The Geochemical Data Imaging and Application in Geoscience: Taking the Northern Daxinganling Metallogenic Belt as an Example

Geochemical data were predominantly expressed by vector format, the research on geochemical data visualization, i.e., raster data format, was not paid proper attention. A total of 39 geochemical elements in 1:200,000 regional geochemical exploration data were rasterized to form images, and then a geochemical image database was generated. This article has carried out the study on geochemical imaging within Daxinganling metallogenic belt. The metallogenic belt had once carried out the regional geochemical survey, the sampling density was 1 site/4 km2, and 39 geochemistry elements including the microelement and trace element have been analyzed. Quintic polynomial method was used to implement the geochemical data interpolation, and the cell size of formed geochemical elemental image is 1 km. The images of the geochemical elements were processed by image enhancement methods, and then hyperspectral remote sensing data processing method was used for prospecting target selection, lithology mapping, and so on. The interpreted results have been verified in practice. All the abovementioned suggested a good development prospect for the rasterized geochemical images. Finally the author puts forward using rasterize geochemical images in combination with other geological, geophysical, and remote sensing data to make better use of the geochemical data and be more extensively applied in the geoscience

Medial Habenula-Interpeduncular Nucleus Circuit Contributes to Anhedonia-Like Behavior in a Rat Model of Depression

The habenula is a nuclear complex composed of the lateral habenula (LHb) and medial habenula (MHb), two distinct structures. Much progress has been made to emphasize the role of the LHb in the pathogenesis of depression. In contrast, relatively less research has focused on the MHb. However, in recent years, the role of the MHb has begun to gain increasing attention. The MHb connects to the interpeduncular nucleus (IPN) both morphologically and functionally. The MHb-IPN pathway plays an important role in regulating higher brain functions, including cognition, reward, and decision making. It indicates a role of the MHb in the pathogenesis of depression. Thus, we investigated the role of the MHb-IPN pathway in depression. MHb metabolic activity was increased in the chronic unpredictable mild stress (CUMS)-exposed rat model of depression. MHb lesions in the CUMS-exposed rats reversed anhedonia-like behavior, as observed in the sucrose preference test, and significantly downregulated the elevated metabolic activity of the IPN. Substance P (SP)-containing neurons of the MHb were found to innervate the IPN and to be the main source of SP in the IPN. SP content of IPN tissue of the CUMS-exposed rats was increased and MHb lesions reversed this change. In the in vitro experiment, firing rate recordings showed that SP perfusion increased the activity of IPN neurons. Our results suggest that hyperactivity of the MHb-IPN circuit is involved in the anhedonia-like behavior of depression, and that SP mediates the effect of the MHb on IPN neurons

Y-DWMS - A digital watermark management system based on smart contracts

With the development of information technology, films, music, and other publications are inclined to be distributed in digitalized form. However, the low cost of data replication and dissemination leads to digital rights problems and brings huge economic losses. Up to now, existing digital rights management (DRM) schemes have been powerless to deter attempts of infringing digital rights and recover losses of copyright holders. This paper presents a YODA-based digital watermark management system (Y-DWMS), adopting non-repudiation of smart contract and blockchain, to implement a DRM mechanism to infinitely amplify the cost of infringement and recover losses copyright holders suffered once the infringement is reported. We adopt game analysis to prove that in Y-DWMS, the decision of non-infringement always dominates rational users, so as to fundamentally eradicate the infringement of digital rights, which current mainstream DRM schemes cannot reach

Development and Utilization of Introgression Lines Using Synthetic Octaploid Wheat (Aegilops tauschii × Hexaploid Wheat) as Donor

