软件工程“361”课程思政育人探讨

教师的根本任务是立德树人,思政是立德树人的重要手段。软件工程课程在教学实践中不断探索、完善,完成了“361”课程思政育人体系构建。通过思政材料的课前发送、课堂点睛、课后延伸,将课前、课中、课后“3”阶段紧密衔接,实现全过程思政育人。通过“思想引领”、“知识传授”、“互动探讨”、“作业回顾”、“项目实践”和“教师示范”“6”环节的密切配合,实现多环节思政育人。课外“1”塑造,学生通过参与竞赛或实践活动,完成团队与个人项目综合实践,不断成长成才,完成课外思政。“361”课程思政育人体系既完成了知识传递,又进行了思想引领、价值塑造,同时提高了学生学习与实践能力,将课程思政落到了实处。

Dual-Path Vision Transformer用于急性缺血性脑卒中辅助诊断

急性缺血性脑卒中是由于脑组织血液供应障碍导致的脑功能障碍,数字减影脑血管造影(DSA)是诊断脑血管疾病的金标准。基于患者的正面和侧面DSA图像,对急性缺血性脑卒中的治疗效果进行分级评估,构建基于Vision Transformer的双路径图像分类智能模型DPVF。为了提高辅助诊断速度,基于EdgeViT的轻量化设计思想进行了模型的构建;为了使模型保持轻量化的同时具有较高的精度,提出空间-通道自注意力模块,促进Transformer模型捕获更全面的特征信息,提高模型的表达能力;此外,对于DPVF的两分支的特征融合,构建交叉注意力模块对两分支输出进行交叉融合,促使模型提取更丰富的特征,从而提高模型表现。实验结果显示DPVF在测试集上的准确率达98.5%,满足实际需求。

miR-361-3p通过靶向S100A6抑制甲状腺癌细胞增殖、迁移、侵袭及凋亡的机制

目的探讨miR-361-3p通过靶向S100A6抑制甲状腺癌细胞增殖、迁移、侵袭及凋亡的机制。方法运用逆转录定量聚合酶链式反应(RT-qPCR)法检测甲状腺癌组织、细胞中miR-361-3p表达水平;脂质体法将miR-con组(转染miRcon)、miR-361-3p组(转染miR-361-3p)、si-con组(转染si-con)、si-L型氨基酸转运蛋白(S100A6)组(转染si-S100A6)、miR-361-3p+pcDNA组(共转染miR-361-3p和pcDNA)、miR-361-3p+pcDNA-S100A6组(共转染miR-361-3p和pcDNA-S100A6)转染至CAL-62细胞。细胞计数试剂盒(CCK)8、5-乙炔基-2′-脱氧尿苷(EDU)法检测细胞增殖情况;划痕实验、Transwell小室实验检测细胞迁移侵袭能力;Western印迹检测S100A6蛋白表达;双荧光素酶报告基因实验检测细胞荧光活性。结果与癌旁组织、Nthy-ori 3-1相比,癌组织、癌细胞(TPC-1、SW579、CAL-62)中miR-361-3p表达均显著降低(P<0.05)。过表达miR-361-3p后,细胞增殖显著降低,EDU阳性率显著降低,划痕抑制率显著升高,迁移侵袭能力显著降低(P<0.05)。miR-361-3p显著抑制野生型S100A6细胞的荧光活性,并负向调控S100A6蛋白,二者在癌组织中表达呈显著负相关(r=-0.627,P<0.05)。敲减S100A6具有与过表达miR-361-3p相似的作用,过表达S100A6部分逆转miR-361-3p增殖、迁移侵袭抑制作用。结论miR-361-3p可抑制甲状腺癌细胞的增殖、迁移侵袭,产生这种作用的机制与靶向S100A6有关。

