Rapid Prototype Development Approach for Genetic Programming

Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals.

The Role and Place of Artificial Neural Network Architectures Structural Redundancy in the Input Data Prototypes and Generalization Development

Neural Networks (NN) are the functional unit of Deep Learning and are known to mimic the behavior of the human brain to solve complex data-driven problems. Whenever we train our own neural networks, we need to take care of something called the generalization of the neural network. The performance of Artificial Neural Networks (ANN) mostly depends upon its generalization capability. In this paper, we propose an innovative approach to enhance the generalization capability of artificial neural networks (ANN) using structural redundancy. A novel perspective on handling input data prototypes and their impact on the development of generalization, which could improve to ANN architectures accuracy and reliability is described.

The Advertisement Translation Based on the Prototype Theory

Based on the Prototype Theory,the prototypical feature of advertisement is found to be the combination of three language functions:the informative function,the expressive function,and the vocative function.The advertisement translation means the adjustment of the informative function and the expressive function according to the differences between languages or cultures in order to maximize the vocative function.The faithful translation is the closest to the prototype of the source text but not necessarily the best translation.

Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.

基于K-prototypes的混合属性数据聚类算法改进

属性数据分为数值型数据和分类型数据,一般情况下对于数值型数据运算前要进行标准化处理,但是对于数值型数据差异大的数据,由于大数掩盖小数的影响,按照K-prototypes聚类算法,数值型数据标准化后而且不对相应的分类数据有任何预处理或者在计算时没有进行任何改变,很可能提高分类数据在聚类中的影响,并且分类型数据并未进一步地细分,不能满足不同要求的混合属性聚类。该文在将数值型数据标准化的基础上,将分类数据细分为二元数据和类型数据,并用相异度系数距离计算分类数据之间的距离,并且赋予二元和类型数据相应的权重,来改进K-prototypes聚类算法,使该算法满足不同要求的混合属性数据聚类,最后通过C#语言,在ArcEngine2010版本上实现。

A multi-purpose prototype test system for mechanical behavior of tunnel supporting structure: Development and application

A multi-purpose prototype test system is developed to study the mechanical behavior of tunnel sup-porting structure,including a modular counterforce device,a powerful loading equipment,an advanced intelligent management system and an efficient noncontact deformation measurement system.The functions of the prototype test system are adjustable size and shape of the modular counterforce structure,sufficient load reserve and accurate loading,multi-connection linkage intelligent management,and high-precision and continuously positioned noncontact deformation measurement.The modular counterforce structure is currently the largest in the world,with an outer diameter of 20.5 m,an inner diameter of 16.5 m and a height of 6 m.The case application proves that the prototype test system can reproduce the mechanical behavior of the tunnel lining during load-bearing,deformation and failure processes in detail.

基于在线梯度下降的Mini Batch K-Prototypes算法

K-Prototypes算法每次迭代都需要花费大量时间来计算所有样本与每个簇中心的相异度以将其划分到各个聚类簇中,这导致K-Prototypes算法在处理大型数据集时运行时间急剧增加。根据在线梯度下降算法对K-Prototypes算法的迭代过程进行优化,减少算法每次迭代所需的计算量从而降低算法的时间复杂度,提升算法运行效率。实验结果表明,提出的基于在线梯度下降的K-Prototypes聚类算法,可以在不影响算法收敛性和有效性的前提下降低算法的时间复杂度,提升算法运行效率。

