The effect of pruning severity on tree growth was analyzed by change point detection using segmented regression. The present study applied this analysis to a well-known published data set including diameter growth res...The effect of pruning severity on tree growth was analyzed by change point detection using segmented regression. The present study applied this analysis to a well-known published data set including diameter growth response, tree age, pruning severity and pretreatment crown size. First, multiple regression analysis was performed to assess the effect of tree age, pruning severity and pretreatment crown size on diameter growth response. Next, segmented regression analysis was performed to assess the effect of pruning severity on diameter growth response. The results of the multiple regression showed that diameter growth response was significantly influenced by pruning severity and pretreatment crown size. The results of the segmented regression showed that in the whole data set, an abrupt change toward a decrease in diameter growth response was detected at 25% of the live crown removed. However, in the group of fully crowned and open-grown, diameter growth response continuously decreased with increasing pruning severity with no significant abrupt change, whereas in the group of 70% - 90% live crown, diameter growth response did not significantly decrease up to the break point (53% crown removed) and then abruptly decreased. This may be the first study to show the numerical evaluation of the effect of pruning severity on tree growth by change point analysis.展开更多
This study investigates the use of a decision tree classification model, combined with Principal Component Analysis (PCA), to distinguish between Assam and Bhutan ethnic groups based on specific anthropometric feature...This study investigates the use of a decision tree classification model, combined with Principal Component Analysis (PCA), to distinguish between Assam and Bhutan ethnic groups based on specific anthropometric features, including age, height, tail length, hair length, bang length, reach, and earlobe type. The dataset was reduced using PCA, which identified height, reach, and age as key features contributing to variance. However, while PCA effectively reduced dimensionality, it faced challenges in clearly distinguishing between the two ethnic groups, a limitation noted in previous research. In contrast, the decision tree model performed significantly better, establishing clear decision boundaries and achieving high classification accuracy. The decision tree consistently selected Height and Reach as the most important classifiers, a finding supported by existing studies on ethnic differences in Northeast India. The results highlight the strengths of combining PCA for dimensionality reduction with decision tree models for classification tasks. While PCA alone was insufficient for optimal class separation, its integration with decision trees improved both the model’s accuracy and interpretability. Future research could explore other machine learning models to enhance classification and examine a broader set of anthropometric features for more comprehensive ethnic group classification.展开更多
In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest a...In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.展开更多
To assess road traffic safety risk in civil aviation airports and develop effective accident prevention measures,this study proposed a risk assessment method based on accident tree and Bayesian network for airport air...To assess road traffic safety risk in civil aviation airports and develop effective accident prevention measures,this study proposed a risk assessment method based on accident tree and Bayesian network for airport aircraft activity areas.It identified influencing factors in the aircraft activity area from the perspectives of person-vehicle-road-environment-management and analyzed their relationships.The Bayesian network was utilized to determine initial probabilities for each influencing factor.Findings indicated a relatively high overall safety level in the airport's road traffic system.Accident trees were employed to qualitatively and quantitatively analyze common human-vehicle accident patterns.The initial probabilities obtained from the Bayesian network served as basic event probabilities in the accident tree to determine the occurrence probability of the top event.Taking a 4F airport in China as an example,accident cause analysis identified five important risk sources in human-vehicle accidents,including blind spots for special vehicles,illegal driving by drivers,pedestrians violating regulations,passengers entering restricted areas,and blind spots at intersections.Corresponding safety management measures were formulated.The study concluded that the integration of Bayesian networks and accident trees effectively determines accident probabilities and offers specific solutions,thus playing a crucial role in enhancing road traffic safety management within aviation airports.展开更多
This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic ...This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.展开更多
A logic fault tree of mine spontaneous combustion of sulphide ores was built by the fault tree analysis (FTA) based on a lot of mechanism investigation of sulphide ore spontaneous combustion in more than ten mines an...A logic fault tree of mine spontaneous combustion of sulphide ores was built by the fault tree analysis (FTA) based on a lot of mechanism investigation of sulphide ore spontaneous combustion in more than ten mines and review of a great amount of relevant展开更多
