Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accura...Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.展开更多
This paper conducted a systematic survey and zoogeographical region analysis of the family Sphingidae in the Guokui Mountain,Heilongjiang Province.Collections were made from May 2023 to August 2024 using the light-tra...This paper conducted a systematic survey and zoogeographical region analysis of the family Sphingidae in the Guokui Mountain,Heilongjiang Province.Collections were made from May 2023 to August 2024 using the light-trap method.A total of 14 species and 11 subspecies from 18 genera and three subfamilies were recorded.One species(Ambulyx tobii)and two subspecies(Ambulyx japonica koreana and Clanis undulosa undulosa)were new records for Heilongjiang Province.The study showed that the subfamily Smerinthinae had the most species(subspecies),while the subfamily Sphinginae had the fewest.Among the world's zoogeographical region,most species(subspecies)in the Guokui Mountain belonged to the palearctic region,with eight species and seven subspecies were also found in the oriental region.This indicated a close biogeographic connection between the two regions.Among the Chinese zoogeographical regions,the northeastern territory,northern territory and northwestern territory had the most abundant species(subspecies).It was also found that the distribution pattern types of hawkmoths in the Guokui Mountain were diverse,with the'northeastern territory-northern territory-northwestern territory'and'northeastern territory-northern territorynorthwestern territory-western plateau-southwestern territory-central territory-southeastern territory'types having the most species(subspecies).In addition,the Guokui Mountain hawkmoths were mostly distributed interregionally.The distribution patterns that contained the northeastern territory were the most numerous,followed by the northern territory.The rich diversity of the family Sphingidae in the Guokui Mountain was closely related to the unique climate,environment and vegetation types in the area.The results could help to improve the biodiversity database of Heilongjiang Province and researches on hawkmoths.展开更多
Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of ...Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of climate change on cotton production and the use of genomic approaches to increase stress tolerance in cotton.This paper discusses the effects of rising temperatures,changing precipitation patterns,and extreme weather events on cotton yield.It then explores various genomic strategies,such as genomic selection and marker-assisted selection,which can be used to develop stress-tolerant cotton varieties.The review emphasizes the need for interdisciplinary research efforts and policy interventions to mitigate the adverse effects of climate change on cotton production.Furthermore,this paper presents advanced prospects,including genomic selection,gene editing,multi-omics integration,highthroughput phenotyping,genomic data sharing,climate-informed breeding,and phenomics-assisted genomic selection,for enhancing stress resilience in cotton.Those innovative approaches can assist cotton researchers and breeders in developing highly resilient cotton varieties capable of withstanding the challenges posed by climate change,ensuring the sustainable and prosperous future of cotton production.展开更多
Samples were collected from two core sediments(C1 and C2) of Xiangjiang River,Chang-Zhu-Tan region,Hunan Province,China.The heavy metal contents are relatively higher,especially for the surface or near the surface lay...Samples were collected from two core sediments(C1 and C2) of Xiangjiang River,Chang-Zhu-Tan region,Hunan Province,China.The heavy metal contents are relatively higher,especially for the surface or near the surface layers.The calculated anthropogenic factor values indicate that all the heavy metals except for Cr in the core samples are enriched,especially for Cd,with the maximum enriching coefficients of 119.44,and 84.67 in C1 and C2,respectively.The correlation of heavy metals with sulphur indicates that they are precipitated as metal sulphides.Correlation matrix shows significant association between heavy metals and mud.Factor analysis identifies that signified anthropogenic activities affect the region of Xiangjiang River.展开更多
