We are evaluating dryland cotton production in Martin County, Texas, measuring cotton lint yield per unit of rainfall. Our goal is to collect rainfall data per 250 - 400 ha. Upon selection of a rainfall gauge, we real...We are evaluating dryland cotton production in Martin County, Texas, measuring cotton lint yield per unit of rainfall. Our goal is to collect rainfall data per 250 - 400 ha. Upon selection of a rainfall gauge, we realized that the cost of using, for example, a tipping bucket-type rain gauge would be too expensive and thus searched for an alternative method. We selected an all-in-one commercially available weather station;hereafter, referred to as a Personal Weather Station (PWS) that is both wireless and solar powered. Our objective was to evaluate average measurements of rainfall obtained with the PWS and to compare these to measurements obtained with an automatic weather station (AWS). For this purpose, we installed four PWS deployed within 20 m of the Plant Stress and Water Conservation Meteorological Tower that was used as our AWS, located at USDA-ARS Cropping Systems Research Laboratory, Lubbock, TX. In addition, we measured and compared hourly average values of short-wave irradiance (R<sub>g</sub>), air temperature (T<sub>air</sub>) and relative humidity (RH), and wind speed (WS), and calculated values of dewpoint temperature (T<sub>dew</sub>). This comparison was done over a 242-day period (1 October 2022-31 May 2023) and results indicated that there was no statistical difference in measurements of rainfall between the PWS and AWS. Hourly average values of R<sub>g</sub> measured with the PWS and AWS agreed on clear days, but PWS measurements were higher on cloudy days. There was no statistical difference between PWS and AWS hourly average measurements of T<sub>air</sub>, RH, and calculated T<sub>dew</sub>. Hourly average measurements of R<sub>g</sub> and WS were more variable. We concluded that the PWS we selected will provide adequate values of rainfall and other weather variables to meet our goal of evaluating dryland cotton lint yield per unit rainfall.展开更多
This study is thefirst attempt to assess the nature of the soil,especially on the western side of the Porali Plain in Balochistan;a new emerging agriculture hub,using weathering and pollution indices supplemented by mu...This study is thefirst attempt to assess the nature of the soil,especially on the western side of the Porali Plain in Balochistan;a new emerging agriculture hub,using weathering and pollution indices supplemented by multi-variate analysis based on geochemical data.The outcomes of this study are expected to help farmers in soil manage-ment and selecting suitable crops for the region.Twenty-five soil samples were collected,mainly from the arable land of the Porali Plain.After drying and coning-quarter-ing,soil samples were analyzed for major and trace ele-ments using the XRF technique;sieving and hydrometric methods were employed for granulometric analysis.Esti-mated data were analyzed using Excel,SPSS,and Surfer software to calculate various indices,correlation matrix,and spatial distribution.The granulometric analysis showed that 76%of the samples belonged to loam types of soil,12%to sand type,and 8%to silt type.Weathering indices:CIA,CIW,PIA,PWI,WIP,CIX,and ICV were calculated to infer the level of alteration.These indices reflect mod-erate to intense weathering;supported by K_(2)O/AI_(2)O_(3),Rb/K_(2)O,Rb/Ti,and Rb/Sr ratios.Assessment of the geo-ac-cumulation and Nemerow Pollution indices pinpoint rela-tively high concentrations of Pb,Ni,and Cr concentration in the soils.The correlation matrix and Principal Compo-nent Analysis show that the soil in this study area is mainly derived from the weathering of igneous rocks of Bela Ophiolite(Cretaceous age)and Jurassic sedimentary rocks of Mor Range having SEDEX/MVT type mineralization.Weathering may result in the undesirable accumulation of certain trace elements which adversely affects crops.展开更多
Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural languag...Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.展开更多
Rock and geotechnical engineering investigations involve drilling holes in ground with or without retrieving soil and rock samples to construct the subsurface ground profile.On the basis of an actual soil nailing dril...Rock and geotechnical engineering investigations involve drilling holes in ground with or without retrieving soil and rock samples to construct the subsurface ground profile.On the basis of an actual soil nailing drilling for a slope stability project in Hong Kong,this paper further develops the drilling process monitoring(DPM)method for digitally profiling the subsurface geomaterials of weathered granitic rocks using a compressed airflow driven percussive-rotary drilling machine with down-the-hole(DTH)hammer.Seven transducers are installed on the drilling machine and record the chuck displacement,DTH rotational speed,and five pressures from five compressed airflows in real-time series.The mechanism and operations of the drilling machine are elaborated in detail,which is essential for understanding and evaluating the drilling data.A MATLAB program is developed to automatically filter the recorded drilling data in time series and classify them into different drilling processes in sub-time series.These processes include penetration,push-in with or without rod,pull-back with or without rod,rod-tightening and rod-untightening.The drilling data are further reconstructed to plot the curve of drill-bit depth versus the net drilling time along each of the six drillholes.Each curve is found to contain multiple linear segments with a constant penetration rate,which implies a zone of homogenous geomaterial with different weathering grades.The effect from fluctuation of the applied pressures is evaluated quantitatively.Detailed analyses are presented for accurately assess and verify the underground profiling and strength in weathered granitic rock,which provided the basis of using DPM method to confidently assess drilling measurements to interpret the subsurface profile in real time.展开更多
Wooden buildings play a very important role in China’s construction and landscape architecture industry.In order to explore the weathering characteristics of the surface layer of landscape wooden buildings,the main c...Wooden buildings play a very important role in China’s construction and landscape architecture industry.In order to explore the weathering characteristics of the surface layer of landscape wooden buildings,the main causes of weathering were analyzed on the basis of summarizing the common types of weathering characterization.The results showed that the weathering characterization was mainly reflected in the surface defects of wood structures,such as cracking,discoloration,peeling,wind erosion wear,and so on.The coating technology on the surface of constructions was the main artificial factor affecting the surface defects of constructions.In the case of similar surface decoration conditions,sunlight and moisture were the main natural factors affecting the weathering of wooden buildings,which will promote the process of weathering.展开更多