During the past decade, coal dust and gas explosions have been the most two serious types of disasters in China, threatening the lives of miners and causing significant losses in terms of national property. In this pa...During the past decade, coal dust and gas explosions have been the most two serious types of disasters in China, threatening the lives of miners and causing significant losses in terms of national property. In this paper, an evaluation model of coal dust and gas explosions was constructed based on a fuzzy fault tree by taking the Xingli Coal Mine as a research site to identify the risk factors of coal dust and gas explosions.Furthermore, the hazards associated with such explosions were evaluated for this particular coal mine.After completing an on-site investigation, the fuzzy probabilities of basic events were obtained through expert scoring, and these expert opinions were then aggregated as trapezoidal fuzzy numbers to calculate the degrees of importance of all basic events. Finally, these degrees of importance were sorted. According to the resulting order, the basic events with higher probabilities were determined to identify key hazards in the daily safety management of this particular coal mine. Moreover, effective measures for preventing gas and coal dust explosions were derived. The fuzzy fault tree analysis method is of high significance in the analysis of accidental coal mine explosions and provides theoretical guidance for improving the efficiency of coal mine safety management in a scientific and feasible manner.展开更多
OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatm...OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.展开更多
Random amplified polymorphic DNA (RAPD) was used to analyze genetic polymophism of 35 Tree Peony cultivars with 7 different color groups. Thirty four primers amplified 418 DNA fragments and 337 polymorphic bands (80.6...Random amplified polymorphic DNA (RAPD) was used to analyze genetic polymophism of 35 Tree Peony cultivars with 7 different color groups. Thirty four primers amplified 418 DNA fragments and 337 polymorphic bands (80.6%), including specific DNA markers for 18 cultivars that could be used to differentiate cultivars. The UPCMA method was used to analyze the genetic relationship among cultivars. The results showed that 35 Peony cultivars could be divided into 2 cluster groups when using similarity criteria of 1.5, and into 4 cluster groups when using similarity criteria of 1.0. The result confirmed that the flower color has no relation to the genetic clusters and the Tree Peony cultivars originated from the same area has close genetic relationship. Therefore, genetic background has no large effect on the genetic relationship. The sequence based on polymorphic rate from high to low was Blue groups > Yellow groups > Bark red groups > Blake groups > White groups>Green groups>Red groups.展开更多
Tree peony(Paeonia section Moutan DC.)seeds are an excellent source of beneficial natural compounds that promote health,and they contain high levels of alpha-linolenic acid(ALA).In recent years,tree peony has been eme...Tree peony(Paeonia section Moutan DC.)seeds are an excellent source of beneficial natural compounds that promote health,and they contain high levels of alpha-linolenic acid(ALA).In recent years,tree peony has been emerging as an oil crop.Therefore,combined analysis of the transcriptome and proteome of tree peony(P.ostii)seeds at 25,32,39,53,67,81,88,95,and 109 days after pollination(DAP)was conducted to better understand the transcriptional and translational regulation of seed development and oil biosynthesis.A total of 38,482 unigenes and 2841 proteins were identified.A total of 26,912 differentially expressed genes(DEGs)and 592 differentially expressed proteins(DEPs)were clustered into three groups corresponding to the rapid growth,seed inclusion enrichment and conversion,and late dehydration and mature stages of seed development.Fifteen lipid metabolism pathways were identified at both the transcriptome and proteome levels.Pathway enrichment analysis revealed that a period of rapid fatty acid biosynthesis occurred at 53–88 DAP.Furthermore,211 genes and 35 proteins associated with the fatty acid metabolism pathway,63 genes and 11 proteins associated with the biosynthesis of unsaturated fatty acids(UFAs),and 115 genes and 24 proteins associated with ALA metabolism were identified.Phylogenetic analysis revealed that 16 putative fatty acid desaturase(FAD)-encoding genes clustered into four FAD groups,eight of which exhibited the highest expression at 53 DAP,suggesting that they play an important role in ALA accumulation.RT-qPCR analysis indicated that the temporal expression patterns of oil biosynthesis genes were largely similar to the RNA-seq results.The expression patterns of fatty acid metabolism-and seed development-related proteins determined by MRM were also highly consistent with the results obtained in the proteomic analysis.Correlation analysis indicated significant differences in the number and abundance of DEGs and DEPs but a high level of consistency in expression patterns and metabolic pathways.The results of the present study represent the first combined transcriptomic and proteomic analysis of tree peony seeds and provide insight into tree peony seed development and oil accumulation.展开更多
A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and ...A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and safety and reliability analyses are increasingly required for these systems.SEFTs combine elements from the traditional fault tree with elements from state-based techniques.In the context of the real-time safety-critical systems,SEFTs do not describe the time properties and important timedependent system behaviors that can lead to system failures.Further,SEFTs lack the precise semantics required for formally modeling time behaviors.In this paper,we present a qualitative analysis method for SEFTs based on transformation from SEFT to timed automata(TA),and use the model checker UPPAAL to verify system requirements’properties.The combination of SEFT and TA is an important step towards an integrated design and verification process for real-time safety-critical systems.Finally,we present a case study of a powerboat autopilot system to confirm our method is viable and valid after achieving the verification goal step by step.展开更多
