An Energy Saving Glass Deep Processing Line Put into Production in Hubei

On July 16, 2013, the first low-E energy saving glass deep processing line of Hubei Zhongyi Glass Co., Ltd. was put into production in Changyang County of Hubei Province. Low-E glass is a kind of new glass featured with good lighting, thermal insulation, and ultraviolet radiation resistance. So far contracts worth about CNY 50 million have been signed.

Chinalco Southeast Coast Aluminum Deep Processing Base Started Construction in Fuzhou

At the end of August,Chinalco Southeast Coast Aluminum Deep Processing Base broke ground at the Fujian-Taiwan(Fuzhou)Industrial Park for Blue Economy.Based on Chilco Ruimin(an aluminum processing subsidiary of Chinalco in Fujian Province)as the main body,Chinalco

B^(2)C^(3)NetF^(2):Breast cancer classification using an end‐to‐end deep learning feature fusion and satin bowerbird optimization controlled Newton Raphson feature selection

Currently,the improvement in AI is mainly related to deep learning techniques that are employed for the classification,identification,and quantification of patterns in clinical images.The deep learning models show more remarkable performance than the traditional methods for medical image processing tasks,such as skin cancer,colorectal cancer,brain tumour,cardiac disease,Breast cancer(BrC),and a few more.The manual diagnosis of medical issues always requires an expert and is also expensive.Therefore,developing some computer diagnosis techniques based on deep learning is essential.Breast cancer is the most frequently diagnosed cancer in females with a rapidly growing percentage.It is estimated that patients with BrC will rise to 70%in the next 20 years.If diagnosed at a later stage,the survival rate of patients with BrC is shallow.Hence,early detection is essential,increasing the survival rate to 50%.A new framework for BrC classification is presented that utilises deep learning and feature optimization.The significant steps of the presented framework include(i)hybrid contrast enhancement of acquired images,(ii)data augmentation to facilitate better learning of the Convolutional Neural Network(CNN)model,(iii)a pre‐trained ResNet‐101 model is utilised and modified according to selected dataset classes,(iv)deep transfer learning based model training for feature extraction,(v)the fusion of features using the proposed highly corrected function‐controlled canonical correlation analysis approach,and(vi)optimal feature selection using the modified Satin Bowerbird Optimization controlled Newton Raphson algorithm that finally classified using 10 machine learning classifiers.The experiments of the proposed framework have been carried out using the most critical and publicly available dataset,such as CBISDDSM,and obtained the best accuracy of 94.5%along with improved computation time.The comparison depicts that the presented method surpasses the current state‐ofthe‐art approaches.

Performance Evaluation of Low-Carbon and Clean Transformation of China’s Coal Economy

In China,the oversupply of coal occurred in 2009,and from that year onwards,China’s coal economy began a low-carbon and clean transformation.Evaluating transformation performance is the research goal of this paper.The data collection for this paper includes data on deep processing of Chinese coal products from 2009 to 2020,as well as data on asset structure evolution and financial performance of 34 listed companies in the Chinese coal mining.Entropy value method is used to calculate the entropy value of low-carbon transformation,and the regression analysis is used to study the performance of cleaner transformation,the conclusion is as follows:(1)From 2009 to 2020,in China’s total energy consumption,coal consumption accounted for 71.6%in 2009 and 56.8%in 2020,the goals set by the state have been achieved.(2)The national goal of reducing the proportion of coal consumption and reducing carbon emissions has forced the transformation of deep processing of coal products.The transformation of coal enterprises towards low-carbon and clean production has achieved remarkable results.(3)From 2009 to 2020,the non coal industry income of 34 listed companies in China’s coal mining industry increased by 8.21%annually.At the same time,the asset structure was adjusted,and nearly 80%of the asset structure evolution showed an orderly development trend.(4)The regression analysis results show that the entropy value of coal deep processing products and the entropy value of asset structure adjustment are significantly related to transformation performance.The paper proposes to summarize the successful experience of China’s coal energy economic transformation,lay a foundation for achieving the carbon peak and carbon neutral goals in the future,further increase the intensity of coal deep processing,increase the proportion of clean energy in total energy consumption,and strive to control asset operation towards the goal of increasing the proportion of non coal industry income.

