Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detectio...Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.展开更多
RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performa...RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.展开更多
This study develops a geological hazard evaluation index system for Shouning County,a key area for disaster prevention in Fujian Province.Through detailed investigation reports and field surveys,six factors were selec...This study develops a geological hazard evaluation index system for Shouning County,a key area for disaster prevention in Fujian Province.Through detailed investigation reports and field surveys,six factors were selected,including elevation,slope gradient,slope aspect,stratigraphic lithological group,distance from the water systems,and geological structures.A geological hazard susceptibility zoning map was created using the Information Quantity Method(IQM).The evaluation showed that elevation,slope aspect,and distance from the water systems are primary risk factors,with high and extremely high susceptibility areas covering 168.57 km^(2)(52.63%of the study area)and a disaster point density of 3.07 points/km^(2).The model achieved an accuracy of 0.73,validating its effectiveness in hazard assessment.These findings provide a valuable reference for disaster prediction and mitigation in Shouning County,supporting improved planning and risk management efforts.展开更多
The types and structures of inorganic pores are key factors in evaluations of the reservoir space and distribution characteristics of shale oil and gas.However,quantitative identification methods for pores of differen...The types and structures of inorganic pores are key factors in evaluations of the reservoir space and distribution characteristics of shale oil and gas.However,quantitative identification methods for pores of different inorganic components have not yet been fully developed.For this reason,a quantitative characterization method of inorganic pores using pixel information was proposed in this study.A machine learning algorithm was used to assist the field emission scanning electron microscopy(FE-SEM)image processing of shale to realize the accurate identification and quantitative characterization of inorganic pores on the surface of high-precision images of shale with a small view.Moreover,large-view image splicing technology,combined with quantitative evaluation of minerals by scanning electron microscopy(QEMSCAN)image joint characterization technology,was used to accurately analyze the distribution characteristics of inorganic pores under different mineral components.The quantitative methods of pore characteristics of different inorganic components under the pixel information of shale were studied.The results showed that(1)the Waikato Environment for Knowledge Analysis(WEKA)machine learning model can effectively identify and extract shale mineral components and inorganic pore distribution,and the large-view FE-SEM images are representative of samples at the 200μm×200μm view scale,meeting statistical requirements and eliminating the influence of heterogeneity;(2)the pores developed by different mineral components of shale had obvious differences,indicating that the development of inorganic pores is highly correlated with the properties of shale minerals themselves;and(3)the pore-forming ability of different mineral components is calculated by the quantitative method of single component pore-forming coefficient.Chlorite showed the highest pore-forming ability,followed by(in descending order)illite,pyrite,calcite,dolomite,albite,orthoclase,quartz,and apatite.This study contributes to advancing our understanding of inorganic pore characteristics in shale.展开更多
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
[Objectives]The paper was to screen new varieties of long cowpea that are suitable for autumn cultivation in Hunan,as well as to develop a comprehensive evaluation method to assess their adaptability and performance.[...[Objectives]The paper was to screen new varieties of long cowpea that are suitable for autumn cultivation in Hunan,as well as to develop a comprehensive evaluation method to assess their adaptability and performance.[Methods]A total of 48 long cowpea varieties were introduced,and a range of comprehensive evaluation methods was employed to assess these varieties through the collection and analysis of field data.[Results]The square Euclidean distance of 14 allowed for the classification of all varieties into eight distinct groups.Groups II,III,and V belong to the autumn dominant group within this region,while groups I and VIII belong to the intermediate group.Additionally,groups IV,VI,and VII belong to the autumn inferior group in this area.Through a comparative analysis of various comprehensive evaluation methods,it was determined that the common factor comprehensive evaluation,grey correlation method,and fuzzy evaluation method were appropriate for application in the selection of long cowpea varieties.Furthermore,the evaluation outcomes were largely consistent with the cluster pedigree diagram.[Conclusions]Through comprehensive index method,ten varieties demonstrating superior performance in autumn cultivation have been identified,including C20,C42,C29,C40,C3,C14,C18,C25,C15,and C47.The selected varieties exhibit several advantageous traits,such as a reduced growth duration,a lower position of initial flower nodes,a decreased number of branches,predominantly green young pods,elongated pod strips,thicker pod structures,an increased number of pods per plant,and higher overall yields.These characteristics render them particularly valuable for extensive cultivation.展开更多