By using the fault tree analysis in reliability theory as the systematical analysis approach, the dust suppression mechanism in a spray system with wetting agent is shown in a logic tree and some graphical models. Fro...By using the fault tree analysis in reliability theory as the systematical analysis approach, the dust suppression mechanism in a spray system with wetting agent is shown in a logic tree and some graphical models. From these diagrams, all factors related to the spray system and their cause and effect relationship can be seen clearly. Based on the built logic tree, several mathematical models and new ideas for expressing the dust suppressing efficiency in the spray system are put forward. The significance of all factors related to the efficiency of suppressing dust is qualitatively described. Furthermore, the new concepts, such as, the effective reaction time between dust particle and droplet, the expansion phenomenon of laden dust droplet, the functions of volatile and the relative size distribution efficiency of wetting agent are presented. All this richenes the existing mechanism of dust abatement by spraying wetting agent. At last, several problems that need to be further investigated are also suggested in the paper.展开更多
Fetal distress is one of the main factors to cesarean section in obstetrics and gynecology. If the fetus lack of oxygen in uterus, threat to the fetal health and fetal death could happen. Cardiotocography (CTG) is the...Fetal distress is one of the main factors to cesarean section in obstetrics and gynecology. If the fetus lack of oxygen in uterus, threat to the fetal health and fetal death could happen. Cardiotocography (CTG) is the most widely used technique to monitor the fetal health and fetal heart rate (FHR) is an important index to identify occurs of fetal distress. This study is to propose discriminant analysis (DA), decision tree (DT), and artificial neural network (ANN) to evaluate fetal distress. The results show that the accuracies of DA, DT and ANN are 82.1%, 86.36% and 97.78%, respectively.展开更多
The propagation of single-event effects(SEEs)on a Xilinx Zynq-7000 system on chip(SoC)was inves-tigated using heavy-ion microbeam radiation.The irradia-tion results reveal several functional blocks’sensitivity locati...The propagation of single-event effects(SEEs)on a Xilinx Zynq-7000 system on chip(SoC)was inves-tigated using heavy-ion microbeam radiation.The irradia-tion results reveal several functional blocks’sensitivity locations and cross sections,for instance,the arithmetic logic unit,register,D-cache,and peripheral,while irradi-ating the on-chip memory(OCM)region.Moreover,event tree analysis was executed based on the obtained microbeam irradiation results.This study quantitatively assesses the probabilities of SEE propagation from the OCM to other blocks in the SoC.展开更多
Purpose:The purpose of this study was to use decision tree modeling to generate profiles of children and youth who were more and less likely to meet the Canadian 24-h movement guidelines during the coronavirus disease...Purpose:The purpose of this study was to use decision tree modeling to generate profiles of children and youth who were more and less likely to meet the Canadian 24-h movement guidelines during the coronavirus disease-2019(COVID-19)outbreak.Methods:Data for this study were from a nationally representative sample of 1472 Canadian parents(Meanage=45.12,SD=7.55)of children(511 years old)or youth(1217 years old).Data were collected in April 2020 via an online survey.Survey items assessed demographic,behavioral,social,micro-environmental,and macro-environmental characteristics.Four decision trees of adherence and non-adherence to all movement recommendations combined and each individual movement recommendation(physical activity(PA),screen time,and sleep)were generated.Results:Results revealed specific combinations of adherence and non-adherence characteristics.Characteristics associated with adherence to the recommendation(s)included high parental perceived capability to restrict screen time,annual household income ofCAD 100,000,increases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,being a boy,having parents younger than 43 years old,and small increases in children’s and youth’s sleep duration since the COVID-19 outbreak began.Characteristics associated with non-adherence to the recommendation(s)included low parental perceived capability to restrict screen time,youth aged 1217 years,decreases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,primary residences located in all provinces except Quebec,low parental perceived capability to support children’s and youth’s sleep and PA,and annual household income ofCAD 99,999.Conclusion:Our results show that specific characteristics interact to contribute to(non)adherence to the movement behavior recommendations.Results highlight the importance of targeting parents’perceived capability for the promotion of children’s and youth’s movement behaviors during challenging times of the COVID-19 pandemic,paying particular attention to enhancing parental perceived capability to restrict screen time.展开更多
In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also gr...In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also greatly improve the performance of models.However,previous studies did not take into account the relationship between user feature extraction and contextual terms.To address this issue,we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method.To be specific,we design user comment feature extraction(UCFE)to distill salient features from users’historical comments and transform them into representative user feature vectors.Then,the aspect-sentence graph convolutional neural network(ASGCN)is used to incorporate innovative techniques for calculating adjacency matrices;meanwhile,ASGCN emphasizes capturing nuanced semantics within relationships among aspect words and syntactic dependency types.Afterward,three embedding methods are devised to embed the user feature vector into the ASGCN model.The empirical validations verify the effectiveness of these models,consistently surpassing conventional benchmarks and reaffirming the indispensable role of deep learning in advancing sentiment analysis methodologies.展开更多
Epidemic hemorrhagic fever has been an ongoing threat to laboratory personnel involved in animal care and use. Laboratory transmissions and severe infections occurred over the past twenty years, even though the standa...Epidemic hemorrhagic fever has been an ongoing threat to laboratory personnel involved in animal care and use. Laboratory transmissions and severe infections occurred over the past twenty years, even though the standards and regulations for laboratory biosafety have been issued, upgraded, and implemented in China. Therefore, there is an urgent need to identify risk factors and to seek effective preventive measures that can curb the incidences of epidemic hemorrhagic fever among laboratory personnel. In the present study, we reviewed literature that relevant to animals laboratory-acquired hemorrhagic fever infections reported from 1995 to 2015, and analyzed these incidences using fault tree analysis （FTA）.展开更多