High-resolution crustal structure of the Yinchuan basin revealed by deep seismic reflection profiling:implications for deep processes of basin

The Yinchuan basin, located on the western margin of the Ordos block, has the characteristics of an active continental rift. A NW-striking deep seismic reflection profile across the center of Yinchuan basin precisely revealed the fine structure of the crust. The images showed that the crust in the Yinchuan basin was characterized by vertical stratifications along a detachment located at a two-way travel time（TWT） of 8.0 s.The most outstanding feature of this seismic profile was the almost flat Mohorovicˇic′ discontinuity（Moho） and a high-reflection zone in the lower crust. This sub-horizontal Moho conflicts with the general assumption of an uplifted Moho under sedimentary basins and continental rifts, and may indicate the action of different processes at depth during the evolution of sedimentary basins or rifts.We present a possible interpretation of these deep processes and the sub-horizontal Moho. The high-reflection zone, which consists of sheets of high-density, mantlederived materials, may have compensated for crustal thinning in the Yinchuan basin, leading to the formation of a sub-horizontal Moho. These high-density materials may have been emplaced by underplating with mantlesourced magma.

Deep Tectonic Processes and Superaccumulation of Metals Related to Granitoids in the Nanling MetaUogenic Province,China

The Nanling region is an important nonferrous and rare metal metallogenic province in South China, in which most of the deposits are related to granitoids in genesis. It covers southern Hunan, southern Jiangxi, Guangxi, Guangdong and Fujian provinces, with a total area of about 550,000 km2. This metallogenic province is well known in the world for its rich tungsten and tin resources. In the past 40-odd years, a vast amount of mineral exploration activities and studies of the geology of mineral deposits have been carried out and great achievements obtained in the province. This paper is focused on a discussion about the deep tectonic processes in the orogenic belt during the Mesozoic and their contribution to the superaccumulation of metals. Tectonically, this metallogenic province is composed of three units: (1) the marginal continental orogenic belt in the Southeastern Coast fold system in the Yanshanian; (2) the intercontinental orogenic belt in the collision suture belt between the Yangtze and Cathay-sian plates mainly in the Caledonian; and (3) the intracontinental orogenic belt induced by subduction of the ocean crust and delimination of the mantle lithosphere in the Yanshanian. It is suggested that superaccumulation of metals in this metallogenic province was caused by the existence of mantle rooted tectonics at the depth based on comprehensive studies of geophysical information of seismic, geothermal and magnetotelluric surveys in Nanling and its adjacent areas. The Xihuashan wolframite quartz vein deposit, the Shizhuyuan W, Sn, Mo, Bi greisen-skarn deposit and the Dachang tin-polymetallic deposit are three typical examples of the deep tectonic processes. However, this kind of deep tectonic processes only act as the 'engine' of the superaccumulation of metals, which means that they should have to correspond with the super-crust ore-controlling pattern of 'lines-rows-clusters' (L-R-C). This recog-nization is expected to play an important role in assessment of mineral resources in this province.

Study on Eogene Basalts: Implication of the Deep Process over the Bohaiwan Basin Evolution

The present paper describes the characteristics of Cenozoic basalt in the Bohaiwan basin and its implication of the control of deep process over the basin evolution. The large scale Eogene basalts lying on the basement of the Bohaiwan basin belong to alkaline series and subalkaline series. The basalt magma originates at a depth of 48-76 km and a temperature of 1 300-1 400 ℃ with the mantle partial melting degree of 8%-14%. In Eogene period, the rising of the top of asthenosphere from 100-140 km to 50-70 km led to the strong extension and thinning of the overlying lithosphere, which was stretched at an average rate of 0.41 cm/a and the β value from 1.9 to 2.3. At the same time, it triggered the great scale rifting in the earth crust, forming large rift basins.

Geochemical Characteristics of Volcanic Rocks from ODP Site 794,Yamato Basin:Implications for Deep Mantle Processes of the Japan Sea

Deep mantle processes and the dynamic mechanism of magmatism in the Japan Sea Basin are important processes that have not been studied in detail. In this paper, systematic evaluation of basalt samples from the ocean drilling program Site 794 in the Japan Sea was performed, which included petrography, whole-rock major- and trace-element analysis, Sr-Nd-Pb isotopic composition, and electron microprobe analysis of plagioclase and clinopyroxene. These basalts belong to the tholeiitic series with porphyritic texture and massive Ca-rich plagioclase, clinopyroxene, and minor olivine phenocrysts. The basalts are characterized as flat rare earth elements and high-field-strength elements with remarkably low ratios of （La/Yb）N （0.75-2.51）, significant positive anomalies of Ba, Sr, and Rb and no Eu anomaly （dEn = 0.99-1.36）. The samples showed relatively high 87Sr/86Sr （0.70425- 0.70522）, 207pb/204pb （15.511-15.610）, and 208pb/204pb （38.064-38.557） values and a low 143Nd/144Nd ratio （0.51271-0.51295）. The basalts from Site 794 can be divided into upper, middle, and lower volcanic rocks （UVR, MVR, and LVR） on the basis of their stratigraphic level. The MVR was geochemically derived from the depleted mantle, whereas the UVR and LVR originated from a nondepleted and relatively enriched mantle source with contributions from subducted Pacific plate fluid and sediments. Use of geothermobarometers indicates that the crystallization pressure for the UVR and LVR （6.25-11.19 kbar） was significantly higher than that of the MVR （3.48-5.84 kbar）. The UVR and LVR may have been derived from the low-degree （5%-10%） partial melting of spinel lherzolite, while the MVR originated from a shallower mantle source with a high degree （10%-20%） of partial melting. In addition, the geochemical characteristics of the samples are consistent with a younger age （13-17 Ma） and the depleted composition of the MVR and an older age （17-23 Ma） and slightly enriched composition of the UVR and LVR. Therefore, temporal changes in the mantle source from old and enriched to young and depleted and subsequently to old and nondepleted may have been associated with progressive lithospheric extension and thinning, as well as at least two episodes of diverse asthenospheric upwelling and pull-apart tectonic motion in the Yamato Basin.