Weathering has always been a concerned around the world,as the first and most important step in the global cycle of elements,which leads to the fractionation of isotopes on the scale of geological age.The Middle Ordov...Weathering has always been a concerned around the world,as the first and most important step in the global cycle of elements,which leads to the fractionation of isotopes on the scale of geological age.The Middle Ordovician Majiagou Formation in Daniudi area of the Ordos Basin had experienced weathering for>130 Myr.Through thin section observation,major and trace element analysis,carbon,oxygen,and magnesium isotopes composition analysis,the dolomitization modes and weathering of ancient dolo-mite in Daniudi area were analyzed in detail.The results showed that the Sabkha and brine-reflux dolomitization modes had developed,and the Mg isotopes in different layers of the karst crust were fractionated by various factors.The vertical vadose zone was affected by weathering,the Mg isotope of dolomite(δ^(26)Mgdol)showed a downward decreasing trend;the horizontal underflow zone was controlled by diagenesis and formation fluid,δ^(26)Mgdol showed a vertical invariance and negative;the main reason for Mg isotope fractionation in the deep slow-flow zone was the brine-reflux dolomitization mode during early burial period,which showed a vertical downward increase.Finally,the Mg isotope characteristic data of the ancient weathering crust were provided and the process of Mg isotope frac-tionationinthekarstcrust was explained.展开更多
Because of the cementation inherited from the parent rock,weathered granitic soil is usually susceptible to disturbance,which poses considerable challenges for laboratory characterization.The cone penetration test wit...Because of the cementation inherited from the parent rock,weathered granitic soil is usually susceptible to disturbance,which poses considerable challenges for laboratory characterization.The cone penetration test with pore pressure measurements has long been known for its reliability in site investigations and stratigraphic profiling.However,although extensive piezocone test results and experience are available for sedimentary soil,similar advances are yet to be made for weathered granitic soil.Moreover,the experience from sedimentary soil may not be directly applicable to weathered profiles because of the essentially different natures of the two types of geomaterials.This study performs seismic piezocone tests in a weathered granitic profile comprising residual granitic soil,completely weathered granite,and highly weathered granite.Pore pressure is measured at both the cone mid-face and the shoulder,and the effects of penetrometer size and penetration rate are considered.A series of updated soil behavior type charts is proposed to interpret the test results,thereby allowing the effect of weathering to be evaluated.This paper offers an important extension to the sparse data on the in situ responses of weathered materials.展开更多
Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable...Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.展开更多
The middle Eocene climatic optimum(MECO,ca.-42 Ma)is a key time period for understanding Cenozoic cooling of the global climate.Still,midlatitude terrestrial records of climate evolution during MEcO epoch are rare.In ...The middle Eocene climatic optimum(MECO,ca.-42 Ma)is a key time period for understanding Cenozoic cooling of the global climate.Still,midlatitude terrestrial records of climate evolution during MEcO epoch are rare.In this study,continuous high-resolution record of shale sediments in mid-Eocene Shahejie Formation(MES shales)in the Bohai Bay Basin were performed with major-element and wavelet analysis.The midlatitude paleoweathering and paleoclimatic evolution during MEcO epoch were analyzed in this study.The MES shales experienced weak-moderate paleoweathering under a subtropical monsoon paleoclimate with mean annual temperature of 8.3-12.9℃ and mean annual precipitation of 685-1100 mm/yr.The MES shales record a mixed provenance involving intermediate igneous rocks,and low compositional maturity.The nutrient-rich environment led to enrichment in organic matter in the MES shales.Wavelet analysis revealed good periodicity about the paleoclimate and weathering during MECO epoch.In the stage I of MES shales depositional process,the paleolake was high in nutrients,and the MES shales experienced high chemical weathering due to a relatively warmer and more humid climate.In contrast,the climate in stage II was relatively cold and dry,and the maturity of the MES shales was relatively high during this stage,suggesting a relatively stable tectonic background.This work provides more terrestrial records of MEco epoch for midlatitude region,and is benefit for better understanding of the palaeoenvironment when MES shales formed.The implication of organic matters enrichment in this study is meaningful for the shale oil/gas exploration in Nanpu Sag.展开更多
The bedrock weathered crust in front of the Altun Mountains in the Qaidam Basin,western China,is different from others because this is a salt-lake basin,where saline water fluid infiltrates and is deposited in the ove...The bedrock weathered crust in front of the Altun Mountains in the Qaidam Basin,western China,is different from others because this is a salt-lake basin,where saline water fluid infiltrates and is deposited in the overlying strata.A large amount of gypsum infills the bedrock weathered crust,and this has changed the pore structure.Using core observation,polarized light microscopy,electron probe,physical property analysis and field emission scanning electron microscopy experiments,the characteristics of the weathered bedrock have been studied.There are cracks and a small number of dissolved pores in the interior of the weathered crust.Matrix micropores are widely developed,especially the various matrix cracks formed by tectonics and weathering,as well as the stress characteristics of small dissolved pores,and physical properties such as porosity and permeability.This‘dual structure’developed in the bedrock is important for guiding the exploration of the lake basin bedrock for natural gas.展开更多
Surfactants were proposed to be added into magnesium sulfate solution to improve the leaching process of weathered crust elution-deposited rare earth ores(WREOs).Effects of surfactants and their concentration on the s...Surfactants were proposed to be added into magnesium sulfate solution to improve the leaching process of weathered crust elution-deposited rare earth ores(WREOs).Effects of surfactants and their concentration on the seepage of leaching solutions and the leaching efficiency of rare earth(RE)and aluminum(Al)were investigated,and the leaching kinetics,the mass transfer process,the adhesion work and the adhesion work reduction factor were analyzed to reveal its strengthening leaching mechanism.The results show that cetyltrimethylammonium bromide(CTAB)has a better strengthening effect on the leaching process than dodecyl trimethyl ammonium bromide(DTAB),sodium dodecyl sulfate(SDS),sodium oleate and oleic acid.In the presence of 0.04%CTAB in 0.2 mol/L solution,the permeability coefficient of WREOs increases from 0.945×10^(-5)to 1.640×10^(-5)cm·s^(-1),and the leaching efficiency of RE increases from 80%to 90%,confirming the promotion of surfactants on the leaching process of WREOs.Kinetic analysis shows that the leaching process conforms to the inner diffusion control model,and the leaching kinetics equations of RE and Al related to CTAB content are obtained.Mass transfer discussion shows a smaller height equivalent to theoretical plate(HETP)of RE and Al at CTAB content of 0.04%,suggesting the higher mass transfer efficiency here.According to the interfacial properties of leaching solutions,the calculated adhesion work and the adhesion work reduction factor further demonstrate the strengthening leaching effect of CTAB on the leaching process of WREOs.展开更多