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
Underground space resources are important for the purposes of urban sustainable development and are a significant means by which to realize three-dimensional urban development.A reasonable and scientific evaluation of...Underground space resources are important for the purposes of urban sustainable development and are a significant means by which to realize three-dimensional urban development.A reasonable and scientific evaluation of underground space resources is the foundation for the rational use of land resources and urban planning.On the basis of the geological conditions used by preceding researchers,this study adds the analysis of two influencing factors of social and economic value,alongside existing facilities and protection needs.The evaluation index is quantified and the comprehensive quality evaluation system of underground space resources is constructed.Finally,taking the Nanshan District of Shenzhen as an example,the evaluation of underground space resources is carried out.The results show that for shallow underground space,the comprehensive quality of underground space resources development in Nanshan District is generally high.Nantou,Nanshan and Yuehai streets are recommended as areas to actively develop underground space,whereas the Qianhai and Houhai areas are recommended to be used with caution in the development and construction of their underground space.In addition,this study also provides a reference for the purposes of underground space planning in the Nanshan district of Shenzhen.展开更多
This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standar...This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.展开更多
The method for precursor information acquisition based on acoustic emission(AE)data for jointed rock masses is of significant importance for the early warning of dynamic disasters in underground engineering.A clusteri...The method for precursor information acquisition based on acoustic emission(AE)data for jointed rock masses is of significant importance for the early warning of dynamic disasters in underground engineering.A clustering-convolutional neural network(CNN)method is proposed,which comprises a clustering component and a CNN component.A series of uniaxial compression tests were conducted on granite specimens containing a persistent sawtooth joint,with different strain rates(105e102 s1)and joint inclination angles(0e50).The results demonstrate that traditional precursory indicators based on full waveforms are effective for obtaining precursor information of the intact rock failure.However,these indicators are not universally applicable to the failure of rock masses with a single joint.The clustering-CNN method has the potential to be applied to obtain precursor information for all three failure modes(Modes I,II and III).Following the waveform clustering analysis,the effective waveforms exhibit a low main frequency,as well as high energy,ringing count,and rise time.Furthermore,the clustering method and the precursory indicators influence the acquisition of final precursor information.The Birch hierarchical clustering method and the S value precursory indicator can help to obtain more accurate results.The findings of this study may contribute to the development of warning methods for underground engineering across faults.展开更多
To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and obj...To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.展开更多
By integrating the merits of the map overlay method and the geographic information system (GIS), a GIS based map overlay method was developed to analyze comprehensively the environmental vulnerability around railway a...By integrating the merits of the map overlay method and the geographic information system (GIS), a GIS based map overlay method was developed to analyze comprehensively the environmental vulnerability around railway and its impact on the environment, which is adapted for the comprehensive assessment of railway environmental impact and the optimization of railway alignments. The assessment process of the GIS based map overlay method was presented, which includes deciding the system structure and weights of assessment factors, making environmental vulnerability grade maps, and evaluating the alternative alignments comprehensively to obtain the best one. With the GIS functions of spatial analysis, such as overlay analysis and buffer analysis, and functions of handling attribute data, the GIS based map overlay method overcomes the shortcomings of the existing map overlay method and the conclusion is more reasonable. In the end, a detailed case study was illustrated to verify the efficiency of the method.展开更多