Magmatism, Deep Processes and Gold Deposits in Eastern Hebei, China

The eastern Hebei Province of China is one of the major concentrating areas of gold mineralization in eastern China, which is an important part of the circum Pacific magmatic tectonic metallogenic belt. There are three types of gold deposits in terms of the characteristics of host rocks. Jinchangyu type gold deposit is situated in the Archean metamorphic basement. Yuerya type gold deposit occurs within the Yanshanian granite. Lengkou (or Wanzhuang ) type gold deposit is located within the covering strata of the Mesoproterozoic dolomitite. These 3 types of gold deposits are very similar in many respects. These deposits formed at Mesozoic and their spatial distribution is closely related to Yanshanian granite. The mineralization characteristics of these gold deposits are very similar. The characteristics of sulfur isotopic and lead isotopic compositions show that the gold deposits in this area are derived from the mantle and deep crust, and are related to Mesozoic magmatism. The gold deposits in this area are believed to be the products of crust mantle exchange and resulted from multistage gold mineralization. Finally a mineralization model of gold deposit in eastern Hebei of China is proposed.

Extensional Tectonic System of Erlian Fault Basin Groupand Its Deep Background

The Erlian fault basin group, a typical Basin and Range type fault basin group, was formed during Late Jurassic to Early Cretaceous, in which there are rich coal, oil and gas resources. In the present paper the abundant geological and petroleum information accumulated in process of industry oil and gas exploration and development of the Erlian basin group is comprehensively analyzed, the structures related to formation of basin are systematically studied, and the complete extensional tectonic system of this basin under conditions of wide rift setting and low extensional ratio is revealed by contrasting study with Basin and Range Province of the western America. Based on the above studies and achievements of the former workers, the deep background of the basin development is treated.

Deep Deformation Processes in the Southern Ningxia Geomorphic Belt: Insight from Two-dimensional Particle-in-cell Finite Difference Numerical Modelling

The deep lateral growth process of the plateau is a hot topic in earth science.As the growth boundary zone of the northeastern Tibetan Plateau,southern Ningxia geomorphic zone is controlled by four major arcuate fault zones(Fig.1),namely Haiyuan fault(HYF),XiangshanTianjingshan fault(XTSF),Yantongshan fault(YTSF).

ABNORMAL GEOMAGNETIC FIELD RESPONSE AT INTRAPLATE TECTONIC BOUNDARY IN CONTINENT AND CONTINENTAL MARGIN IN SOUTHEASTERN CHINA

We used matched filter, spectrum analysis, and continuation methods of potential field for data processing and obtained the geomagnetic field distribution about the continent and continental margin in southeast China. On the basis of grid data, inversion was conducted and magnetic field distribution and magnetic structure on bedding of different depths were obtained. The new results show that: 1. The magnetic field characteristics are largely different in horizontal and vertical directions and they can be divided into zones according to the continental blocks of Yangtze, Cathaysia, Kangdian (Sichuan-Yunnan) and Qinling-Dabie. 2. The Tanlu fault extends southward along the Ganjiang fault and the Wuchuan-Sihui fault after it crossed over the Yangtze River and was offset locally in the east-west direction. The Tanlu fault finally slips into the South China Sea at Hainan Island. 3. The boundary between Yangtze and Cathaysia blocks starts from Hangzhou Bay in the east, extends along Jiangshao fault and passes through Nanchang, Changsha, and Guilin, and finally enters the sea at Qinzhou, Guangxi. 4. The distribution of buried structure zone is located at 24.5°-26° N.