miR-361介导PI3K/Akt/Ca^(2+)通路对大鼠肥大细胞增殖情况及组胺与IL-4表达水平的影响

目的:探讨miR-361介导PI3K/AKt/Ca^(2+)通路对活化大鼠肥大细胞增殖情况及组胺与白细胞介素-4(IL-4)表达水平的影响。方法:将大鼠肥大细胞(RBL-2H3细胞)分为miR-361过表达组、miR-361抑制组、miR-361对照组和正常对照组,miR-361过表达组、miR-361抑制组、miR-361对照组细胞分别转染miR-361过表达、miR-361抑制及miR-361无义序列寡核苷酸片段,测定并比较各组细胞miR-361 mRNA、组胺、IL-4及PI3K/AKt/Ca^(2+)通路相关蛋白水平。结果:miR-361过表达组细胞miR-361 mRNA相对表达水平高于miR-361抑制组、miR-361对照组及正常对照组,差异均有统计学意义(P<0.05)。CCK-8法检测结果显示,miR-361过表达组24、48、72 h细胞增值率均低于miR-361抑制组、miR-361对照组及正常对照组,差异均有统计学意义(P<0.05)。ELISA法检测结果显示,miR-361过表达组细胞组胺和IL-4水平的表达水平低于miR-361抑制组、miR-361对照组及正常对照组,差异均有统计学意义(P<0.05)。Western印迹法检测结果显示,miR-361过表达组细胞p-AKT、AKT、p-PI3K、PI3K蛋白表达水平均高于miR-361抑制组、miR-361对照组及正常对照组,差异均有统计学意义(P<0.05)。结论:miR-361过表达可抑制大鼠肥大细胞的增殖,降低组胺与IL-4的表达水平,其作用机制可能与其能够提高PI3K/AKt/Ca^(2+)通路活性有关。

Enhancing Critical Path Problem in Neutrosophic Environment Using Python

In the real world,one of the most common problems in project management is the unpredictability of resources and timelines.An efficient way to resolve uncertainty problems and overcome such obstacles is through an extended fuzzy approach,often known as neutrosophic logic.Our rigorous proposed model has led to the creation of an advanced technique for computing the triangular single-valued neutrosophic number.This innovative approach evaluates the inherent uncertainty in project durations of the planning phase,which enhances the potential significance of the decision-making process in the project.Our proposed method,for the first time in the neutrosophic set literature,not only solves existing problems but also introduces a new set of problems not yet explored in previous research.A comparative study using Python programming was conducted to examine the effectiveness of responsive and adaptive planning,as well as their differences from other existing models such as the classical critical path problem and the fuzzy critical path problem.The study highlights the use of neutrosophic logic in handling complex projects by illustrating an innovative dynamic programming framework that is robust and flexible,according to the derived results,and sets the stage for future discussions on its scalability and application across different industries.

Optimal search path planning of UUV in battlefeld ambush scene

Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.

An Improved Bounded Conflict-Based Search for Multi-AGV Pathfinding in Automated Container Terminals

As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.

胃癌组织miR-23a-3p、miR-361-5p表达与PI3K/AKT/mTOR信号通路和预后的关系研究

目的探讨胃癌组织微小核糖核酸(miR)-23a-3p、miR-361-5p表达与磷脂酰肌醇3激酶(PI3K)/蛋白激酶B(AKT)/哺乳动物雷帕霉素靶蛋白(mTOR)信号通路和预后的关系。方法采用实时荧光定量聚合酶链反应检测120例胃癌患者胃癌组织与癌旁组织中miR-23a-3p、miR-361-5p、PI3K mRNA、AKT mRNA、mTOR mRNA表达。Pearson相关分析胃癌组织中miR-23a-3p、miR-361-5p表达与PI3K mRNA、AKT mRNA、mTOR mRNA表达的相关性,以及分析miR-23a-3p、miR-361-5p表达与胃癌患者临床病理特征的关系。Kaplan-Meier生存分析胃癌组织中不同miR-23a-3p、miR-361-5p表达与胃癌患者生存预后的关系。单因素及多因素COX回归分析影响胃癌患者生存预后因素。结果相比于癌旁组织,胃癌组织中miR-23a-3p、miR-361-5p表达明显较低,而PI3K mRNA、AKT mRNA、mTOR mRNA表达明显较高,差异有统计学意义(均P<0.05)。Pearson相关分析结果显示,胃癌组织中miR-23a-3p、miR-361-5p表达与PI3K mRNA、AKT mRNA、mTOR mRNA表达呈负相关(均P<0.05)。不同肿瘤TNM分期、肿瘤分化程度、术后辅助化疗及淋巴结转移的胃癌患者胃癌组织中miR-23a-3p、miR-361-5p表达比较,差异有统计学意义(均P<0.05)。miR-23a-3p低表达胃癌患者3年总体生存率为46.77%(29/62),低于miR-23a-3p高表达胃癌患者3年总体生存率[81.03%(47/58)],差异有统计学意义(Log-Rankχ^(2)=30.243,P<0.001)。miR-361-5p低表达胃癌患者3年总体生存率为50.79%(32/63),低于miR-361-5p高表达胃癌患者3年总体生存率[77.19%(44/57)],差异有统计学意义(Log-Rankχ^(2)=24.932,P<0.001)。单因素及多因素Cox回归分析结果显示,TNM分期Ⅲ期、有淋巴结转移、无术后辅助化疗、miR-23a-3p低表达、miR-361-5p低表达是影响胃癌患者不良预后的独立危险因素(P<0.05)。结论胃癌患者胃癌组织中miR-23a-3p、miR-361-5p表达降低,二者表达与PI3K/AKT/mTOR信号通路有关,是潜在的胃癌预后相关的肿瘤标志物。