Solar stills are considered an effective method to solve the scarcity of drinkable water.However,it is still missing a way to forecast its production.Herein,it is proposed that a convenient forecasting model which jus...Solar stills are considered an effective method to solve the scarcity of drinkable water.However,it is still missing a way to forecast its production.Herein,it is proposed that a convenient forecasting model which just needs to input the conventional weather forecasting data.The model is established by using machine learning methods of random forest and optimized by Bayesian algorithm.The required data to train the model are obtained from daily measurements lasting9 months.To validate the accuracy model,the determination coefficients of two types of solar stills are calculated as 0.935and 0.929,respectively,which are much higher than the value of both multiple linear regression(0.767)and the traditional models(0.829 and 0.847).Moreover,by applying the model,we predicted the freshwater production of four cities in China.The predicted production is approved to be reliable by a high value of correlation(0.868)between the predicted production and the solar insolation.With the help of the forecasting model,it would greatly promote the global application of solar stills.展开更多
A mesoscale convective system(MCS)is an organized cluster of thunderstorms known to be the most important convective mode in causing disastrous high-impact weather,such as heavy rainfall,hail,damaging winds,and tornad...A mesoscale convective system(MCS)is an organized cluster of thunderstorms known to be the most important convective mode in causing disastrous high-impact weather,such as heavy rainfall,hail,damaging winds,and tornadoes.The small spatial scale and fast temporal evolution of MCSs make their observation and prediction very challenging.East Asia is home to the world’s most prominent monsoon,setting the stage for various severe convective weather events.MCSs and their associated high-impact weather have long been critical issues of concern;as such,their research efforts are valued by governments in East Asia.展开更多
Both CT and Avizo software were used to explore the effect of particle gradation on the evolution characteristics of pore structure and seepage paths in weathered crust elution-deposited rare earth ores during leachin...Both CT and Avizo software were used to explore the effect of particle gradation on the evolution characteristics of pore structure and seepage paths in weathered crust elution-deposited rare earth ores during leaching.The results showed that the pore areas in four kinds of ore samples before leaching were mainly concentrated in 10^(4)–10^(7)μm^(2),whose pore quantities accounted for 96.89%,94.94%,90.48%,and 89.45%,respectively,while the corresponding pore volume only accounted for 30.74%,14.55%,7.58%,and 2.84%of the total pore volume.With the decrease of fractal dimension,the average pore throat length increased,but pore throat quantities,the average pore throat radius and coordination number decreased.Compared with that before leaching,the change degree of pore structure during leaching increased with the fractal dimension decreasing.For example,the reduction rate of the average coordination number of ore samples was 14.36%,21.30%,28.00%,and 32.90%,respectively.Seepage simulation results indicated that seepage paths were uniformly distributed before leaching while the streamline density and seepage velocity increased with the fractal dimension decreasing.Besides,the phenomenon of the streamline interruption gradually reduced during leaching while preferential seepage got more obvious with the decrease of the fractal dimension.展开更多
Weathering crust reservoirs have obvious vertical zonation,which is the focus of weathering crust reservoir research,but there is a lack of quantitative characterization indexes.To achieve the quantitative characteriz...Weathering crust reservoirs have obvious vertical zonation,which is the focus of weathering crust reservoir research,but there is a lack of quantitative characterization indexes.To achieve the quantitative characterization of granite weathering crust reservoir and provide the basis for oil exploration of granite weathering crust buried hill reservoir,in this paper,the vertical zonation of granite weathering crust reservoir is quantitatively divided by testing and analyzing the uniaxial compressive strength(UCS),magnetic susceptibility(MS),permeability,and chemical index of alteration(CIA)of the Mesozoic granite weathering crust in the coastal area of eastern Fujian.The results show that the granite weathering crust reservoir can be divided into four zones vertically:a soil zone(SZ),weathered and dissolved zone(WDZ),fracture zone(FZ),and bedrock zone(BZ).A cataclastic area is developed in the FZ and BZ,in which structural fractures are well-developed,the fracture surface density is usually greater than 200 m/m^(2),and the contribution to the fractures in the rock mass is up to about 50%,making this the sweet spot of the reservoir.In the SZ,the rocks are loose,and the pores are well-developed.The UCS is less than 10 MPa,and the average rate of change of the UCS(Δ_(σ))is 0.90.The average permeability is 2823.00 mD,and the average rate of change of the permeability(Δ_(κ))is 5.13.The average CIA is 74.9%.The average clay mineral content is 7%.The rocks in the WDZ have been significantly weathered by physical and chemical processes,and the weathering fractures and dissolution pores are well-developed.The average UCS is 18.2 MPa,and the averageΔ_(σ)is 0.70.The average permeability is 143.80 mD,and averageΔ_(κ)is 4.17.The average CIA is 65.3%.The average clay mineral content is 4%.Under the influence of tectonic movement and physical weathering,the rocks in the FZ have developed structural fractures and a few weathered fractures.The average UCS is 57.9 MPa,and the averageΔ_(σ)is 0.18.The average permeability is 5.50 mD,and the averageΔ_(κ)is 2.55.The average CIA is 61.6%.The average clay mineral content is 2%.In the BZ,the rocks are intact and hard.The average UCS is 69.9 MPa,and the average Ds is 0.13.The average permeability is 1.46 mD,and the averageΔ_(κ)is 1.43.The average CIA is 57.8%.The average clay mineral content is less than 1%.The multi-parameter combination of the UCS,Δ_(σ),permeability,Δ_(κ),CIA,and clay mineral content achieved good results in the division of the zones of the weathering crust.The UCS increases gradually from top to bottom,while Ds,permeability,Δ_(κ),CIA,and clay mineral content all decrease gradually.In addition,based on the petrophysical parameters of the rocks,including the density,resistivity,and acoustic velocity,a good division effect was also achieved,which can provide a basis for the vertical zonation of the granite buried-hill weathering crust reservoir.展开更多