The remote sensing snow cover data from Moderate Resolution Imaging Spectroradiometer(MODIS) satellite from 2000 to 2007 have been used to analyze some climate change indicators in the Himalayan region.In particular,t...The remote sensing snow cover data from Moderate Resolution Imaging Spectroradiometer(MODIS) satellite from 2000 to 2007 have been used to analyze some climate change indicators in the Himalayan region.In particular,the variability in the fractional snow coverage with elevations,its temporal variability (8-day,monthly and seasonal)and its展开更多
The cold regions are located in high latitudes and cold climates.The local excellent ornamental plant resources are relatively scarce.The plant species that are suitable for both ornamental and productive benefits of ...The cold regions are located in high latitudes and cold climates.The local excellent ornamental plant resources are relatively scarce.The plant species that are suitable for both ornamental and productive benefits of landscape of flower sea construction are also even fewer.Therefore,it is imperative to introduce and screen the plant resources suitable for cold regions to create the landscape of flower sea.The rape,an oilseed crop,was used as a research object in order to create a productive flower landscape with both ornamental and economic values in cold regions.Four rape flower varieties,Qingza No.5,7,9,and 11,were introduced from Qinghai Hufeng Agricultural Science and Technology Group Co.,Ltd.They were planted in the experimental practice base of Northeast Agricultural University in three batches.Development characteristics and seed yield of rape flowers on different sowing dates were studied.The fuzzy probability method was used to comprehensively evaluate the varieties.The results showed that the rape flowers grew well in Harbin City during the experimental sowing period,which could form a good landscape of flower sea and had a considerable rapeseed yield.It could be widely used in cold urban and rural areas,such as Harbin City.In view of the experimental results,the strategies of creating a productive landscape of rape flower sea were proposed and the economic benefits were analyzed.It could change the status quo of a uniform landscape of flower sea in cold regions,help the development of rural tourism,and promote local economic income.展开更多
In this work,the flow surrounding the train was obtained using a detached eddy simulation(DES)for slipstream analysis.Two different streamlined nose lengths were investigated:a short nose(4 m)and a long nose(9 m).The ...In this work,the flow surrounding the train was obtained using a detached eddy simulation(DES)for slipstream analysis.Two different streamlined nose lengths were investigated:a short nose(4 m)and a long nose(9 m).The time-average slipstream velocity and the time-average slipstream pressure along the car bodies were compared and explained in detail.In addition to the time-averaged values,the _(max)imum velocities and the pressure peak-to-peak values around the two trains were analyzed.The result showed that the nose length affected the slipstream velocity along the entire train length at the lower and upper regions of the side of the train.However,no significant effect was recognized at the middle height of the train along its length,except in the nose region.Moreover,within the train’s side regions(y=2.0-2.5 m and z=2-4 m)and(y=2.5-3.5 m and z=0.2-0.7 m),the ratio of slipstream velocity U_(max) between the short and long nose trains was notably higher.This occurrence also manifested at the train’s upper section,specifically where y=0-2.5 m and z=4.2-5.0 m.Similarly,regarding the ratio of _(max)imum pressure peak-to-peak values Cp-p_(max),significant regions were observed at the train’s side(y=1.8-2.6 m and z=1-4 m)and above the train(y=0-2 m and z=3.9-4.8 m).展开更多
[Background]As one of the most serious environmental issues in the world,soil erosion causes water pollution,reservoir siltation,soil productivity decline,thus threatens agricultural systems and even affects global cl...[Background]As one of the most serious environmental issues in the world,soil erosion causes water pollution,reservoir siltation,soil productivity decline,thus threatens agricultural systems and even affects global climate.The benefits of ecological soil and water conservation measures(ESWCMs,such as micro basins tillage and contour tillage)are widely understood,including runoff and soil loss reducing to a certain extent when compared with traditional tillage.While few studies have focused on China’s different soil types and erosion characteristics.