This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions,employing a deep learning classification algorithm for speech signal analysi...This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions,employing a deep learning classification algorithm for speech signal analysis.In this study,speech samples are categorized for both training and testing purposes based on their geographical origin.Category 1 comprises speech samples from speakers outside of India,whereas Category 2 comprises live-recorded speech samples from Indian speakers.Testing speech samples are likewise classified into four distinct sets,taking into consideration both geographical origin and the language spoken by the speakers.Significantly,the results indicate a noticeable difference in gender identification accuracy among speakers from different geographical areas.Indian speakers,utilizing 52 Hindi and 26 English phonemes in their speech,demonstrate a notably higher gender identification accuracy of 85.75%compared to those speakers who predominantly use 26 English phonemes in their conversations when the system is trained using speech samples from Indian speakers.The gender identification accuracy of the proposed model reaches 83.20%when the system is trained using speech samples from speakers outside of India.In the analysis of speech signals,Mel Frequency Cepstral Coefficients(MFCCs)serve as relevant features for the speech data.The deep learning classification algorithm utilized in this research is based on a Bidirectional Long Short-Term Memory(BiLSTM)architecture within a Recurrent Neural Network(RNN)model.展开更多
The gold concentration areas in the northwestern Jiaodong Peninsula constituted an important gold metallogenetic region in Eastern China during the Mesozoic. The deep geological bodies' texture characteristic is impo...The gold concentration areas in the northwestern Jiaodong Peninsula constituted an important gold metallogenetic region in Eastern China during the Mesozoic. The deep geological bodies' texture characteristic is important for exploring the resources thoroughly and understanding the metallogenic process. The detailed textures were revealed using high-resolution seismic profiles through the three major ore-controlling structures-Sanshandao fault zone, Jiaojia fault zone and Zhaoping fault zone. This study aims to establish a deep structural framework of this area. Based on their formation mechanism, the fault structures developed in the area can be divided into regional and local fault structures. The structural styles are characterised by superimposing their compressional, strike-slip and extensional multi-stage activities. The crust is cut by vertical structures corresponding to a left-lateral strike-slip fault system on the surface. Nearby these structures are the arc-shape structures formed by multi-stage magma intrusions into the upper crust. Bounded by the Tancheng–Lujiang and Muping–Jimo fault zones, the current Jiaodong block, developed a series of NE-trending strike-slip fault systems, was probably formed by the assemblage of several obliquely aligned blocks. The intensive magmatism and hydrothermal activity between the blocks induced large-scale mineralisation. It provides a new angle of view for understanding the cratonic destruction and large ore-concentration formed during the Mesozoic.展开更多
Drilling wells reveal that the organic matter abundance of Miocene marine source rocks in shallow water area of the Qiongdongnan Basin is relatively low with poor hydrocarbon generation poten- tial. However, in some d...Drilling wells reveal that the organic matter abundance of Miocene marine source rocks in shallow water area of the Qiongdongnan Basin is relatively low with poor hydrocarbon generation poten- tial. However, in some drilling wells of deep water area close to the central depression belt, Miocene marine source rocks with better organic matter abundance and hydrocarbon generation have been found, which have achieved better source rock standard based on the analysis of geochemical charac- teristics. Although there are no exploratory wells in deep water area of the research region, through the comparative analysis of geochemical data of several typical exploratory wells respectively from shallow water area in the basin, central depression belt margin in deep-water area of the basin and Site 1148 of deep sea drilling in the South China Sea Basin, it reveals that the tendency of the quality of source rocks becomes positive gradually from delta to bathyal environment, which then becomes negative as in deep oceanic environment. Owing to the lack of terrestrial organic matter input, the important controlling factors of Miocene marine source rocks in the Qiongdongnan Basin are ocean productivity and preservation conditions of organic matter. The element geochemistry data indicate that the tendency of the paleoproductivity and the preservation conditions of organic matter become positive as water depth increase from shallow area to bathyal area close to central depression belt. So it is speculated that there must exist high quality source rocks in the central depression area where the preservation conditions of organic matter are much better. Besides, in theory, in oxygen-poor zone of oceanic environment at the water depth 400–1 000 m, the preservation conditions of organic matter are well thus forming high-quality marine source rocks. The result- ing speculation, it is reasonable to consider that there are high hydrocarbon generation potential source rocks in bathyal environment of the Qiongdongnan Basin, especially at the water depth 400– 1 000 m.展开更多
The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies wh...The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.展开更多
The natural gas generation process is simulated by heating source rocks of the Yacheng Formation, including the onshore-offshore mudstone and coal with kerogens of Type II2-III in the Qiongdongnan Basin. The aim is to...The natural gas generation process is simulated by heating source rocks of the Yacheng Formation, including the onshore-offshore mudstone and coal with kerogens of Type II2-III in the Qiongdongnan Basin. The aim is to quantify the natural gas generation from the Yacheng Formation and to evaluate the geological prediction and kinetic parameters using an optimization procedure based on the basin modeling of the shallow-water area. For this, the hydrocarbons produced have been grouped into four classes(C1, C2, C3 and C4-6). The results show that the onset temperature of methane generation is predicted to occur at 110℃ during the thermal history of sediments since 5.3 Ma by using data extrapolation. The hydrocarbon potential for ethane, propane and heavy gaseous hydrocarbons(C4-6) is found to be almost exhausted at geological temperature of 200℃ when the transformation ratio(TR) is over 0.8, but for which methane is determined to be about 0.5 in the shallow-water area. In contrast, the end temperature of the methane generation in the deep-water area was over 300℃ with a TR over 0.8. It plays an important role in the natural gas exploration of the deep-water basin and other basins in the broad ocean areas of China. Therefore, the natural gas exploration for the deep-water area in the Qiongdongnan Basin shall first aim at the structural traps in the Ledong, Lingshui and Beijiao sags, and in the forward direction of the structure around the sags, and then gradually develop toward the non-structural trap in the deep-water area basin of the broad ocean areas of China.展开更多