基于改进K-prototypes与GBDT的城市干道车辆出行群体辨识模型

为了掌握城市干道交通运行规律,向交通管理部门制定相关交通需求管理政策提供理论依据,提出了一种基于组合模型的城市干道车辆出行群体辨识模型。基于青岛市胶州湾隧道过车数据,从出行强度、出行时间与出行习惯3个维度构建了出行特征指标体系以全面刻画车辆个体的出行行为。基于相关性分析剔除了冗余指标以避免对辨识研究的影响。针对混合属性出行特征指标数据,使用改进K-prototypes算法以有效地实现车辆出行群体划分,将其与GBDT算法相结合,建立了一种基于改进K-prototypes与GBDT的辨识模型,随机选取10000个样本开展辨识研究。结果表明:研究道路存在5类车辆出行群体:高频通勤群体、低频通勤群体、营运群体、频次稳定群体与普通群体,对于这5类车辆出行群体,平均识别准确率为97.75%,最高识别准确率可达99.47%。

Development and preliminary results of a large-pixel two-layer LaBr_(3) Compton camera prototype

Lanthanum bromide(LaBr_(3))crystal has a high energy resolution and time resolution and has been used in Compton cameras(CCs)over the past few decades.However,LaBr_(3) crystal arrays are difficult to process because LaBr_(3) is easy to crack and break;thus,few LaBr_(3)-based CC prototypes have been built.In this study,we designed and fabricated a large-pixel LaBr_(3) CC prototype and evaluated its performance with regard to position,energy,and angular resolution.We used two 10×10 LaBr_(3) crystal arrays with a pixel size of 5 mm×5 mm,silicon photomultipliers(SiPMs),and corresponding decoding circuits to construct our prototype.Additionally,a framework based on a Voronoi diagram and a lookup table was developed for list-mode projection data acquisition.Monte Carlo(MC)simulations based on Geant4 and experiments were conducted to evaluate the performance of our CC prototype.The lateral position resolution was 5 mm,and the maximum deviation in the depth direction was 2.5 and 5 mm for the scatterer and absorber,respectively.The corresponding measured energy resolu-tions were 7.65%and 8.44%,respectively,at 511 keV.The experimental results of ^(137)Cs point-like sources were consistent with the MC simulation results with regard to the spatial positions and full widths at half maximum(FWHMs).The angular resolution of the fabricated prototype was approximately 6°when a point-like ^(137)Cs source was centrally placed at a distance of 5 cm from the scatterer.We proposed and investigated a large-pixel LaBr_(3) CC for the first time and verified its feasibility for use in accurate spatial positioning of radiative sources with a high angular resolution.The proposed CC can satisfy the requirements of radiative source imaging and positioning in the nuclear industry and medical applications.

UAV-Aided Data and Energy Integrated Network: System Design and Prototype Development

Terminal devices deployed in outdoor environments are facing a thorny problem of power supply.Data and energy integrated network(DEIN)is a promising technology to solve the problem,which simultaneously transfers data and energy through radio frequency signals.State-of-the-art researches mostly focus on theoretical aspects.By contrast,we provide a complete design and implementation of a fully functioning DEIN system with the support of an unmanned aerial vehicle(UAV).The UAV can be dispatched to areas of interest to remotely recharge batteryless terminals,while collecting essential information from them.Then,the UAV uploads the information to remote base stations.Our system verifies the feasibility of the DEIN in practical applications.

Complement-dependent neuroinflammation in spinal cord injury:from pathology to therapeutic implications

Spinal cord injury remains a major cause of disability in young adults,and beyond acute decompression and rehabilitation,there are no pharmacological treatments to limit the progression of injury and optimize recovery in this population.Following the thorough investigation of the complement system in triggering and propagating cerebral neuroinflammation,a similar role for complement in spinal neuroinflammation is a focus of ongoing research.In this work,we survey the current literature investigating the role of complement in spinal cord injury including the sources of complement proteins,triggers of complement activation,and role of effector functions in the pathology.We study relevant data demonstrating the different triggers of complement activation after spinal cord injury including direct binding to cellular debris,and or activation via antibody binding to damage-associated molecular patterns.Several effector functions of complement have been implicated in spinal cord injury,and we critically evaluate recent studies on the dual role of complement anaphylatoxins in spinal cord injury while emphasizing the lack of pathophysiological understanding of the role of opsonins in spinal cord injury.Following this pathophysiological review,we systematically review the different translational approaches used in preclinical models of spinal cord injury and discuss the challenges for future translation into human subjects.This review emphasizes the need for future studies to dissect the roles of different complement pathways in the pathology of spinal cord injury,to evaluate the phases of involvement of opsonins and anaphylatoxins,and to study the role of complement in white matter degeneration and regeneration using translational strategies to supplement genetic models.

