Spatial-temporal distribution and geochemistry of highly evolved Mesozoic granites in Great Xing’an Range,NE China:Discriminant criteria and geological significance

Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental data for highly evolved granitic intrusions from the Great Xing’an Range(GXR),NE China,to elucidate their discriminant criteria,spatial-temporal distribution,differentiation and geodynamic mecha-nism.Geochemical data of these highly evolved granites suggest that high w(SiO_(2))(>70%)and differentiation index(DI>88)could be quantified indicators,while strong Eu depletion,high TE_(1,3),lowΣREE and low Zr/Hf,Nb/Ta,K/Rb could only be qualitative indicators.Zircon U-Pb ages suggest that the highly evolved gran-ites in the GXR were mainly formed in Late Mesozoic,which can be divided into two major stages:Late Ju-rassic-early Early Cretaceous(162-136 Ma,peak at 138 Ma),and late Early Cretaceous(136-106 Ma,peak at 126 Ma).The highly evolved granites are mainly distributed in the central-southern GXR,and display a weakly trend of getting younger from northwest to southeast,meanwhile indicating the metallogenic potential of rare metals within the central GXR.The spatial-temporal distribution,combined with regional geological data,indicates the highly evolved Mesozoic granites in the GXR were emplaced in an extensional environ-ment,of which the Late Jurassic-early Early Cretaceous extension was related to the closure of the Mongol-Okhotsk Ocean and roll-back of the Paleo-Pacific Plate,while the late Early Cretaceous extension was mainly related to the roll-back of the Paleo-Pacific Plate.

Spatial-Temporal Distribution Characteristics and Limiting Factors of Medium-low Yield Farmland in Tianjin

[Objective] This paper aimed to understand the area change and distribu- tion of medium-low yield farmland, and offered basis to the improvement of mediumlow farmland and its increase of grain production in Tianjin. [Method] Based on the statistical date of Tianjin and its relevant counties and districts, the yield standard was set up to classify high-yield, medium-yield and low-yield farmland in Tianjin. The author analyzed area change of medium-low yield farmland in six agricultural counties and districts （including Jixian County, Wuqing District, Baodi District, Ninghe County, Jinghai County and Dagang district of Binghai New Area） from 1980 to 2010. [Result] The results showed that the average yield of grain rose from 2 445 kg/hm^2 in 1980 to 5 130 kg/hm^2 in 2010, increasing 109.82%. The area of mediumlow yield farmland was reduced from 291 250.13 hm^2 in 1985 to 76 489.87 hm^2 in 2010, coming down 74%. In Tianjin, the area of medium-low yield farmland of 2010 accounted for 19% of the total farmland, of which the ratios of medium-low yield farmland of Jinghai County, Jixian County, Dagang district of Binghai New Area, Wuqing District, Baodi District and Ninghe County were 43.12%, 18.59%, 17.23%, 14.01%, 7.05% and 0, respectively. Low soil nutrient content, drought and water shortage, as well as soil salinization were the main yield limiting factors to mediumlow yield farmland in Tianjin in 2010. [Conclusion] The countermeasures to improve the medium-low yield farmland were proposed, involving enhancing the investment of the government, strengthening the construction of water conservancy infrastructure, further improving the soil fertility, as well as saline and alkaline land, optimizing the farming system and planting drought and salt tolerance crops, etc.

Analysis on Features of Spatial and Temporal Distribution of Thunderstorm in Shanghai

Based in 11 daily weather observation station data in Shanghai from 1971 to 2008,a careful research and analysis on the features of thunderstorms spatial and temporal distribution and thunderstorm movement in Shanghai was carried out by using the statistical software of SAS,the method of Mann-Kendall test and wavelets. The results showed that the average annual numbers of thunderstorms days were 26.1,and inter-annual thunderstorm variability was obvious,the annual number of thunderstorm days had a decreasing trend,its value of decreasing days was about-0.418 5 d/10 a. Mann-Kendall test showed that there was an abrupt change in 2000. The seasonal variation of thunderstorm in Shanghai was explicit. The period from March to September was the season when thunderstorm occurred most frequently,about 64.9% of the thunderstorms in a year took place in summer. The results from wavelets analysis showed that the variation cycle period of the annual number of thunderstorms days was about 3,5,12 and 20 years.