The Deep Seismic Sounding( DSS) projects carried out from the 1970 s in the lower Yangtze region and its neighboring area were reviewed in this paper,then the basic wave group features of those wide angle reflection /...The Deep Seismic Sounding( DSS) projects carried out from the 1970 s in the lower Yangtze region and its neighboring area were reviewed in this paper,then the basic wave group features of those wide angle reflection / refraction record sections,and of the crustal structure are summarized. It shows that there were in total five clear wave groups on the record sections,which include the first arrival Pg,the reflection P1 from the bottom interface of the upper crust,the reflection P3 from the bottom interface of the middle crust,the strong reflection Pm from the Moho boundary,and the refraction Pn from uppermost mantle. In general,these phases are easily consistently traced and compared,despite some first arrivals being delayed or arriving earlier than normal due to the shallow sedimentary cover or bedrocks. In particular,in the Dabie Mountain region the seismic events of a few gathered shots always have weak reflection energy,are twisted,or exhibit disorganized waveforms, which could be attributed to the disruption variations of reflection depth,the broken Moho,and the discontinuity of the reflection boundary within crust. The regional crustal structures are composed of the upper,middle and lower crust,of which the middle and lower layers can be divided into two weak reflection ones. The crustal thickness of the North China and Yangtze platform are 30km- 36 km,and the Moho exhibits a flat geometry despite some local uplifts. The average pressure velocity in lower crust beneath this two tectonic area is 6. 7 ± 0. 3km / s. Nevertheless,beneath the Dabieshan area the crustal thickness is 32km- 41 km,the Moho bends down sharply andtakes an abrupt 4km- 7km dislocation in the vertical direction. The average pressure velocity in the lower crust beneath the Dabieshan area is 6. 8 ± 0. 2km / s.展开更多
To better understand the heterogeneity of deep-crust and mantle interfaces in the region of the Three Gorges, China, we used the Parker-Oldenburg iterative inversion method to invert existing Bouguer gravity data from...To better understand the heterogeneity of deep-crust and mantle interfaces in the region of the Three Gorges, China, we used the Parker-Oldenburg iterative inversion method to invert existing Bouguer gravity data from the Three Gorges area ( 1 : 500000) , a new gravity map of the Three Gorges Dam ( 1 : 200000) , and the results of deep seismic soundings. The inversion results show a Moho depth of 42 km be- tween Badong and Zigui and the depth of the B2 lower-crustal interface beneath the Jianghan Plain and sur- rounding areas at 21 -25 km. The morphology of crustal interfaces and the surface geology present an over- pass structure. The mid-crust beneath the Three Gorges Dam is approximately 9 km thick, which is the thin- nest in the Three Gorges area and may be related to the shallow low-density body near the Huangling anti- cline. The upper crust is seismogenic, and there is a close relationship between seismicity and the deep- crust and mantle interfaces. For example, the MS. 1 Zigui earthquake occurred where the gradients of the Moho and the B2 interface are the steepest, showing that deep structure has a very important effect on re- gional seismicity.展开更多
The northern Wuyi area,which is located in the northern Wuyi metallogenic belt,has superior mineralization conditions.The Pingxiang-Guangfeng-Jiangshan-Shaoxing fault(PSF)extends across the whole region regardless of ...The northern Wuyi area,which is located in the northern Wuyi metallogenic belt,has superior mineralization conditions.The Pingxiang-Guangfeng-Jiangshan-Shaoxing fault(PSF)extends across the whole region regardless of whether or how the PSF relates to the near-surface mineralization.We carried out an MT survey in the region and obtained a reliable 2D model of the crustal electrical structure to a depth of 30 km.In the resistivity model,we inferred that a continuous high conductivity belt that ranges from the shallow to deep crust is a part of the PSF.Then,we estimated the fluid content and pressure gradient to identify the deep sources of fluid as well as its pattern of motion pattern.Finally,we proposed a model for the deep metallogenic migration processes that combines geological data,fluid content data,pressure gradient data,and the subsurface resistivity model.The model analysis showed that the Jiangnan orogenic belt and the Cathaysia block formed the PSF during the process of com.The deep fluid migrated upward through the PSF to the shallow crust.Therefore,we believe that the PSF is an ore-forming fluid migration channel and that it laid the material basis for large-scale mineralization in the shallow crust.展开更多
It is a significant task to predict the solar activity for space weather and solar physics. All kinds of approaches have been used to forecast solar activities, and they have been applied to many areas such as the sol...It is a significant task to predict the solar activity for space weather and solar physics. All kinds of approaches have been used to forecast solar activities, and they have been applied to many areas such as the solar dynamo of simulation and space mission planning. In this paper, we employ the long-shortterm memory(LSTM) and neural network autoregression(NNAR) deep learning methods to predict the upcoming 25 th solar cycle using the sunspot area(SSA) data during the period of May 1874 to December2020. Our results show that the 25 th solar cycle will be 55% stronger than Solar Cycle 24 with a maximum sunspot area of 3115±401 and the cycle reaching its peak in October 2022 by using the LSTM method. It also shows that deep learning algorithms perform better than the other commonly used methods and have high application value.展开更多
BSR (Bottom Simulating Reflector) occurs widely in the strata since the late Miocene in the deep-water area of the northern continental slope of South China Sea (SCS). It is an important seismic reference mark whi...BSR (Bottom Simulating Reflector) occurs widely in the strata since the late Miocene in the deep-water area of the northern continental slope of South China Sea (SCS). It is an important seismic reference mark which identifies the gas hydrate and its distribution influenced by the tectonic movements. Single-point basin modeling was conducted using 473 points in the study area. To discuss the relationships between the tectonic subsidence and BSR, the volume and rate of tectonic subsidence in each geological time have been simulated. The results show that there are three tectonic accelerate subsidence processes in the study area since the late Miocene, especially since 1.8Ma the tectonic subsidence accelerates more apparently. Since the Late Miocene to Pleistocene, the rate of tectonic subsidence in deep-water underwent a transformation from weak to strong. The ratio of tectonic subsidence to the total subsidence was relatively high (65-70%). Through the superposition of the BSR developed areas and the contours of tectonic subsidence in this area, it was discovered that more than 80% of BSR tend to be distributed at the slope break or depression-uplift structural transfer zone and the average tectonic subsidence rate ranges from 70 m/Ma to 125 m/Ma.展开更多