OBJECTIVE:To treat patients with psoriasis vulgaris using Traditional Chinese Medicine(TCM),one must stratify patients into subtypes(known as TCM syndromes or Zheng)and apply appropriate TCM treatments to different su...OBJECTIVE:To treat patients with psoriasis vulgaris using Traditional Chinese Medicine(TCM),one must stratify patients into subtypes(known as TCM syndromes or Zheng)and apply appropriate TCM treatments to different subtypes.However,no unified symptom-based classification scheme of subtypes(Zheng)exists for psoriasis vulgaris.The present paper aims to classify patients with psoriasis vulgaris into different subtypes via the analysis of clinical TCM symptom and sign data.METHODS:A cross-sectional survey was carried out in Beijing from 2005-2008,collecting clinical TCM symptom and sign data from 2764 patients with psoriasis vulgaris.Roughly 108 symptoms and signs were initially analyzed using latent tree analysis,with a selection of the resulting latent variables then used as features to cluster patients into subtypes.RESULTS:The initial latent tree analysis yielded a model with 43 latent variables.The second phase of the analysis divided patients into three subtype groups with clear TCM Zheng connotations:'blood deficiency and wind dryness';'blood heat';and'blood stasis'.CONCLUSIONS:Via two-phase analysis of clinic symptom and sign data,three different Zheng subtypes were identified for psoriasis vulgaris.Statistical characteristics of the three subtypes are presented.This constitutes an evidence-based solution to the syndromedifferentiation problem that exists with psoriasis vulgaris.展开更多
Newcastle disease (ND) virus is a leading threat to commercial and domestic poultry in Pakistan. The virus infects and constitutes irreversible impairment to the nervous system, damages the respiratory system, and mar...Newcastle disease (ND) virus is a leading threat to commercial and domestic poultry in Pakistan. The virus infects and constitutes irreversible impairment to the nervous system, damages the respiratory system, and marks severe gastrointestinal lesions leading to heavy mortality in short-living birds and substantial losses in layers and breeders. The continuous emergence and evolution of the virus made it inclined to evade the humoral response and indirectly the circumvention of artificial active immunization. Newcastle disease is caused by the orthoavula genus of the paramyxoviridae family and has shown high genetic diversity even in their genotypes while information regarding enzootic trends of the virus is scanty in Pakistan. A total of 40 tracheal samples of NDV were collected from different commercial broiler farms and 11 isolates of NDV were identified. In the current study, we determined the genetic diversity of the Newcastle disease virus based on the partial sequencing of the fusion protein gene available in the NCBI database. Genetic analysis showed that seven isolates belonged to class I genotype VII and four belonged to class II genotype II. Interestingly, two isolates had epidemiological connections with vaccine-like class II genotype II. Our findings, concerning the recent outbreaks of class I genotype VII and class II genotype II of NDV in vaccinated commercial flocks, suggest possible potential partial mutations in the fusion protein gene. Genetic diversity and formation of the new cleavage site in an important neutralizing protein of wild strain are linked with the potency of artificial active immunization and a major cause of vaccine failure.展开更多
The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ...The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ZigBee devices facilitate numerous applications such as pervasive computing, security monitoring and control. ZigBee end devices collect sensing data and send them to ZigBee Coordinator. The Coordinator processes end device requests. The effect of a large number of random unsynchronized requests may degrade the overall network performance. An effective technique is particularly needed for synchronizing available node’s request processing to design a reliable ZigBee network. In this paper, region based priority mechanism is implemented to synchronize request with Tree Routing Method. Riverbed is used to simulate and analyze overall ZigBee network performance. The results show that the performance of the overall priority based ZigBee network model is better than without a priority based model. This research paves the way for further designing and modeling a large scale ZigBee network.展开更多
文摘The effect of pruning severity on tree growth was analyzed by change point detection using segmented regression. The present study applied this analysis to a well-known published data set including diameter growth response, tree age, pruning severity and pretreatment crown size. First, multiple regression analysis was performed to assess the effect of tree age, pruning severity and pretreatment crown size on diameter growth response. Next, segmented regression analysis was performed to assess the effect of pruning severity on diameter growth response. The results of the multiple regression showed that diameter growth response was significantly influenced by pruning severity and pretreatment crown size. The results of the segmented regression showed that in the whole data set, an abrupt change toward a decrease in diameter growth response was detected at 25% of the live crown removed. However, in the group of fully crowned and open-grown, diameter growth response continuously decreased with increasing pruning severity with no significant abrupt change, whereas in the group of 70% - 90% live crown, diameter growth response did not significantly decrease up to the break point (53% crown removed) and then abruptly decreased. This may be the first study to show the numerical evaluation of the effect of pruning severity on tree growth by change point analysis.