Convective storms and lightning are among the most important weather phenomena that are challenging to forecast.In this study,a novel multi-task learning(MTL)encoder-decoder U-net neural network was developed to forec...Convective storms and lightning are among the most important weather phenomena that are challenging to forecast.In this study,a novel multi-task learning(MTL)encoder-decoder U-net neural network was developed to forecast convective storms and lightning with lead times for up to 90 min,using GOES-16 geostationary satellite infrared brightness temperatures(IRBTs),lightning flashes from Geostationary Lightning Mapper(GLM),and vertically integrated liquid(VIL)from Next Generation Weather Radar(NEXRAD).To cope with the heavily skewed distribution of lightning data,a spatiotemporal exponent-weighted loss function and log-transformed lightning normalization approach were developed.The effects of MTL,single-task learning(STL),and IRBTs as auxiliary input features on convection and lightning nowcasting were investigated.The results showed that normalizing the heavily skew-distributed lightning data along with a log-transformation dramatically outperforms the min-max normalization method for nowcasting an intense lightning event.The MTL model significantly outperformed the STL model for both lightning nowcasting and VIL nowcasting,particularly for intense lightning events.The MTL also helped delay the lightning forecast performance decay with the lead times.Furthermore,incorporating satellite IRBTs as auxiliary input features substantially improved lightning nowcasting,but produced little difference in VIL forecasting.Finally,the MTL model performed better for forecasting both lightning and the VIL of organized convective storms than for isolated cells.展开更多
Considering the effects of increased economic globalization and global warming,developing methods for reducing shipping costs and greenhouse gas emissions in ocean transportation has become crucial.Owing to its key ro...Considering the effects of increased economic globalization and global warming,developing methods for reducing shipping costs and greenhouse gas emissions in ocean transportation has become crucial.Owing to its key role in modern navigation technology,ship weather routing is the research focus of several scholars in this field.This study presents a hybrid genetic algorithm for the design of an optimal ship route for safe transoceanic navigation under complicated sea conditions.On the basis of the basic genetic algorithm,simulated annealing algorithm is introduced to enhance its local search ability and avoid premature convergence,with the ship’s voyage time and fuel consumption as optimization goals.Then,a mathematical model of ship weather routing is developed based on the grid system.A measure of fitness calibration is proposed,which can change the selection pressure of the algorithm as the population evolves.In addition,a hybrid crossover operator is proposed to enhance the ability to find the optimal solution and accelerate the convergence speed of the algorithm.Finally,a multi-population technique is applied to improve the robustness of the algorithm using different evolutionary strategies.展开更多
The(ultra-)mafic mine tailings pond revealed a weathering discrepancy in the tailings profile,which provided a valuable analog to assess the role of carbonate and silicate weathering of the basalt.In this study,drill-...The(ultra-)mafic mine tailings pond revealed a weathering discrepancy in the tailings profile,which provided a valuable analog to assess the role of carbonate and silicate weathering of the basalt.In this study,drill-cores samples were selected from the Wanniangou V–Ti–Fe mine tailings pond(Sichuan province,China)to investigate the mineralogicand geochemical characteristics in the tailings profile.The results reveal(1)the tailings pond profile consist of upper and lower layers.The upper layer is composed of carbonate weathering(1.4%),which was formed in the initial stages of tailings exposure and represented a minimal weathering degree.(2)The lower layer was primarily observed at the aquifer zone of the tailings pond,and was consistent with 0.45%carbonate weathering and 48.4%silicate weathering.(3)The weathering discrepancy in the tailings profile could be due to the sulfide oxidation and aerobic/flowing aquifer,which facilitate the water-tailings reactions.The tailings profile provides an analog to studying basalt weathering,as it spans both carbonate and silicate weathering.This research reinforces the idea that silicate weathering is predominant in basaltic areas and plays a crucial role in regulating atmospheric CO_(2)(carbon dioxide)levels on Earth.展开更多
Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a de...Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.展开更多
Forecasting the weather is a challenging task for human beings because of the unpredictable nature of the climate.However,effective forecasting is vital for the general growth of a country due to the significance of w...Forecasting the weather is a challenging task for human beings because of the unpredictable nature of the climate.However,effective forecasting is vital for the general growth of a country due to the significance of weather forecasting in science and technology.The primary motivation behind this work is to achieve a higher level of forecasting accuracy to avoid any damage.Currently,most weather forecasting work is based on initially observed numerical weather data that cannot fully cover the changing essence of the atmosphere.In this work,sensors are used to collect real-time data for a particular location to capture the varying nature of the atmosphere.Our solution can give the anticipated results with the least amount of human engagement by combining human intelligence and machine learning with the help of the cognitive Internet of Things.The Authors identified weatherrelated parameters such as temperature,humidity,wind speed,and rainfall and then applied cognitive data collection methods to train and validate their findings.In addition,the Authors have examined the efficacy of various machine learning algorithms by using them on both data sets i.e.,pre-recorded metrological data sets and live sensor data sets collected from multiple locations.The Authors noticed that the results were superior on the sensor data.The Authors developed ensemble learning model using stacked method that achieved 99.25%accuracy,99%recall,99%precision,and 99%F1-score for Sensor data.It also achieved 85%accuracy,86%recall,85%precision,and 86%F1 score for Australian rainfall data.展开更多
文摘We are evaluating dryland cotton production in Martin County, Texas, measuring cotton lint yield per unit of rainfall. Our goal is to collect rainfall data per 250 - 400 ha. Upon selection of a rainfall gauge, we realized that the cost of using, for example, a tipping bucket-type rain gauge would be too expensive and thus searched for an alternative method. We selected an all-in-one commercially available weather station;hereafter, referred to as a Personal Weather Station (PWS) that is both wireless and solar powered. Our objective was to evaluate average measurements of rainfall obtained with the PWS and to compare these to measurements obtained with an automatic weather station (AWS). For this purpose, we installed four PWS deployed within 20 m of the Plant Stress and Water Conservation Meteorological Tower that was used as our AWS, located at USDA-ARS Cropping Systems Research Laboratory, Lubbock, TX. In addition, we measured and compared hourly average values of short-wave irradiance (R<sub>g</sub>), air temperature (T<sub>air</sub>) and relative humidity (RH), and wind speed (WS), and calculated values of dewpoint temperature (T<sub>dew</sub>). This comparison was done over a 242-day period (1 October 2022-31 May 2023) and results indicated that there was no statistical difference in measurements of rainfall between the PWS and AWS. Hourly average values of R<sub>g</sub> measured with the PWS and AWS agreed on clear days, but PWS measurements were higher on cloudy days. There was no statistical difference between PWS and AWS hourly average measurements of T<sub>air</sub>, RH, and calculated T<sub>dew</sub>. Hourly average measurements of R<sub>g</sub> and WS were more variable. We concluded that the PWS we selected will provide adequate values of rainfall and other weather variables to meet our goal of evaluating dryland cotton lint yield per unit rainfall.