In order to study the movement characteristics of groundwater in a deep mining area and solve the dispute of the distri- bution rule of hydro-chemical zoning which is contradicted by lixiviation water zoning in a hori...In order to study the movement characteristics of groundwater in a deep mining area and solve the dispute of the distri- bution rule of hydro-chemical zoning which is contradicted by lixiviation water zoning in a horizontal direction, we directed our attention to the source of deep groundwater, its seepage and hydro-chemical characteristics in a typical mining area. We used a neotectonic water-control theory, chemical and isotope methods, as well as a method for analyzing dynamic groundwater conditions. The results indicate that 1) Karst water in the deep and medium parts of this mining area is recharged by vertical leakage through neotectonic fractures rather than seepage along strata from subcrop parts or surrounding flows; 2) from surface to deep leakage paths, the variation in the types of chemical groundwater agrees with the normal lixiviation water distribution rule and the age of mixed groundwater increases; 3) the water-rich zones along neotectonic fractures correspond with water-diluted zones in a hori-zontal direction; 4) the leakage coefficient and water capacity of aquifers increases during the flow process of Karst water along the antidip direction (from west to east) and 5) Karst water in shallow mining areas forms a strong runoff belt along strikes and quickly dilutes the water from deep and medium mining areas. Overall, chemical and dynamic water characteristics actually agree with in terms of the entire consideration for differences in vertical leakage and abnormalities in the zone of water chemical distribution, along a horizontal runoff direction.展开更多
Urban Growth Models (UGMs) are very essential for a sustainable development of a city as they predict the future urbanization based on the present scenario. Neural Network based Cellular Automata models have proved to...Urban Growth Models (UGMs) are very essential for a sustainable development of a city as they predict the future urbanization based on the present scenario. Neural Network based Cellular Automata models have proved to predict the urban growth more close to reality. Recently, deep learning based techniques are being used for the prediction of urban growth. In this current study, urban growth of Chennai Metropolitan Area (CMA) of 2017 was predicted using Neural Network based Cellular Automata (NN-CA) model and Deep belief based Cellular Automata (DB-CA) model using 2010 and 2013 urban maps. Since the study area experienced congested type of urban growth, “Existing Built-Up” of 2013 alone was used as the agent of urbanization to predict urban growth in 2017. Upon validating, DB-CA model proved to be the better model, as it predicted 524.14 km2 of the study area as urban with higher accuracy (kappa co-efficient: 0.73) when compared to NN-CA model which predicted only 502.42 km2 as urban (kappa co-efficient: 0.71), while the observed urban cover of CMA in 2017 was 572.11 km2. This study also aimed at analyzing the effects of different types of neighbourhood configurations (Rectangular: 3 × 3, 5 × 5, 7 × 7 and Circular: 3 × 3) on the prediction output based on DB-CA model. To understand the direction and type of the urban growth, the study area was divided into five distance based zones with the State Secretariat as the center and entropy values were calculated for the zones. Results reveal that Chennai Corporation and its periphery experience congested urbanization whereas areas away from the Corporation boundary follow dispersed type of urban growth in 2017.展开更多
Petrological and geochemical studies of deep-derived enclaves from the Liuhe-Xiangduo area, eastern Tibet, showed that the enclaves involve five types of rocks, i.e., garnet diopsidite, garnet amphibolite, garnet horn...Petrological and geochemical studies of deep-derived enclaves from the Liuhe-Xiangduo area, eastern Tibet, showed that the enclaves involve five types of rocks, i.e., garnet diopsidite, garnet amphibolite, garnet hornblendite, amphibolite and hornblendite, whose main mineral assemblages are Grt+Di+Hbl, Grt+Pl+Hbl+Di, Grt+Hbl+Pl, Pl+Hbl, and Hbl+Bt, respectively. The enclaves exhibit typical crystalloblastic texture, and growth zones are well developed in garnet (Grt) in the enclaves. In view of major element geochemistry, the deep|derived enclaves are characterized by high MgO and FeO+*, ranging from {12.00%} to {12.30%} and {8.15%} to {10.94%}, respectively. The protolith restoration of metamorphic rocks revealed that the enclaves belong to ortho-metamorphic rocks. The REE abundances vary over a wide range, and ∑REE ranges from {53.39} to {129.04} μg/g. The REE patterns slightly incline toward the HREE side with weak LREE enrichment. The contents of Rb, Sr, and Ba range from {8.34} to 101μg/g, 165 to 1485 μg/g, and 105 to 721 μg/g, respectively. The primitive mantle-normalized spider diagrams of trace elements show obvious negative Nb, Ta, Zr and Hf anomalies. Sr-Nd isotopic compositions of the enclaves indicated that the potential source of deep-derived enclaves is similar to the depleted|mantle, and their {({}+{87}Sr/+{86}Sr)-i} ratios vary from {0.706314} to {0.707198}, {({}+{147}Nd/+{144}Nd)-i} ratios from {0.512947} to {0.513046}, and {ε-{Nd}(T)} values from {+7.0} to {+9.0}, respectively. The potential source of the enclaves is obviously different from the EM2-type mantle from which high-K igneous rocks stemmed (the host rocks), i.e., there is no direct genetic relationship between the enclaves and the host rocks. Deep-derived enclaves in the host rocks belong to mafic xenoliths, and those in the Liuhe-Xiangduo area, eastern Tibet, are some middle-lower crust ortho-metamorphic rocks which were accidentally captured at 20-50 km level by rapidly entrained high-temperature high-K magma, whose source is considered to be located at 50-km depth or so.展开更多
The relationships between crustal stretching and thinning,basin structure and petroleum geology in Baiyun deep-water area were analyzed using large area 3D seismic,gravity,magnetic,ocean bottom seismic(OBS),deep-water...The relationships between crustal stretching and thinning,basin structure and petroleum geology in Baiyun deep-water area were analyzed using large area 3D seismic,gravity,magnetic,ocean bottom seismic(OBS),deep-water exploration wells and integrated ocean drilling program(IODP).During the early syn-rifting period,deep-water area was a half-graben controlled by high angle faults influenced by the brittle extension of upper crust.In the mid syn-rifting period,this area was a broad-deep fault depression controlled by detachment faults undergone brittle-ductile deformation and differentiated extension in the crust.In the late syn-rifting period,this area experienced fault-sag transition due to saucer-shaped rheology change dominated by crustal ductile deformation.A broad-deep fault depression controlled by the large detachment faults penetrating through the crust is an important feature of deep-water basin.The study suggests that the broad-deep Baiyun sag provides great accommodation space for the development of massive deltaic-lacustrine deposition system and hydrocarbon source rocks.The differentiated lithospheric thinning also resulted in the different thermal subsidence during post-rifting period,and then controlled the development of continental shelf break and deep-water reservoir sedimentary environment.The high heat flow background caused by the strong thinning of lithosphere and the rise of mantle source resulted in particularities in the reservoir diagenesis,hydrocarbon generation process and accumulation of deep-water area in northern South China Sea.展开更多