Signal processing in underwater acoustic communication system for manned deep submersible "Jiaolong"

For the first time in the world, underwater acoustic transmission of images, human voice, data and texts between vehicle under 7000 m depth and surface ship was accomplished by underwater acoustic communication system of manned deep submersible Jiaolong＇. In this paper, signal processing in underwater acoustic communication system for manned deep submersible ＂Jiaolong＂ is introduced. （1） Four communication methods are integrated to meet different needs： 1） coherent underwater acoustic communication, with a variable transmission rate from 5 kbps to 15 kbps, to transmit images. 2） Non-coherent underwater acoustic com- munication, with a transmission rate 300 bps, to transmit texts, instructions, and sensor data. 3） Spread spectrum underwater acoustic communication, with a transmission rate 16 bps, to transmit instructions. 4） Underwater voice communication, using single sideband modulation to transmit hmnan voice. （2） Signal processing method in coherent communication mainly consists of concatenation of decision feedback equalizer and Turbo decoder, and wavelet based image compression with fixed length coding. In the equalizer, Doppler compensation, multi- channel combining and equalizer coefficients updating are all using fast self-optimized adaptive algorithm. （3） A linear hydrophone array is lowered from the mother ship to certain depth, and spatial diversity combining technology is adopted. （4） Diving trials of ＂Jiaolong＂ were carried out in Pacific Ocean. The communication range can cover nearly all ocean depth. One optical/acoustic image can be transmitted in 7 or 14 seconds.

DSC based Dual-Resunet for radio frequency interference identification

Radio frequency interference(RFI)will pollute the weak astronomical signals received by radio telescopes,which in return will seriously affect the time-domain astronomical observation and research.In this paper,we use a deep learning method to identify RFI in frequency spectrum data,and propose a neural network based on Unet that combines the principles of depthwise separable convolution and residual,named DSC Based Dual-Resunet.Compared with the existing Unet network,DSC Based Dual-Resunet performs better in terms of accuracy,F1 score,and MIoU,and is also better in terms of computation cost where the model size and parameter amount are 12.5%of Unet and the amount of computation is 38%of Unet.The experimental results show that the proposed network is a high-performance and lightweight network,and it is hopeful to be applied to RFI identification of radio telescopes on a large scale.

Call for Papers Special Section on Deep Learning for Natural Language Processing

The publication of Tsinghua Science and Technology was started in 1996.Since then,it has been an international academic journal sponsored by Tsinghua University and published bimonthly.This journal aims at presenting the state-of-the-art scientific achievements in computer science and other IT fields.

Baise Mining Group's Annual 1-million-ton Deep Aluminum Processing Project Commenced

The Baise Municipal Government held a commencement ceremony for Baise Mining Group’s1-million-ton deep aluminum processing project('Project')at its base in the Poverty Alleviation Industrial Park in Pingguo County.It’s learnt that the Project includes an annual450,000-ton medium and thick plates and plate belts for transportation project,an annual 160。

Test of Deep Seismic Reflection Profiling across Central Uplift of Qiangtang Terrane in Tibetan Plateau

A test of deep seismic reflection profiling across the central uplift or metamorphic belt of the Qiangtang （羌塘） terrane, Tibet plateau, provides a first image of the crustal structure. Complex reflection patterns in the upper crust are interpreted as a series of folds and thrusts, and bivergent reflections in the lower crust may represent a convergence between the Indian and the Eurasian plates.

Automated extraction of attributes from natural language attribute-based access control(ABAC)Policies

The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.

Greedy nonlinear autoregression for multifidelity computer models at different scales

Although the popular multi-fidelity surrogate models,stochastic collocation and nonlinear autoregression have been applied successfully to multiple benchmark problems in different areas of science and engineering,they have certain limitations.We propose a uniform Bayesian framework that connects these two methods allowing us to combine the strengths of both.To this end,we introduce Greedy-NAR,a nonlinear Bayesian autoregressive model that can handle complex between-fidelity correlations and involves a sequential construction that allows for significant improvements in performance given a limited computational budget.The proposed enhanced nonlinear autoregressive method is applied to three benchmark problems that are typical of energy applications,namely molecular dynamics and computational fluid dynamics.The results indicate an increase in both prediction stability and accuracy when compared to those of the standard multi-fidelity autoregression implementations.The results also reveal the advantages over the stochastic collocation approach in terms of accuracy and computational cost.Generally speaking,the proposed enhancement provides a straightforward and easily implemented approach for boosting the accuracy and efficiency of concatenated structure multi-fidelity simulation methods,e.g.,the nonlinear autoregressive model,with a negligible additional computational cost.

Automated extraction of attributes from natural language attribute-based access control(ABAC)Policies

The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.