[Methods]We reviewed literature from Web of Science,Scopus,and China National Knowledge Infrastructure using terms like“Conservation practice”“Contour tillage”“Runoff”“Sediment”“Erosion”and“China”and retained literatures based on criteria such as natural or simulated precipitation,runoff or soil loss data,reported replications and statistics,recorded factors like location and slope,and at least two data pairs per group.Ultimately,49 literatures were selected to quantify the impacts on different ESWCMs and identify the slope and precipitation for the greatest runoff and sediment reduction by calculating the log response ratio(LRR).[Results]The three regions’soil and water conservation benefits varied due to the differences in climate,terrain,and soil properties:1)ESWCMs applied in the black soil region of Northeast China were the most effective in reducing runoff and soil loss(66.65%runoff and 75.83%sediment),followed by those applied in the purple soil region of Southwest China(39.98%runoff and 58.30%sediment)and loess soil region of Northwest China(16.36%runoff and 32.44%sediment).2)Micro basins tillage(MBT)(71.79%runoff and 87.03%sediment)no-tillage with mulch(NTM)(17.30%runoff and 32.51%sediment),collecting soil to form a ridge with no-till(CSNT)(55.78%runoff and 71.36%sediment reduction)were the most efficient soil and water conservation measures in controlling water erosion in the black soil of Northeast China,the loess soil region of Northwest China and the purple soil region of Southwest China,respectively.3)The slope gradients ranged from 0-3°,>3°-5°and>10°-15°(0-3°:97.09%;>3°-5°:74.62%;and>10°-15°:39.41%)caused the largest reduction of runoff in the black soil region of Northeast China,the loess soil region of Northwest China,and the purple soil region of Southwest China.Meanwhile,the effects of sediment reduction were the most obvious,ranging from 0-3°,>10°-15°,and>20°-25°(0-3°:89.32%;>10°-15°:75.94%;and>20°-25°:67.25%).4)The effect of ESWCMs under rainstorms was the most obvious in the black soil region of Northeast China.The effect on runoff reduction under light rain in the purple soil region of Southwest China was the most obvious,but it failed to pass the significance test in sediment reduction.[Conclusions]The results provided optimal conservation tillage measures for three regions,different slopes and different rainfalls,and provided data support for reducing regional soil and water loss in China.展开更多
Forest fire accidents caused by distribution line faults occur frequently,resulting in heavy impacts on people’s safety and social and economic development.Currently,there are few risk assessments for forest fires in...Forest fire accidents caused by distribution line faults occur frequently,resulting in heavy impacts on people’s safety and social and economic development.Currently,there are few risk assessments for forest fires induced by over-head distribution lines,and existing assessment methods may have difficulties in data acquisition.On this basis,a novel as-sessment framework based on an analytic hierarchy process,a Bayesian network and a Fussel-Vesely importance metric is proposed in this paper.The framework combines field research and historical operation and maintenance data to assess the regional-scale risk of forest fires induced by overhead distribution lines to derive the probability of forest fires and to identify high-risk lines and key hazard events in the assessment region.Finally,taking the southern Anhui region as an ex-ample,the annual fire probability of forest fires induced by overhead distribution lines in the southern Anhui region is 5.88%,and rectification measures are proposed.This study provides management with a complete assessment framework that optimizes the difficulty of data collection and allows for additional targeted corrective measures to be proposed for the entire region and route on the basis of the assessment results.展开更多
