新工科背景下融合OBE-CDIO理念的“C#程序设计”课程改革创新与实践

针对当前新工科建设中面临的高职院校工程应用人才培养无法满足产业快速发展需求的现状,以江苏信息职业技术学院的“C#程序设计”课程教学改革为例进行深入分析。通过对课程内容、教学资源、学习情境以及考核评价的系统改进,探讨如何将OBE能力导向与CDIO工程实践导向教育理念融合应用于高职软件类课程改革的创新实践中,揭示了这种复合教育理念对学生综合素质和职业能力的培养带来的积极影响,为高职软件类课程改革提供了有效参考和借鉴。

基于C#+OpenGL的多探头测井井筒三维成像软件研制与应用研究

基于油水、气水等多相流实验数据和图像资料,采用C#语言结合Tao框架OpenGL研发一套适用于MAPS阵列多探头测井(以下简称“MAPS测井”)仪器的井筒流体三维成像显示(COSL-MapsView)软件。该软件可实现测井数据的直接加载,快速精确直观显示井筒内油气水的分布情况。基于图像重构对MAPS测井仪器进行了适用性研究,表明MAPS测井在水平井和大斜度井中低流量情况下的分层流中具有良好的应用效果,在高流量分散流中应用效果不佳。经验证,该软件成像效果达到了国外同等水平,对海上油气田找堵水等工程作业具有指导意义。

Prenatal programing of motivated behaviors:can innate immunity prime behavior?

Prenatal programming during pregnancy sets physiological outcomes in the offspring by integrating external or internal stimuli.Accordingly,pregnancy is an important stage of physiological adaptations to the environment where the fetus becomes exposed and adapted to the maternal milieu.Maternal exposure to high-energy dense diets can affect motivated behavior in the offs p ring leading to addiction and impaired sociability.A high-energy dense exposure also increases the pro-inflammatory cytokines profile in plasma and brain and favors microglia activation in the offspring.While still under investigation,prenatal exposure to high-energy dense diets promotes structural abnormalities in selective brain regions regulating motivation and social behavior in the offspring.The current review addresses the role of energy-dense foods programming central and peripheral inflammatory profiles during embryonic development and its effect on motivated behavior in the offspring.We provide preclinical and clinical evidence that supports the contribution of prenatal programming in shaping immune profiles that favor structural and brain circuit disruption leading to aberrant motivated behaviors after birth.We hope this minireview encourages future research on novel insights into the mechanisms underlying maternal programming of motivated behavior by central immune networks.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

基于高速大数据与C#编程的路段出行结构分析

随着我国高速公路信息化与数字化的快速发展,高速公路信息系统每天都会产生大量的交通数据,高速公路OD数据和路段流量的采集越来越便捷。以湖北省为例,2022年湖北省高速公路出行产生了3亿车次的通行数据。高速公路改扩建项目通过对这些数据进行分析,可以对车辆在高速公路上的行驶轨迹进行还原,进而分析出高速公路路段的出行结构。目前,国内已经积累了大量高速大数据的研究成果。

基于OBE理念的C#编程与SQL数据库应用课程教学改革

为有效培养自动化专业学生应具备的系统分析、设计与研发能力,针对C#编程与SQL数据库应用课程存在的教学模式单一、课程内容实践不够、学生能力培养不足等问题,制定以工程意识和工程素质为核心的培养目标,以云班课教学平台为依托,探索线上线下混合式、课堂企业交叉式教学模式。基于成果导向的教学理念的理论与实践相结合的教学内容,通过项目驱动式方法改革授课方式,采用自主式、团队式相融合的方法改革实践教学,并探讨全方位多层次的考评方法,以提高学生解决复杂工程问题的能力。

