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Satellite-ground integrated digital twin networks (SGIDTNs) are regarded as innovative network architectures for reducing network congestion, enabling nearly-instant data mapping from the physical world to digital systems, and offering ubiquitous intelligence services to terrestrial users. However, the challenges, such as the pricing policy, the stochastic task arrivals, the time-varying satellite locations, mutual channel interference, and resource scheduling mechanisms between the users and cloud servers, are critical for improving quality of service in SGIDTNs. Hence, we establish a blockchain-aided Stackelberg game model for maximizing the pricing profits and network throughput in terms of minimizing overhead of privacy protection, thus performing computation offloading, decreasing channel interference, and improving privacy protection. Next, we propose a Lyapunov stability theory-based model-agnostic metalearning aided multi-agent deep federated reinforcement learning (MAML-MADFRL) framework for optimizing the CPU cycle frequency, channel selection, task-offloading decision, block size, and cloud server price, which facilitate the integration of communication, computation, and block resources. Subsequently, the extensive performance analyses show that the proposed MAMLMADFRL algorithm can strengthen the privacy protection via the transaction verification mechanism, approach the optimal time average penalty, and fulfill the long-term average queue size via lower computational complexity. Finally, our simulation results indicate that the proposed MAML-MADFRL learning framework is superior to the existing baseline methods in terms of network throughput, channel interference, cloud server profits, and privacy overhead.

Frost damage is one of the main factors leading to wheat yield reduction. Therefore, the detection of wheat frost accurately and efficiently is beneficial for growers to take corresponding measures in time to reduce economic loss. To detect the wheat frost, in this paper we create a hyperspectral wheat frost data set by collecting the data characterized by temperature, wheat yield, and hyperspectral information provided by the handheld hyperspectral spectrometer. However, due to the imbalance of data, that is, the number of healthy samples is much higher than the number of frost damage samples, a deep learning algorithm tends to predict biasedly towards the healthy samples resulting in model overfitting of the healthy samples. Therefore, we propose a method based on deep cost-sensitive learning, which uses a one-dimensional convolutional neural network as the basic framework and incorporates cost-sensitive learning with fixed factors and adjustment factors into the loss function to train the network. Meanwhile, the accuracy and score are used as evaluation metrics. Experimental results show that the detection accuracy and the score reached 0.943 and 0.623 respectively, this demonstration shows that this method not only ensures the overall accuracy but also effectively improves the detection rate of frost samples., 7 pages, 4 figures, accepted by ICBAIE 2022

A more detailed analysis and deduction of adjacent sampling

Additional file 1: Table S1. Characteristics of patients. Table S2. Clinical information of lung cancer patients. Figure S1. Length and width distribution of microfibers and microplastics. a the length distribution of microfibers; b the width distribution of microfibers; c the length distribution of microplastics; d the width distribution of microplastics. MF microfiber, MP microplastic. T tumor tissue, N normal tissue. Figure S2. Microfiber characteristics in matched tumor/normal samples. a width and length distribution; b color and composition type distribution. T tumor tissue, N normal tissue. Note: Only patients samples possessing microfibers in both tumor and adjacent normal tissue are included in this figure. Figure S3. Representative pictures of airborne cotton and rayon. a cotton with smooth surface; b cotton with rough surface; c rayon with smooth surface; d rayon with rough surface. Figure S4. Representative pictures of laboratory prepared cotton and rayon microfibers before and after experimental processes (digestion, observation, and identification). a cotton before processes; b cotton after processes; c rayon before processes; d rayon after processes. Figure S5. Microfiber surficial elemental composition illustrated by SEM/EDS. a cotton from a tumor tissue; b cotton from a normal tissue; c EDS figure for (a); d EDS figure for (b); e polyester from a tumor tissue; f polyester from a normal tissue; g EDS figure for (e); h EDS figure for (f).

SO3 in the copper smelting flue gas not only causes serious corrosion in heat exchange and dust collection equipment but also increases the amount of sewage acid (waste acid or polluted acid from copper smelting). In this study, we attempted to reduce the damage by ejecting pyrite into the flue to suppress SO3 formation in the flue. First, the Gibbs free energy for the chemical reactions between the substances was obtained after ejecting pyrite. Subsequently, the thermodynamic study of SO2-O2-H2O-N2-CO2-CO system was performed. Then, a kinetic study on the decomposition and oxidation behaviour of pyrite in the flue system was performed through thermogravimetric experiments. Results show that pyrite decomposition and oxidation in the flue system have a very strong oxygen consumption capacity. The SO3 formation in the copper smelting flue gas is suppressed by the consumption of oxygen in the flue to control the reaction direction of 2SO2 + O2 ⇋ 2SO3 and the partial pressure of SO3.