A Multi-Constraint Path Optimization Scheme Based on Information Fusion in Software Defined Network

The existingmultipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is alack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptationof service requirements and network resources. To address these issues, we propose a multi-constraint pathoptimization scheme based on information fusion in SDN. The proposed scheme collects network topology andnetwork state information on the network side and computes disjoint paths between end hosts. It uses the FuzzyAnalytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters andconstructs a composite quality evaluation function for the paths to determine the priority of the disjoint paths. TheSDN controller extracts the service attributes by analyzing the packet header and selects the optimal path for flowrule forwarding. Furthermore, the service attributes are fed back to the path composite quality evaluation function,and the path priority is dynamically adjusted to achieve dynamic adaptation between service requirements andnetwork status. By continuously monitoring and analyzing the service attributes, the scheme can ensure optimalrouting decisions in response to varying network conditions and evolving service demands. The experimentalresults demonstrated that the proposed scheme can effectively improve average throughput and link utilizationwhile meeting the Quality of Service (QoS) requirements of various applications.

Distal-scanning common path probe for optical coherence tomography

In this paper,we present a distal-scanning common path probe for optical coherence tomography(OCT)equipped with a hollow ultrasonic motor and a simple and specially designed beam-splitter.This novel probe proves to be able to effectively circumvent polarization and dispersion mismatch caused by fiber motion and is more robust to a variety of interfering factors during the imaging process,experimentally compared to a conventional noncommon path probe.Furthermore,our design counteracts the attenuation of backscattering with depth and the fall-off of the signal,resulting in a more balanced signal range and greater imaging depth.Spectral-domain OCT imaging of phantom and biological tissue is also demonstrated with a sensitivity of∼100dB and a lateral resolution of∼3μm.This low-cost probe offers simplified system configuration and excellent robustness,and is therefore particularly suitable for clinical diagnosis as one-off medical apparatus.

Mechanical response and dilatancy characteristics of deep marble under different stress paths:A sight from energy dissipation

Dilatancy is a fundamental volumetric growth behavior observed during loading and serves as a key index to comprehending the intricate nonlinear behavior and constitutive equation structure of rock.This study focuses on Jinping marble obtained from the Jinping Underground Laboratory in China at a depth of 2400 m.Various uniaxial and triaxial tests at different strain rates,along with constant confining pressure tests and reduced confining pressure tests under different confining pressures were conducted to analyze the mechanical response and dilatancy characteristics of the marble under four stress paths.Subsequently,a new empirical dilatancy coefficient is proposed based on the energy dissipation method.The results show that brittle failure characteristics of marble under uniaxial compression are more obvious with the strain rate increasing,and plastic failure characteristics of marble under triaxial compression are gradually strengthened.Furthermore,compared to the constant confining pressure,the volume expansion is relatively lower under unloading condition.The energy dissipation is closely linked to the process of dilatancy,with a rapid increase of dissipated energy coinciding with the beginning of dilatancy.A new empirical dilatancy coefficient is defined according to the change trend of energy dissipation rate curve,of which change trend is consistent with the actual dilatancy response in marble under different stress paths.The existing empirical and theoretical dilatancy models are analyzed,which shows that the empirical dilatancy coefficient based on the energy background is more universal.