Weather is a key factor affecting the control of air traffic.Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air trafficflow management.Curren...Weather is a key factor affecting the control of air traffic.Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air trafficflow management.Current researches mostly use traditional machine learning methods to extract features of weather scenes,and clustering algorithms to divide similar scenes.Inspired by the excellent performance of deep learning in image recognition,this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering(IDCEC),which uses the com-bination of the encoding layer and the decoding layer to reduce the dimensionality of the weather image,retaining useful information to the greatest extent,and then uses the combination of the pre-trained encoding layer and the clustering layer to train the clustering model of the similar scenes in the terminal area.Finally,term-inal area of Guangzhou Airport is selected as the research object,the method pro-posed in this article is used to classify historical weather data in similar scenes,and the performance is compared with other state-of-the-art methods.The experi-mental results show that the proposed IDCEC method can identify similar scenes more accurately based on the spatial distribution characteristics and severity of weather;at the same time,compared with the actualflight volume in the Guangz-hou terminal area,IDCEC's recognition results of similar weather scenes are con-sistent with the recognition of experts in thefield.展开更多
Taking the Dapingzhang copper-polymetallic deposit in Yunnan Province, China as the research object, the maximum entropy model was used to extract the mining information, and the mineral resource prediction model was ...Taking the Dapingzhang copper-polymetallic deposit in Yunnan Province, China as the research object, the maximum entropy model was used to extract the mining information, and the mineral resource prediction model was established by using the exploration data of the deposit and related regions in this area, so as to determine the prospecting prospect area in the study area. In this paper, the Jacknife analysis module of maximum entropy model is used to quantitatively rank the importance of 39 geochemical element variables, and finally obtain the prospecting prospect map of the study area. The research results show that the Dapingzhang mining area has the potential to find hidden ore in the deep and surrounding areas, and the northern and southern ends and western sides of the rock ore control structural belt in the eastern region of the mining area have good prospecting prospects. The research results provide an important basis for the deployment of follow-up exploration work in the study area, and the maximum entropy model has a good application effect in mineral resources exploration.展开更多
Parkinson's disease(PD)is a chronic progressive neurodegenerative disease.Deep brain stimulation(DBS)is an effective treatment for patients with advanced PD.There are many DBS targets for PD,including subthalamic ...Parkinson's disease(PD)is a chronic progressive neurodegenerative disease.Deep brain stimulation(DBS)is an effective treatment for patients with advanced PD.There are many DBS targets for PD,including subthalamic nucleus(STN),globus pallidus(GPi),meso-ventral thalamic nucleus(VIM),pontine peduncle nucleus(PPN),posterior subthalamic region(PSA)and zonation of undetermined zone(ZI).This paper summarizes the efficacy of each target in the treatment of PD with DBS,not only makes a systematic analysis and comparison of motor symptoms,but also makes a detailed description of the efficacy of non-motor symptoms,so as to provide a personalized treatment basis for PD patients to select appropriate target targets in DBS.展开更多
Deep geothermal resources mainly refer to the thermal energy stored in subsurface rocks and fluids therein at a depth of 3-10 km,which is a kind of renewable and sustainable clean energy unaffected by weather and seas...Deep geothermal resources mainly refer to the thermal energy stored in subsurface rocks and fluids therein at a depth of 3-10 km,which is a kind of renewable and sustainable clean energy unaffected by weather and seasonal changes.Large scale exploitation of the deep geothermal resources is of great significance to ensuring national energy security and achieving the“Carbon Peak and Carbon Neutrality”.Based on the latest terrestrial heat flow data,this paper estimated the potential of deep geothermal resources in the terrestrial areas of China,and the results show that the total amount of geothermal resources within 3e10 km under the Earth's surface in the terrestrial areas of China is 24.6×10^(15)GJ.In line with climate zones categorized,the geothermal resource proportion is 43.81%for severe cold regions,29.19%for cold regions,6.92%for mild regions,13.82%for hot summer and cold winter regions,and 6.26%for hot summer and warm winter regions.Statistics according to the burial depth range reveal that the resources within depth ranges of 3-5 km,5-7 km and 7-10 km under the Earth's surface are 4.3119×10^(15)GJ,6.37674×10^(15)GJ and 13.89594×10^(15)GJ respectively,showing an increasing trend of geothermal potential with increasing burial depth.The deep geothermal resources are mainly of medium-to-high temperature reserves,and the energy supply strategy can be optimized by combining the climate conditions and population distribution,as well as considering power generation.In regions of cold or severe cold climate,the geothermal resources may be applied to geothermal power generation and district heating in combination;in regions of hot summer and cold winter or mild climates,the resources can be used for geothermal power generation combined with cooling and heating;in regions of hot summer and warm winter climates,the resources may be applied to geothermal power generation combined with cooling and industrial and agricultural utilization.Exploitation of deep geothermal resources also can be combined with carbon dioxide sequestration,multi-mineral resources extraction and energy storage to realize comprehensive exploitation and utilization of various energy resources.It is suggested that theoretical technology research should be combined with pilot tests and field demonstrations,and large-scale economic exploitation of deep geothermal resources should be arranged in a coordinated manner,following the principles of overall planning and step-by-step implementation.展开更多
文摘This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions,employing a deep learning classification algorithm for speech signal analysis.In this study,speech samples are categorized for both training and testing purposes based on their geographical origin.Category 1 comprises speech samples from speakers outside of India,whereas Category 2 comprises live-recorded speech samples from Indian speakers.Testing speech samples are likewise classified into four distinct sets,taking into consideration both geographical origin and the language spoken by the speakers.Significantly,the results indicate a noticeable difference in gender identification accuracy among speakers from different geographical areas.Indian speakers,utilizing 52 Hindi and 26 English phonemes in their speech,demonstrate a notably higher gender identification accuracy of 85.75%compared to those speakers who predominantly use 26 English phonemes in their conversations when the system is trained using speech samples from Indian speakers.The gender identification accuracy of the proposed model reaches 83.20%when the system is trained using speech samples from speakers outside of India.In the analysis of speech signals,Mel Frequency Cepstral Coefficients(MFCCs)serve as relevant features for the speech data.The deep learning classification algorithm utilized in this research is based on a Bidirectional Long Short-Term Memory(BiLSTM)architecture within a Recurrent Neural Network(RNN)model.