BACKGROUND The definition of pediatric AKI continues to evolve. We aimed to find a better AKI definition to predict outcomes and identify risk factors for AKI in a Chinese PICU. METHODS This study consisted of 3338 patients hospitalized in a Chinese PICU between 2016 and 2018. AKI was defined and staged using pROCK criteria, which were compared with KDIGO criteria. AKI outcomes, including mortality, daily cost and length of stay (LOS), were assessed. Risk factors for AKI were also estimated. RESULTS The incidence of AKI in the PICU was 7.7% according to pROCK criteria. The characteristics of patients with KDIGO-defined AKI who did not meet the pROCK were similar to those without AKI. pROCK outperformed KDIGO in predicting mortality with a higher c index in the Cox models (0.81 versus 0.79, P = 0.013). AKI, as well as AKI stages, were associated with higher mortality (HR: 10.5, 95%CI: 6.66-19.5), daily cost (β = 2064, P

The magnetic focusing effect of Halbach array has a wide range of applications in many areas. In this paper, based on the general theory of static magnetic field, various factors affecting the energy harvesting output voltage of Halbach array are analyzed. After that, according to the simulation carried out by Comsol, the magnetic field distribution of the four module Halbach array with different numbers of magnets was obtained, which verified that the shape of the magnetic field was a periodic sinusoidal distribution converging on one side. Then a Halbach array rotor was designed, and the output voltage of the Halbach array energy harvesting structure with different numbers of magnets under the influence of different factors was simulated, and the optimal Halbach array energy harvesting structure was obtained. At the same time, the halbach array composed of 12 magnets was verified through experiments. The experimental results are consistent with the simulation results, and higher voltage and higher power can be obtained. The designed Halbach array with simple structure and small size, can be more suitable to the lower frequency vibration or motion.

Gain-of-function mutation in isocitrate dehydrogenase 1 (IDH1) is closely related to certain human cancers and is emerging as an attractive antitumor target. However, developing safe and effective inhibitors of mutant IDH1 (mIDH1) are facing many challenges. In this study, an integrated computational approach was applied to a series of 3-pyrimidin-4-yl-oxazolidin-2-one derivatives to explore the critical factors contributing to their inhibitory activity against mIDH1. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques were used to generate 3D-QSAR models. Good predictability was obtained for our best CoMFA model (q2 = 0.584; r2 = 0.952; r2pred = 0.915) and CoMSIA model (q2 = 0.759; r2 = 0.927; r2pred = 0.793). 3D contour maps generated from CoMFA and CoMSIA illustrated that the hydrophobic and H-bond donor/acceptor fields played key roles for the inhibitory activity. Molecular docking and molecular dynamics (MD) simulation were carried out to further understand the binding modes and the interactions between the protein and these inhibitors. The docking scores and the binding free energies calculated for these inhibitors agreed well with the experimental bioactivity and demonstrated that hydrophobic interaction was the main driving force for their binds. Based on these results, seven new potent molecules with better predicted activity than the drug candidates in the literature have been designed.

Analyzing protein structure and function and identifying gene expression levels that vary in health and disease can lead to elucidation of disease mechanisms, drug target discovery and identification of underlying biomarkers. To this end, this dissertation focuses on three areas involving drug development and disease comprehension. In the first part, an RNA-Seq based gene signature for the prediction of breast cancer metastasis was identified and validated to be prognostic for risk assessment and patient stratification. After diagnosis, cancer progression and metastasis play critical roles in patient survival, thus identifying the genes that correlate with cancer progression and metastasis is essential for selecting effective treatment. Using the new gene signature, survival analysis was conducted and a metastasis risk score was developed that provides a practical tool for assessing the risks of metastasis. In the second part, structure-based virtual screening was adopted to investigate which of the already FDA approved drugs can be potentially repositioned to be used against tuberculosis. Because of their known profiles of ADMET, repositioning known drugs for novel indications can shorten the length of time of drug discovery and increase the rate of success. Using virtual screening with molecular docking, a short list of compounds targeting essential TB proteins was identified. More investigations would be needed to further study the potential of the docking hits as repositioning candidates. In the third part, the relationships between moonlighting proteins and diseases were reviewed, and characteristics that correlate with proteins performing moonlighting functions were illustrated. Moonlighting proteins are proteins that have more than one biochemical or biophysical function performed by the same peptide chain. The switching of functions can be activated by a variety of elements such as expression in different cellular localizations. By having moonlighting functions, proteins can coordinate multiple cellular processes in cellular metabolism, which is essential for health. In conclusion, my analysis of gene expression and investigations of protein structure and function explored in three specific areas, which contributes to a better comprehension of the molecular mechanisms of health and disease.

