Differentiating consistency of meningioma based on grey-level histogram analysis of T2WI

Objective To observe the value of grey-level histogram analysis based on T2WI for differentiating consistency of meningioma.Methods Data of 109 patients with meningioma were retrospectively analyzed.The patients were divided into hard group(n=71)and soft group(n=38)according to the consistency of tumors.Tumor ROI was outlined on axial T2WI showing the largest tumor section,gray levels were extracted and histogram analysis was performed.The value of each histogram parameter were compared between groups.Then receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the efficiency for differentiating soft and hard meningioma.Results P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI in soft group were all higher than those in hard group(all P<0.05),while the variance,the kurtosis and the skewness were not significantly different between groups(all P>0.05).The differentiating efficiency of P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI were all fine,with AUC of 0.774 to 0.833,and no significant difference was found(all P>0.05).Conclusion Parameters of grey-level histogram analysis such as P 1,P 10,P 50,P 90,P 99 and the mean values based on T2WI were all valuable for differentiating soft and hard meningioma.

Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

Influence of initial check, information exchange, final accuracy check, reaction information nursing on the psychology of elderly with lung cancer

BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychological problems.AIM To investigate the effectiveness of the initial check,information exchange,final accuracy check,reaction(IIFAR)information care model on the mental health status of elderly patients with lung cancer.METHODS This study is a single-centre study.We randomly recruited 60 elderly patients with lung cancer who attended our hospital from January 2021 to January 2022.These elderly patients with lung cancer were randomly divided into two groups,with the control group taking the conventional propaganda and education and the observation group taking the IIFAR information care model based on the conventional care protocol.The differences in psychological distress,anxiety and depression,life quality,fatigue,and the locus of control in psychology were compared between these two groups,and the causes of psychological distress were analyzed.RESULTS After the intervention,Distress Thermometer,Hospital Anxiety and Depression Scale(HADS)for anxiety and the HADS for depression,Revised Piper’s Fatigue Scale,and Chance Health Locus of Control scores were lower in the observation group compared to the pre-intervention period in the same group and were significantly lower in the observation group compared to those of the control group(P<0.05).After the intervention,Quality of Life Questionnaire Core 30(QLQ-C30),Internal Health Locus of Control,and Powerful Others Health Locus of Control scores were significantly higher in the observation and the control groups compared to the pre-intervention period in their same group,and QLQ-C30 scores were significantly higher in the observation group compared to those of the control group(P<0.05).CONCLUSION The IIFAR information care model can help elderly patients with lung cancer by reducing their anxiety and depression,psychological distress,and fatigue,improving their tendencies on the locus of control in psychology,and enhancing their life qualities.

Identifying Brand Consistency by Product Differentiation Using CNN

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.

Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems

Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications.Although there is an extensive literature on qualitative properties such as safety and liveness,there is still a lack of quantitative and uncertain property verifications for these systems.In uncertain environments,agents must make judicious decisions based on subjective epistemic.To verify epistemic and measurable properties in multi-agent systems,this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge(FCTLK).We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy epistemic interpreted systems.In addition,we provide a transformation algorithm from fuzzy epistemic interpreted systems to fuzzy Kripke structures,as well as transformation rules from FCTLK formulas to Fuzzy Computation Tree Logic(FCTL)formulas.Accordingly,we transform the FCTLK model checking problem into the FCTL model checking.This enables the verification of FCTLK formulas by using the fuzzy model checking algorithm of FCTL without additional computational overheads.Finally,we present correctness proofs and complexity analyses of the proposed algorithms.Additionally,we further illustrate the practical application of our approach through an example of a train control system.