基金supported by a project of Special Research on Land and Research Public Welfare Industry(201511029)founded by Ministry of Land and Resources of the People’s Republic of China
文摘The gold concentration areas in the northwestern Jiaodong Peninsula constituted an important gold metallogenetic region in Eastern China during the Mesozoic. The deep geological bodies' texture characteristic is important for exploring the resources thoroughly and understanding the metallogenic process. The detailed textures were revealed using high-resolution seismic profiles through the three major ore-controlling structures-Sanshandao fault zone, Jiaojia fault zone and Zhaoping fault zone. This study aims to establish a deep structural framework of this area. Based on their formation mechanism, the fault structures developed in the area can be divided into regional and local fault structures. The structural styles are characterised by superimposing their compressional, strike-slip and extensional multi-stage activities. The crust is cut by vertical structures corresponding to a left-lateral strike-slip fault system on the surface. Nearby these structures are the arc-shape structures formed by multi-stage magma intrusions into the upper crust. Bounded by the Tancheng–Lujiang and Muping–Jimo fault zones, the current Jiaodong block, developed a series of NE-trending strike-slip fault systems, was probably formed by the assemblage of several obliquely aligned blocks. The intensive magmatism and hydrothermal activity between the blocks induced large-scale mineralisation. It provides a new angle of view for understanding the cratonic destruction and large ore-concentration formed during the Mesozoic.
基金The Major State Basic Research Development Program (973 Program) under contract No. 2009CB219402
文摘Drilling wells reveal that the organic matter abundance of Miocene marine source rocks in shallow water area of the Qiongdongnan Basin is relatively low with poor hydrocarbon generation poten- tial. However, in some drilling wells of deep water area close to the central depression belt, Miocene marine source rocks with better organic matter abundance and hydrocarbon generation have been found, which have achieved better source rock standard based on the analysis of geochemical charac- teristics. Although there are no exploratory wells in deep water area of the research region, through the comparative analysis of geochemical data of several typical exploratory wells respectively from shallow water area in the basin, central depression belt margin in deep-water area of the basin and Site 1148 of deep sea drilling in the South China Sea Basin, it reveals that the tendency of the quality of source rocks becomes positive gradually from delta to bathyal environment, which then becomes negative as in deep oceanic environment. Owing to the lack of terrestrial organic matter input, the important controlling factors of Miocene marine source rocks in the Qiongdongnan Basin are ocean productivity and preservation conditions of organic matter. The element geochemistry data indicate that the tendency of the paleoproductivity and the preservation conditions of organic matter become positive as water depth increase from shallow area to bathyal area close to central depression belt. So it is speculated that there must exist high quality source rocks in the central depression area where the preservation conditions of organic matter are much better. Besides, in theory, in oxygen-poor zone of oceanic environment at the water depth 400–1 000 m, the preservation conditions of organic matter are well thus forming high-quality marine source rocks. The result- ing speculation, it is reasonable to consider that there are high hydrocarbon generation potential source rocks in bathyal environment of the Qiongdongnan Basin, especially at the water depth 400– 1 000 m.
基金supported by the Key Laboratory of Defense Science and Technology Foundation of Luoyang Electro-optical Equipment Research Institute(6142504200108)。
文摘The ever-changing battlefield environment requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned combat aerial vehicles(UCAVs) aim to integrate such advanced technologies while increasing the tactical capabilities of combat aircraft. As a research object, common UCAV uses the neural network fitting strategy to obtain values of attack areas. However, this simple strategy cannot cope with complex environmental changes and autonomously optimize decision-making problems. To solve the problem, this paper proposes a new deep deterministic policy gradient(DDPG) strategy based on deep reinforcement learning for the attack area fitting of UCAVs in the future battlefield. Simulation results show that the autonomy and environmental adaptability of UCAVs in the future battlefield will be improved based on the new DDPG algorithm and the training process converges quickly. We can obtain the optimal values of attack areas in real time during the whole flight with the well-trained deep network.
基金The Western Light Talent Culture Project of the Chinese Academy of Sciences under contract No.Y404RC1the National Petroleum Major Projects of China under contract No.2016ZX05026-007-005+2 种基金the Key Laboratory of Petroleum Resources Research Fund of the Chinese Academy of Sciences under contract No.KFJJ2013-04the Science and Technology Program of Gansu Province under contract No.1501RJYA006the Key Laboratory Project of Gansu Province of China under contract No.1309RTSA041
文摘The natural gas generation process is simulated by heating source rocks of the Yacheng Formation, including the onshore-offshore mudstone and coal with kerogens of Type II2-III in the Qiongdongnan Basin. The aim is to quantify the natural gas generation from the Yacheng Formation and to evaluate the geological prediction and kinetic parameters using an optimization procedure based on the basin modeling of the shallow-water area. For this, the hydrocarbons produced have been grouped into four classes(C1, C2, C3 and C4-6). The results show that the onset temperature of methane generation is predicted to occur at 110℃ during the thermal history of sediments since 5.3 Ma by using data extrapolation. The hydrocarbon potential for ethane, propane and heavy gaseous hydrocarbons(C4-6) is found to be almost exhausted at geological temperature of 200℃ when the transformation ratio(TR) is over 0.8, but for which methane is determined to be about 0.5 in the shallow-water area. In contrast, the end temperature of the methane generation in the deep-water area was over 300℃ with a TR over 0.8. It plays an important role in the natural gas exploration of the deep-water basin and other basins in the broad ocean areas of China. Therefore, the natural gas exploration for the deep-water area in the Qiongdongnan Basin shall first aim at the structural traps in the Ledong, Lingshui and Beijiao sags, and in the forward direction of the structure around the sags, and then gradually develop toward the non-structural trap in the deep-water area basin of the broad ocean areas of China.