Metasurfaces provide a potent platform for the dynamic manipulation of electromagnetic waves.Coupled with phase-change materials,they facilitate the creation of versatile metadevices,showcasing various tunable functio...Metasurfaces provide a potent platform for the dynamic manipulation of electromagnetic waves.Coupled with phase-change materials,they facilitate the creation of versatile metadevices,showcasing various tunable functions based on the transition between amorphous and crystalline states.However,the inherent limitation in tunable states imposes constraints on the multiplexing channels of metadevices.Here,this paper introduces a novel approach-a multi-functional metadevice achieved through the two-level control of the encoding phasechange metaatoms.Utilizing the phase-change material Ge_(2)Sb_(2)Se_(4)Te1(GSST)and high refractive-index liquid diiodomethane(CH_(2)I_(2)),this paper showcases precise control over electromagnetic wave manipulation.The GSST state governs the tunable function,switching it ON and OFF,while the presence of liquid in the hole dictates the deflection angle when the tunable function is active.Importantly,our tunable coding metasurface exhibits robust performance across a broad wavelength spectrum.The incorporation of high refractive-index liquid extends the regulatory dimension of the metadevice,enabling dynamic switching of encoding bit levels.This two-level tunable metadevice,rooted in phase-change materials,presents a promising avenue for the dynamic control of functions.展开更多
The laser-guided bomb(LGB)is an air-to-ground pre-cision-guided weapon that offers high hit rates,great power,and ease of use.LGBs are guided by semi-active laser ground-seek-ing technology,which means that atmospheri...The laser-guided bomb(LGB)is an air-to-ground pre-cision-guided weapon that offers high hit rates,great power,and ease of use.LGBs are guided by semi-active laser ground-seek-ing technology,which means that atmospheric conditions can affect their accuracy.The spatial release region(SRR)of LGBs is difficult to calculate precisely,especially when there is a poor field of view.This can result in a lower real hit probability.To increase the hit probability of LGBs in tough atmospheric situa-tions,a novel method for calculating the SRR has been pro-posed.This method is based on the transmittance model of the 1.06μm laser in atmospheric species and the laser diffuse reflection model of the target surface to determine the capture target time of the laser seeker.Then,it calculates the boundary ballistic space starting position by ballistic model and gets the spatial scope of the spatial release region.This method can determine the release region of LGBs based on flight test data such as instantaneous velocity,altitude,off-axis angle,and atmospheric visibility.By more effectively employing aircraft release conditions,atmospheric visibility and other factors,the SRR calculation method can improve LGB hit probabi-lity by 9.2%.展开更多
Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A light...Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.展开更多
Biochar is widely used to improve soil physical properties and carbon sequestration. However, few studies focuse on the impact of maize stalk biochar on labile organic carbon(LOC) pool and the relationship between phy...Biochar is widely used to improve soil physical properties and carbon sequestration. However, few studies focuse on the impact of maize stalk biochar on labile organic carbon(LOC) pool and the relationship between physical properties and LOC fractions. A field positioning experiment was performed in Mollisols region of Northeast China to evaluate the influence of maize stalk biochar on the spatial distribution and temporal changes of physical properties and LOC fractions. Maize stalk biochar treatments included C1(1.5 kg·hm^(-2)), C2(3 kg·hm^(-2)), C3(15 kg·hm^(-2)), C4(30 kg·hm^(-2)), and CK(0). The results showed that maize stalk biochar increased soil water contents(SWC) and soil porosity(SP), but reduced bulk density(BD). Maize stalk biochar reduced dissolved organic carbon(DOC) contents in the 0-20 cm soil layer, ranging from 0.25 g·kg^(-1) to 0.31 g·kg^(-1) in harvest period, while increased in the 20-40 cm soil layer. In addition, the application of biochar had a significant impact on the spatial distribution and temporal change of SWC, BD, SP, DOC, hot-water extractable carbon(HWC), acid hydrolyzed organic carbon(AHC Ⅰ, Ⅱ), and readily oxidized organic carbon(ROC). High amounts of maize stalk biochar up-regulated the contents of soil organic carbon SOC, HWC, AHC Ⅰ, AHC Ⅱ, and ROC. In addition, SWC and SP were the key physical factors to affect LOC fractions. In conclusions, maize stalk biochar could improve physical properties, and then influence LOC fractions, and maize stalk biochar could be used as an organic amendment for restoring degraded soils governed by their rates of addition.展开更多
文摘Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.