Antibodies elicited by Newcastle disease virus-vectored H7N9 avian influenza vaccine are functional in activating the complement system

H7N9 subtype avian influenza virus poses a great challenge for poultry industry.Newcastle disease virus(NDV)-vectored H7N9 avian influenza vaccines(NDV_(vec)H7N9)are effective in disease control because they are protective and allow mass administration.Of note,these vaccines elicit undetectable H7N9-specific hemagglutination-inhibition(HI)but high IgG antibodies in chickens.However,the molecular basis and protective mechanism underlying this particular antibody immunity remain unclear.Herein,immunization with an NDV_(vec)H7N9 induced low anti-H7N9 HI and virus neutralization titers but high levels of hemagglutinin(HA)-binding IgG antibodies in chickens.Three residues(S150,G151 and S152)in HA of H7N9 virus were identified as the dominant epitopes recognized by the NDV_(vec)H7N9 immune serum.Passively transferred NDV_(vec)H7N9 immune serum conferred complete protection against H7N9 virus infection in chickens.The NDV_(vec)H7N9 immune serum can mediate a potent lysis of HA-expressing and H7N9 virus-infected cells and significantly suppress H7N9 virus infectivity.These activities of the serum were significantly impaired after heat-inactivation or treatment with complement inhibitor,suggesting the engagement of the complement system.Moreover,mutations in the 150-SGS-152 sites in HA resulted in significant reductions in cell lysis and virus neutralization mediated by the NDV_(vec)H7N9 immune serum,indicating the requirement of antibody-antigen binding for complement activity.Therefore,antibodies induced by the NDV_(vec)H7N9 can activate antibody-dependent complement-mediated lysis of H7N9 virus-infected cells and complement-mediated neutralization of H7N9 virus.Our findings unveiled a novel role of the complement in protection conferred by the NDV_(vec)H7N9,highlighting a potential benefit of engaging the complement system in H7N9 vaccine design.

Association of complement components with risk of colorectal cancer:A systematic review and meta-analysis

BACKGROUND Complement components could contribute to the tumor microenvironment and the systemic immune response.Nevertheless,their role in colorectal cancer(CRC)remains a contentious subject.AIM To elucidate the relationship between complement components and CRC risk and clinical characteristics.METHODS Searches were conducted in PubMed,the Cochrane Library,and the China National Knowledge Infrastructure database until June 1,2023.We included cohort studies encompassing participants aged≥18 years,investigating the association between complement components and CRC.The studies were of moderate quality or above,as determined by the Agency for Healthcare Research and Quality.The meta-analysis employed fixed-effects or random-effects models based on the I^(2)test,utilizing risk ratio(RR)and their corresponding 95%confidence interval(CI)for outcomes.Sensitivity and subgroup analyses were performed to validate the robustness of the collective estimates and identify the source of heterogeneity.RESULTS Data from 15 studies,comprising 1631 participants that met the inclusion criteria,were included in the meta-analysis.Our findings indicated that protein levels of cluster of differentiation 46(CD46)(RR=3.66,95%CI:1.75-7.64,P<0.001),CD59(RR=2.86,95%CI:1.36-6.01,P=0.005),and component 1(C1)(RR=5.88,95%CI:1.75-19.73,P=0.004)and serum levels of C3(standardized mean difference=1.82,95%CI:0.06-3.58,P=0.040)were significantly elevated in patients with CRC compared to healthy controls.Strong expression of CD55 or CD59 was associated with a higher incidence of lymph node metastasis,whereas strong CD46 expression correlated with a higher incidence of tumor differentiation compared to low CD46 expression(P<0.05 for all).Although specific pooled results demonstrated notable heterogeneity,subgroup analyses pointed to regional differences as the primary source of inconsistency among the studies.CONCLUSION Our analysis underscores that increased levels of specific complement components are associated with a heightened risk of CRC,emphasizing the potential significance of monitoring elevated complement component levels.

