Research on Online Moisture Detector in Grain Drying Process Based on V/F Conversion

An online resistance grain moisture detector is designed, based on the model of the relationship between measurement frequency and grain moisture and the nonlinear correction method of temperature. The detector consists of lower computer, the core function of which is the sensing of grain resistance values which is based on V/F conversion, and upper computer, the core function of which is the conversion of moisture and frequency and the nonlinear correction of temperature. The performance of the online moisture detector is tested in a self-designed experimental system; the test and analysis results indicate that the precision and stability of the detector can reach the level of the similar products, which can be still improved

Locate and Verify: A Two-Stream Network for Improved Deepfake Detection

Deepfake has taken the world by storm, triggering a trust crisis. Current deepfake detection methods are typically inadequate in generalizability, with a tendency to overfit to image contents such as the background, which are frequently occurring but relatively unimportant in the training dataset. Furthermore, current methods heavily rely on a few dominant forgery regions and may ignore other equally important regions, leading to inadequate uncovering of forgery cues. In this paper, we strive to address these shortcomings from three aspects: (1) We propose an innovative two-stream network that effectively enlarges the potential regions from which the model extracts forgery evidence. (2) We devise three functional modules to handle the multi-stream and multi-scale features in a collaborative learning scheme. (3) Confronted with the challenge of obtaining forgery annotations, we propose a Semi-supervised Patch Similarity Learning strategy to estimate patch-level forged location annotations. Empirically, our method demonstrates significantly improved robustness and generalizability, outperforming previous methods on six benchmarks, and improving the frame-level AUC on Deepfake Detection Challenge preview dataset from 0.797 to 0.835 and video-level AUC on CelebDF$\_$v1 dataset from 0.811 to 0.847. Our implementation is available at https://github.com/sccsok/Locate-and-Verify.Comment: 10 pages, 8 figures, 60 references. This paper has been accepted for ACM MM 202

The performance of mixture refrigerant R134a/R152a in a novel gas engine-driven heat pump system

In the present article, a novel gas engine-driven heat pump (GEHP) which could independently provide heating, cooling, and hot water for the buildings with its autonomous power supply system was presented, and the cooling performance characteristics of GEHP using mixture refrigerant R134a/R152a were investigated experimentally. The thermophysical properties and flammability of this proposed mixture refrigerant were analyzed and experimented to approve that it could be used safely in GEHP. The experimental results indicated that the cooling capacity, waste heat recovered from cylinder jacket and exhaust gas, gas engine energy consumption, and compressor power increased with the increase of the gas engine speeds and evaporator water inlet flow rate, but changed in a small range with the increase of the evaporator water inlet temperature except cooling capacity. The generator power remained about 4.90 kW in different operating conditions. Furthermore, the coefficient of performance (COP) and the primary energy ratio (PER) of GEHP also increased with the increase of the evaporator water inlet flow rate and temperature, but decreased with the increase of gas engine speeds. Finally, maximum COP and PER with mixture refrigerant R134a/R152a has been estimated with 8.88 and 1.69 in the aforementioned conditions.The National Natural Science Foundation of China (Grant No. 51076112 and 51276124) and the Science and Technology Project of Tiajin City (Grant No. 12ZCDGGX49400).http://www.tandfonline.com/loi/ljge20hb2016Mechanical and Aeronautical Engineerin

Rapid Algorithm for Generating and Selecting Optimal Metro Train Speed Curves Based on Alpha Zero and Expert Experience

According to the current research status of urban rail transit’s fully automatic operation (FAO), the train driving speed curves are usually obtained through simulation and calculation. The train driving speed curves obtained by this method not only have low efficiency but also are not suitable for complex road conditions. Inspired by AlphaZero, a reinforcement learning algorithm that utilised vast amounts of artificial data to defeat AlphaGo, an AI Go program, this paper investigates and analyses methods for rapidly generating a large number of speed curves and selecting those with superior performance for train operation. Firstly, we use the powerful third-party library in Python as the basis, combined with the idea of AlphaZero, to produce artificial speed curves for metro train driving. Secondly, we set relevant parameters with reference to expert experience to quickly produce massive reasonable artificial speed curves. Thirdly, we analysed relevant indicators such as energy consumption, running time error and passenger comfort to select some speed curves with better comprehensive performance. Finally, through the many observations with different running distances and different speed limits, we found that the speed curves produced and selected by our algorithm are more productive, diverse and conducive to the research of train driving operation than the actual data from traditional manual driving and ATO (automatic train operation) system

Tailoring the surface of perovskite through in situ growth of Ru/RuO2 nanoparticles as robust symmetrical electrodes for reversible solid oxide cells