Multi-circular formation control with reinforced transient profiles for nonholonomic vehicles:A path-following framework

This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.

On traceable iterated line graph and hamiltonian path index

Xiong and Liu[21]gave a characterization of the graphs G for which the n-iterated line graph L^(n)(G)is hamiltonian,for n≥2.In this paper,we study the existence of a hamiltonian path in L^(n)(G),and give a characterization of G for which L^(n)(G)has a hamiltonian path.As applications,we use this characterization to give several upper bounds on the hamiltonian path index of a graph.

Ground threat prediction-based path planning of unmanned autonomous helicopter using hybrid enhanced artificial bee colony algorithm

Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.

Correlation and Pathway Analysis of the Carbon,Nitrogen,and Phosphorus in Soil-Microorganism-Plant with Main Quality Components of Tea(Camellia sinensis)

The contents of carbon(C),nitrogen(N),and phosphorus(P)in soil-microorganisms-plant significantly affect tea quality by altering the main quality components of tea,such as tea polyphenols,amino acids,and caffeine.However,few studies have quantified the effects of these factors on the main quality components of tea.The study aimed to explore the interactions of C,N,and P in soil-microorganisms-plants and the effects of these factors on the main quality components of tea by using the path analysis method.The results indicated that(1)The contents of C,N,and P in soil,microorganisms,and tea plants were highly correlated and collinear,and showed significant correlations with the main quality components of tea.(2)Optimal regression equations were established to esti-mate tea polyphenol,amino acid,catechin,caffeine,and water extract content based on C,N,and P contents in soil,microorganisms,and tea plants(R^(2)=0.923,0.726,0.954,0.848,and 0.883,respectively).(3)Pathway analysis showed that microbial biomass phosphorus(MBP),root phosphorus,branch nitrogen,and microbial biomass carbon(MBC)were the largest direct impact factors on tea polyphenol,catechin,water extracts,amino acid,and caffeine content,respectively.Leaf carbon,root phosphorus,and leaf nitrogen were the largest indirect impact factors on tea polyphenol,catechin,and water extract content,respectively.Leaf carbon indirectly affected tea polyphenol content mainly by altering MBP content.Root phosphorus indirectly affected catechin content mainly by altering soil organic carbon content.Leaf nitrogen indirectly affected water extract content mainly by altering branch nitrogen content.The research results provide the scientific basis for reasonable fertilization in tea gardens and tea quality improvement.

A Path Planning Algorithm Based on Improved RRT Sampling Region

For the problem of slow search and tortuous paths in the Rapidly Exploring Random Tree(RRT)algorithm,a feedback-biased sampling RRT,called FS-RRT,is proposedbasedon RRT.Firstly,toimprove the samplingefficiency of RRT to shorten the search time,the search area of the randomtree is restricted to improve the sampling efficiency.Secondly,to obtain better information about obstacles to shorten the path length,a feedback-biased sampling strategy is used instead of the traditional random sampling,the collision of the expanding node with an obstacle generates feedback information so that the next expanding node avoids expanding within a specific angle range.Thirdly,this paper proposes using the inverse optimization strategy to remove redundancy points from the initial path,making the path shorter and more accurate.Finally,to satisfy the smooth operation of the robot in practice,auxiliary points are used to optimize the cubic Bezier curve to avoid path-crossing obstacles when using the Bezier curve optimization.The experimental results demonstrate that,compared to the traditional RRT algorithm,the proposed FS-RRT algorithm performs favorably against mainstream algorithms regarding running time,number of search iterations,and path length.Moreover,the improved algorithm also performs well in a narrow obstacle environment,and its effectiveness is further confirmed by experimental verification.