This study explores the influence of after-school tutoring on reading comprehension skills of students with dyslexia(DD)in grades 3-5 in China and its participating factors.Using a mixed-methods design,the quantitativ...This study explores the influence of after-school tutoring on reading comprehension skills of students with dyslexia(DD)in grades 3-5 in China and its participating factors.Using a mixed-methods design,the quantitative data(GORT-4 reading test)of 50 public primary school students in Qingdao and their parents’feedback were collected through questionnaires,supplemented by semi-structured interviews with eight parents for qualitative analysis.The findings are as follows:(1)Family socioeconomic status and parents’awareness of DD are the key factors to participate in after-school counseling;(2)The students who participated in the after-school counseling performed significantly better in the GORT-4 comprehension test(P<0.05);(3)Counseling makes up for the lack of classroom learning through personalized strategies(such as multi-sensory teaching and phonological awareness training),but parents’psychological support is the core of successful intervention.The necessity of early targeted intervention was emphasized,and practical enlightenment was provided for the educational support system of DD students in China.展开更多
During fully mechanized caving mining of thick coal seams,a large amount of strain energy accumulates in the roof,especially when the roof is thick and hard,making it difficultfor the roof to collapse naturally.When t...During fully mechanized caving mining of thick coal seams,a large amount of strain energy accumulates in the roof,especially when the roof is thick and hard,making it difficultfor the roof to collapse naturally.When the roof eventually collapses,the accumulated energy is released instantaneously,exerting a strong impact on the roadway.To address this issue,we proposed the synergistic control method of directional comprehensive pressure relief and energy-absorbing support(PREA)for roadways with hard roofs.In this study,we developed a three-dimensional physical model test apparatus for roof cutting and pressure relief.The 122108 ventilation roadway at the Caojiatan Coal Mine,which has a thick and hard roof,was taken as the engineering example.We analyzed the evolution patterns of stress and displacement in both the stope and the roadway surrounding rocks under different schemes.The PREA reinforcement mechanism for the roadway was investigated through comparative model tests between the new and original methods.The results showed that,compared to the original method,the new method reduced surrounding rock stress by up to 60.4%,and the roadway convergence decreased by up to 52.1%.Based on these results,we proposed corresponding engineering recommendations,which can guide fieldreinforcement design and application.The results demonstrate that the PREA method effectively reduces stress and ensures the safety and stability of the roadway.展开更多
Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex ...Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex web pages.Through ana-lyzing various statistical characteristics of HTML el-ements in web documents,this paper proposes,based on statistical features,an unsupervised web data ex-traction method—traversing the HTML DOM parse tree at first,calculating and generating the statistical matrix of the elements,and then locating data records by clustering method and heuristic rules that reveal in-herent links between the visual characteristics of the data recording areas and the statistical characteristics of the HTML nodes—which is both suitable for data records extraction of single-page and multi-pages,and it has strong generality and needs no training.The ex-periments show that the accuracy and efficiency of this method are equally better than the current data extrac-tion method.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deplo...Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deploying solar power plants.This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process(AHP),Fuzzy Analytical Hierarchy Process(FAHP),and Full Consistency Method(FUCOM).The results show that 35%of the Chadian territory,i.e.,an area of 449,400 km2,is compatible with the implementation of Concentrating Solar Power.The North,North,East,Southeast,and East zones are the most suitable.The main criteria for influence are direct normal irradiation,the soil slope,and the water resource.FUCOM gave a weight of 41.9%for Direct Normal Irradiation(DNI)compared to 32.71%and 31.81%for AHP and FAHP.This method can be applied to other renewable energy technologies such as photovoltaics,wind power,and biomass.Combining its different analyses will be a valuable tool for planning any renewable energy project in Chad.This work should also facilitate the techno-economic analysis of future CSP plants in Chad.展开更多
We propose a hierarchical multi-scale attention mechanism-based model in response to the low accuracy and inefficient manual classification of existing oceanic biological image classification methods. Firstly, the hie...We propose a hierarchical multi-scale attention mechanism-based model in response to the low accuracy and inefficient manual classification of existing oceanic biological image classification methods. Firstly, the hierarchical efficient multi-scale attention(H-EMA) module is designed for lightweight feature extraction, achieving outstanding performance at a relatively low cost. Secondly, an improved EfficientNetV2 block is used to integrate information from different scales better and enhance inter-layer message passing. Furthermore, introducing the convolutional block attention module(CBAM) enhances the model's perception of critical features, optimizing its generalization ability. Lastly, Focal Loss is introduced to adjust the weights of complex samples to address the issue of imbalanced categories in the dataset, further improving the model's performance. The model achieved 96.11% accuracy on the intertidal marine organism dataset of Nanji Islands and 84.78% accuracy on the CIFAR-100 dataset, demonstrating its strong generalization ability to meet the demands of oceanic biological image classification.展开更多