Few-shot image recognition based on multi-scale features prototypical network

In order to improve the models capability in expressing features during few-shot learning,a multi-scale features prototypical network(MS-PN)algorithm is proposed.The metric learning algo-rithm is employed to extract image features and project them into a feature space,thus evaluating the similarity between samples based on their relative distances within the metric space.To sufficiently extract feature information from limited sample data and mitigate the impact of constrained data vol-ume,a multi-scale feature extraction network is presented to capture data features at various scales during the process of image feature extraction.Additionally,the position of the prototype is fine-tuned by assigning weights to data points to mitigate the influence of outliers on the experiment.The loss function integrates contrastive loss and label-smoothing to bring similar data points closer and separate dissimilar data points within the metric space.Experimental evaluations are conducted on small-sample datasets mini-ImageNet and CUB200-2011.The method in this paper can achieve higher classification accuracy.Specifically,in the 5-way 1-shot experiment,classification accuracy reaches 50.13%and 66.79%respectively on these two datasets.Moreover,in the 5-way 5-shot ex-periment,accuracy of 66.79%and 85.91%are observed,respectively.

Complement factor Ⅰ knockdown inhibits colon cancer development by affecting Wnt/β-catenin/c-Myc signaling pathway and glycolysis

BACKGROUND Colon cancer(CC)occurrence and progression are considerably influenced by the tumor microenvironment.However,the exact underlying regulatory mechanisms remain unclear.AIM To investigate immune infiltration-related differentially expressed genes(DEGs)in CC and specifically explored the role and potential molecular mechanisms of complement factor I(CFI).METHODS Immune infiltration-associated DEGs were screened for CC using bioinformatics.Quantitative reverse transcription polymerase chain reaction was used to examine hub DEGs expression in the CC cell lines.Stable CFI-knockdown HT29 and HCT116 cell lines were constructed,and the diverse roles of CFI in vitro were assessed using CCK-8,5-ethynyl-2’-deoxyuridine,wound healing,and transwell assays.Hematoxylin and eosin staining and immunohistochemistry staining were employed to evaluate the influence of CFI on the tumorigenesis of CC xenograft models constructed using BALB/c male nude mice.Key proteins associated with glycolysis and the Wnt pathway were measured using western blotting.RESULTS Six key immune infiltration-related DEGs were screened,among which the expression of CFI,complement factor B,lymphoid enhancer binding factor 1,and SRY-related high-mobility-group box 4 was upregulated,whereas that of fatty acid-binding protein 1,and bone morphogenic protein-2 was downregulated.Furthermore,CFI could be used as a diagnostic biomarker for CC.Functionally,CFI silencing inhibited CC cell proliferation,migration,invasion,and tumor growth.Mechanistically,CFI knockdown downregulated the expression of key glycolysis-related proteins(glucose transporter type 1,hexokinase 2,lactate dehydrogenase A,and pyruvate kinase M2)and the Wnt pathway-related proteins(β-catenin and c-Myc).Further investigation indicated that CFI knockdown inhibited glycolysis in CC by blocking the Wnt/β-catenin/c-Myc pathway.CONCLUSION The findings of the present study demonstrate that CFI plays a crucial role in CC development by influencing glycolysis and the Wnt/β-catenin/c-Myc pathway,indicating that it could serve as a promising target for therapeutic intervention in CC.

