Micro segment analysis of supercritical methane thermal-hydraulic performance and pseudo-boiling in a PCHE straight channel

The printed circuit heat exchanger(PCHE) is receiving wide attention as a new kind of compact heat exchanger and is considered as a promising vaporizer in the LNG process. In this paper, a PCHE straight channel in the length of 500 mm is established, with a semicircular cross section in a diameter of 1.2 mm.Numerical simulation is employed to investigate the flow and heat transfer performance of supercritical methane in the channel. The pseudo-boiling theory is adopted and the liquid-like, two-phase-like, and vapor-like regimes are divided for supercritical methane to analyze the heat transfer and flow features.The results are presented in micro segment to show the local convective heat transfer coefficient and pressure drop. It shows that the convective heat transfer coefficient in segments along the channel has a significant peak feature near the pseudo-critical point and a heat transfer deterioration when the average fluid temperature in the segment is higher than the pseudo-critical point. The reason is explained with the generation of vapor-like film near the channel wall that the peak feature related to a nucleateboiling-like state and heat transfer deterioration related to a film-boiling-like state. The effects of parameters, including mass flow rate, pressure, and wall heat flux on flow and heat transfer were analyzed.In calculating of the averaged heat transfer coefficient of the whole channel, the traditional method shows significant deviation and the micro segment weighted average method is adopted. The pressure drop can mainly be affected by the mass flux and pressure and little affected by the wall heat flux. The peak of the convective heat transfer coefficient can only form at high mass flux, low wall heat flux, and near critical pressure, in which condition the nucleate-boiling-like state is easier to appear. Moreover,heat transfer deterioration will always appear, since the supercritical flow will finally develop into a filmboiling-like state. So heat transfer deterioration should be taken seriously in the design and safe operation of vaporizer PCHE. The study of this work clarified the local heat transfer and flow feature of supercritical methane in microchannel and contributed to the deep understanding of supercritical methane flow of the vaporization process in PCHE.

Numerical Simulation-Based Analysis of the Impact of Overloading on Segmentally Assembled Bridges

Segmentally assembled bridges are increasinglyfinding engineering applications in recent years due to their unique advantages,especially as urban viaducts.Vehicle loads are one of the most important variable loads acting on bridge structures.Accordingly,the influence of overloaded vehicles on existing assembled bridge structures is an urgent concern at present.This paper establishes thefinite element model of the segmentally assembled bridge based on ABAQUS software and analyzes the influence of vehicle overload on an assembled girder bridge struc-ture.First,afinite element model corresponding to the target bridge is established based on ABAQUS software,and the load is controlled to simulate vehicle movement in each area of the traveling zone at different times.Sec-ond,the key cross-sections of segmental girder bridges are monitored in real time based on the force character-istics of continuous girder bridges,and they are compared with the simulation results.Finally,a material damage ontology model is introduced,and the structural damage caused by different overloading rates is compared and analyzed.Results show that thefinite element modeling method is accurate by comparing with on-site measured data,and it is suitable for the numerical simulation of segmental girder bridges;Dynamic sensors installed at 1/4L,1/2L,and 3/4L of the segmental girder main beams could be used to identify the dynamic response of segmental girder bridges;The bottom plate of the segmental girder bridge is mostly damaged at the position where the length of the precast beam section changes and the midspan position.With the increase in load,damage in the direction of the bridge develops faster than that in the direction of the transverse bridge.Thefindings of this study can guide maintenance departments in the management and maintenance of bridges and vehicles.

Impact of primary percutaneous coronary intervention on ST-segment elevation myocardial infarction patients:A comprehensive analysis