Millimeter wave (mmWave) based gesture recognition technology provides a good human computer interaction (HCI) experience. Prior works focus on the close-range gesture recognition, but fall short in range extension, i.e., they are unable to recognize gestures more than one meter away from considerable noise motions. In this paper, we design a long-range gesture recognition model which utilizes a novel data processing method and a customized artificial Convolutional Neural Network (CNN). Firstly, we break down gestures into multiple reflection points and extract their spatial-temporal features which depict gesture details. Secondly, we design a CNN to learn changing patterns of extracted features respectively and output the recognition result. We thoroughly evaluate our proposed system by implementing on a commodity mmWave radar. Besides, we also provide more extensive assessments to demonstrate that the proposed system is practical in several real-world scenarios., Comment: 15pages,16 figures

For the threaded connection, elastic model and collision model were established. According to elastic deflection of thread, the axial load distribution of thread was determined and the stiffness of threaded connection was calculated. Meanwhile, collision model for threaded connection was proposed, and the calculation methods of collision time and collision force were given. Through tensile tests of threaded connections and impact experiments of projectiles penetrating into concrete targets, thread stiffness and deceleration data were obtained respectively. At the same time, finite element model were created to study the collision process on the interface of threaded connection between projectile and fuze. In order to obtain the time-frequency characteristic of deceleration, the wavelet analysis for measured deceleration and the vibration frequency analysis for projectile and fuze were conducted. The good agreement among the calculation value, finite element analysis and experiment data proved that the thread collision between projectile and fuze really exist and have very serious influence for the measured deceleration.

Mutant isocitrate dehydrogenase 2 (mIDH2) is an emerging target for the treatment of cancer. AG-221 is the first mIDH2 inhibitor approved by the FDA for acute myeloid leukemia treatment, but its acquired resistance has recently been observed, necessitating the development of new inhibitor. In this study, a multi-step virtual screening protocol was employed for the analysis of a large database of compounds to identify potential mIDH2 inhibitors. To this end, we firstly utilized molecular dynamics (MD) simulations and binding free energy calculations to elucidate the key factors affecting ligand binding and drug resistance. Based on these findings, the receptor-ligand interaction-based pharmacophore (IBP) model and hierarchical docking-based virtual screening were sequentially carried out to assess 212,736 compounds from the Specs database. The resulting hits were finally ranked by PAINS filter and ADME prediction and the top compounds were obtained. Among them, six molecules were identified as mIDH2 putative inhibitors with high selectivity by interacting with the capping residue Asp312. Furthermore, subsequent docking and MD experiments demonstrated that compound V2 might have potential inhibitory activity against the AG-221-resistant mutants, thereby making it a promising lead for the development of novel mIDH2 inhibitors.

By introducing the working principle of the two-stage decoupled micro-machined gyroscope, the vibration equation of the driving mode is established. Using Laplace transform, the differential equation and the analytical solution are solved, and the amplitude–frequency characteristics of the driving mode are obtained. Moreover, this article introduces the hardware of the noncontact vibration measurement system and the algorithm. By experiments, the characteristic of vibration of the tested micro-machined gyroscope is obtained. Experimental results indicate that the precision of the amplitude is 0.1 µm, and the two-stage decoupled micro-machined gyroscope is immune to mechanical coupling and has high linearity inherently.

This paper introduces the working principle of the two-stage decoupled micro-machined gyroscope, and establishes the vibration equation of the driving mode. By solving the differential equation, the analytical solution and the amplitude-frequency characteristics of the driving mode are obtained. By the visual measurement based on high-speed photography and the post image processing, it measures the natural frequency of the driving mode of the micro-machined gyroscope. And it measures the damping coefficient in time domain and frequency domain respectively using this method. The comparison to the theoretical solution proves that the method is effective and accurate; it will help the study for the micro-machined gyroscope vibration and provides a new way to measure MEMS.