基金Supported by the Department of Ecology and Environment of Heilongjiang Province(HST2022ST003)。
文摘This paper conducted a systematic survey and zoogeographical region analysis of the family Sphingidae in the Guokui Mountain,Heilongjiang Province.Collections were made from May 2023 to August 2024 using the light-trap method.A total of 14 species and 11 subspecies from 18 genera and three subfamilies were recorded.One species(Ambulyx tobii)and two subspecies(Ambulyx japonica koreana and Clanis undulosa undulosa)were new records for Heilongjiang Province.The study showed that the subfamily Smerinthinae had the most species(subspecies),while the subfamily Sphinginae had the fewest.Among the world's zoogeographical region,most species(subspecies)in the Guokui Mountain belonged to the palearctic region,with eight species and seven subspecies were also found in the oriental region.This indicated a close biogeographic connection between the two regions.Among the Chinese zoogeographical regions,the northeastern territory,northern territory and northwestern territory had the most abundant species(subspecies).It was also found that the distribution pattern types of hawkmoths in the Guokui Mountain were diverse,with the'northeastern territory-northern territory-northwestern territory'and'northeastern territory-northern territorynorthwestern territory-western plateau-southwestern territory-central territory-southeastern territory'types having the most species(subspecies).In addition,the Guokui Mountain hawkmoths were mostly distributed interregionally.The distribution patterns that contained the northeastern territory were the most numerous,followed by the northern territory.The rich diversity of the family Sphingidae in the Guokui Mountain was closely related to the unique climate,environment and vegetation types in the area.The results could help to improve the biodiversity database of Heilongjiang Province and researches on hawkmoths.
基金supported by major national R&D projects(No.2023ZD04040-01)National Natural Science Foundation of China(No.5201101621)National Key R&D Plan(No.2022YFD1200304).
文摘Cotton is an essential agricultural commodity,but its global yield is greatly affected by climate change,which poses a serious threat to the agriculture sector.This review aims to provide an overview of the impact of climate change on cotton production and the use of genomic approaches to increase stress tolerance in cotton.This paper discusses the effects of rising temperatures,changing precipitation patterns,and extreme weather events on cotton yield.It then explores various genomic strategies,such as genomic selection and marker-assisted selection,which can be used to develop stress-tolerant cotton varieties.The review emphasizes the need for interdisciplinary research efforts and policy interventions to mitigate the adverse effects of climate change on cotton production.Furthermore,this paper presents advanced prospects,including genomic selection,gene editing,multi-omics integration,highthroughput phenotyping,genomic data sharing,climate-informed breeding,and phenomics-assisted genomic selection,for enhancing stress resilience in cotton.Those innovative approaches can assist cotton researchers and breeders in developing highly resilient cotton varieties capable of withstanding the challenges posed by climate change,ensuring the sustainable and prosperous future of cotton production.
基金Project(1212010) supported by the China Geological Survey for Ecosystem Geochemistry Assessment in City of Changsha,Zhuzhou and Xiangtan
文摘Samples were collected from two core sediments(C1 and C2) of Xiangjiang River,Chang-Zhu-Tan region,Hunan Province,China.The heavy metal contents are relatively higher,especially for the surface or near the surface layers.The calculated anthropogenic factor values indicate that all the heavy metals except for Cr in the core samples are enriched,especially for Cd,with the maximum enriching coefficients of 119.44,and 84.67 in C1 and C2,respectively.The correlation of heavy metals with sulphur indicates that they are precipitated as metal sulphides.Correlation matrix shows significant association between heavy metals and mud.Factor analysis identifies that signified anthropogenic activities affect the region of Xiangjiang River.