BACKGROUND Myocardial infarction,particularly ST-segment elevation myocardial infarction(STEMI),is a key global mortality cause.Our study investigated predictors of mortality in 96 STEMI patients undergoing primary percutaneous coronary intervention at Erbil Cardiac Center.Multiple factors were identified influencing in-hospital mortality.Significantly,time from symptom onset to hospital arrival emerged as a decisive factor.Consequently,our study hypothesis is:"Reducing time from symptom onset to hospital arrival significantly improves STEMI prognosis."AIM To determine the key factors influencing mortality rates in STEMI patients.METHODS We studied 96 consecutive STEMI patients undergoing primary percutaneous coronary intervention(PPCI)at the Erbil Cardiac Center.Their clinical histories were compiled,and coronary evaluations were performed via angiography on admission.Data included comorbid conditions,onset of cardiogenic shock,complications during PPCI,and more.Post-discharge,one-month follow-up assessments were completed.Statistical significance was set at P<0.05.RESULTS Our results unearthed several significant findings.The in-hospital and 30-d mortality rates among the 96 STEMI patients were 11.2%and 2.3%respectively.On the investigation of independent predictors of in-hospital mortality,we identified atypical presentation,onset of cardiogenic shock,presence of chronic kidney disease,Thrombolysis In Myocardial Infarction grades 0/1/2,triple vessel disease,ventricular tachycardia/ventricular fibrillation,coronary dissection,and the no-reflow phenomenon.Specifically,the recorded average time from symptom onset to hospital arrival amongst patients who did not survive was significantly longer(6.92±3.86 h)compared to those who survived(3.61±1.67 h),P<0.001.These findings underscore the critical role of timely intervention in improving the survival outcomes of STEMI patients.CONCLUSION Our results affirm that early hospital arrival after symptom onset significantly improves survival rates in STEMI patients,highlighting the critical need for prompt intervention.

An image segmentation method of pulverized coal for particle size analysis

An important index to evaluate the process efficiency of coal preparation is the mineral liberation degree of pulverized coal,which is greatly influenced by the particle size and shape distribution acquired by image segmentation.However,the agglomeration effect of fine powders and the edge effect of granular images caused by scanning electron microscopy greatly affect the precision of particle image segmentation.In this study,we propose a novel image segmentation method derived from mask regional convolutional neural network based on deep learning for recognizing fine coal powders.Firstly,an atrous convolution is introduced into our network to learn the image feature of multi-sized powders,which can reduce the missing segmentation of small-sized agglomerated particles.Then,a new mask loss function combing focal loss and dice coefficient is used to overcome the false segmentation caused by the edge effect.The final comparative experimental results show that our method achieves the best results of 94.43%and 91.44%on AP50 and AP75 respectively among the comparison algorithms.In addition,in order to provide an effective method for particle size analysis of coal particles,we study the particle size distribution of coal powders based on the proposed image segmentation method and obtain a good curve relationship between cumulative mass fraction and particle size.

Temperature-Triggered Hardware Trojan Based Algebraic Fault Analysis of SKINNY-64-64 Lightweight Block Cipher

SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length,and it is mainly used on the Internet of Things(IoT).Currently,faults can be injected into cryptographic devices by attackers in a variety of ways,but it is still difficult to achieve a precisely located fault attacks at a low cost,whereas a Hardware Trojan(HT)can realize this.Temperature,as a physical quantity incidental to the operation of a cryptographic device,is easily overlooked.In this paper,a temperature-triggered HT(THT)is designed,which,when activated,causes a specific bit of the intermediate state of the SKINNY-64-64 to be flipped.Further,in this paper,a THT-based algebraic fault analysis(THT-AFA)method is proposed.To demonstrate the effectiveness of the method,experiments on algebraic fault analysis(AFA)and THT-AFA have been carried out on SKINNY-64-64.In the THT-AFA for SKINNY-64-64,it is only required to activate the THT 3 times to obtain the master key with a 100%success rate,and the average time for the attack is 64.57 s.However,when performing AFA on this cipher,we provide a relation-ship between the number of different faults and the residual entropy of the key.In comparison,our proposed THT-AFA method has better performance in terms of attack efficiency.To the best of our knowledge,this is the first HT attack on SKINNY-64-64.

A novel technique of three-dimensional reconstruction segmentation and analysis for sliced images of biological tissues

A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.

A Comparative Analysis of the New -3(-n) - 1 Remer Conjecture and a Proof of the 3n + 1 Collatz Conjecture

This scientific paper is a comparative analysis of two mathematical conjectures. The newly proposed -3(-n) - 1 Remer conjecture and how it is related to and a proof of the more well known 3n + 1 Collatz conjecture. An overview of both conjectures and their respective iterative processes will be presented. Showcasing their unique properties and behavior to each other. Through a detailed comparison, we highlight the similarities and differences between these two conjectures and discuss their significance in the field of mathematics. And how they prove each other to be true.

Correlation analysis-based image segmentation approach for automatic agriculture vehicle

It is important to segment image correctly to extract guidance information for automatic agriculture vehicle. If we can make the computer know where the crops are, we can extract the guidance line easily. Images were divided into some rec-tangle small windows, then a pair of 1-D arrays was constructed in each small windows. The correlation coefficients of every small window constructed the features to segment images. The results showed that correlation analysis is a potential approach for processing complex farmland for guidance system, and more correlation analysis methods must be researched.