Zonal distribution features of high frequency planetary waves in the oceans derived from satellite altimeter data

Based on TOPEX/Poseidon (T/P) and ERS-1 and 2 satellite altimeter data between October 1992 and December 2000, high frequency oscillations with periods less than 150 d are analyzed and their spatial distributions are described. The ratio, instead of the energy itself, of the energy corresponding to certain frequency band from power spectrum relative to the total energy in the 20～143 d range is analyzed. The results show that the period of the most energetic oscillations in this band increases with latitude from about 1 month near the tropics to about 4 months near 30°, in agreement with the latitudinal dependency of the phase speed of westward propagating long Rossby waves,which dominate the variability in those latitudes.As a result,the global spatial distributions of the period of the dominant oscillations are largely zonal, with relatively small differences between different ocean basins. It suggests that the oscillations with periods around 60 d are mainly associated with planetary Rossby waves except the often regarded as tidal aliasing.

Cytogenetic Mapping of Disease Resistance Genes and Analysis of Their Distribution Features on Chromosomes in Maize

Cytogenetic maps of four clusters of disease resistance genes were generated by ISH of the two RFLP markers tightly linked to and flanking each of maize resistance genes and the cloned resistance genes from other plant species onto maize chromosomes, combining with data published before. These genes include Helminthosporium turcium Pass resistance genes Ht1, Htn1 and Ht2, Helminthosporium maydis Nisik resistance genes Rhm1 and Rhm2, maize dwarf mosaic virus resistance gene Mdm1, wheat streak mosaic virus resistance gene Wsm1, Helminthosporium carbonum ULLstrup resistance gene Hml and the cloned Xanthomonas oryzae pv. Oryzae resistance gene Xa21 of rice, Cladosporium fulvum resistance genes Cf-9 and Cf-2.1 of tomato,and Pseudomonas syringae resistance gene RPS2 of Arabidopsis. Most of the tested disease resistance genes located on the four chromosomes, i.e., chromosomes1, 3, 6 and 8, and they closely distributed at the interstitial regions of these chromosomal long arms with percentage distances ranging 31.44(±3.72)-72.40(±3.25) except for genes Rhm1, Rhm2, Mdm1 and Wsm1 which mapped on the satellites of the short arms of chromosome6. It showed that the tested RFLP markers and genes were duplicated or triplicated in maize genome. Homology and conservation of disease resistance genes among species, and relationship between distribution features and functions of the genes were discussed. The results provide important scientific basis for deeply understanding structure and function of disease resistance genes and breeding in maize.

Distributional features of temperature and salinity in the southern Taiwan Strait and its adjacent sea areas in late summer, 1994

Based on the CTD data obtained in the southern Taiwan Strait and its adjacent areas in August and September of 1994, the distributional features of the temperature and salinity in the studied area have been analyzed in detail. The results are as follows: (1) There are two low temperature and high salinity regions in the nearshore area between Dongshan and Shantou and in the southeastern Taiwan Shoal, respectively, which may be caused by upwellings. (2) There exists a cold eddy in the northwestern sea area and a warm eddy with two high temperature cores in the eastern sea area of the Dongsha Islands, which are related to the anti-cyclonic turning of the seawater near the Dongsha Islands. (3) A westward high temperature and high salinity water tongue extends through the northern Luzon Strait and reaches the sea areas near the Dengsha Islands and southern Taiwan Strait.

Petroleum Hydrocarbon Distribution Features in Water and Sediment off Fujian Shore

This study on the distribution features of petroleum hydrocarbon in water and sediment off the Fujian shore using data obtained from the baseline research on oceanic contamination in Fujian showed that: during the research period, petroleum hydrocarbon concentrations in water varied from 5.77 μg/L to 37.28 μg/L, averaged 14.48 μg/L; was lower in the wet season than in the dry season; and was highest in the Minjiang Estuary and Jiulong Estuary in both seasons. The petroleum hydrocarbon concentrations in shore sediment varied from 14.48 mg/kg to 784.36 mg/kg, averaged 133.3 mg/kg, and was closely related to sediment types (granularity).

The Spatial-Temporal Distribution Patterns of Dyke Swarms in Central Asia and their Tectonic Significance: Case Studies in Eastern Tianshan and Western Junggar

Dykes are a special kind of intrusive rocks which were formed by deep magma intruded into the existing brittle fractures in the crust.Dykes swarms in different tectonic environments are very significant to re-construct the

CHANGING FEATURES AND TREND OF LIGHT INDUSTRY DISTRIBUTION IN NORTHEAST CHINA

Modern industry in northeast China started from light industry. From the end of 19th century to 1931 was the phase of initial development of light industry in northeast China. During this period, the development of light industry gave priority to grain processing industry. After occupying northeast China, Japanese vigorously developed heavy industry to meet the needs of munitions and paid more attention to raw materials and semi-finished articles industry for the purpose of the war. Light industry was impeded and developed slowly. After the founding of New China, large-scale economic construction took place in northeast and heavy industry received prior investment and equipment. Northeast region became the first heavy industry base through several five-year plans, the development of light industry made giant strides. The present features of light industry distribution are: difference of light industry distribution, similarity of light industry structure, and imbalance of light industry development.