基于C#的动物离心机上位机控制系统设计

为满足航空航天实验需要,研发一款平稳运行、功能齐全的动物离心机。根据动物离心机的结构,将控制策略分为两部分,利用电子计算机+运动控制器实现试验平台的位置控制,利用电子计算机+伺服驱动器实现主轴旋转运动控制,采用编码器反馈控制精度。上位机操作系统基于C#语言,使用Visual Studio开发工具,MySQL数据库,设置了输入异常、通信异常、主轴转速阈值、试验平台旋转角度阈值等异常处理方案,确保动物离心机设备的运行稳定。开发出的控制系统具有较高的稳定性和精确性,在离心机主轴转速为10、15、20、30 r/min,试验平台旋转角度和俯仰角度为5°、10°、15°、20°时,编码器测量结果与输入参数基本符合,运行平稳达到实验要求。研发出的动物离心机设备能够灵活、可靠运转,提供多轴向G值加速度力学环境仿真,便利高载荷力学环境下生理实验研究。

C#程序设计课程思政教学实践研究

C#程序设计是理工类专业的计算机基础课程之一,通过多年教学实践,该课程所蕴含的大量思政元素正不断涌现,文章就C#程序设计课程中思政元素的挖掘,以及相对应的教学方法、教学设计等教学环节进行探究,引导学生在掌握C#程序设计课程知识点的同时,做到对价值观念的启发和引导,从课程学习和思想教育两个维度进行思政教学探索和研究。

In vivo astrocyte reprogramming following spinal cord injury

Harmful and helpful roles of astrocytes in spinal cord injury(SCI):SCI induce gradable sensory,motor and autonomic impairments that correlate with the lesion severity and the rostro-caudal location of the injury site.The absence of spontaneous axonal regeneration after injury results from neuron-intrinsic and neuron-extrinsic parameters.Indeed,not only adult neurons display limited capability to regrow axons but also the injury environment contains inhibitors to axonal regeneration and a lack of growth-promoting factors.Amongst other cell populations that respond to the lesion,reactive astrocytes were first considered as only detrimental to spontaneous axonal regeneration.Indeed,astrocytes.

Transcriptional reprogramming during human osteoclast differentiation identifies regulators of osteoclast activity

Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone formation.As novel antiosteoporotic therapeutics are needed,understanding the genetic regulation of human osteoclastogenesis could help identify potential treatment targets.This study aimed to provide an overview of transcriptional reprogramming during human osteoclast differentiation.Osteoclasts were differentiated from CD14+monocytes from eight female donors.RNA sequencing during differentiation revealed 8980 differentially expressed genes grouped into eight temporal patterns conserved across donors.These patterns revealed distinct molecular functions associated with postmenopausal osteoporosis susceptibility genes based on RNA from iliac crest biopsies and bone mineral density SNPs.Network analyses revealed mutual dependencies between temporal expression patterns and provided insight into subtype-specific transcriptional networks.The donor-specific expression patterns revealed genes at the monocyte stage,such as filamin B(FLNB)and oxidized low-density lipoprotein receptor 1(OLR1,encoding LOX-1),that are predictive of the resorptive activity of mature osteoclasts.The expression of differentially expressed G-protein coupled receptors was strong during osteoclast differentiation,and these receptors are associated with bone mineral density SNPs,suggesting that they play a pivotal role in osteoclast differentiation and activity.The regulatory effects of three differentially expressed G-protein coupled receptors were exemplified by in vitro pharmacological modulation of complement 5 A receptor 1(C5AR1),somatostatin receptor 2(SSTR2),and free fatty acid receptor 4(FFAR4/GPR120).Activating C5AR1 enhanced osteoclast formation,while activating SSTR2 decreased the resorptive activity of mature osteoclasts,and activating FFAR4 decreased both the number and resorptive activity of mature osteoclasts.In conclusion,we report the occurrence of transcriptional reprogramming during human osteoclast differentiation and identified SSTR2 and FFAR4 as antiresorptive G-protein coupled receptors and FLNB and LOX-1 as potential molecular markers of osteoclast activity.These data can help future investigations identify molecular regulators of osteoclast differentiation and activity and provide the basis for novel antiosteoporotic targets.

Glia-to-neuron reprogramming to the rescue?

Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be changed.An exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state.

Improved Unit Commitment with Accurate Dynamic Scenarios Clustering Based on Multi-Parametric Programming and Benders Decomposition

Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment.