基金funded by the Special Public Welfare Industry Research of China Earthquake Administration(201408023)Academician Chen Yong Workstation Special Funds of Yunnan Province and Natural Science Foundation of China(41374062,41174075)
文摘The Deep Seismic Sounding( DSS) projects carried out from the 1970 s in the lower Yangtze region and its neighboring area were reviewed in this paper,then the basic wave group features of those wide angle reflection / refraction record sections,and of the crustal structure are summarized. It shows that there were in total five clear wave groups on the record sections,which include the first arrival Pg,the reflection P1 from the bottom interface of the upper crust,the reflection P3 from the bottom interface of the middle crust,the strong reflection Pm from the Moho boundary,and the refraction Pn from uppermost mantle. In general,these phases are easily consistently traced and compared,despite some first arrivals being delayed or arriving earlier than normal due to the shallow sedimentary cover or bedrocks. In particular,in the Dabie Mountain region the seismic events of a few gathered shots always have weak reflection energy,are twisted,or exhibit disorganized waveforms, which could be attributed to the disruption variations of reflection depth,the broken Moho,and the discontinuity of the reflection boundary within crust. The regional crustal structures are composed of the upper,middle and lower crust,of which the middle and lower layers can be divided into two weak reflection ones. The crustal thickness of the North China and Yangtze platform are 30km- 36 km,and the Moho exhibits a flat geometry despite some local uplifts. The average pressure velocity in lower crust beneath this two tectonic area is 6. 7 ± 0. 3km / s. Nevertheless,beneath the Dabieshan area the crustal thickness is 32km- 41 km,the Moho bends down sharply andtakes an abrupt 4km- 7km dislocation in the vertical direction. The average pressure velocity in the lower crust beneath the Dabieshan area is 6. 8 ± 0. 2km / s.
基金supported by grant 201008001 from China Earthquake Ad-ministration201156085 from Institute of Seismology,China Earthquake Administration
文摘To better understand the heterogeneity of deep-crust and mantle interfaces in the region of the Three Gorges, China, we used the Parker-Oldenburg iterative inversion method to invert existing Bouguer gravity data from the Three Gorges area ( 1 : 500000) , a new gravity map of the Three Gorges Dam ( 1 : 200000) , and the results of deep seismic soundings. The inversion results show a Moho depth of 42 km be- tween Badong and Zigui and the depth of the B2 lower-crustal interface beneath the Jianghan Plain and sur- rounding areas at 21 -25 km. The morphology of crustal interfaces and the surface geology present an over- pass structure. The mid-crust beneath the Three Gorges Dam is approximately 9 km thick, which is the thin- nest in the Three Gorges area and may be related to the shallow low-density body near the Huangling anti- cline. The upper crust is seismogenic, and there is a close relationship between seismicity and the deep- crust and mantle interfaces. For example, the MS. 1 Zigui earthquake occurred where the gradients of the Moho and the B2 interface are the steepest, showing that deep structure has a very important effect on re- gional seismicity.
基金This research was jointly supported by the National Natural Science Foundation of China(Grant Nos.92062108,41574133,41630320,41864004)Geological Survey Project of China(Grant Nos.DD20190012,DD20160082,DD20221643)+1 种基金Innovation Fund Designated for Graduate Students of Jiangxi Province(Grant No.YC2019-B108)National Key Research and Development Program of China(Grant No.2016YFC0600201).
文摘The northern Wuyi area,which is located in the northern Wuyi metallogenic belt,has superior mineralization conditions.The Pingxiang-Guangfeng-Jiangshan-Shaoxing fault(PSF)extends across the whole region regardless of whether or how the PSF relates to the near-surface mineralization.We carried out an MT survey in the region and obtained a reliable 2D model of the crustal electrical structure to a depth of 30 km.In the resistivity model,we inferred that a continuous high conductivity belt that ranges from the shallow to deep crust is a part of the PSF.Then,we estimated the fluid content and pressure gradient to identify the deep sources of fluid as well as its pattern of motion pattern.Finally,we proposed a model for the deep metallogenic migration processes that combines geological data,fluid content data,pressure gradient data,and the subsurface resistivity model.The model analysis showed that the Jiangnan orogenic belt and the Cathaysia block formed the PSF during the process of com.The deep fluid migrated upward through the PSF to the shallow crust.Therefore,we believe that the PSF is an ore-forming fluid migration channel and that it laid the material basis for large-scale mineralization in the shallow crust.
基金supported by the National Natural Science Foundation of China under Grant numbers U2031202,U1731124 and U1531247the special foundation work of the Ministry of Science and Technology of the People’s Republic of China under Grant number 2014FY120300the 13th Five-year Informatization Plan of Chinese Academy of Sciences under Grant number XXH13505-04。
文摘It is a significant task to predict the solar activity for space weather and solar physics. All kinds of approaches have been used to forecast solar activities, and they have been applied to many areas such as the solar dynamo of simulation and space mission planning. In this paper, we employ the long-shortterm memory(LSTM) and neural network autoregression(NNAR) deep learning methods to predict the upcoming 25 th solar cycle using the sunspot area(SSA) data during the period of May 1874 to December2020. Our results show that the 25 th solar cycle will be 55% stronger than Solar Cycle 24 with a maximum sunspot area of 3115±401 and the cycle reaching its peak in October 2022 by using the LSTM method. It also shows that deep learning algorithms perform better than the other commonly used methods and have high application value.