Tumor-related factor complement Clq/TNF-related protein 6 affects the development of digestive system tumors through the phosphatidylinositol 3-kinase pathway

In this editorial,we review the work of Razali et al published in World J Gas-troenterology,with a particular focus on the effect of rs10889677 variation in the phosphatidylinositol 3-kinase(PI3K)pathway and buparlisib on colitis-associated cancer.The role of PI3K in promoting cancer progression has been widely recognized,as it is involved in regulating the survival,differentiation,and prolif-eration of cancer cells.The complement Clq/TNF-related protein 6(CTRP6)is a newer tumor-associated factor.Recent studies have revealed the pro-tumor effect of CTRP6 in gastric cancer,hepatocellular carcinoma,colorectal cancer,and other gastrointestinal tumors through the PI3K pathway.This article attempts to reveal the mechanism through which the CTRP6 affects the development of digestive system tumors through the PI3K pathway by summarizing recent research.

Repetitive traumatic brain injury–induced complement C1–related inflammation impairs long-term hippocampal neurogenesis

Repetitive traumatic brain injury impacts adult neurogenesis in the hippocampal dentate gyrus,leading to long-term cognitive impairment.However,the mechanism underlying this neurogenesis impairment remains unknown.In this study,we established a male mouse model of repetitive traumatic brain injury and performed long-term evaluation of neurogenesis of the hippocampal dentate gyrus after repetitive traumatic brain injury.Our results showed that repetitive traumatic brain injury inhibited neural stem cell proliferation and development,delayed neuronal maturation,and reduced the complexity of neuronal dendrites and spines.Mice with repetitive traumatic brain injuryalso showed deficits in spatial memory retrieval.Moreover,following repetitive traumatic brain injury,neuroinflammation was enhanced in the neurogenesis microenvironment where C1q levels were increased,C1q binding protein levels were decreased,and canonical Wnt/β-catenin signaling was downregulated.An inhibitor of C1 reversed the long-term impairment of neurogenesis induced by repetitive traumatic brain injury and improved neurological function.These findings suggest that repetitive traumatic brain injury–induced C1-related inflammation impairs long-term neurogenesis in the dentate gyrus and contributes to spatial memory retrieval dysfunction.

PARAMETERIZED-PROTOTYPE-BASED DYNAMIC OPTIMIZATION DESIGN FOR CAM PROFILE

Aiming at the problems in current cam profile optimization processes, such as simple dynamics models, limited geometric accuracy and low design automatization level, a new dynamic optimization mode is put forward. Based on the parameterization modeling technique of MSC. ADAMS platform, the different steps in current mode are reorganized, thus obtaining an upgraded mode called the ＂parameterized-prototype-based cam profile dynamic optimization mode＂. A parameterized prototype（PP） of valve mechanism is constructed in the course of dynamic optimization for cam profiles. Practically, by utilizing PP and considering the flexibility of the parts in valve mechanism, geometric accuracy and design automatization are improved.

Experimental Investigation on Basic Prototype of Solid Propellant Impulsive Microthrusters

A new type of impulsive microthruster and its measurement system were designed for the aim of testing the performance of a basic prototype of solid propellant impulsive microthruster. Two sets of tests were conducted. The tests show that the ignitor and the main charge of the microthruster match well, the dynamic and static capability of the test and measurement meets the test requirement and the result is creditable. The measured technical characteristics of the microthruster are that the ignition delay time is shorter than 0 3?ms, the total impulse is over 3?N·s, the operational time is shorter than 16?ms and the mass ratio of the thruster is 0 216.

基于K-prototypes的混合属性数据聚类算法

通过对基于K-prototypes算法对混合属性数据处理的聚类问题进行研究,改进了K-prototypes算法中分类属性相异度计算公式,使之能更加精确反映样本间的差异;在此基础上提出了一种用于处理混合属性数据的聚类算法,并将改进后的算法应用于英语借词数据的聚类分析中。实验结果表明,与K-prototypes算法相比,改进后的算法具有更好的稳定性和更高的精度。