文摘The remote sensing snow cover data from Moderate Resolution Imaging Spectroradiometer(MODIS) satellite from 2000 to 2007 have been used to analyze some climate change indicators in the Himalayan region.In particular,the variability in the fractional snow coverage with elevations,its temporal variability (8-day,monthly and seasonal)and its
基金the National Nature Science Foundation of China(31770437)。
文摘The cold regions are located in high latitudes and cold climates.The local excellent ornamental plant resources are relatively scarce.The plant species that are suitable for both ornamental and productive benefits of landscape of flower sea construction are also even fewer.Therefore,it is imperative to introduce and screen the plant resources suitable for cold regions to create the landscape of flower sea.The rape,an oilseed crop,was used as a research object in order to create a productive flower landscape with both ornamental and economic values in cold regions.Four rape flower varieties,Qingza No.5,7,9,and 11,were introduced from Qinghai Hufeng Agricultural Science and Technology Group Co.,Ltd.They were planted in the experimental practice base of Northeast Agricultural University in three batches.Development characteristics and seed yield of rape flowers on different sowing dates were studied.The fuzzy probability method was used to comprehensively evaluate the varieties.The results showed that the rape flowers grew well in Harbin City during the experimental sowing period,which could form a good landscape of flower sea and had a considerable rapeseed yield.It could be widely used in cold urban and rural areas,such as Harbin City.In view of the experimental results,the strategies of creating a productive landscape of rape flower sea were proposed and the economic benefits were analyzed.It could change the status quo of a uniform landscape of flower sea in cold regions,help the development of rural tourism,and promote local economic income.
基金Project(52202426)supported by the National Natural Science Foundation of ChinaProjects(15205723,15226424)supported by the Research Grants Council of the Hong Kong Special Administrative Region(SAR),China+1 种基金Project(K2021J041)supported by the Technology Research and Development Program of China RailwayProject(1-BD23)supported by The Hong Kong Polytechnic University,China。
文摘In this work,the flow surrounding the train was obtained using a detached eddy simulation(DES)for slipstream analysis.Two different streamlined nose lengths were investigated:a short nose(4 m)and a long nose(9 m).The time-average slipstream velocity and the time-average slipstream pressure along the car bodies were compared and explained in detail.In addition to the time-averaged values,the _(max)imum velocities and the pressure peak-to-peak values around the two trains were analyzed.The result showed that the nose length affected the slipstream velocity along the entire train length at the lower and upper regions of the side of the train.However,no significant effect was recognized at the middle height of the train along its length,except in the nose region.Moreover,within the train’s side regions(y=2.0-2.5 m and z=2-4 m)and(y=2.5-3.5 m and z=0.2-0.7 m),the ratio of slipstream velocity U_(max) between the short and long nose trains was notably higher.This occurrence also manifested at the train’s upper section,specifically where y=0-2.5 m and z=4.2-5.0 m.Similarly,regarding the ratio of _(max)imum pressure peak-to-peak values Cp-p_(max),significant regions were observed at the train’s side(y=1.8-2.6 m and z=1-4 m)and above the train(y=0-2 m and z=3.9-4.8 m).
基金Science and Technology Major Project of Tibetan Autonomous Region of China(XZ202201ZD0005G02)National Natural Science Foundation of China(42277353)Chengdu Science and Technology Project(2022-YF05-01162-SN)。
文摘[Background]As one of the most serious environmental issues in the world,soil erosion causes water pollution,reservoir siltation,soil productivity decline,thus threatens agricultural systems and even affects global climate.The benefits of ecological soil and water conservation measures(ESWCMs,such as micro basins tillage and contour tillage)are widely understood,including runoff and soil loss reducing to a certain extent when compared with traditional tillage.While few studies have focused on China’s different soil types and erosion characteristics.