基金supported by the National 973 Basic Research Program (Grant No. 2009CB219502)National Natural Science Foundation of China (Grant No. 41072084)
文摘BSR (Bottom Simulating Reflector) occurs widely in the strata since the late Miocene in the deep-water area of the northern continental slope of South China Sea (SCS). It is an important seismic reference mark which identifies the gas hydrate and its distribution influenced by the tectonic movements. Single-point basin modeling was conducted using 473 points in the study area. To discuss the relationships between the tectonic subsidence and BSR, the volume and rate of tectonic subsidence in each geological time have been simulated. The results show that there are three tectonic accelerate subsidence processes in the study area since the late Miocene, especially since 1.8Ma the tectonic subsidence accelerates more apparently. Since the Late Miocene to Pleistocene, the rate of tectonic subsidence in deep-water underwent a transformation from weak to strong. The ratio of tectonic subsidence to the total subsidence was relatively high (65-70%). Through the superposition of the BSR developed areas and the contours of tectonic subsidence in this area, it was discovered that more than 80% of BSR tend to be distributed at the slope break or depression-uplift structural transfer zone and the average tectonic subsidence rate ranges from 70 m/Ma to 125 m/Ma.
基金Projects 2007CB209400 supported by the National Basic Research Program of China, 5057409050634050 by the National Natural Science Foundation of China
文摘In order to study the movement characteristics of groundwater in a deep mining area and solve the dispute of the distri- bution rule of hydro-chemical zoning which is contradicted by lixiviation water zoning in a horizontal direction, we directed our attention to the source of deep groundwater, its seepage and hydro-chemical characteristics in a typical mining area. We used a neotectonic water-control theory, chemical and isotope methods, as well as a method for analyzing dynamic groundwater conditions. The results indicate that 1) Karst water in the deep and medium parts of this mining area is recharged by vertical leakage through neotectonic fractures rather than seepage along strata from subcrop parts or surrounding flows; 2) from surface to deep leakage paths, the variation in the types of chemical groundwater agrees with the normal lixiviation water distribution rule and the age of mixed groundwater increases; 3) the water-rich zones along neotectonic fractures correspond with water-diluted zones in a hori-zontal direction; 4) the leakage coefficient and water capacity of aquifers increases during the flow process of Karst water along the antidip direction (from west to east) and 5) Karst water in shallow mining areas forms a strong runoff belt along strikes and quickly dilutes the water from deep and medium mining areas. Overall, chemical and dynamic water characteristics actually agree with in terms of the entire consideration for differences in vertical leakage and abnormalities in the zone of water chemical distribution, along a horizontal runoff direction.
文摘Urban Growth Models (UGMs) are very essential for a sustainable development of a city as they predict the future urbanization based on the present scenario. Neural Network based Cellular Automata models have proved to predict the urban growth more close to reality. Recently, deep learning based techniques are being used for the prediction of urban growth. In this current study, urban growth of Chennai Metropolitan Area (CMA) of 2017 was predicted using Neural Network based Cellular Automata (NN-CA) model and Deep belief based Cellular Automata (DB-CA) model using 2010 and 2013 urban maps. Since the study area experienced congested type of urban growth, “Existing Built-Up” of 2013 alone was used as the agent of urbanization to predict urban growth in 2017. Upon validating, DB-CA model proved to be the better model, as it predicted 524.14 km2 of the study area as urban with higher accuracy (kappa co-efficient: 0.73) when compared to NN-CA model which predicted only 502.42 km2 as urban (kappa co-efficient: 0.71), while the observed urban cover of CMA in 2017 was 572.11 km2. This study also aimed at analyzing the effects of different types of neighbourhood configurations (Rectangular: 3 × 3, 5 × 5, 7 × 7 and Circular: 3 × 3) on the prediction output based on DB-CA model. To understand the direction and type of the urban growth, the study area was divided into five distance based zones with the State Secretariat as the center and entropy values were calculated for the zones. Results reveal that Chennai Corporation and its periphery experience congested urbanization whereas areas away from the Corporation boundary follow dispersed type of urban growth in 2017.
文摘Petrological and geochemical studies of deep-derived enclaves from the Liuhe-Xiangduo area, eastern Tibet, showed that the enclaves involve five types of rocks, i.e., garnet diopsidite, garnet amphibolite, garnet hornblendite, amphibolite and hornblendite, whose main mineral assemblages are Grt+Di+Hbl, Grt+Pl+Hbl+Di, Grt+Hbl+Pl, Pl+Hbl, and Hbl+Bt, respectively. The enclaves exhibit typical crystalloblastic texture, and growth zones are well developed in garnet (Grt) in the enclaves. In view of major element geochemistry, the deep|derived enclaves are characterized by high MgO and FeO+*, ranging from {12.00%} to {12.30%} and {8.15%} to {10.94%}, respectively. The protolith restoration of metamorphic rocks revealed that the enclaves belong to ortho-metamorphic rocks. The REE abundances vary over a wide range, and ∑REE ranges from {53.39} to {129.04} μg/g. The REE patterns slightly incline toward the HREE side with weak LREE enrichment. The contents of Rb, Sr, and Ba range from {8.34} to 101μg/g, 165 to 1485 μg/g, and 105 to 721 μg/g, respectively. The primitive mantle-normalized spider diagrams of trace elements show obvious negative Nb, Ta, Zr and Hf anomalies. Sr-Nd isotopic compositions of the enclaves indicated that the potential source of deep-derived enclaves is similar to the depleted|mantle, and their {({}+{87}Sr/+{86}Sr)-i} ratios vary from {0.706314} to {0.707198}, {({}+{147}Nd/+{144}Nd)-i} ratios from {0.512947} to {0.513046}, and {ε-{Nd}(T)} values from {+7.0} to {+9.0}, respectively. The potential source of the enclaves is obviously different from the EM2-type mantle from which high-K igneous rocks stemmed (the host rocks), i.e., there is no direct genetic relationship between the enclaves and the host rocks. Deep-derived enclaves in the host rocks belong to mafic xenoliths, and those in the Liuhe-Xiangduo area, eastern Tibet, are some middle-lower crust ortho-metamorphic rocks which were accidentally captured at 20-50 km level by rapidly entrained high-temperature high-K magma, whose source is considered to be located at 50-km depth or so.