层厚对使用CT/SIM Check模体联合iQA软件检测CT模拟机的影响

目的探讨层厚大小对使用CT/SIM Check模体联合iQA软件检测放疗CT模拟机数据结果的影响。方法对1台西门子Sensation Open CT模拟机,使用6种放疗扫描协议扫描1套CT/SIM Check模体,扫描完成后重建1.5、2、3、4和5 mm共5种层厚的CT图像序列。使用iQA软件对这些CT图像序列进行自动分析并生成报表,对报表上的质控数据结果进行分析和比较。结果通过对报表数据进行分析,得到了6种扫描协议和5种层厚情形下22种参数的质控数据,对5种不同层厚的数据计算得到了相应的四分位数间距值。由数据结果可见,HU均一性和插件4内标准差的数据随层厚的增加而减小;扫描中心纵向坐标的数值随层厚的增加有下降的趋势;线宽比-灵敏度截面的数据随层厚的增加而变大。结论使用CT/SIM Check模体联合iQA软件检测CT模拟机,层厚对HU均一性、插件4内标准差、扫描中心纵向坐标和线宽比-灵敏度截面的质控数据结果有较大影响,对其他参数的数据也有不同程度的影响。本研究为物理师使用CT/SIM Check模体联合iQA软件检测放疗CT模拟机的质控工作,提供了有益的数据参考。

Consistency check of degradation mechanism between natural storage and enhancement test for missile servo system

Reliability enhancement testing(RET) is an accelerated testing which hastens the performance degradation process to surface its inherent defects of design and manufacture. It is an important hypothesis that the degradation mechanism of the RET is the same as the one of the normal stress condition. In order to check the consistency of two mechanisms, we conduct two enhancement tests with a missile servo system as an object of the study, and preprocess two sets of test data to establish the accelerated degradation models regarding the temperature change rate that is assumed to be the main applied stress of the servo system during the natural storage. Based on the accelerated degradation models and natural storage profile of the servo system, we provide and demonstrate a procedure to check the consistency of two mechanisms by checking the correlation and difference of two sets of degradation data. The results indicate that the two degradation mechanisms are significantly consistent with each other.

Blockchain Consistency Check Protocol for Improved Reliability

Blockchain is a technology that provides security features that can be used for more than just cryptocurrencies.Blockchain achieves security by saving the information of one block in the next block.Changing the information of one block will require changes to all the next block in order for that change to take effect.Which makes it unfeasible for such an attack to happen.However,the structure of how blockchain works makes the last block always vulnerable for attacks,given that its information is not saved yet in any block.This allows malicious node to change the information of the last block and generate a new block and broadcast it to the network.Given that the nodes always follow the longer chain wins rule,the malicious node will win given that it has the longest chain in the network.This paper suggests a solution to this issue by making the nodes send consistency check messages before broadcasting a block.If the nodes manage to successfully verify that the node that generated a new block hasn’t tampered with the blockchain than that block will be broadcasted.The results of the simulation show suggested protocol provided better security compared to the regular blockchain.

Identifying Counterexamples Without Variability in Software Product Line Model Checking

Product detection based on state abstraction technologies in the software product line(SPL)is more complex when compared to a single system.This variability constitutes a new complexity,and the counterexample may be valid for some products but spurious for others.In this paper,we found that spurious products are primarily due to the failure states,which correspond to the spurious counterexamples.The violated products correspond to the real counterexamples.Hence,identifying counterexamples is a critical problem in detecting violated products.In our approach,we obtain the violated products through the genuine counterexamples,which have no failure state,to avoid the tedious computation of identifying spurious products dealt with by the existing algorithm.This can be executed in parallel to improve the efficiency further.Experimental results showthat our approach performswell,varying with the growth of the system scale.By analyzing counterexamples in the abstract model,we observed that spurious products occur in the failure state.The approach helps in identifying whether a counterexample is spurious or genuine.The approach also helps to check whether a failure state exists in the counterexample.The performance evaluation shows that the proposed approach helps significantly in improving the efficiency of abstraction-based SPL model checking.