基于SA-Apriori的道路事故风险评估研究

道路事故风险评估是提高道路安全水平的有效方式。为实现在道路网络特征视角下的道路事故风险评估,融合线段分析与频繁集算法,提出SA-Apriori的特征提取算法,进而构建SA-Apriori道路事故风险评估模型,以重庆市大渡口区作为分析对象,建立以道路网络特征变量为指标的道路事故风险等级划分体系,评估其道路事故风险水平,结合商业点位分布情况对该评估方法的有效性进行验证。并针对大渡口区道路事故风险情况,提出道路事故风险的管理对策与建议。结果表明:该道路事故风险评估方法具有较高的可靠性,可为基于路网特征的道路事故风险评估提供参考。

偏心作用下预制拼装桥墩-盖梁体系抗震性能研究

目的 研究不同盖梁节段和盖梁-桥墩连接方式对预制拼装双柱墩偏心作用下的抗震性能的影响。方法 采用有限元软件ABAQUS建立7组预制拼装双柱墩,对其进行偏心作用下拟静力模拟研究,改变桥墩的盖梁节段连接和盖梁-桥墩连接方式,对比分析拼装桥墩和现浇桥墩的滞回曲线、骨架曲线、破坏形态、耗能性能和延性,研究不同盖梁节段连接和盖梁-桥墩连接方式的桥墩抗震性能。结果 盖梁节段键齿连接桥墩,采用灌浆套筒和预应力连接的承载能力与现浇桥墩相比均有小幅度提高,提高幅度在10%以内,抗震性能参数几乎一致。结论 盖梁斜键齿连接,盖梁-桥墩灌浆套筒和盖梁-桥墩预应力连接的预制拼装桥墩与现浇桥墩性能基本一致,同样具有良好抗震性能和整体性,满足抗震要求。

Visual Motion Segmentation in Crowd Videos Based on Spatial-Angular Stacked Sparse Autoencoders

Visual motion segmentation(VMS)is an important and key part of many intelligent crowd systems.It can be used to figure out the flow behavior through a crowd and to spot unusual life-threatening incidents like crowd stampedes and crashes,which pose a serious risk to public safety and have resulted in numerous fatalities over the past few decades.Trajectory clustering has become one of the most popular methods in VMS.However,complex data,such as a large number of samples and parameters,makes it difficult for trajectory clustering to work well with accurate motion segmentation results.This study introduces a spatial-angular stacked sparse autoencoder model(SA-SSAE)with l2-regularization and softmax,a powerful deep learning method for visual motion segmentation to cluster similar motion patterns that belong to the same cluster.The proposed model can extract meaningful high-level features using only spatial-angular features obtained from refined tracklets(a.k.a‘trajectories’).We adopt l2-regularization and sparsity regularization,which can learn sparse representations of features,to guarantee the sparsity of the autoencoders.We employ the softmax layer to map the data points into accurate cluster representations.One of the best advantages of the SA-SSAE framework is it can manage VMS even when individuals move around randomly.This framework helps cluster the motion patterns effectively with higher accuracy.We put forward a new dataset with itsmanual ground truth,including 21 crowd videos.Experiments conducted on two crowd benchmarks demonstrate that the proposed model can more accurately group trajectories than the traditional clustering approaches used in previous studies.The proposed SA-SSAE framework achieved a 0.11 improvement in accuracy and a 0.13 improvement in the F-measure compared with the best current method using the CUHK dataset.

Seismic Analysis of the Connections of Buried Segmented Pipes

Seismic analysis of buried pipes has been one study focus during the last decades,but the systematic seismic research of pipe connections,especially its relationship with the connected straight pipe,is nearly blank.On the basis,the influence of pipe connections on the joint deformations(JDs)of buried segmented pipes is analyzed in detail by considering different parameters,namely,connection shapes,ground conditions,pipe diameters,branch angles,seismic incident angles,and input ground motions.Moreover,an influence coefficient,which measures the influence of pipe connections on pipe JDs,is calculated.Results show that pipe connections can reduce the JDs of segmented pipes by 40%-50%.Furthermore,the JD is more sensitive to the connection shape,ground condition and pipe diameter than the incident angle and characteristics of seismic waves.An influence coefficient of 0.65 is recommended conservatively for the design of the buried segmented pipes.