基金Supported by the Science and Technology Project of CNOOC Ltd.(YXKY-2012-SHENHAI-01)China National Science and Technology Major Project(2011ZX05025-003+1 种基金 2016ZX05026-003)the National Natural Science Foundation of China(91128207)
文摘The relationships between crustal stretching and thinning,basin structure and petroleum geology in Baiyun deep-water area were analyzed using large area 3D seismic,gravity,magnetic,ocean bottom seismic(OBS),deep-water exploration wells and integrated ocean drilling program(IODP).During the early syn-rifting period,deep-water area was a half-graben controlled by high angle faults influenced by the brittle extension of upper crust.In the mid syn-rifting period,this area was a broad-deep fault depression controlled by detachment faults undergone brittle-ductile deformation and differentiated extension in the crust.In the late syn-rifting period,this area experienced fault-sag transition due to saucer-shaped rheology change dominated by crustal ductile deformation.A broad-deep fault depression controlled by the large detachment faults penetrating through the crust is an important feature of deep-water basin.The study suggests that the broad-deep Baiyun sag provides great accommodation space for the development of massive deltaic-lacustrine deposition system and hydrocarbon source rocks.The differentiated lithospheric thinning also resulted in the different thermal subsidence during post-rifting period,and then controlled the development of continental shelf break and deep-water reservoir sedimentary environment.The high heat flow background caused by the strong thinning of lithosphere and the rise of mantle source resulted in particularities in the reservoir diagenesis,hydrocarbon generation process and accumulation of deep-water area in northern South China Sea.
基金supported by the Fundamental Research Funds for the CentralUniversities under Grant NS2020045. Y.L.G received the grant.
文摘Weather is a key factor affecting the control of air traffic.Accurate recognition and classification of similar weather scenes in the terminal area is helpful for rapid decision-making in air trafficflow management.Current researches mostly use traditional machine learning methods to extract features of weather scenes,and clustering algorithms to divide similar scenes.Inspired by the excellent performance of deep learning in image recognition,this paper proposes a terminal area similar weather scene classification method based on improved deep convolution embedded clustering(IDCEC),which uses the com-bination of the encoding layer and the decoding layer to reduce the dimensionality of the weather image,retaining useful information to the greatest extent,and then uses the combination of the pre-trained encoding layer and the clustering layer to train the clustering model of the similar scenes in the terminal area.Finally,term-inal area of Guangzhou Airport is selected as the research object,the method pro-posed in this article is used to classify historical weather data in similar scenes,and the performance is compared with other state-of-the-art methods.The experi-mental results show that the proposed IDCEC method can identify similar scenes more accurately based on the spatial distribution characteristics and severity of weather;at the same time,compared with the actualflight volume in the Guangz-hou terminal area,IDCEC's recognition results of similar weather scenes are con-sistent with the recognition of experts in thefield.
文摘Taking the Dapingzhang copper-polymetallic deposit in Yunnan Province, China as the research object, the maximum entropy model was used to extract the mining information, and the mineral resource prediction model was established by using the exploration data of the deposit and related regions in this area, so as to determine the prospecting prospect area in the study area. In this paper, the Jacknife analysis module of maximum entropy model is used to quantitatively rank the importance of 39 geochemical element variables, and finally obtain the prospecting prospect map of the study area. The research results show that the Dapingzhang mining area has the potential to find hidden ore in the deep and surrounding areas, and the northern and southern ends and western sides of the rock ore control structural belt in the eastern region of the mining area have good prospecting prospects. The research results provide an important basis for the deployment of follow-up exploration work in the study area, and the maximum entropy model has a good application effect in mineral resources exploration.
基金Natural Science Foundation of Hainan Province (No.821RC682)。
文摘Parkinson's disease(PD)is a chronic progressive neurodegenerative disease.Deep brain stimulation(DBS)is an effective treatment for patients with advanced PD.There are many DBS targets for PD,including subthalamic nucleus(STN),globus pallidus(GPi),meso-ventral thalamic nucleus(VIM),pontine peduncle nucleus(PPN),posterior subthalamic region(PSA)and zonation of undetermined zone(ZI).This paper summarizes the efficacy of each target in the treatment of PD with DBS,not only makes a systematic analysis and comparison of motor symptoms,but also makes a detailed description of the efficacy of non-motor symptoms,so as to provide a personalized treatment basis for PD patients to select appropriate target targets in DBS.
基金supported by the Joint Petrochemical Fund project of National Natural Science Foundation of China”Deep Geological Processes and Resource Effects in the Basin”(Fund No.U20B6001).
文摘Deep geothermal resources mainly refer to the thermal energy stored in subsurface rocks and fluids therein at a depth of 3-10 km,which is a kind of renewable and sustainable clean energy unaffected by weather and seasonal changes.Large scale exploitation of the deep geothermal resources is of great significance to ensuring national energy security and achieving the“Carbon Peak and Carbon Neutrality”.Based on the latest terrestrial heat flow data,this paper estimated the potential of deep geothermal resources in the terrestrial areas of China,and the results show that the total amount of geothermal resources within 3e10 km under the Earth's surface in the terrestrial areas of China is 24.6×10^(15)GJ.In line with climate zones categorized,the geothermal resource proportion is 43.81%for severe cold regions,29.19%for cold regions,6.92%for mild regions,13.82%for hot summer and cold winter regions,and 6.26%for hot summer and warm winter regions.Statistics according to the burial depth range reveal that the resources within depth ranges of 3-5 km,5-7 km and 7-10 km under the Earth's surface are 4.3119×10^(15)GJ,6.37674×10^(15)GJ and 13.89594×10^(15)GJ respectively,showing an increasing trend of geothermal potential with increasing burial depth.The deep geothermal resources are mainly of medium-to-high temperature reserves,and the energy supply strategy can be optimized by combining the climate conditions and population distribution,as well as considering power generation.In regions of cold or severe cold climate,the geothermal resources may be applied to geothermal power generation and district heating in combination;in regions of hot summer and cold winter or mild climates,the resources can be used for geothermal power generation combined with cooling and heating;in regions of hot summer and warm winter climates,the resources may be applied to geothermal power generation combined with cooling and industrial and agricultural utilization.Exploitation of deep geothermal resources also can be combined with carbon dioxide sequestration,multi-mineral resources extraction and energy storage to realize comprehensive exploitation and utilization of various energy resources.It is suggested that theoretical technology research should be combined with pilot tests and field demonstrations,and large-scale economic exploitation of deep geothermal resources should be arranged in a coordinated manner,following the principles of overall planning and step-by-step implementation.