Dynamic Modeling Framework of Sediment Trapped by Check-Dam Networks:A Case Study of a Typical Watershed on the Chinese Loess Plateau

Check-dam construction is an effective and widely used method for sediment trapping in the Yellow River Basin and other places over the world that are prone to severe soil erosion.Quantitative estimations of the dynamic sediment trapped by check dams are necessary for evaluating the effects of check dams and planning the construction of new ones.In this study,we propose a new framework,named soil and water assessment tool(SWAT)–dynamic check dam(DCDam),for modeling the sediment trapped by check dams dynamically,by integrating the widely utilized SWAT model and a newly developed module called DCDam.We then applied this framework to a typical loess watershed,the Yan River Basin,to assess the time-varying effects of check-dam networks over the past 60 years(1957–2016).The DCDam module generated a specific check-dam network to conceptualize the complex connections at each time step(monthly).In addition,the streamflow and sediment load simulated by using the SWAT model were employed to force the sediment routing in the check-dam network.The evaluation results revealed that the SWAT-DCDam framework performed satisfactorily,with an overestimation of 11.50%,in simulating sediment trapped by check dams,when compared with a field survey of the accumulated sediment deposition.For the Yan River Basin,our results indicated that the designed structural parameters of check dams have evolved over the past 60 years,with higher dams(37.14%and 9.22%increase for large dams and medium dams,respectively)but smaller controlled areas(46.03%and 10.56%decrease for large dams and medium dams,respectively)in recent years.Sediment retained by check dams contributed to approximately 15.00%of the total sediment load reduction in the Yan River during 1970–2016.Thus,our developed framework can be a promising tool for evaluating check-dam effects,and this study can provide valuable information and support to decision-making for soil and water conservation and check-dam planning and management.

A Data Consistency Insurance Method for Smart Contract

As one of the major threats to the current DeFi(Decentralized Finance)ecosystem,reentrant attack induces data inconsistency of the victim smart contract,enabling attackers to steal on-chain assets from DeFi projects,which could terribly do harm to the confidence of the blockchain investors.However,protecting DeFi projects from the reentrant attack is very difficult,since generating a call loop within the highly automatic DeFi ecosystem could be very practicable.Existing researchers mainly focus on the detection of the reentrant vulnerabilities in the code testing,and no method could promise the non-existent of reentrant vulnerabilities.In this paper,we introduce the database lock mechanism to isolate the correlated smart contract states from other operations in the same contract,so that we can prevent the attackers from abusing the inconsistent smart contract state.Compared to the existing resolutions of front-running,code audit,andmodifier,our method guarantees protection resultswith better flexibility.And we further evaluate our method on a number of de facto reentrant attacks observed from Etherscan.The results prove that our method could efficiently prevent the reentrant attack with less running cost.

Asymptotic Consistency of the James-Stein Shrinkage Estimator

The study explores the asymptotic consistency of the James-Stein shrinkage estimator obtained by shrinking a maximum likelihood estimator. We use Hansen’s approach to show that the James-Stein shrinkage estimator converges asymptotically to some multivariate normal distribution with shrinkage effect values. We establish that the rate of convergence is of order and rate , hence the James-Stein shrinkage estimator is -consistent. Then visualise its consistency by studying the asymptotic behaviour using simulating plots in R for the mean squared error of the maximum likelihood estimator and the shrinkage estimator. The latter graphically shows lower mean squared error as compared to that of the maximum likelihood estimator.

Flood risk assessment of check dams in the Wangmaogou watershed on the Loess Plateau of China

Check dams have been widely used in China’s Loess Plateau region due to their effectiveness in erosion and flood control.However,the safety and stability of the check dam decrease with the operation process,which increases the probability of dam failure during flood events and threatens local residents’ life and property.Thus,this study simulated flood process of the check dam failure in the Wangmaogou watershed in Yulin City,Shaanxi Province,China,calculated different types of inundation losses based on the flood inundation area within the watershed,and determined the number of key flood protection check dams by classifying the flood risk levels of the check dams.The results showed that 5 dams in the watershed were subject to overtopping during different rainfall return periods,which was related to their flood discharge capacity.Dam failure flood process showed a rapid growth trend followed by slow decrease,and the time of flood peak advanced with increase in the return period.After harmonization of evaluation scales,the magnitude of flood inundation losses can be ranked as:economic losses(212.409 million yuan) > life losses(10.368 million yuan) > ecological losses(6.433 million yuan).The risk value for both individual dams and the whole dam system decreases as the return period increases.The number of key flood protection check dams in the Wangmaogou watershed was 2,3,3,3,4,and 5 for floods with return periods of 10,20,30,50,100,and 200 years,respectively.The results provided a theoretical basis for the safe operation and risk evaluation of check dams in the Loess Plateau Hills watershed.