基金supported by the Dean Faculty of Science,University of Karachi research grant.
文摘This study is thefirst attempt to assess the nature of the soil,especially on the western side of the Porali Plain in Balochistan;a new emerging agriculture hub,using weathering and pollution indices supplemented by multi-variate analysis based on geochemical data.The outcomes of this study are expected to help farmers in soil manage-ment and selecting suitable crops for the region.Twenty-five soil samples were collected,mainly from the arable land of the Porali Plain.After drying and coning-quarter-ing,soil samples were analyzed for major and trace ele-ments using the XRF technique;sieving and hydrometric methods were employed for granulometric analysis.Esti-mated data were analyzed using Excel,SPSS,and Surfer software to calculate various indices,correlation matrix,and spatial distribution.The granulometric analysis showed that 76%of the samples belonged to loam types of soil,12%to sand type,and 8%to silt type.Weathering indices:CIA,CIW,PIA,PWI,WIP,CIX,and ICV were calculated to infer the level of alteration.These indices reflect mod-erate to intense weathering;supported by K_(2)O/AI_(2)O_(3),Rb/K_(2)O,Rb/Ti,and Rb/Sr ratios.Assessment of the geo-ac-cumulation and Nemerow Pollution indices pinpoint rela-tively high concentrations of Pb,Ni,and Cr concentration in the soils.The correlation matrix and Principal Compo-nent Analysis show that the soil in this study area is mainly derived from the weathering of igneous rocks of Bela Ophiolite(Cretaceous age)and Jurassic sedimentary rocks of Mor Range having SEDEX/MVT type mineralization.Weathering may result in the undesirable accumulation of certain trace elements which adversely affects crops.
基金Supported by the Key Research Program of the Chinese Academy of Sciences(ZDRE-KT-2021-3)。
文摘Both analyzing a large amount of space weather observed data and alleviating personal experience bias are significant challenges in generating artificial space weather forecast products.With the use of natural language generation methods based on the sequence-to-sequence model,space weather forecast texts can be automatically generated.To conduct our generation tasks at a fine-grained level,a taxonomy of space weather phenomena based on descriptions is presented.Then,our MDH(Multi-Domain Hybrid)model is proposed for generating space weather summaries in two stages.This model is composed of three sequence-to-sequence-based deep neural network sub-models(one Bidirectional Auto-Regressive Transformers pre-trained model and two Transformer models).Then,to evaluate how well MDH performs,quality evaluation metrics based on two prevalent automatic metrics and our innovative human metric are presented.The comprehensive scores of the three summaries generating tasks on testing datasets are 70.87,93.50,and 92.69,respectively.The results suggest that MDH can generate space weather summaries with high accuracy and coherence,as well as suitable length,which can assist forecasters in generating high-quality space weather forecast products,despite the data being starved.
基金supported by grants from the Research Grant Council of the Hong Kong Special Administrative Region,China(Project Nos.HKU 7137/03E and R7005/01E)。
文摘Rock and geotechnical engineering investigations involve drilling holes in ground with or without retrieving soil and rock samples to construct the subsurface ground profile.On the basis of an actual soil nailing drilling for a slope stability project in Hong Kong,this paper further develops the drilling process monitoring(DPM)method for digitally profiling the subsurface geomaterials of weathered granitic rocks using a compressed airflow driven percussive-rotary drilling machine with down-the-hole(DTH)hammer.Seven transducers are installed on the drilling machine and record the chuck displacement,DTH rotational speed,and five pressures from five compressed airflows in real-time series.The mechanism and operations of the drilling machine are elaborated in detail,which is essential for understanding and evaluating the drilling data.A MATLAB program is developed to automatically filter the recorded drilling data in time series and classify them into different drilling processes in sub-time series.These processes include penetration,push-in with or without rod,pull-back with or without rod,rod-tightening and rod-untightening.The drilling data are further reconstructed to plot the curve of drill-bit depth versus the net drilling time along each of the six drillholes.Each curve is found to contain multiple linear segments with a constant penetration rate,which implies a zone of homogenous geomaterial with different weathering grades.The effect from fluctuation of the applied pressures is evaluated quantitatively.Detailed analyses are presented for accurately assess and verify the underground profiling and strength in weathered granitic rock,which provided the basis of using DPM method to confidently assess drilling measurements to interpret the subsurface profile in real time.
基金Science and technology research projects of colleges and universities in Inner Mongolia(NJZY22511)Funds for basic scientific research in universities of Inner Mongolia:Key project of Philosophy and Social Science Foundation of Inner Mongolia Agricultural University(BR220603)。
文摘Wooden buildings play a very important role in China’s construction and landscape architecture industry.In order to explore the weathering characteristics of the surface layer of landscape wooden buildings,the main causes of weathering were analyzed on the basis of summarizing the common types of weathering characterization.The results showed that the weathering characterization was mainly reflected in the surface defects of wood structures,such as cracking,discoloration,peeling,wind erosion wear,and so on.The coating technology on the surface of constructions was the main artificial factor affecting the surface defects of constructions.In the case of similar surface decoration conditions,sunlight and moisture were the main natural factors affecting the weathering of wooden buildings,which will promote the process of weathering.
基金supported by the National Natural Science Foundation of China(42072177)National Natural Science Foundation of China(U19B6003)Frontier Project of Chinese Academy of Sciences(XDA14010201).