文摘This study investigates the use of a decision tree classification model, combined with Principal Component Analysis (PCA), to distinguish between Assam and Bhutan ethnic groups based on specific anthropometric features, including age, height, tail length, hair length, bang length, reach, and earlobe type. The dataset was reduced using PCA, which identified height, reach, and age as key features contributing to variance. However, while PCA effectively reduced dimensionality, it faced challenges in clearly distinguishing between the two ethnic groups, a limitation noted in previous research. In contrast, the decision tree model performed significantly better, establishing clear decision boundaries and achieving high classification accuracy. The decision tree consistently selected Height and Reach as the most important classifiers, a finding supported by existing studies on ethnic differences in Northeast India. The results highlight the strengths of combining PCA for dimensionality reduction with decision tree models for classification tasks. While PCA alone was insufficient for optimal class separation, its integration with decision trees improved both the model’s accuracy and interpretability. Future research could explore other machine learning models to enhance classification and examine a broader set of anthropometric features for more comprehensive ethnic group classification.
文摘In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.
文摘To assess road traffic safety risk in civil aviation airports and develop effective accident prevention measures,this study proposed a risk assessment method based on accident tree and Bayesian network for airport aircraft activity areas.It identified influencing factors in the aircraft activity area from the perspectives of person-vehicle-road-environment-management and analyzed their relationships.The Bayesian network was utilized to determine initial probabilities for each influencing factor.Findings indicated a relatively high overall safety level in the airport's road traffic system.Accident trees were employed to qualitatively and quantitatively analyze common human-vehicle accident patterns.The initial probabilities obtained from the Bayesian network served as basic event probabilities in the accident tree to determine the occurrence probability of the top event.Taking a 4F airport in China as an example,accident cause analysis identified five important risk sources in human-vehicle accidents,including blind spots for special vehicles,illegal driving by drivers,pedestrians violating regulations,passengers entering restricted areas,and blind spots at intersections.Corresponding safety management measures were formulated.The study concluded that the integration of Bayesian networks and accident trees effectively determines accident probabilities and offers specific solutions,thus playing a crucial role in enhancing road traffic safety management within aviation airports.
文摘This paper presents an approximate algorithm based on simulated annealing to achieve the maximum probability of the minimal cut sets for a fault tree. Near optimal minimal cut sets and important sequence of the basic events are also solved by the method. Computer simulations show that the algorithm performs very well.
文摘A logic fault tree of mine spontaneous combustion of sulphide ores was built by the fault tree analysis (FTA) based on a lot of mechanism investigation of sulphide ore spontaneous combustion in more than ten mines and review of a great amount of relevant
基金supported by the National Natural Science Foundation of China (Nos.51504008,71371014,and 51774012)the Natural Science Foundation of Anhui Higher Education Institutions of China (No.KJ2015A068)+3 种基金the Anhui Provincial Natural Science Foundation (No.1608085QE115)the China Postdoctoral Science Foundation funded project (Nos.2015M571913 and 2018T110612)the Postdoctoral Fund of Anhui Province (No.2017B212)the Scientific Research Foundation for Introduction of Talent of Anhui University of Science & Technology (No.ZY530)
文摘During the past decade, coal dust and gas explosions have been the most two serious types of disasters in China, threatening the lives of miners and causing significant losses in terms of national property. In this paper, an evaluation model of coal dust and gas explosions was constructed based on a fuzzy fault tree by taking the Xingli Coal Mine as a research site to identify the risk factors of coal dust and gas explosions.Furthermore, the hazards associated with such explosions were evaluated for this particular coal mine.After completing an on-site investigation, the fuzzy probabilities of basic events were obtained through expert scoring, and these expert opinions were then aggregated as trapezoidal fuzzy numbers to calculate the degrees of importance of all basic events. Finally, these degrees of importance were sorted. According to the resulting order, the basic events with higher probabilities were determined to identify key hazards in the daily safety management of this particular coal mine. Moreover, effective measures for preventing gas and coal dust explosions were derived. The fuzzy fault tree analysis method is of high significance in the analysis of accidental coal mine explosions and provides theoretical guidance for improving the efficiency of coal mine safety management in a scientific and feasible manner.