Check dam extraction from remote sensing images using deep learning and geospatial analysis:A case study in the Yanhe River Basin of the Loess Plateau,China

Check dams are widely used on the Loess Plateau in China to control soil and water losses,develop agricultural land,and improve watershed ecology.Detailed information on the number and spatial distribution of check dams is critical for quantitatively evaluating hydrological and ecological effects and planning the construction of new dams.Thus,this study developed a check dam detection framework for broad areas from high-resolution remote sensing images using an ensemble approach of deep learning and geospatial analysis.First,we made a sample dataset of check dams using GaoFen-2(GF-2)and Google Earth images.Next,we evaluated five popular deep-learning-based object detectors,including Faster R-CNN,You Only Look Once(version 3)(YOLOv3),Cascade R-CNN,YOLOX,and VarifocalNet(VFNet),to identify the best one for check dam detection.Finally,we analyzed the location characteristics of the check dams and used geographical constraints to optimize the detection results.Precision,recall,average precision at intersection over union(IoU)threshold of 0.50(AP_(50)),IoU threshold of 0.75(AP_(75)),and average value for 10 IoU thresholds ranging from 0.50-0.95 with a 0.05 step(AP_(50-95)),and inference time were used to evaluate model performance.All the five deep learning networks could identify check dams quickly and accurately,with AP_(50-95),AP_(50),and AP_(75)values higher than 60.0%,90.0%,and 70.0%,respectively,except for YOLOv3.The VFNet had the best performance,followed by YOLOX.The proposed framework was tested in the Yanhe River Basin and yielded promising results,with a recall rate of 87.0%for 521 check dams.Furthermore,the geographic analysis deleted about 50%of the false detection boxes,increasing the identification accuracy of check dams from 78.6%to 87.6%.Simultaneously,this framework recognized 568 recently constructed check dams and small check dams not recorded in the known check dam survey datasets.The extraction results will support efficient watershed management and guide future studies on soil erosion in the Loess Plateau.

Sediment sources and their impacts on a check dam-controlled watershed, Loess Plateau, China

Soil erosion is a major issue in Loess Plateau,China,and quantitative analyses of sediment sources are crucial for soil erosion control.In this study,a combination of flood couplet analysis and composite fingerprint identification was used for historical reconstructions of soil erosion in sediment source areas in Loess Plateau.Each flood couplet was constructed based on sediment 137Cs activity,and past soil erosion was calculated using soil bulk density and storage capacity curves.The contribution rates of the sediment sources were calculated using the fingerprinting method,and the amount of erosion in the sediment source areas was estimated.The best fingerprint combination(Cr,Ni,V,and TOC)enabled a 97.2%recognition of sediment sources from 29 flood events(1956–1990)in the Loess Plateau.The contribution rates of gullies,farmland,grassland,and shrubland were 44.89%,26.38%,10.49%,and 18.24%,respectively.These four land use types contributed 1,227,751,512,and 279 tons of sediments,respectively.Re-vegetation decreased soil erosion(1966–1983),whereas deforestation increased soil erosion(1956–1965 and 1984–1990).Rational soil and water conservation measures on slopes and check dam construction in gullies are therefore suggested to mitigate erosion.