[Methods]We reviewed literature from Web of Science,Scopus,and China National Knowledge Infrastructure using terms like“Conservation practice”“Contour tillage”“Runoff”“Sediment”“Erosion”and“China”and retained literatures based on criteria such as natural or simulated precipitation,runoff or soil loss data,reported replications and statistics,recorded factors like location and slope,and at least two data pairs per group.Ultimately,49 literatures were selected to quantify the impacts on different ESWCMs and identify the slope and precipitation for the greatest runoff and sediment reduction by calculating the log response ratio(LRR).[Results]The three regions’soil and water conservation benefits varied due to the differences in climate,terrain,and soil properties:1)ESWCMs applied in the black soil region of Northeast China were the most effective in reducing runoff and soil loss(66.65%runoff and 75.83%sediment),followed by those applied in the purple soil region of Southwest China(39.98%runoff and 58.30%sediment)and loess soil region of Northwest China(16.36%runoff and 32.44%sediment).2)Micro basins tillage(MBT)(71.79%runoff and 87.03%sediment)no-tillage with mulch(NTM)(17.30%runoff and 32.51%sediment),collecting soil to form a ridge with no-till(CSNT)(55.78%runoff and 71.36%sediment reduction)were the most efficient soil and water conservation measures in controlling water erosion in the black soil of Northeast China,the loess soil region of Northwest China and the purple soil region of Southwest China,respectively.3)The slope gradients ranged from 0-3°,>3°-5°and>10°-15°(0-3°:97.09%;>3°-5°:74.62%;and>10°-15°:39.41%)caused the largest reduction of runoff in the black soil region of Northeast China,the loess soil region of Northwest China,and the purple soil region of Southwest China.Meanwhile,the effects of sediment reduction were the most obvious,ranging from 0-3°,>10°-15°,and>20°-25°(0-3°:89.32%;>10°-15°:75.94%;and>20°-25°:67.25%).4)The effect of ESWCMs under rainstorms was the most obvious in the black soil region of Northeast China.The effect on runoff reduction under light rain in the purple soil region of Southwest China was the most obvious,but it failed to pass the significance test in sediment reduction.[Conclusions]The results provided optimal conservation tillage measures for three regions,different slopes and different rainfalls,and provided data support for reducing regional soil and water loss in China.
基金This work was supported by the National Key Research and Development Program of China(2022YFC3003101)the Fundamental Research Funds for the Central Universities(WK2320000050)the Science and Technology Program of State Grid Anhui Electric Power Co.,Ltd.(521205220001).
文摘Forest fire accidents caused by distribution line faults occur frequently,resulting in heavy impacts on people’s safety and social and economic development.Currently,there are few risk assessments for forest fires induced by over-head distribution lines,and existing assessment methods may have difficulties in data acquisition.On this basis,a novel as-sessment framework based on an analytic hierarchy process,a Bayesian network and a Fussel-Vesely importance metric is proposed in this paper.The framework combines field research and historical operation and maintenance data to assess the regional-scale risk of forest fires induced by overhead distribution lines to derive the probability of forest fires and to identify high-risk lines and key hazard events in the assessment region.Finally,taking the southern Anhui region as an ex-ample,the annual fire probability of forest fires induced by overhead distribution lines in the southern Anhui region is 5.88%,and rectification measures are proposed.This study provides management with a complete assessment framework that optimizes the difficulty of data collection and allows for additional targeted corrective measures to be proposed for the entire region and route on the basis of the assessment results.
基金Supported by the Strategic Priority Research Program(B)of Chinese Academy of Sciences(XDB0580000,XDB43010200)National Natural Science Foundation of China(62222514,62350073,U2341226,61991440)+6 种基金National Key Research and Development Program of China(2023YFA1406900)Shanghai Science and Technology Committee(23ZR1482000,22JC1402900,22ZR1472700)Natural Science Foundation of Zhejiang Province(LR22F050004)Shanghai Municipal Science and Technology Major Project(2019SHZDZX01)Youth Innovation Promotion Association(Y2021070)and International Partnership Program(112GJHZ2022002FN)of Chinese Academy of SciencesShanghai Human Resources and Social Security Bureau(2022670)China Postdoctoral Science Foundation(2023T160661,2022TQ0353 and 2022M713261).