基金supported by the Hong Kong Research Grants Council under grant NO.16202515 and 16212516Guangzhou HKUST Fok Ying Tung Research Institute,China Ministry of Science and Technology TCM Special Research Projects Program under grant No.200807011,No.201007002 and No.201407001-8+2 种基金Beijing Science and Technology Program under grant No.Z111107056811040Beijing New Medical Discipline Development Program under grant No.XK100270569Project of Beijing University of Chinese Medicine under grant No.2011-CXTD-23
文摘OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.
文摘Random amplified polymorphic DNA (RAPD) was used to analyze genetic polymophism of 35 Tree Peony cultivars with 7 different color groups. Thirty four primers amplified 418 DNA fragments and 337 polymorphic bands (80.6%), including specific DNA markers for 18 cultivars that could be used to differentiate cultivars. The UPCMA method was used to analyze the genetic relationship among cultivars. The results showed that 35 Peony cultivars could be divided into 2 cluster groups when using similarity criteria of 1.5, and into 4 cluster groups when using similarity criteria of 1.0. The result confirmed that the flower color has no relation to the genetic clusters and the Tree Peony cultivars originated from the same area has close genetic relationship. Therefore, genetic background has no large effect on the genetic relationship. The sequence based on polymorphic rate from high to low was Blue groups > Yellow groups > Bark red groups > Blake groups > White groups>Green groups>Red groups.
基金supported by the Natural Science Foundation of China(Nos.U1804233,31370697)the Henan Province Science and Technology Innovation Outstanding Talent Fund(No.162400510013).
文摘Tree peony(Paeonia section Moutan DC.)seeds are an excellent source of beneficial natural compounds that promote health,and they contain high levels of alpha-linolenic acid(ALA).In recent years,tree peony has been emerging as an oil crop.Therefore,combined analysis of the transcriptome and proteome of tree peony(P.ostii)seeds at 25,32,39,53,67,81,88,95,and 109 days after pollination(DAP)was conducted to better understand the transcriptional and translational regulation of seed development and oil biosynthesis.A total of 38,482 unigenes and 2841 proteins were identified.A total of 26,912 differentially expressed genes(DEGs)and 592 differentially expressed proteins(DEPs)were clustered into three groups corresponding to the rapid growth,seed inclusion enrichment and conversion,and late dehydration and mature stages of seed development.Fifteen lipid metabolism pathways were identified at both the transcriptome and proteome levels.Pathway enrichment analysis revealed that a period of rapid fatty acid biosynthesis occurred at 53–88 DAP.Furthermore,211 genes and 35 proteins associated with the fatty acid metabolism pathway,63 genes and 11 proteins associated with the biosynthesis of unsaturated fatty acids(UFAs),and 115 genes and 24 proteins associated with ALA metabolism were identified.Phylogenetic analysis revealed that 16 putative fatty acid desaturase(FAD)-encoding genes clustered into four FAD groups,eight of which exhibited the highest expression at 53 DAP,suggesting that they play an important role in ALA accumulation.RT-qPCR analysis indicated that the temporal expression patterns of oil biosynthesis genes were largely similar to the RNA-seq results.The expression patterns of fatty acid metabolism-and seed development-related proteins determined by MRM were also highly consistent with the results obtained in the proteomic analysis.Correlation analysis indicated significant differences in the number and abundance of DEGs and DEPs but a high level of consistency in expression patterns and metabolic pathways.The results of the present study represent the first combined transcriptomic and proteomic analysis of tree peony seeds and provide insight into tree peony seed development and oil accumulation.
基金supported by the National Natural Science Foundation of China(11832012)
文摘A state/event fault tree(SEFT)is a modeling technique for describing the causal chains of events leading to failure in software-controlled complex systems.Such systems are ubiquitous in all areas of everyday life,and safety and reliability analyses are increasingly required for these systems.SEFTs combine elements from the traditional fault tree with elements from state-based techniques.In the context of the real-time safety-critical systems,SEFTs do not describe the time properties and important timedependent system behaviors that can lead to system failures.Further,SEFTs lack the precise semantics required for formally modeling time behaviors.In this paper,we present a qualitative analysis method for SEFTs based on transformation from SEFT to timed automata(TA),and use the model checker UPPAAL to verify system requirements’properties.The combination of SEFT and TA is an important step towards an integrated design and verification process for real-time safety-critical systems.Finally,we present a case study of a powerboat autopilot system to confirm our method is viable and valid after achieving the verification goal step by step.