As the diploid progenitor of common wheat, Aegilops tauschii Cosson (DD, 2n = 2x = 14) is considered to be a promising genetic resource for the improvement of common wheat. In this work, we demonstrated that the efficiency of transferring A. tauschii segments to common wheat was clearly improved through the use of synthetic octaploid wheat (AABBDDDD, 2n = 8x = 56) as a “bridge.” The synthetic octaploid was obtained by chromosome doubling of hybrid F1 (A. tauschii T015 × common wheat Zhoumai 18). A set of introgression lines (BC1F8) containing 6016 A. tauschii segments was developed and displayed significant phenotype variance among lines. Twelve agronomic traits, including growth duration, panicle traits, grain traits, and plant height (PH), were evaluated. And transgressive segregation was identified in partial lines. Additionally, better agronomic traits could be observed in some lines, compared to the recurrent parent Zhoumai 18. To verify that the significant variance of those agronomic traits was supposedly controlled by A. tauschii segments, 14 quantitative trait loci (QTLs) for three important agronomic traits (thousand kernel weight, spike length, and PH) were further located in the two environments (Huixian and Zhongmou), indicating the introgression of favorable alleles from A. tauschii into common wheat. This study provides an ameliorated strategy to improve common wheat utilizing a single A. tauschii genome

Automatic 3D tooth segmentation using convolutional neural networks in harmonic parameter space

Automatic segmentation of 3D tooth models into individual teeth is an important step in orthodontic CAD systems. 3D tooth segmentation is a mesh instance segmentation task. Complex geometric features on the surface of 3D tooth models often lead to failure of tooth boundary detection, so it is difficult to achieve automatic and accurate segmentation by traditional mesh segmentation methods. We propose a novel solution to address this problem. We map a 3D tooth model isomorphically to a 2D harmonic parameter space and convert it into an image. This allows us to use a CNN to learn a highly robust image segmentation model to achieve automated and accurate segmentation of 3D tooth models. Finally, we map the image segmentation mask back to the 3D tooth model and refine the segmentation result using an improved Fuzzy Clustering-and-Cuts algorithm. Our method has been incorporated into an orthodontic CAD system, and performs well in practice

Dual-timescale control for power electronic zigzag transformer

Power electronic zigzag transformer is an attractive solution for the flexible interconnection of smart distribution networks. It is constituted by slow-response and low-precision thyristor converters and fast-response and high-accuracy voltage source converters. This paper models its primary circuit and addresses its basic operation mechanism. Then a dual-timescale control scheme is investigated to realize the coordinated regulation of both types of converter. A simulation case is established in PSCAD containing interconnected mid-voltage distribution networks. Simulations with poor- and well-matched control timescales are both carried out. And accordingly, the power flow controllability under these conditions is compared. When the shorter control timescale is no more than tenth of the longer one, the power electronic zigzag transformer will operate with satisfying performances

A high gain, noise cancelling 2515-4900 MHz CMOS LNA for China mobile 5G communication application

© 2020 Tech Science Press. All rights reserved. With the development of the times, people\u27s requirements for communication technology are becoming higher and higher. 4G communication technology has been unable to meet development needs, and 5G communication technology has emerged as the times require. This article proposes the design of a low-noise amplifier (LNA) that will be used in the 5G band of China Mobile Communications. A low noise amplifier for mobile 5G communication is designed based on Taiwan Semiconductor Manufacturing Company (TSMC) 0.13 μm Radio Frequency (RF) Complementary Metal Oxide Semiconductor (CMOS) process. The LNA employs self-cascode devices in current-reuse configuration to enable lower supply voltage operation without compromising the gain. This design uses an active feedback amplifier to achieve input impedance matching, avoiding the introduction of resistive negative feedback to reduce gain. A common source (CS) amplifier is used as the input of the low noise amplifier. In order to achieve the low power consumption of LNA, current reuse technology is used to reduce power consumption. Noise cancellation techniques are used to eliminate noise. The simulation results in a maximum power gain of 22.783, the reverse isolation (S12) less than -48.092 dB, noise figure (NF) less than 1.878 dB, minimum noise figure (NFmin)=1.203 dB, input return loss (S11) and output return loss (S22) are both less than -14.933 dB in the frequency range of 2515-4900 MHz. The proposed Ultra-wideband (UWB) LNA consumed 1.424 mW without buffer from a 1.2 V power supply