[Objective] The aim was to propose a new entropy weight fuzzy compre- hensive evaluation method for assessing cotton salt tolerance, realizing the objective, accurate and comprehensive evaluation of salt tolerance of ...[Objective] The aim was to propose a new entropy weight fuzzy compre- hensive evaluation method for assessing cotton salt tolerance, realizing the objective, accurate and comprehensive evaluation of salt tolerance of cotton. [Method] A sand culture experiment under salt stress of 150 mmol/L of NaCI was designed. The in- dicator weight was determined with the entropy weight fuzzy comprehensive evalu- ation method, based on the salt injury index of indicators. The salt tolerance of cotton was evaluated comprehensively. [Result] At the germination stage, the entropy and weight of salt injury index of germination energy, vigor index, hypocotyl length and fresh weight were highest, followed by germination rate and germination index, and of root length were lowest. At the seedling stage, the entropy and weight of salt injury index of plasma membrane permeability, root vigor and leaf expansion rate were highest, followed by plant height and net photosynthetic rate, and of shoot dry weight and root dry weight were lowest. The salt tolerance of cotton differed a- mong growth stages and cultivars. Among the 11 cultivars, CCRI-44 and CCRI-75 were steadily salt-tolerant at both germination and seedling stages; CCRI-17, Sumi- an 22, Sumian 15 and Dexiamianl had a stable moderate salt tolerance; while Sumian 12 and Simian 3 were steadily salt-sensitive. [Conclusion] The evaluated result was objective and exact, which indicated that this method could be used in comprehensive evaluation of salt tolerance of cotton.展开更多
A multi-level evaluation model for the superstructure of a damaged prestressed concrete girder or beam bridge is established, and the evaluation indices of the model as well as the rating standards are defined. A norm...A multi-level evaluation model for the superstructure of a damaged prestressed concrete girder or beam bridge is established, and the evaluation indices of the model as well as the rating standards are defined. A normal relative function about the evaluation indices of each element is developed to calculate the relative degree, and for each element there are no sub-level elements. When evaluating the elements in the sub-item level or the index level of the model, the weights of elements pertain to one adopted element, taking into account their degrees of deterioration. Since the relative degrees and structure evaluation scales on the damage conditions are applied to characterize the superstructure of damaged prestressed concrete girder bridges, this method can evaluate the prestressed structure in detail, and the evaluation results agree with the Code for Maintenance of Highway Bridges and Culvers （JTG Hll--2004 ）. Finally, a bridge in Jilin province is taken as an example, using the method developed to evaluate its damage conditions, which gives an effective way for bridge engineering.展开更多
基金National Natural Science Foundation of China(grant numbers 42293351,41877239,51422904 and 51379112).
文摘Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.
基金supported by grants from the National Science Foundation of China(Grant Nos.12375038 and 12075171 to ZJT,and 12205223 to YLT).
文摘RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.
基金2024 Guiding Science and Technology Program of Fujian Province(No.2024H0026)2025 Innovation Fund Project of Fujian Province(No.2025C0004).
文摘This study develops a geological hazard evaluation index system for Shouning County,a key area for disaster prevention in Fujian Province.Through detailed investigation reports and field surveys,six factors were selected,including elevation,slope gradient,slope aspect,stratigraphic lithological group,distance from the water systems,and geological structures.A geological hazard susceptibility zoning map was created using the Information Quantity Method(IQM).The evaluation showed that elevation,slope aspect,and distance from the water systems are primary risk factors,with high and extremely high susceptibility areas covering 168.57 km^(2)(52.63%of the study area)and a disaster point density of 3.07 points/km^(2).The model achieved an accuracy of 0.73,validating its effectiveness in hazard assessment.These findings provide a valuable reference for disaster prediction and mitigation in Shouning County,supporting improved planning and risk management efforts.
基金supported by the National Natural Science Foundation of China(42372144)the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2024D01E09)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX2020-01-05).