文摘Weathering has always been a concerned around the world,as the first and most important step in the global cycle of elements,which leads to the fractionation of isotopes on the scale of geological age.The Middle Ordovician Majiagou Formation in Daniudi area of the Ordos Basin had experienced weathering for>130 Myr.Through thin section observation,major and trace element analysis,carbon,oxygen,and magnesium isotopes composition analysis,the dolomitization modes and weathering of ancient dolo-mite in Daniudi area were analyzed in detail.The results showed that the Sabkha and brine-reflux dolomitization modes had developed,and the Mg isotopes in different layers of the karst crust were fractionated by various factors.The vertical vadose zone was affected by weathering,the Mg isotope of dolomite(δ^(26)Mgdol)showed a downward decreasing trend;the horizontal underflow zone was controlled by diagenesis and formation fluid,δ^(26)Mgdol showed a vertical invariance and negative;the main reason for Mg isotope fractionation in the deep slow-flow zone was the brine-reflux dolomitization mode during early burial period,which showed a vertical downward increase.Finally,the Mg isotope characteristic data of the ancient weathering crust were provided and the process of Mg isotope frac-tionationinthekarstcrust was explained.
基金This paper was financially supported by the National Natural Science Foundation of China(Grant No.41972285)the Youth Innovation Promotion Association CAS(Grant No.2018363)Key R&D projects of Hubei Province,China(Grant No.2021BAA186).
文摘Because of the cementation inherited from the parent rock,weathered granitic soil is usually susceptible to disturbance,which poses considerable challenges for laboratory characterization.The cone penetration test with pore pressure measurements has long been known for its reliability in site investigations and stratigraphic profiling.However,although extensive piezocone test results and experience are available for sedimentary soil,similar advances are yet to be made for weathered granitic soil.Moreover,the experience from sedimentary soil may not be directly applicable to weathered profiles because of the essentially different natures of the two types of geomaterials.This study performs seismic piezocone tests in a weathered granitic profile comprising residual granitic soil,completely weathered granite,and highly weathered granite.Pore pressure is measured at both the cone mid-face and the shoulder,and the effects of penetrometer size and penetration rate are considered.A series of updated soil behavior type charts is proposed to interpret the test results,thereby allowing the effect of weathering to be evaluated.This paper offers an important extension to the sparse data on the in situ responses of weathered materials.
基金partially funded by Sao Paulo Research Foundation(FAPESP),Brazil,grant numbers#2015/18808-0,#2018/23064-8,#2019/23382-2.
文摘Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.
基金funded by Science Foundation of China University of Petroleum,Beijing(No.2462022XKBH005)China Postdoctoral Science Foundation(2022M723487)+1 种基金the National Science and Technology Major Project of the Ministry of Science and Technology of China(2016ZX05006-006)PetroChina Project(2021DJ0704).
文摘The middle Eocene climatic optimum(MECO,ca.-42 Ma)is a key time period for understanding Cenozoic cooling of the global climate.Still,midlatitude terrestrial records of climate evolution during MEcO epoch are rare.In this study,continuous high-resolution record of shale sediments in mid-Eocene Shahejie Formation(MES shales)in the Bohai Bay Basin were performed with major-element and wavelet analysis.The midlatitude paleoweathering and paleoclimatic evolution during MEcO epoch were analyzed in this study.The MES shales experienced weak-moderate paleoweathering under a subtropical monsoon paleoclimate with mean annual temperature of 8.3-12.9℃ and mean annual precipitation of 685-1100 mm/yr.The MES shales record a mixed provenance involving intermediate igneous rocks,and low compositional maturity.The nutrient-rich environment led to enrichment in organic matter in the MES shales.Wavelet analysis revealed good periodicity about the paleoclimate and weathering during MECO epoch.In the stage I of MES shales depositional process,the paleolake was high in nutrients,and the MES shales experienced high chemical weathering due to a relatively warmer and more humid climate.In contrast,the climate in stage II was relatively cold and dry,and the maturity of the MES shales was relatively high during this stage,suggesting a relatively stable tectonic background.This work provides more terrestrial records of MEco epoch for midlatitude region,and is benefit for better understanding of the palaeoenvironment when MES shales formed.The implication of organic matters enrichment in this study is meaningful for the shale oil/gas exploration in Nanpu Sag.
基金the National Major Project of Science and Technology in developing great oil&gas field and coal bed gas(Grant No.2016ZX05007-006)the Study on water-cut control and production stabilization in the old gasfields and efficient development in new gasfields in Qaidam Basin(Grant No.2016E-0106GF)。
文摘The bedrock weathered crust in front of the Altun Mountains in the Qaidam Basin,western China,is different from others because this is a salt-lake basin,where saline water fluid infiltrates and is deposited in the overlying strata.A large amount of gypsum infills the bedrock weathered crust,and this has changed the pore structure.Using core observation,polarized light microscopy,electron probe,physical property analysis and field emission scanning electron microscopy experiments,the characteristics of the weathered bedrock have been studied.There are cracks and a small number of dissolved pores in the interior of the weathered crust.Matrix micropores are widely developed,especially the various matrix cracks formed by tectonics and weathering,as well as the stress characteristics of small dissolved pores,and physical properties such as porosity and permeability.This‘dual structure’developed in the bedrock is important for guiding the exploration of the lake basin bedrock for natural gas.
基金Financial supports for this work from National Natural Science Foundation of China(Nos.22078252 and 52274266)the Graduate Education Innovation Foundation of Wuhan Institute of Technology(No.CX2021463)the Young Top-notch Talent Cultivation Program of Hubei Province are greatly appreciated.
文摘Surfactants were proposed to be added into magnesium sulfate solution to improve the leaching process of weathered crust elution-deposited rare earth ores(WREOs).Effects of surfactants and their concentration on the seepage of leaching solutions and the leaching efficiency of rare earth(RE)and aluminum(Al)were investigated,and the leaching kinetics,the mass transfer process,the adhesion work and the adhesion work reduction factor were analyzed to reveal its strengthening leaching mechanism.The results show that cetyltrimethylammonium bromide(CTAB)has a better strengthening effect on the leaching process than dodecyl trimethyl ammonium bromide(DTAB),sodium dodecyl sulfate(SDS),sodium oleate and oleic acid.In the presence of 0.04%CTAB in 0.2 mol/L solution,the permeability coefficient of WREOs increases from 0.945×10^(-5)to 1.640×10^(-5)cm·s^(-1),and the leaching efficiency of RE increases from 80%to 90%,confirming the promotion of surfactants on the leaching process of WREOs.Kinetic analysis shows that the leaching process conforms to the inner diffusion control model,and the leaching kinetics equations of RE and Al related to CTAB content are obtained.Mass transfer discussion shows a smaller height equivalent to theoretical plate(HETP)of RE and Al at CTAB content of 0.04%,suggesting the higher mass transfer efficiency here.According to the interfacial properties of leaching solutions,the calculated adhesion work and the adhesion work reduction factor further demonstrate the strengthening leaching effect of CTAB on the leaching process of WREOs.