Research on the Distributional Features of and Interrelationships Between the Dissolved Oxygen, Salinity, pH Value and Nutrient Salts in the Honghai Bay Waters

In this paper, the environmental factors are surveyed of the mariculture waters of the Honghai Bay from the late spring to the early summer (June) in 1998. The distributional features and variation laws of dissolved oxygen, salinity, pH value and nutrient salts in the sea water are expounded. Also discussed are their relationships between each other. The results show that the contents of dissolved oxygen and pH value in the sea water increase with the increasing temperature from north (except for No.15~17 stations) to south (expect for No.6 station). At the same time it is affirmed that photosynthesis is the major cause of the high contents of dissolved oxygen and pH value. And the nutrient salt shows a negative correlation with salinity. The total content of phytoplankton obviously increased with the reduction of nutrient salts from north to south.

Analysis of Temporal and Spatial Distribution and Large-Scale Circulation Features of Extreme Weather Events in Shanxi Province, China in Recent 30 Years

Extreme weather events such as persistent high temperatures, heavy rains or sudden cold waves in Shanxi Province in China have brought great losses and disasters to people’s production and life. It is of great practical significance to study the temporal and spatial distribution characteristics of extreme weather events and the circulation background field. We selected daily high temperature data (≥35°C), daily minimum temperature data and daily precipitation data (≥50 mm) from 109 meteorological stations in Shanxi Province, China from 1981 to 2010, then set the period in which the temperature is ≥35°C for more than 3 days as a high temperature extreme weather event, define the station in which 24 hour cumulative precipitation is ≥50 mm precipitation on a certain day (20 - 20 hours, Beijing time) as a rainstorm weather, and determine the cold air activity with daily minimum temperature dropped by more than 8°C for 24 hours, or decreased by 10°C for 48 h, and a daily minimum temperature of ≤4°C as a cold weather process. We statistically analyze the temporal and spatial characteristics and trends of high temperature, heavy rain and cold weather and the circulation background field. We count the number of extreme weather events such as persistent high temperatures, heavy rains and cold weather frosts in Shanxi, and analyze the temporal and spatial distribution characteristics, trends and general circulation background of extreme weather events. We analyze and find out the common features of the large-scale circulation background field in various extreme weather events. Through the study of the temporal and spatial distribution characteristics of extreme weather events in Shanxi, including persistent high temperature, heavy rain or sudden cold wave frost weather, we summarize the large-scale circulation characteristics of such extreme weather events. It will provide some reference for future related weather forecasting.

Comparative Study and Spatial-Temporal Distribution of Regolith and Rock Geochemical Data from Xingmeng-North China

1 Introduction Geochemical mapping at national and continental scales continues to present challenges worldwide due to variations in geologic and geotectonic units.Use of the proper sampling media can provide rich information on

Effect of geomorphologic features and climate change on vegetation distribution in the arid hot valleys of Jinsha River,Southwest China

Rapid change of climate in vertical and considerable geomorphologic features form a typical diversity and distribution of biota in mountain ecosystems,i.e.,the subalpine forest zone(SFZ),the valley savanna zone(VSZ),and the transition zone between them.The arid hot valley in the middle and lower reaches of Jinsha River,China represents a well target area to study distribution and the driving factors in these typical mountain ecosystems.Therefore,this study selects four sub-sample areas in the arid-hot valley to explore the distinctive changes of vegetation during 1990 to 2020,and their driving factors in the three different vegetation zones on spatiotemporal scales.On the spatial scale,the Moran’s index was applied to identify the transition zone between the SFZ and the VSZ.Results show that the VSZ at low altitudes(less than 600-1000 m from the valley bottom)is mainly affected by geomorphologic features,especially the slope aspect.With increase in altitude,the climate factors(e.g.,humidity,temperature,etc.)play a more significant role in the development of the SFZ,while the effect of geomorphologic features gradually weakens.On the time scale,The SFZ at higher altitudes experienced more rapid changes in temperature(temperature increase of 1.41°C over the last 60 years)than the VSZ at lower altitudes(temperature increase of 0.172°C over the past 60 years).It caused the forest cover increase faster than that of savanna grassland.Humidity and heat conditions are altered by topography and climate conditions,which shapes the development and physiology of plants as they adapt to the different climatic zones.Furthermore,according to the driving factors(geomorphologic and climate factors)of vegetation distribution found in this study,it suggests that suitable tree species should be planted in the transition zone to evolve into the forest zone and making the forest zone to recover from high to low altitudes gradually.

