描仪的原理、结构、工作状况以及设备的技术参数。最后指出更高分辨率(小于1μm)的生物芯片扫描仪是该设备今后的发展趋势。     

BER Performance of Frequency Domain Differential Demodulation OFDM in Flat Fading Channel

A closed form expression for the bit error rate (BER) performance of frequency domaindifferential demodulation(FDDD) for orthogonal frequency division multiplexing system in flat fadingchannel is derived.The performance is evaluated by computer simulation and compared with the timedomain differential demodulation(TDDD).The results indicate that the performance of FDDD is betterthan that of TDDD,and the lower band of BER in the former is lower than that of the latter.     

Terahertz Direct Modulation Techniques for High-speed Communication Systems

Terahertz communication technology can provide abundant frequency resources,strong confidentiality,antijamming capability,communication tracking capability and ...