文摘The types and structures of inorganic pores are key factors in evaluations of the reservoir space and distribution characteristics of shale oil and gas.However,quantitative identification methods for pores of different inorganic components have not yet been fully developed.For this reason,a quantitative characterization method of inorganic pores using pixel information was proposed in this study.A machine learning algorithm was used to assist the field emission scanning electron microscopy(FE-SEM)image processing of shale to realize the accurate identification and quantitative characterization of inorganic pores on the surface of high-precision images of shale with a small view.Moreover,large-view image splicing technology,combined with quantitative evaluation of minerals by scanning electron microscopy(QEMSCAN)image joint characterization technology,was used to accurately analyze the distribution characteristics of inorganic pores under different mineral components.The quantitative methods of pore characteristics of different inorganic components under the pixel information of shale were studied.The results showed that(1)the Waikato Environment for Knowledge Analysis(WEKA)machine learning model can effectively identify and extract shale mineral components and inorganic pore distribution,and the large-view FE-SEM images are representative of samples at the 200μm×200μm view scale,meeting statistical requirements and eliminating the influence of heterogeneity;(2)the pores developed by different mineral components of shale had obvious differences,indicating that the development of inorganic pores is highly correlated with the properties of shale minerals themselves;and(3)the pore-forming ability of different mineral components is calculated by the quantitative method of single component pore-forming coefficient.Chlorite showed the highest pore-forming ability,followed by(in descending order)illite,pyrite,calcite,dolomite,albite,orthoclase,quartz,and apatite.This study contributes to advancing our understanding of inorganic pore characteristics in shale.
基金supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
文摘The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
基金Supported by China Agricultural Industry Research System(CARS-23-G31)Technology Innovation Guidance Project of Changde City(CDKJJ20220265,CDKJJ2023YF33).
文摘[Objectives]The paper was to screen new varieties of long cowpea that are suitable for autumn cultivation in Hunan,as well as to develop a comprehensive evaluation method to assess their adaptability and performance.[Methods]A total of 48 long cowpea varieties were introduced,and a range of comprehensive evaluation methods was employed to assess these varieties through the collection and analysis of field data.[Results]The square Euclidean distance of 14 allowed for the classification of all varieties into eight distinct groups.Groups II,III,and V belong to the autumn dominant group within this region,while groups I and VIII belong to the intermediate group.Additionally,groups IV,VI,and VII belong to the autumn inferior group in this area.Through a comparative analysis of various comprehensive evaluation methods,it was determined that the common factor comprehensive evaluation,grey correlation method,and fuzzy evaluation method were appropriate for application in the selection of long cowpea varieties.Furthermore,the evaluation outcomes were largely consistent with the cluster pedigree diagram.[Conclusions]Through comprehensive index method,ten varieties demonstrating superior performance in autumn cultivation have been identified,including C20,C42,C29,C40,C3,C14,C18,C25,C15,and C47.The selected varieties exhibit several advantageous traits,such as a reduced growth duration,a lower position of initial flower nodes,a decreased number of branches,predominantly green young pods,elongated pod strips,thicker pod structures,an increased number of pods per plant,and higher overall yields.These characteristics render them particularly valuable for extensive cultivation.
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金The project of the Chinese Geological Survey'Survey of geothermal resources in the northern branch of Luoxiao Mountains'(Grant No.DD20221677-2)the special funds for basic scientific research business'Research on dome structure and circulation mechanism of annular hot spring chain'(Grant No.JKY202004)funded this research project。
文摘Underground space resources are important for the purposes of urban sustainable development and are a significant means by which to realize three-dimensional urban development.A reasonable and scientific evaluation of underground space resources is the foundation for the rational use of land resources and urban planning.On the basis of the geological conditions used by preceding researchers,this study adds the analysis of two influencing factors of social and economic value,alongside existing facilities and protection needs.The evaluation index is quantified and the comprehensive quality evaluation system of underground space resources is constructed.Finally,taking the Nanshan District of Shenzhen as an example,the evaluation of underground space resources is carried out.The results show that for shallow underground space,the comprehensive quality of underground space resources development in Nanshan District is generally high.Nantou,Nanshan and Yuehai streets are recommended as areas to actively develop underground space,whereas the Qianhai and Houhai areas are recommended to be used with caution in the development and construction of their underground space.In addition,this study also provides a reference for the purposes of underground space planning in the Nanshan district of Shenzhen.
文摘This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.
基金support from the National Natural Science Foundation of China(Grant Nos.52079134 and 51991393).