Mesozoic Volcanic-Intrusive Complexes in the Coastal Area of Southeastern Zhejiang Province: Their Features, Petrogenesis and Distribution Pattern

On the basis of previous studies and by means of field geological, remote sensing, petrographical,mineralogical, petrochemical and geochemical investigations, the authors studied the temporal-spatial distribu-tion of the regional structures, volcanic structures and products of volcanic activity in the coastal area ofsoutheastern Zhejiang. On the basis and through a systematic comparison of the products of magmatism in thearea, it is considered that there exists a compsite volcanic structural belt composed of linear and circular struc-tures and it has been demonstrated that there exist volcanic intrusive complexes--'trinity' composed of vol-canic, subvolcanic and plutonic rocks. It is suggested that the volcanic intrusive complexes in the area belong tothe typical syntexis series and that its materials were derived from a mixed source of crust and mantle.

Statistical study on the spatial - temporal distribution features of the arctic sea ice extent

On the basis of the arctic monthly mean sea ice extent data set during 1953-1984, the arctic region is divided into eight subregions,and the analyses of empirical orthogonal functions, power spectrum and maximum entropy spectrum are made to indentify the major spatial and temporal features of the sea ice fluctuations within 32-year period. And then, a brief appropriate physical explanation is tentatively suggested. The results show that both seasonal and non-seasonal variations of the sea ice extent are remarkable, and iis mean annual peripheral positions as well as their interannu-al shifting amplitudes are quite different among all subregions. These features are primarily affected by solar radiation, o-cean circulation, sea surface temperature and maritime-continental contrast, while the non-seasonal variations are most possibly affected by the cosmic-geophysical factors such as earth pole shife, earth rotation oscillation and solar activity.

Feature Extraction Method Based on Pseudo-Wigner-Ville Distribution for Rotational Machinery in Variable Operating Conditions

In the case of fault diagnosis for roller bearings, the conventional diagnosis approaches by using the time interval of energy impacts in time-frequency distribution or the pass-frequencies are based on the assumption that machinery operates under a constant rotational speed. However, when the rotational speed varies in the broader range, the pass-frequencies vary with the change of rotational speed and bearing faults cannot be identified by the interval of impacts. Researches related to automatic diagnosis for rotational machinery in variable operating conditions were quite few. A novel automatic feature extraction method is proposed based on a pseudo-Wigner-Ville distribution （PWVD） and an extraction of symptom parameter （SP）. An extraction method for instantaneous feature spectrum is presented using the relative crossing information （RCI） and sequential inference approach, by which the feature spectrum from time-frequency distribution can be automatically, sequentially extracted. The SPs are considered in the frequency domain using the extracted feature spectrum to identify among the conditions of a machine. A method to obtain the synthetic symptom parameter is also proposed by the least squares mapping （LSM） technique for increasing the diagnosis sensitivity of SP. Practical examples of diagnosis for bearings are given in order to verify the effectiveness of the proposed method. The verification results show that the features of bearing faults, such as the outer-race, inner-race and roller element defects have been effectively extracted, and the proposed method can be used for condition diagnosis of a machine under the variable rotational speed.

Boosting Adversarial Training with Learnable Distribution

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural networks.Adversarial training is one of the most potent methods to defend against adversarial attacks.However,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial training.This paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture model.The distribution centroid is built to classify samples and constrain the distribution of the sample features.The natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the model.The proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial training.This algorithm gradually increases the accuracy and robustness of the model by scaling perturbation.Finally,the proposed method outputs the predicted labels and the distance between the sample and the distribution centroid.The distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model defense.The effectiveness of the proposed method is demonstrated through comprehensive experiments.