基金Project supported by the National Key Research and Development Program of China(Grant No.2018YFE0127800)the Science,Technology&Innovation Funding Authority(STIFA),Egypt grant(Grant No.40517)+1 种基金China Postdoctoral Science Foundation(Grant No.2020M682411)the Fundamental Research Funds for the Central Universities(Grant No.2019kfy RCPY045)。
文摘Solar stills are considered an effective method to solve the scarcity of drinkable water.However,it is still missing a way to forecast its production.Herein,it is proposed that a convenient forecasting model which just needs to input the conventional weather forecasting data.The model is established by using machine learning methods of random forest and optimized by Bayesian algorithm.The required data to train the model are obtained from daily measurements lasting9 months.To validate the accuracy model,the determination coefficients of two types of solar stills are calculated as 0.935and 0.929,respectively,which are much higher than the value of both multiple linear regression(0.767)and the traditional models(0.829 and 0.847).Moreover,by applying the model,we predicted the freshwater production of four cities in China.The predicted production is approved to be reliable by a high value of correlation(0.868)between the predicted production and the solar insolation.With the help of the forecasting model,it would greatly promote the global application of solar stills.
文摘A mesoscale convective system(MCS)is an organized cluster of thunderstorms known to be the most important convective mode in causing disastrous high-impact weather,such as heavy rainfall,hail,damaging winds,and tornadoes.The small spatial scale and fast temporal evolution of MCSs make their observation and prediction very challenging.East Asia is home to the world’s most prominent monsoon,setting the stage for various severe convective weather events.MCSs and their associated high-impact weather have long been critical issues of concern;as such,their research efforts are valued by governments in East Asia.
基金the National Natural Science Foundation of China(Nos.52174258,92162109,52222405 and 52004184).
文摘Both CT and Avizo software were used to explore the effect of particle gradation on the evolution characteristics of pore structure and seepage paths in weathered crust elution-deposited rare earth ores during leaching.The results showed that the pore areas in four kinds of ore samples before leaching were mainly concentrated in 10^(4)–10^(7)μm^(2),whose pore quantities accounted for 96.89%,94.94%,90.48%,and 89.45%,respectively,while the corresponding pore volume only accounted for 30.74%,14.55%,7.58%,and 2.84%of the total pore volume.With the decrease of fractal dimension,the average pore throat length increased,but pore throat quantities,the average pore throat radius and coordination number decreased.Compared with that before leaching,the change degree of pore structure during leaching increased with the fractal dimension decreasing.For example,the reduction rate of the average coordination number of ore samples was 14.36%,21.30%,28.00%,and 32.90%,respectively.Seepage simulation results indicated that seepage paths were uniformly distributed before leaching while the streamline density and seepage velocity increased with the fractal dimension decreasing.Besides,the phenomenon of the streamline interruption gradually reduced during leaching while preferential seepage got more obvious with the decrease of the fractal dimension.
基金supported by the Key Research and Development Program of Jilin Province(grant No.20230203107SF)the National Natural Science Foundation of China(Grant No.41790453)+1 种基金the National Key Research and Development Program of China(Grant No.2019YFC0605402)the National Major Science and Technology Project of the Ministry of Science and Technology of China(Grant No.2016ZX05026-004-001).
文摘Weathering crust reservoirs have obvious vertical zonation,which is the focus of weathering crust reservoir research,but there is a lack of quantitative characterization indexes.To achieve the quantitative characterization of granite weathering crust reservoir and provide the basis for oil exploration of granite weathering crust buried hill reservoir,in this paper,the vertical zonation of granite weathering crust reservoir is quantitatively divided by testing and analyzing the uniaxial compressive strength(UCS),magnetic susceptibility(MS),permeability,and chemical index of alteration(CIA)of the Mesozoic granite weathering crust in the coastal area of eastern Fujian.The results show that the granite weathering crust reservoir can be divided into four zones vertically:a soil zone(SZ),weathered and dissolved zone(WDZ),fracture zone(FZ),and bedrock zone(BZ).A cataclastic area is developed in the FZ and BZ,in which structural fractures are well-developed,the fracture surface density is usually greater than 200 m/m^(2),and the contribution to the fractures in the rock mass is up to about 50%,making this the sweet spot of the reservoir.In the SZ,the rocks are loose,and the pores are well-developed.The UCS is less than 10 MPa,and the average rate of change of the UCS(Δ_(σ))is 0.90.The average permeability is 2823.00 mD,and the average rate of change of the permeability(Δ_(κ))is 5.13.The average CIA is 74.9%.The average clay mineral content is 7%.The rocks in the WDZ have been significantly weathered by physical and chemical processes,and the weathering fractures and dissolution pores are well-developed.The average UCS is 18.2 MPa,and the averageΔ_(σ)is 0.70.The average permeability is 143.80 mD,and averageΔ_(κ)is 4.17.The average CIA is 65.3%.The average clay mineral content is 4%.Under the influence of tectonic movement and physical weathering,the rocks in the FZ have developed structural fractures and a few weathered fractures.The average UCS is 57.9 MPa,and the averageΔ_(σ)is 0.18.The average permeability is 5.50 mD,and the averageΔ_(κ)is 2.55.The average CIA is 61.6%.The average clay mineral content is 2%.In the BZ,the rocks are intact and hard.The average UCS is 69.9 MPa,and the average Ds is 0.13.The average permeability is 1.46 mD,and the averageΔ_(κ)is 1.43.The average CIA is 57.8%.The average clay mineral content is less than 1%.The multi-parameter combination of the UCS,Δ_(σ),permeability,Δ_(κ),CIA,and clay mineral content achieved good results in the division of the zones of the weathering crust.The UCS increases gradually from top to bottom,while Ds,permeability,Δ_(κ),CIA,and clay mineral content all decrease gradually.In addition,based on the petrophysical parameters of the rocks,including the density,resistivity,and acoustic velocity,a good division effect was also achieved,which can provide a basis for the vertical zonation of the granite buried-hill weathering crust reservoir.