Although numerous perovskite oxides can enhance the electrochemical activity via exsolved metallic nanoparticles on the surface, most of them can only be applied as catalysts in a reducing atmosphere. These nanoparticles cause serious performance degradation in oxidizing conditions due to the formation of low-conductive metal oxides. This poses a big challenge to the design of highly active catalysts of electrochemical devices, especially for symmetrical solid oxide cells. Herein, based on the strategy of exsolved metallic nanoparticles in A-site deficient perovskite, a unique and simple method is demonstrated for the synthesis of Ru/RuO2 nanoparticles on the surface of perovskite oxide via in situ growth. The electrode material (La0.75Sr0.25)0.9Cr0.5Mn0.45Ru0.05O3−δ (LSCMR) is designed through careful choice of composition and the core idea is to make use of the exsolved nanoparticles concept applied for the first time at both hydrogen electrode and oxygen electrode for symmetrical solid oxide cells. Inspired by exsolved Ru and RuO2, the surface-decorated LSCMR exhibits significantly enhanced electrochemical activity for both H2 and O2, respectively, accompanied by high redox long-term stability. Moreover, simple, low-cost, and environmental-friendly synthesis of Ru/RuO2 nanoparticles on the substrate of typical perovskites is realized with this in situ growth approach

Investigation of the Acetylation Mechanism by GCN5 Histone Acetyltransferase

The histone acetylation of post-translational modification can be highly dynamic and play a crucial role in regulating cellular proliferation, survival, differentiation and motility. Of the enzymes that mediate post-translation modifications, the GCN5 of the histone acetyltransferase (HAT) proteins family that add acetyl groups to target lysine residues within histones, has been most extensively studied. According to the mechanism studies of GCN5 related proteins, two key processes, deprotonation and acetylation, must be involved. However, as a fundamental issue, the structure of hGCN5/AcCoA/pH3 remains elusive. Although biological experiments have proved that GCN5 mediates the acetylation process through the sequential mechanism pathway, a dynamic view of the catalytic process and the molecular basis for hGCN5/AcCoA/pH3 are still not available and none of theoretical studies has been reported to other related enzymes in HAT family. To explore the molecular basis for the catalytic mechanism, computational approaches including molecular modeling, molecular dynamic (MD) simulation and quantum mechanics/molecular mechanics (QM/MM) simulation were carried out. The initial hGCN5/AcCoA/pH3 complex structure was modeled and a reasonable snapshot was extracted from the trajectory of a 20 ns MD simulation, with considering post-MD analysis and reported experimental results. Those residues playing crucial roles in binding affinity and acetylation reaction were comprehensively investigated. It demonstrated Glu80 acted as the general base for deprotonation of Lys171 from H3. Furthermore, the two-dimensional QM/MM potential energy surface was employed to study the sequential pathway acetylation mechanism. Energy barriers of addition-elimination reaction in acetylation obtained from QM/MM calculation indicated the point of the intermediate ternary complex. Our study may provide insights into the detailed mechanism for acetylation reaction of GCN5, and has important implications for the discovery of regulators against GCN5 enzymes and related HAT family enzymes

Solution-processed blue/deep blue and white phosphorescent organic light emitting diodes (PhOLEDs) hosted by a polysiloxane derivative with pendant mCP (1, 3-bis(9-carbazolyl)benzene)

The synthesis and characterization is reported of an efficient polysiloxane derivative containing the 1,3-bis(9-carbazolyl)benzene (mCP) moiety as a pendant unit on the polysiloxane backbone. In comparison with mCP, the mCP-polysiloxane hybrid (PmCPSi) has significantly improved thermal and morphological stabilities with a high decomposition temperature (Td = 523 °C) and glass transition temperature (Tg = 194 °C). The silicon–oxygen linkage of PmCPSi prevents intermolecular π-stacking and ensures a high triplet energy level (ET = 3.0 eV). Using PmCPSi as a host, blue phosphorescent organic light emitting devices (PhOLEDs) effectively confine triplet excitons, with efficient energy transfer to the guest emitter and a relatively low turn-on voltage of 5.8 V. A maximum external quantum efficiency of 9.24% and maximum current efficiency of 18.93 cd/A are obtained. These values are higher than for directly analogous poly(vinylcarbazole) (PVK) based devices (6.76%, 12.29 cd/A). Good color stability over a range of operating voltages is observed. A two-component “warm-white” device with a maximum current efficiency of 10.4 cd/A is obtained using a blend of blue and orange phosphorescent emitters as dopants in PmCPSi host. These results demonstrate that well-designed polysiloxane derivatives are highly efficient hosts suitable for low-cost solution-processed PhOLEDs