Hyperspectral remote sensing identification of marine oil emulsions based on the fusion of spatial and spectral features

Marine oil spill emulsions are difficult to recover,and the damage to the environment is not easy to eliminate.The use of remote sensing to accurately identify oil spill emulsions is highly important for the protection of marine environments.However,the spectrum of oil emulsions changes due to different water content.Hyperspectral remote sensing and deep learning can use spectral and spatial information to identify different types of oil emulsions.Nonetheless,hyperspectral data can also cause information redundancy,reducing classification accuracy and efficiency,and even overfitting in machine learning models.To address these problems,an oil emulsion deep-learning identification model with spatial-spectral feature fusion is established,and feature bands that can distinguish between crude oil,seawater,water-in-oil emulsion(WO),and oil-in-water emulsion(OW)are filtered based on a standard deviation threshold–mutual information method.Using oil spill airborne hyperspectral data,we conducted identification experiments on oil emulsions in different background waters and under different spatial and temporal conditions,analyzed the transferability of the model,and explored the effects of feature band selection and spectral resolution on the identification of oil emulsions.The results show the following.(1)The standard deviation–mutual information feature selection method is able to effectively extract feature bands that can distinguish between WO,OW,oil slick,and seawater.The number of bands was reduced from 224 to 134 after feature selection on the Airborne Visible Infrared Imaging Spectrometer(AVIRIS)data and from 126 to 100 on the S185 data.(2)With feature selection,the overall accuracy and Kappa of the identification results for the training area are 91.80%and 0.86,respectively,improved by 2.62%and 0.04,and the overall accuracy and Kappa of the identification results for the migration area are 86.53%and 0.80,respectively,improved by 3.45%and 0.05.(3)The oil emulsion identification model has a certain degree of transferability and can effectively identify oil spill emulsions for AVIRIS data at different times and locations,with an overall accuracy of more than 80%,Kappa coefficient of more than 0.7,and F1 score of 0.75 or more for each category.(4)As the spectral resolution decreasing,the model yields different degrees of misclassification for areas with a mixed distribution of oil slick and seawater or mixed distribution of WO and OW.Based on the above experimental results,we demonstrate that the oil emulsion identification model with spatial–spectral feature fusion achieves a high accuracy rate in identifying oil emulsion using airborne hyperspectral data,and can be applied to images under different spatial and temporal conditions.Furthermore,we also elucidate the impact of factors such as spectral resolution and background water bodies on the identification process.These findings provide new reference for future endeavors in automated marine oil spill detection.

The abundance,distribution,and enrichment mechanism of harmful trace elements in coals from Guizhou,Southwestern China

Coal seams can enrich a variety of harmful trace elements under specific geological conditions.The spatial distribution of harmful trace elements in coal is extremely uneven,and the distribution characteristics of each element content are different.The harmful elements released in the process of coal mining and utilization will cause serious harm to the environment and the human body.It is of great resource significance to study the geochemistry of coal that affects the enrichment and distribution characteristics of harmful trace elements.Based on the domestic and foreign literature on coal geochemistry in Guizhou published by previous investigators,this study counted 1097 sample data from 23 major coal-producing counties in Guizhou Province,systematically summarized the relevant research results of harmful trace elements in the coal of Guizhou,and revealed the overall distribution and enrichment characteristics of harmful trace elements in the coal of Guizhou.The results show that the average contents of Cd,Pb,Se,Cu,Mo,U,V,As,Hg,and Cr in coal of Guizhou are higher than those in Chinese coal and world coal.A variety of harmful trace elements in the coal of Guizhou have high background values,especially in Liupanshui,Xingyi and Qianbei coalfield.The enrichment of various harmful trace elements in the Late Permian coal in Guizhou is mainly related to the combined action of various geological and geochemical factors.The supply of terrigenous debris and sedimentary environment may be the basic background of the enrichment of harmful elements in western Guizhou,while low-temperature hydrothermal activity and volcanic ash deposition may be the main reasons for the enrichment of harmful elements in southwestern Guizhou.

Human Visual Attention Mechanism-Inspired Point-and-Line Stereo Visual Odometry for Environments with Uneven Distributed Features

Visual odometry is critical in visual simultaneous localization and mapping for robot navigation.However,the pose estimation performance of most current visual odometry algorithms degrades in scenes with unevenly distributed features because dense features occupy excessive weight.Herein,a new human visual attention mechanism for point-and-line stereo visual odometry,which is called point-line-weight-mechanism visual odometry(PLWM-VO),is proposed to describe scene features in a global and balanced manner.A weight-adaptive model based on region partition and region growth is generated for the human visual attention mechanism,where sufficient attention is assigned to position-distinctive objects(sparse features in the environment).Furthermore,the sum of absolute differences algorithm is used to improve the accuracy of initialization for line features.Compared with the state-of-the-art method(ORB-VO),PLWM-VO show a 36.79%reduction in the absolute trajectory error on the Kitti and Euroc datasets.Although the time consumption of PLWM-VO is higher than that of ORB-VO,online test results indicate that PLWM-VO satisfies the real-time demand.The proposed algorithm not only significantly promotes the environmental adaptability of visual odometry,but also quantitatively demonstrates the superiority of the human visual attention mechanism.