文摘By using the fault tree analysis in reliability theory as the systematical analysis approach, the dust suppression mechanism in a spray system with wetting agent is shown in a logic tree and some graphical models. From these diagrams, all factors related to the spray system and their cause and effect relationship can be seen clearly. Based on the built logic tree, several mathematical models and new ideas for expressing the dust suppressing efficiency in the spray system are put forward. The significance of all factors related to the efficiency of suppressing dust is qualitatively described. Furthermore, the new concepts, such as, the effective reaction time between dust particle and droplet, the expansion phenomenon of laden dust droplet, the functions of volatile and the relative size distribution efficiency of wetting agent are presented. All this richenes the existing mechanism of dust abatement by spraying wetting agent. At last, several problems that need to be further investigated are also suggested in the paper.
文摘Fetal distress is one of the main factors to cesarean section in obstetrics and gynecology. If the fetus lack of oxygen in uterus, threat to the fetal health and fetal death could happen. Cardiotocography (CTG) is the most widely used technique to monitor the fetal health and fetal heart rate (FHR) is an important index to identify occurs of fetal distress. This study is to propose discriminant analysis (DA), decision tree (DT), and artificial neural network (ANN) to evaluate fetal distress. The results show that the accuracies of DA, DT and ANN are 82.1%, 86.36% and 97.78%, respectively.
基金This work was supported by the National Natural Science Foundation of China(Nos.11575138,11835006,11690040,11690043,and 11705216)the Innovation Center of Radiation Application(No.KFZC2019050321)the China Scholarships Council program(No.201906280343).
文摘The propagation of single-event effects(SEEs)on a Xilinx Zynq-7000 system on chip(SoC)was inves-tigated using heavy-ion microbeam radiation.The irradia-tion results reveal several functional blocks’sensitivity locations and cross sections,for instance,the arithmetic logic unit,register,D-cache,and peripheral,while irradi-ating the on-chip memory(OCM)region.Moreover,event tree analysis was executed based on the obtained microbeam irradiation results.This study quantitatively assesses the probabilities of SEE propagation from the OCM to other blocks in the SoC.
文摘Purpose:The purpose of this study was to use decision tree modeling to generate profiles of children and youth who were more and less likely to meet the Canadian 24-h movement guidelines during the coronavirus disease-2019(COVID-19)outbreak.Methods:Data for this study were from a nationally representative sample of 1472 Canadian parents(Meanage=45.12,SD=7.55)of children(511 years old)or youth(1217 years old).Data were collected in April 2020 via an online survey.Survey items assessed demographic,behavioral,social,micro-environmental,and macro-environmental characteristics.Four decision trees of adherence and non-adherence to all movement recommendations combined and each individual movement recommendation(physical activity(PA),screen time,and sleep)were generated.Results:Results revealed specific combinations of adherence and non-adherence characteristics.Characteristics associated with adherence to the recommendation(s)included high parental perceived capability to restrict screen time,annual household income ofCAD 100,000,increases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,being a boy,having parents younger than 43 years old,and small increases in children’s and youth’s sleep duration since the COVID-19 outbreak began.Characteristics associated with non-adherence to the recommendation(s)included low parental perceived capability to restrict screen time,youth aged 1217 years,decreases in children’s and youth’s outdoor PA/sport since the COVID-19 outbreak began,primary residences located in all provinces except Quebec,low parental perceived capability to support children’s and youth’s sleep and PA,and annual household income ofCAD 99,999.Conclusion:Our results show that specific characteristics interact to contribute to(non)adherence to the movement behavior recommendations.Results highlight the importance of targeting parents’perceived capability for the promotion of children’s and youth’s movement behaviors during challenging times of the COVID-19 pandemic,paying particular attention to enhancing parental perceived capability to restrict screen time.
基金This work is partly supported by the Fundamental Research Funds for the Central Universities(CUC230A013)It is partly supported by Natural Science Foundation of Beijing Municipality(No.4222038)It is also supported by National Natural Science Foundation of China(Grant No.62176240).
文摘In recent years,deep learning methods have developed rapidly and found application in many fields,including natural language processing.In the field of aspect-level sentiment analysis,deep learning methods can also greatly improve the performance of models.However,previous studies did not take into account the relationship between user feature extraction and contextual terms.To address this issue,we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method.To be specific,we design user comment feature extraction(UCFE)to distill salient features from users’historical comments and transform them into representative user feature vectors.Then,the aspect-sentence graph convolutional neural network(ASGCN)is used to incorporate innovative techniques for calculating adjacency matrices;meanwhile,ASGCN emphasizes capturing nuanced semantics within relationships among aspect words and syntactic dependency types.Afterward,three embedding methods are devised to embed the user feature vector into the ASGCN model.The empirical validations verify the effectiveness of these models,consistently surpassing conventional benchmarks and reaffirming the indispensable role of deep learning in advancing sentiment analysis methodologies.