Pest Detection Method Using Multi-Fractal Analysis

A novel method for pest detection is proposed based on the theory of multi-fractal spectrum to extract pests on plant leaves.Both local and global information of the image regularity were obtained by multi-fractal analysis.By applying fractal dimension,the spots on leaf images can be extracted without loosing or introducing any information.The different parts of images are re-analysis by morphology operations to determine the candidate regions of pests.The performance of multi-fractal analysis of whitefly detection is investigated through greenhouse experiments.The experimental results show that the proposed method is robust to noise from light and is not sensitive to the complex environment.

Test and Numerical Analysis on Performance of Reinforced Concrete Segment in Subway Tunnel

To investigate the mechanical behavior of segmental lining, a three-dimensional numerical analysis and test using three actual segments were used to analyze the effects of axial force and reinforcement ratio on the failure mechanism and ultimate bearing capacity of segmental lining. Both numerical and test results confirmed that the cracking load, yield and ultimate load were strongly influenced by axial force, and it was also proved that the yield and ultimate load would increase with the increase of reinforcement ratio, but the cracking load was almost not affected. The cracking load, yield and ultimate load are about 28.7%, 500% and 460% larger due to the effect of axial force respectively. The comparison between numerical calculation and test results showed that the finite element analysis resuits were in good agreement with the test results.

Integrated use of GIS, remote sensing and multi-criteria decision analysis to assess ecological land suitability in multi-functional forestry

The Zagros forests are a treasure of valuable oak forests, but they have been severely degraded from long-term misuse. Geographic information systems （GIS） and multi-criteria decision analysis （MCDA） have been increasingly used to improve the management of vulnerable ecosystems to prevent further degradation and increase the sustainability of land use. This study presents a methodology to assess land suitability using remote sensing （RS） to obtain wall-to-wall data for the calculations, GIS to analyze the data, and MCDA to rank alternative land uses. The criteria and subcriteria affecting the suitability of land for different uses were identified and weighted using an analytic hierarchy process. Variables used as subcriteria were assessed using satellite data and other sources of information such as existing maps and field surveys. Numerical values for the subcriteria were classified, and each class was given a priority rating according to expert judgments. Based on the ratings and weights of the subcriteria, a priority map was created for each land use using the weighted linear combination method. The priority maps for different land uses were overlaid to obtain a preliminary land use map, which often indicated several simultaneous land uses for the same location. The preliminary map was further edited by removing unrealistic, mutually exclusive land-use combinations. The study tested and demonstrated the potential of integrating RS, G1S and MCDA techniques for solving complicated land allocation problems in forested regions using a scientifically sound and practical approach for efficient and sustainable allocation of forestland for different uses.

Symplectic analysis for elastic wave propagation in two-dimensional cellular structures

On the basis of the finite element analysis, the elastic wave propagation in cellular structures is investigated using the symplectic algorithm. The variation principle is first applied to obtain the dual variables and the wave propagation problem is then transformed into two-dimensional （2D） symplectic eigenvalue problems, where the extended Wittrick-Williams algorithm is used to ensure that no phase propagation eigenvalues are missed during computation. Three typical cellular structures, square, triangle and hexagon, are introduced to illustrate the unique feature of the symplectic algorithm in higher-frequency calculation, which is due to the conserved properties of the structure-preserving symplectic algorithm. On the basis of the dispersion relations and phase constant surface analysis, the band structure is shown to be insensitive to the material type at lower frequencies, however, much more related at higher frequencies. This paper also demonstrates how the boundary conditions adopted in the finite element modeling process and the structures＇ configurations affect the band structures. The hexagonal cells are demonstrated to be more efficient for sound insulation at higher frequencies, while the triangular cells are preferred at lower frequencies. No complete band gaps are observed for the square cells with fixed-end boundary conditions. The analysis of phase constant surfaces guides the design of 2D cellular structures where waves at certain frequencies do not propagate in specified directions. The findings from the present study will provide invaluable guidelines for the future application of cellular structures in sound insulation.