基金supported by the Science and Technology Grant No.520120210003,Jibei Electric Power Company of the State Grid Corporation of China。
文摘Convective storms and lightning are among the most important weather phenomena that are challenging to forecast.In this study,a novel multi-task learning(MTL)encoder-decoder U-net neural network was developed to forecast convective storms and lightning with lead times for up to 90 min,using GOES-16 geostationary satellite infrared brightness temperatures(IRBTs),lightning flashes from Geostationary Lightning Mapper(GLM),and vertically integrated liquid(VIL)from Next Generation Weather Radar(NEXRAD).To cope with the heavily skewed distribution of lightning data,a spatiotemporal exponent-weighted loss function and log-transformed lightning normalization approach were developed.The effects of MTL,single-task learning(STL),and IRBTs as auxiliary input features on convection and lightning nowcasting were investigated.The results showed that normalizing the heavily skew-distributed lightning data along with a log-transformation dramatically outperforms the min-max normalization method for nowcasting an intense lightning event.The MTL model significantly outperformed the STL model for both lightning nowcasting and VIL nowcasting,particularly for intense lightning events.The MTL also helped delay the lightning forecast performance decay with the lead times.Furthermore,incorporating satellite IRBTs as auxiliary input features substantially improved lightning nowcasting,but produced little difference in VIL forecasting.Finally,the MTL model performed better for forecasting both lightning and the VIL of organized convective storms than for isolated cells.
基金funded by the Russian Foundation for Basic Research(RFBR)(No.20-07-00531).
文摘Considering the effects of increased economic globalization and global warming,developing methods for reducing shipping costs and greenhouse gas emissions in ocean transportation has become crucial.Owing to its key role in modern navigation technology,ship weather routing is the research focus of several scholars in this field.This study presents a hybrid genetic algorithm for the design of an optimal ship route for safe transoceanic navigation under complicated sea conditions.On the basis of the basic genetic algorithm,simulated annealing algorithm is introduced to enhance its local search ability and avoid premature convergence,with the ship’s voyage time and fuel consumption as optimization goals.Then,a mathematical model of ship weather routing is developed based on the grid system.A measure of fitness calibration is proposed,which can change the selection pressure of the algorithm as the population evolves.In addition,a hybrid crossover operator is proposed to enhance the ability to find the optimal solution and accelerate the convergence speed of the algorithm.Finally,a multi-population technique is applied to improve the robustness of the algorithm using different evolutionary strategies.
基金financially supported by Sichuan Science and Technology Program(No.2023YFS0408)。
文摘The(ultra-)mafic mine tailings pond revealed a weathering discrepancy in the tailings profile,which provided a valuable analog to assess the role of carbonate and silicate weathering of the basalt.In this study,drill-cores samples were selected from the Wanniangou V–Ti–Fe mine tailings pond(Sichuan province,China)to investigate the mineralogicand geochemical characteristics in the tailings profile.The results reveal(1)the tailings pond profile consist of upper and lower layers.The upper layer is composed of carbonate weathering(1.4%),which was formed in the initial stages of tailings exposure and represented a minimal weathering degree.(2)The lower layer was primarily observed at the aquifer zone of the tailings pond,and was consistent with 0.45%carbonate weathering and 48.4%silicate weathering.(3)The weathering discrepancy in the tailings profile could be due to the sulfide oxidation and aerobic/flowing aquifer,which facilitate the water-tailings reactions.The tailings profile provides an analog to studying basalt weathering,as it spans both carbonate and silicate weathering.This research reinforces the idea that silicate weathering is predominant in basaltic areas and plays a crucial role in regulating atmospheric CO_(2)(carbon dioxide)levels on Earth.
基金supported by the China Ministry of Industry and Information Technology Foundation and Aeronautical Science Foundation of China(ASFC-201920007002)the National Key Research and Development Plan(2021YFB1600603)the Open Fund of Key Laboratory of Civil Aircraft Airworthiness Technology,Civil Aviation University of China.
文摘Considering the problem that the scattering echo images of airborne Doppler weather radar are often reduced by ground clutters,the accuracy and confidence of meteorology target detection are reduced.In this paper,a deep convolutional neural network(DCNN)is proposed for meteorology target detection and ground clutter suppression with a large collection of airborne weather radar images as network input.For each weather radar image,the corresponding digital elevation model(DEM)image is extracted on basis of the radar antenna scan-ning parameters and plane position,and is further fed to the net-work as a supplement for ground clutter suppression.The fea-tures of actual meteorology targets are learned in each bottle-neck module of the proposed network and convolved into deeper iterations in the forward propagation process.Then the network parameters are updated by the back propagation itera-tion of the training error.Experimental results on the real mea-sured images show that our proposed DCNN outperforms the counterparts in terms of six evaluation factors.Meanwhile,the network outputs are in good agreement with the expected mete-orology detection results(labels).It is demonstrated that the pro-posed network would have a promising meteorology observa-tion application with minimal effort on network variables or parameter changes.
文摘Forecasting the weather is a challenging task for human beings because of the unpredictable nature of the climate.However,effective forecasting is vital for the general growth of a country due to the significance of weather forecasting in science and technology.The primary motivation behind this work is to achieve a higher level of forecasting accuracy to avoid any damage.Currently,most weather forecasting work is based on initially observed numerical weather data that cannot fully cover the changing essence of the atmosphere.In this work,sensors are used to collect real-time data for a particular location to capture the varying nature of the atmosphere.Our solution can give the anticipated results with the least amount of human engagement by combining human intelligence and machine learning with the help of the cognitive Internet of Things.The Authors identified weatherrelated parameters such as temperature,humidity,wind speed,and rainfall and then applied cognitive data collection methods to train and validate their findings.In addition,the Authors have examined the efficacy of various machine learning algorithms by using them on both data sets i.e.,pre-recorded metrological data sets and live sensor data sets collected from multiple locations.The Authors noticed that the results were superior on the sensor data.The Authors developed ensemble learning model using stacked method that achieved 99.25%accuracy,99%recall,99%precision,and 99%F1-score for Sensor data.It also achieved 85%accuracy,86%recall,85%precision,and 86%F1 score for Australian rainfall data.