文摘Metasurfaces provide a potent platform for the dynamic manipulation of electromagnetic waves.Coupled with phase-change materials,they facilitate the creation of versatile metadevices,showcasing various tunable functions based on the transition between amorphous and crystalline states.However,the inherent limitation in tunable states imposes constraints on the multiplexing channels of metadevices.Here,this paper introduces a novel approach-a multi-functional metadevice achieved through the two-level control of the encoding phasechange metaatoms.Utilizing the phase-change material Ge_(2)Sb_(2)Se_(4)Te1(GSST)and high refractive-index liquid diiodomethane(CH_(2)I_(2)),this paper showcases precise control over electromagnetic wave manipulation.The GSST state governs the tunable function,switching it ON and OFF,while the presence of liquid in the hole dictates the deflection angle when the tunable function is active.Importantly,our tunable coding metasurface exhibits robust performance across a broad wavelength spectrum.The incorporation of high refractive-index liquid extends the regulatory dimension of the metadevice,enabling dynamic switching of encoding bit levels.This two-level tunable metadevice,rooted in phase-change materials,presents a promising avenue for the dynamic control of functions.
基金This work was supported by the major research projects within the military-international class(JY2021B077).
文摘The laser-guided bomb(LGB)is an air-to-ground pre-cision-guided weapon that offers high hit rates,great power,and ease of use.LGBs are guided by semi-active laser ground-seek-ing technology,which means that atmospheric conditions can affect their accuracy.The spatial release region(SRR)of LGBs is difficult to calculate precisely,especially when there is a poor field of view.This can result in a lower real hit probability.To increase the hit probability of LGBs in tough atmospheric situa-tions,a novel method for calculating the SRR has been pro-posed.This method is based on the transmittance model of the 1.06μm laser in atmospheric species and the laser diffuse reflection model of the target surface to determine the capture target time of the laser seeker.Then,it calculates the boundary ballistic space starting position by ballistic model and gets the spatial scope of the spatial release region.This method can determine the release region of LGBs based on flight test data such as instantaneous velocity,altitude,off-axis angle,and atmospheric visibility.By more effectively employing aircraft release conditions,atmospheric visibility and other factors,the SRR calculation method can improve LGB hit probabi-lity by 9.2%.
基金This work was supported by the Natural Science Foundation of Heilongjiang Province(LH2022F049).
文摘Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.
基金Supported by the National Natural Science Foundation of China Project(31770582)。
文摘Biochar is widely used to improve soil physical properties and carbon sequestration. However, few studies focuse on the impact of maize stalk biochar on labile organic carbon(LOC) pool and the relationship between physical properties and LOC fractions. A field positioning experiment was performed in Mollisols region of Northeast China to evaluate the influence of maize stalk biochar on the spatial distribution and temporal changes of physical properties and LOC fractions. Maize stalk biochar treatments included C1(1.5 kg·hm^(-2)), C2(3 kg·hm^(-2)), C3(15 kg·hm^(-2)), C4(30 kg·hm^(-2)), and CK(0). The results showed that maize stalk biochar increased soil water contents(SWC) and soil porosity(SP), but reduced bulk density(BD). Maize stalk biochar reduced dissolved organic carbon(DOC) contents in the 0-20 cm soil layer, ranging from 0.25 g·kg^(-1) to 0.31 g·kg^(-1) in harvest period, while increased in the 20-40 cm soil layer. In addition, the application of biochar had a significant impact on the spatial distribution and temporal change of SWC, BD, SP, DOC, hot-water extractable carbon(HWC), acid hydrolyzed organic carbon(AHC Ⅰ, Ⅱ), and readily oxidized organic carbon(ROC). High amounts of maize stalk biochar up-regulated the contents of soil organic carbon SOC, HWC, AHC Ⅰ, AHC Ⅱ, and ROC. In addition, SWC and SP were the key physical factors to affect LOC fractions. In conclusions, maize stalk biochar could improve physical properties, and then influence LOC fractions, and maize stalk biochar could be used as an organic amendment for restoring degraded soils governed by their rates of addition.