基金supported by Special Fund for Health Sector of China[Grant No.201302006]
文摘Epidemic hemorrhagic fever has been an ongoing threat to laboratory personnel involved in animal care and use. Laboratory transmissions and severe infections occurred over the past twenty years, even though the standards and regulations for laboratory biosafety have been issued, upgraded, and implemented in China. Therefore, there is an urgent need to identify risk factors and to seek effective preventive measures that can curb the incidences of epidemic hemorrhagic fever among laboratory personnel. In the present study, we reviewed literature that relevant to animals laboratory-acquired hemorrhagic fever infections reported from 1995 to 2015, and analyzed these incidences using fault tree analysis （FTA）.
基金Supported by the Foundation for Establishing Psoriasis Vulgaris Syndrome Diagnostic Criterion by Latent Structure(QN2009-14)by the Scientific Project of Beijing Municipal Science Technology Commission:Study on the Composition Rules of Syndrome Elements on Psoriasis Vulgaris and Standardized Treatments of TCM(D09050703550901)。
文摘OBJECTIVE:To treat patients with psoriasis vulgaris using Traditional Chinese Medicine(TCM),one must stratify patients into subtypes(known as TCM syndromes or Zheng)and apply appropriate TCM treatments to different subtypes.However,no unified symptom-based classification scheme of subtypes(Zheng)exists for psoriasis vulgaris.The present paper aims to classify patients with psoriasis vulgaris into different subtypes via the analysis of clinical TCM symptom and sign data.METHODS:A cross-sectional survey was carried out in Beijing from 2005-2008,collecting clinical TCM symptom and sign data from 2764 patients with psoriasis vulgaris.Roughly 108 symptoms and signs were initially analyzed using latent tree analysis,with a selection of the resulting latent variables then used as features to cluster patients into subtypes.RESULTS:The initial latent tree analysis yielded a model with 43 latent variables.The second phase of the analysis divided patients into three subtype groups with clear TCM Zheng connotations:'blood deficiency and wind dryness';'blood heat';and'blood stasis'.CONCLUSIONS:Via two-phase analysis of clinic symptom and sign data,three different Zheng subtypes were identified for psoriasis vulgaris.Statistical characteristics of the three subtypes are presented.This constitutes an evidence-based solution to the syndromedifferentiation problem that exists with psoriasis vulgaris.
文摘Newcastle disease (ND) virus is a leading threat to commercial and domestic poultry in Pakistan. The virus infects and constitutes irreversible impairment to the nervous system, damages the respiratory system, and marks severe gastrointestinal lesions leading to heavy mortality in short-living birds and substantial losses in layers and breeders. The continuous emergence and evolution of the virus made it inclined to evade the humoral response and indirectly the circumvention of artificial active immunization. Newcastle disease is caused by the orthoavula genus of the paramyxoviridae family and has shown high genetic diversity even in their genotypes while information regarding enzootic trends of the virus is scanty in Pakistan. A total of 40 tracheal samples of NDV were collected from different commercial broiler farms and 11 isolates of NDV were identified. In the current study, we determined the genetic diversity of the Newcastle disease virus based on the partial sequencing of the fusion protein gene available in the NCBI database. Genetic analysis showed that seven isolates belonged to class I genotype VII and four belonged to class II genotype II. Interestingly, two isolates had epidemiological connections with vaccine-like class II genotype II. Our findings, concerning the recent outbreaks of class I genotype VII and class II genotype II of NDV in vaccinated commercial flocks, suggest possible potential partial mutations in the fusion protein gene. Genetic diversity and formation of the new cleavage site in an important neutralizing protein of wild strain are linked with the potency of artificial active immunization and a major cause of vaccine failure.
文摘The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ZigBee devices facilitate numerous applications such as pervasive computing, security monitoring and control. ZigBee end devices collect sensing data and send them to ZigBee Coordinator. The Coordinator processes end device requests. The effect of a large number of random unsynchronized requests may degrade the overall network performance. An effective technique is particularly needed for synchronizing available node’s request processing to design a reliable ZigBee network. In this paper, region based priority mechanism is implemented to synchronize request with Tree Routing Method. Riverbed is used to simulate and analyze overall ZigBee network performance. The results show that the performance of the overall priority based ZigBee network model is better than without a priority based model. This research paves the way for further designing and modeling a large scale ZigBee network.