Heuristic Expanding Disconnected Graph:A Rapid Path Planning Method for Mobile Robots

Existing mobile robots mostly use graph search algorithms for path planning,which suffer from relatively low planning efficiency owing to high redundancy and large computational complexity.Due to the limitations of the neighborhood search strategy,the robots could hardly obtain the most optimal global path.A global path planning algorithm,denoted as EDG*,is proposed by expanding nodes using a well-designed expanding disconnected graph operator(EDG)in this paper.Firstly,all obstacles are marked and their corners are located through the map pre-processing.Then,the EDG operator is designed to find points in non-obstruction areas to complete the rapid expansion of disconnected nodes.Finally,the EDG*heuristic iterative algorithm is proposed.It selects the candidate node through a specific valuation function and realizes the node expansion while avoiding collision with a minimum offset.Path planning experiments were conducted in a typical indoor environment and on the public dataset CSM.The result shows that the proposed EDG*reduced the planning time by more than 90%and total length of paths reduced by more than 4.6%.Compared to A*,Dijkstra and JPS,EDG*does not show an exponential explosion effect in map size.The EDG*showed better performance in terms of path smoothness,and collision avoidance.This shows that the EDG*algorithm proposed in this paper can improve the efficiency of path planning and enhance path quality.

A Reverse Path Planning Approach for Enhanced Performance of Multi-Degree-of-Freedom Industrial Manipulators

In the domain of autonomous industrial manipulators,precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance,such as handling,heat sealing,and stacking.While Multi-Degree-of-Freedom(MDOF)manipulators offer kinematic redundancy,aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites,their path planning entails intricate multiobjective optimization,encompassing path,posture,and joint motion optimization.Achieving satisfactory results in practical scenarios remains challenging.In response,this study introduces a novel Reverse Path Planning(RPP)methodology tailored for industrial manipulators.The approach commences by conceptualizing the manipulator’s end-effector as an agent within a reinforcement learning(RL)framework,wherein the state space,action set,and reward function are precisely defined to expedite the search for an initial collision-free path.To enhance convergence speed,the Q-learning algorithm in RL is augmented with Dyna-Q.Additionally,we formulate the cylindrical bounding box of the manipulator based on its Denavit-Hartenberg(DH)parameters and propose a swift collision detection technique.Furthermore,the motion performance of the end-effector is refined through a bidirectional search,and joint weighting coefficients are introduced to mitigate motion in high-power joints.The efficacy of the proposed RPP methodology is rigorously examined through extensive simulations conducted on a six-degree-of-freedom(6-DOF)manipulator encountering two distinct obstacle configurations and target positions.Experimental results substantiate that the RPP method adeptly orchestrates the computation of the shortest collision-free path while adhering to specific posture constraints at the target point.Moreover,itminimizes both posture angle deviations and joint motion,showcasing its prowess in enhancing the operational performance of MDOF industrial manipulators.

A robust triaxial localization method of AE source using refraction path

Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.

Multi-UAVs Collaborative Path Planning in the Cramped Environment

Due to its flexibility and complementarity, the multiUAVs system is well adapted to complex and cramped workspaces, with great application potential in the search and rescue(SAR) and indoor goods delivery fields. However, safe and effective path planning of multiple unmanned aerial vehicles(UAVs)in the cramped environment is always challenging: conflicts with each other are frequent because of high-density flight paths, collision probability increases because of space constraints, and the search space increases significantly, including time scale, 3D scale and model scale. Thus, this paper proposes a hierarchical collaborative planning framework with a conflict avoidance module at the high level and a path generation module at the low level. The enhanced conflict-base search(ECBS) in our framework is improved to handle the conflicts in the global path planning and avoid the occurrence of local deadlock. And both the collision and kinematic models of UAVs are considered to improve path smoothness and flight safety. Moreover, we specifically designed and published the cramped environment test set containing various unique obstacles to evaluating our framework performance thoroughly. Experiments are carried out relying on Rviz, with multiple flight missions: random, opposite, and staggered, which showed that the proposed method can generate smooth cooperative paths without conflict for at least 60 UAVs in a few minutes.The benchmark and source code are released in https://github.com/inin-xingtian/multi-UAVs-path-planner.