The homology of the sequences, reported and registered in GenBank, of different strains ofAvian influenza virus(AIV),Newcastle disease virus(NDV),Classical swine fever virus(CSFV) andFoot-and-mouth disease virus(FMDV), was analysed and compared with each other. According to the properties of these viruses, the conservative domain of theMgene for AIV, theFgene for NDV, the 5' non-coding domain end for CSFV and the2Bgene for FMDV were selected for polymerase chain reaction (PCR) amplification. In order to prevent the formation of conformational dimers between different primers, four pairs of primers designed with the DNAsis system under the condition of G+C (50–60%),18–25 bp in length andTm(72–85), were analysed using the VNTI5.5 system. The specific fragments amplified were as follows: 141 bp for FMDV, 200 bp for CSFV, 319 bp for NDV and 471 bp for AIV. The optimal conditions of PCR for each virus mentioned above were determined by orthogonal assay, and two or four of the four pairs of primers were then combined and used for amplification trials. The results showed that four specific fragments of different lengths would be successfully amplified in one tube at the same time. The products of PCR were tested to be specific by sequencing. Out of 46 pathological samples detected with the multiple PCR, there were 5 AIVs, 7 NDVs, 15 CSFVs and 6 FMDVs. The amplification above was identified with a single PCR. On the other hand, the results corresponded to those of electronic microscopy, haemagglutination (HA) and enzyme-linked immunosorbent assay (ELISA). The method described here is practicable, sensitive, specific, simple and cheap. It could be used for diagnosing AIV, NDV, CSFV and FMDV in different animals.

An iteration method of statistic linearization (IMSL) is presented. By this method, an equivalent linear term was formed in geometric relation and then an equivalent stiffness matrix for nonlinear term in vibration equation was established. Using the method to solve the statistic linear vibration equations, the effect of geometric nonlinearity on the random response of rotational shell is obtained.

We show that by using data-dependent superimposed training and an iterative feedback algorithm, residual CD, PMD, polarization rotation and frequency offset can be compensated efficiently in single carrier coherent optical systems, without any bandwidth loss.

The micro-machined gyroscope, with advantages of small size, lower weight, high reliability, lower power consumption and lower cost, has an observably increasing usage in many fields. In order to verify the designed performance parameters of capacitive micro-machined gyroscope, the open-loop drive circuit is designed and tested. In the laboratory condition, because the open-loop drive circuit has the advantages of simpler design, easier regulation, and without interference of the others signal and noise, the open-loop drive circuit can be used to drive up the micro-machined gyroscope. However, when the natural frequency of micro gyroscope changes for some reasons, the output signal offset will appear and the measurement accuracy will decrease. Therefore, the open-loop drive circuit is only in laboratory. While in practice, the closed-loop drive circuit which can automatic tracking the natural frequency of drive mode should be used to make sure highly linear output signal.

Based on the PID(Proportional-Integral-Differential) control algorithm, by analyzing the control system with control variable varying in the form of arbitrary function, a simple control method with control variable varying in the form of arbitrary function was presented, i.e. PID control algorithm with set value which is constant in small zone. The paper introduced the mathematical model and the parameter tuning method of the PID control algorithm briefly, analyzed and the selection principle of the parameters of the advance control, lag control, ideal control. And used the MATLAB to simulate and verify this algorithm, the simulation results are satisfactory. Tests were carried out on different equipments and in different experimental conditions; results of the experiment are successful. Then this method is applied to the practical engineering practice, proves that it makes remarkable effects on the practical utilization.

Vibratory gyroscope exploit a coriolis force coupling between two degree of freedom internal to the sensor for detection of the sensor's angular rotation rate. The peripheral circuit is the key part to realize the function of the gyro system. The peripheral circuit traditionally adopts pure analog circuit. However, the analog circuit has some inherent shortcomings. These limit the accuracy of the gyro. In this paper, a digital control system for micro-comb is introduced. According to testing the gyro performance is much improved by means of the digital control system.

The micro-machined gyroscope, with advantages of small size, lower weight, high reliability, lower power consumption and lower cost, has an observably increasing usage in many fields. At present, the development of comb capacitive micro-machined gyroscope is very fast dueto its high reliability. The resent gyroscopes are in rate grade and can not satisfy the demands on tactical grade and navigation grade. Therefore, how to improve the performance of gyroscope has become a main target pursued by designers. The comb capacitive micro-machined gyroscope basing on the Coriolis's effect is a kind of vibration gyroscope. The vibration properties are important parameters for the micro-machined gyroscope. The working performance of micro gyroscope can be clearly understood and its other performances can be known only when its vibration properties were obtained. We tested the vibration properties of comb capacitive micro-machined gyroscope in normal atmosphere. Some instruments used in testing experiment are turntable, direct current power source, dynamic signal analyzer, data acquisition circuit and data storage system etc. From the testing results, we obtained the driving resonant frequency and the detection resonant frequency of micro gyroscope. The quality factors in two directions are also obtained.