文摘The method for precursor information acquisition based on acoustic emission(AE)data for jointed rock masses is of significant importance for the early warning of dynamic disasters in underground engineering.A clustering-convolutional neural network(CNN)method is proposed,which comprises a clustering component and a CNN component.A series of uniaxial compression tests were conducted on granite specimens containing a persistent sawtooth joint,with different strain rates(105e102 s1)and joint inclination angles(0e50).The results demonstrate that traditional precursory indicators based on full waveforms are effective for obtaining precursor information of the intact rock failure.However,these indicators are not universally applicable to the failure of rock masses with a single joint.The clustering-CNN method has the potential to be applied to obtain precursor information for all three failure modes(Modes I,II and III).Following the waveform clustering analysis,the effective waveforms exhibit a low main frequency,as well as high energy,ringing count,and rise time.Furthermore,the clustering method and the precursory indicators influence the acquisition of final precursor information.The Birch hierarchical clustering method and the S value precursory indicator can help to obtain more accurate results.The findings of this study may contribute to the development of warning methods for underground engineering across faults.
基金support of the project“State Grid Corporation Headquarters Science and Technology Program(5108-202299258A-1-0-ZB)”.
文摘To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.
文摘By integrating the merits of the map overlay method and the geographic information system (GIS), a GIS based map overlay method was developed to analyze comprehensively the environmental vulnerability around railway and its impact on the environment, which is adapted for the comprehensive assessment of railway environmental impact and the optimization of railway alignments. The assessment process of the GIS based map overlay method was presented, which includes deciding the system structure and weights of assessment factors, making environmental vulnerability grade maps, and evaluating the alternative alignments comprehensively to obtain the best one. With the GIS functions of spatial analysis, such as overlay analysis and buffer analysis, and functions of handling attribute data, the GIS based map overlay method overcomes the shortcomings of the existing map overlay method and the conclusion is more reasonable. In the end, a detailed case study was illustrated to verify the efficiency of the method.
文摘This study explores the influence of after-school tutoring on reading comprehension skills of students with dyslexia(DD)in grades 3-5 in China and its participating factors.Using a mixed-methods design,the quantitative data(GORT-4 reading test)of 50 public primary school students in Qingdao and their parents’feedback were collected through questionnaires,supplemented by semi-structured interviews with eight parents for qualitative analysis.The findings are as follows:(1)Family socioeconomic status and parents’awareness of DD are the key factors to participate in after-school counseling;(2)The students who participated in the after-school counseling performed significantly better in the GORT-4 comprehension test(P<0.05);(3)Counseling makes up for the lack of classroom learning through personalized strategies(such as multi-sensory teaching and phonological awareness training),but parents’psychological support is the core of successful intervention.The necessity of early targeted intervention was emphasized,and practical enlightenment was provided for the educational support system of DD students in China.
基金supported by the National Natural Science Foundation of China(Grant Nos.U24A2088 and 42277174)the Fundamental Research Funds for the Central Universities,China(Grant No.2024JCCXSB01).
文摘During fully mechanized caving mining of thick coal seams,a large amount of strain energy accumulates in the roof,especially when the roof is thick and hard,making it difficultfor the roof to collapse naturally.When the roof eventually collapses,the accumulated energy is released instantaneously,exerting a strong impact on the roadway.To address this issue,we proposed the synergistic control method of directional comprehensive pressure relief and energy-absorbing support(PREA)for roadways with hard roofs.In this study,we developed a three-dimensional physical model test apparatus for roof cutting and pressure relief.The 122108 ventilation roadway at the Caojiatan Coal Mine,which has a thick and hard roof,was taken as the engineering example.We analyzed the evolution patterns of stress and displacement in both the stope and the roadway surrounding rocks under different schemes.The PREA reinforcement mechanism for the roadway was investigated through comparative model tests between the new and original methods.The results showed that,compared to the original method,the new method reduced surrounding rock stress by up to 60.4%,and the roadway convergence decreased by up to 52.1%.Based on these results,we proposed corresponding engineering recommendations,which can guide fieldreinforcement design and application.The results demonstrate that the PREA method effectively reduces stress and ensures the safety and stability of the roadway.