Image analysis and machine learning-based malaria assessment system

Malaria is an important and worldwide fatal disease that has been widely reported by the World Health Organization(WHO),and it has about 219 million cases worldwide,with 435,000 of those mortal.The common malaria diagnosis approach is heavily reliant on highly trained experts,who use a microscope to examine the samples.Therefore,there is a need to create an automated solution for the diagnosis of malaria.One of the main objectives of this work is to create a design tool that could be used to diagnose malaria from the image of a blood sample.In this paper,we firstly developed a graphical user interface that could be used to help segment red blood cells and infected cells and allow the users to analyze the blood samples.Secondly,a Feed-forward Neural Network(FNN)is designed to classify the cells into two classes.The achieved results show that the proposed techniques can be used to detect malaria,as it has achieved 92%accuracy with a database that contains 27,560 benchmark images.

Influence of lens position as detected by an anterior segment analysis system on postoperative refraction in cataract surgery

AIM:To predict postoperative intraocular lens(IOL)position using the Sirius anterior segment analysis system and investigate the effect of lens position and IOL type on postoperative refraction.METHODS:A total of 97 patients(102 eyes)were enrolled in the final analysis.An anterior segment biometry measurement was performed preoperatively with Sirius and Lenstar.The results of predicted lens position(PLP)and IOL power were automatically calculated by the software used by the instruments.Effective lens position(ELP)was measured manually using Sirius 3 mo postoperatively.Pearson's correlation analysis and linear regression analysis were used to determine the correlation of lens position to other parameters.RESULTS:PLP and ELP were positively correlated to axial length(AL;r=0.42,P<0.0001 and r=0.49,P<0.0001,respectively).There was a weak correlation between the peLP(ELP-PLP)and the prediction error of spherical refraction(peSR;r=0.34,P<0.0001).The peLP of Softec HD IOL differed statistically from those of both the TECNIS ZCB00 and Sensor AR40E IOLs.Multiple linear regression was used to obtain the prediction formula:ELP=0.66+0.63×[aqueous depth(AQD)+0.6 LT](r=0.61,P<0.0001),and a new variable(AQD+0.6 LT)was found to have the strongest correlation with ELP.CONCLUSION:The Sirius anterior segment analysis system is helpful to predict ELP,which reduces postoperative refraction error.

Semi-supervised learning based probabilistic latent semantic analysis for automatic image annotation

In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficient and effective searching environment for users to query their images more easily. In this paper,a semi-supervised learning based probabilistic latent semantic analysis( PLSA) model for automatic image annotation is presenred. Since it's often hard to obtain or create labeled images in large quantities while unlabeled ones are easier to collect,a transductive support vector machine( TSVM) is exploited to enhance the quality of the training image data. Then,different image features with different magnitudes will result in different performance for automatic image annotation. To this end,a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible. Finally,a PLSA model with asymmetric modalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores. Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PLSA for the task of automatic image annotation.

Shenqi Fuzheng injection combined with GP chemotherapy in the treatment of advanced non-small cell lung cancer： a meta-analysis

Objective： To evaluate the clinical efficacy of Shenqi Fuzheng injection combined with gemcitabine plus cisplatin（GP） in the treatment of advanced non-small cell lung cancer （NSCLC）. Methods： we performed a systematicsearch in the electronic databases such as Cochrane Library, Pubmed, Embase, Chinese Journal Full-text Database,Chinese Biomedical Literature Database, Chinese Science and Technology Periodical Full-text Database andWanfang Database up to 30 January 2017. Randomized controlled trials （RCT） of Shenqi Fuzheng Injectioncombined with GP chemotherapy in the treatment of advanced NSCLC were searched, and all the RCTs wereconducted on methodological quality assessment. Data extraction and data analysis were according to standards ofCochrane systematic review. Results： Eight trials were included including a total of 701 patients. Meta-analysisresults： Shenqi Fuzheng injection combined with GP chemotherapy could significantly improve the functionalstatus of patients with NSCLC （OR = 3.44, 95% CI [2.26, 5.25], P 〈 0.0001） and clinical treatment efficacy （OR =（OR = 0.31, 95%CI [0.20, 0.47], P 〈 0.0001. The rate of leukopenia （OR = .31, 95%CI [0.20,0.47], P 〈 0.0001）,thrombocytopenia （OR = 0.58, 95%CI [0.37, 0.91], P = 0.020）, hemoglobin decline （（OR = 0.31, 95%CI [0.16,0.59], P = 0.0004） and incidence of gastrointestinal reactions （OR = 0.58,P 〈 0.05） could be reduced. Conclusion：Shenqi Fuzheng injection combined with GP chemotherapy in the treatment of advanced NSCLC obtainedsignificantly clinical efficacy. The quality of the literature incorporated is low, the conclusion requires high-qualityresearch to further prove.