Adaptive Graph Embedding With Consistency and Specificity for Domain Adaptation

Domain adaptation(DA) aims to find a subspace,where the discrepancies between the source and target domains are reduced. Based on this subspace, the classifier trained by the labeled source samples can classify unlabeled target samples well.Existing approaches leverage Graph Embedding Learning to explore such a subspace. Unfortunately, due to 1) the interaction of the consistency and specificity between samples, and 2) the joint impact of the degenerated features and incorrect labels in the samples, the existing approaches might assign unsuitable similarity, which restricts their performance. In this paper, we propose an approach called adaptive graph embedding with consistency and specificity(AGE-CS) to cope with these issues. AGE-CS consists of two methods, i.e., graph embedding with consistency and specificity(GECS), and adaptive graph embedding(AGE).GECS jointly learns the similarity of samples under the geometric distance and semantic similarity metrics, while AGE adaptively adjusts the relative importance between the geometric distance and semantic similarity during the iterations. By AGE-CS,the neighborhood samples with the same label are rewarded,while the neighborhood samples with different labels are punished. As a result, compact structures are preserved, and advanced performance is achieved. Extensive experiments on five benchmark datasets demonstrate that the proposed method performs better than other Graph Embedding methods.

Fast clogging problem of open check dams and a new type suggestion:curved footed type open check dam

Driftwood is one of the important physical components in mountainous rivers which causes severe hazards due to the clogging of bridges,culverts,and narrow sections during floods.Therefore,the understanding of driftwood dynamics and mitigation measures are crucial for managing wood in rivers.Open check dams are the most commonly used engineering measure for preventing driftwood from reaching downstream areas.Nevertheless,these open check dams frequently lose their sediment transport function when they are blocked by sediment and driftwood,especially during major flood events.This paper proposes a new type of open check dam for preventing from clogging.Thus,flume experiments were conducted to examine the influence of different types of open check dams on the characteristics of driftwood deposition.For the model with wood length(LWD)=16.5 cm,wood diameter(D)=15 mm,and wood number(N)=172,the highest trapping efficiency was observed with 90.1%and 87.2%retention rates for the classical debris flow breaker and curved footed open check dams,respectively.Laboratory tests showed that through this proposed design,woody debris blockage in a very short time was prevented from the accumulation of woods beside the dam.In addition to this,most of the sediment passed through the check dam and most of the driftwood got trapped.It can be briefly stated that the geometrical design of the structure plays an important role and can be chosen carefully to optimize trapping efficiency.By designing this type of open check dams in mountain river basins,it may provide a better understanding of the driftwood accumulation and basis for the optimal design of these structures.Further development of the solution proposed in this work can pave the way for designing different types of open check dams for effective flood management.

Review of Software Model-Checking Techniques for Dealing with Error Detection in Program Codes

Debugging software code has been a challenge for software developers since the early days of computer programming. A simple need, because the world is run by software. So perhaps the biggest engineering challenge is finding ways to make software more reliable. This review provides an overview of techniques developed over time in the field of software model checking to solve the problem of detecting errors in program code. In addition, the challenges posed by this technology are discussed and ways to mitigate them in future research and applications are proposed. A comprehensive examination of the various model verification methods used to detect program code errors is intended to lay the foundation for future research in this area.

Study on Problems and Countermeasures in the Management of Spot Check of Chinese Herbal Pieces

Objective To provide suggestions for optimizing the sampling management of Chinese herbal pieces and improving the quality Chinese herbal pieces.Methods Logical reasoning method was used to analyze the problems in the drug spot check of Chinese herbal pieces based on the data of drug quality published by the National Medical Products Administration from 2013 to 2021,combined with the current provisions and implementation of drug spot check management in China.Results and Conclusion At present,there are some problems in the drug spot check of Chinese herbal pieces,such as fewer varieties of Chinese herbal pieces in the national drug spot check,the unreasonable sampling links,the insufficient territorial management in some areas,and error-prone sample extraction.It is suggested that the actual quantity and overall quality of Chinese herbal pieces should be fully considered in the formulation of sampling plan.Besides,the variety coverage of drug spot check of traditional Chinese medicine should be strengthened.In the planning,the sampling links shall be made as a whole,and the credit rating and distribution of drug production,operation and use units within the jurisdiction shall be fully combined.While strengthening the sampling management at the production end in areas with concentrated industries,regional special drug spot check should be carried out or the administrative forces at the provincial,municipal and county levels should be fully mobilized to avoid local protection.In the assigned tasks,the name of Chinese herbal pieces should be accurately expressed to avoid the sampling errors of Chinese herbal pieces with the same original medicinal materials and different processing methods.