文摘Web data extraction has become a key technology for extracting valuable data from websites.At present,most extraction methods based on rule learning,visual pattern or tree matching have limited performance on complex web pages.Through ana-lyzing various statistical characteristics of HTML el-ements in web documents,this paper proposes,based on statistical features,an unsupervised web data ex-traction method—traversing the HTML DOM parse tree at first,calculating and generating the statistical matrix of the elements,and then locating data records by clustering method and heuristic rules that reveal in-herent links between the visual characteristics of the data recording areas and the statistical characteristics of the HTML nodes—which is both suitable for data records extraction of single-page and multi-pages,and it has strong generality and needs no training.The ex-periments show that the accuracy and efficiency of this method are equally better than the current data extrac-tion method.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
文摘Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deploying solar power plants.This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process(AHP),Fuzzy Analytical Hierarchy Process(FAHP),and Full Consistency Method(FUCOM).The results show that 35%of the Chadian territory,i.e.,an area of 449,400 km2,is compatible with the implementation of Concentrating Solar Power.The North,North,East,Southeast,and East zones are the most suitable.The main criteria for influence are direct normal irradiation,the soil slope,and the water resource.FUCOM gave a weight of 41.9%for Direct Normal Irradiation(DNI)compared to 32.71%and 31.81%for AHP and FAHP.This method can be applied to other renewable energy technologies such as photovoltaics,wind power,and biomass.Combining its different analyses will be a valuable tool for planning any renewable energy project in Chad.This work should also facilitate the techno-economic analysis of future CSP plants in Chad.
基金supported by the National Natural Science Foundation of China (Nos.61806107 and 61702135)。
文摘We propose a hierarchical multi-scale attention mechanism-based model in response to the low accuracy and inefficient manual classification of existing oceanic biological image classification methods. Firstly, the hierarchical efficient multi-scale attention(H-EMA) module is designed for lightweight feature extraction, achieving outstanding performance at a relatively low cost. Secondly, an improved EfficientNetV2 block is used to integrate information from different scales better and enhance inter-layer message passing. Furthermore, introducing the convolutional block attention module(CBAM) enhances the model's perception of critical features, optimizing its generalization ability. Lastly, Focal Loss is introduced to adjust the weights of complex samples to address the issue of imbalanced categories in the dataset, further improving the model's performance. The model achieved 96.11% accuracy on the intertidal marine organism dataset of Nanji Islands and 84.78% accuracy on the CIFAR-100 dataset, demonstrating its strong generalization ability to meet the demands of oceanic biological image classification.
基金Supported by Jiangsu Agricultural Science and Technology Innovation Fund(CX(12)5035)Jiangsu Agricultural "Three New Engineering" Project(SXGC[2014]299)~~
文摘[Objective] The aim was to propose a new entropy weight fuzzy compre- hensive evaluation method for assessing cotton salt tolerance, realizing the objective, accurate and comprehensive evaluation of salt tolerance of cotton. [Method] A sand culture experiment under salt stress of 150 mmol/L of NaCI was designed. The in- dicator weight was determined with the entropy weight fuzzy comprehensive evalu- ation method, based on the salt injury index of indicators. The salt tolerance of cotton was evaluated comprehensively. [Result] At the germination stage, the entropy and weight of salt injury index of germination energy, vigor index, hypocotyl length and fresh weight were highest, followed by germination rate and germination index, and of root length were lowest. At the seedling stage, the entropy and weight of salt injury index of plasma membrane permeability, root vigor and leaf expansion rate were highest, followed by plant height and net photosynthetic rate, and of shoot dry weight and root dry weight were lowest. The salt tolerance of cotton differed a- mong growth stages and cultivars. Among the 11 cultivars, CCRI-44 and CCRI-75 were steadily salt-tolerant at both germination and seedling stages; CCRI-17, Sumi- an 22, Sumian 15 and Dexiamianl had a stable moderate salt tolerance; while Sumian 12 and Simian 3 were steadily salt-sensitive. [Conclusion] The evaluated result was objective and exact, which indicated that this method could be used in comprehensive evaluation of salt tolerance of cotton.
文摘A multi-level evaluation model for the superstructure of a damaged prestressed concrete girder or beam bridge is established, and the evaluation indices of the model as well as the rating standards are defined. A normal relative function about the evaluation indices of each element is developed to calculate the relative degree, and for each element there are no sub-level elements. When evaluating the elements in the sub-item level or the index level of the model, the weights of elements pertain to one adopted element, taking into account their degrees of deterioration. Since the relative degrees and structure evaluation scales on the damage conditions are applied to characterize the superstructure of damaged prestressed concrete girder bridges, this method can evaluate the prestressed structure in detail, and the evaluation results agree with the Code for Maintenance of Highway Bridges and Culvers （JTG Hll--2004 ）. Finally, a bridge in Jilin province is taken as an example, using the method developed to evaluate its damage conditions, which gives an effective way for bridge engineering.