Quercetin Alleviates Lipopolysaccharide-Induced Cardiac Inflammation via Inhibiting Autophagy and Programmed Cell Death

Objective The aim of this study is to explore the potential modulatory role of quercetin against Endotoxin or lipopolysaccharide(LPS)induced septic cardiac dysfunction.Methods Specific pathogen-free chicken embryos(n=120)were allocated untreated control,phosphate buffer solution(PBS)vehicle,PBS with ethanol vehicle,LPS(500 ng/egg),LPS with quercetin treatment(10,20,or 40 nmol/egg,respectively),Quercetin groups(10,20,or 40 nmol/egg).Fifteenday-old embryonated eggs were inoculated with abovementioned solutions via the allantoic cavity.At embryonic day 19,the hearts of the embryos were collected for histopathological examination,RNA extraction,real-time polymerase chain reaction,immunohistochemical investigations,and Western blotting.Results They demonstrated that the heart presented inflammatory responses after LPS induction.The LPS-induced higher mRNA expressions of inflammation-related factors(TLR4,TNFα,MYD88,NF-κB1,IFNγ,IL-1β,IL-8,IL-6,IL-10,p38,MMP3,and MMP9)were blocked by quercetin with three dosages.Quercetin significantly decreased immunopositivity to TLR4 and MMP9 in the treatment group when compared with the LPS group.Quercetin significantly decreased protein expressions of TLR4,IFNγ,MMP3,and MMP9 when compared with the LPS group.Quercetin treatment prevented LPS-induced increase in the mRNA expression of Claudin 1 and ZO-1,and significantly decreased protein expression of claudin 1 when compared with the LPS group.Quercetin significantly downregulated autophagyrelated gene expressions(PPARα,SGLT1,APOA4,AMPKα1,AMPKα2,ATG5,ATG7,Beclin-1,and LC3B)and programmed cell death(Fas,Bcl-2,CASP1,CASP12,CASP3,and RIPK1)after LPS induction.Quercetin significantly decreased immunopositivity to APOA4,AMPKα2,and LC3-II/LC3-I in the treatment group when compared with the LPS group.Quercetin significantly decreased protein expressions of AMPKα1,LC3-I,and LC3-II.Quercetin significantly decreased the protein expression to CASP1 and CASP3 by immunohistochemical investigation or Western blotting in treatment group when compared with LPS group.Conclusion Quercetin alleviates cardiac inflammation induced by LPS through modulating autophagy,programmed cell death,and myocardiocytes permeability.

An Empirical Application of User-Guided Program Analysis

Although static program analysis methods are frequently employed to enhance software quality,their efficiency in commercial settings is limited by their high false positive rate.The EUGENE tool can effectively lower the false positive rate.However,in continuous integration(CI)environments,the code is always changing,and user feedback from one version of the software cannot be applied to a subsequent version.Additionally,people find it difficult to distinguish between true positives and false positives in the analytical output.In this study,we developed the EUGENE-CI technique to address the CI problem and the EUGENE-rank lightweight heuristic algorithm to rate the reports of the analysis output in accordance with the likelihood that they are true positives.On the three projects ethereum,go-cloud,and kubernetes,we assessed our methodologies.According to the trial findings,EUGENE-CI may drastically reduce false positives while EUGENE-rank can make it much easier for users to identify the real positives among a vast number of reports.We paired our techniques with GoInsight~1 and discovered a vulnerability.We also offered a patch to the community.

Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

基于C#语言的ABB机器人远程示教方法

随着工业机器人网络化特征的日益增强,越来越多的场景需要采用远程监控技术对工业机器人进行监视和调控。现有上位机更多的是实现工作站工作状态和关键信息的显示与控制,缺乏远程示教功能。鉴于此,文章采用C#语言结合ABB工业机器人的PC SDK工具包,实现了远程示教功能。通过上位机可以对工业机器人6个关节轴进行调整和姿态示教。该示教方法摆脱了有线示教器的地理限制,拓展了工业机器人的应用场景。

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

Efficacy comparison of fruquintinib,regorafenib monotherapy or plus programmed death-1 inhibitors for microsatellite stable metastatic colorectal cancer

BACKGROUND Regorafenib(R)and fruquintinib(F)are the standard third-line regimens for colorectal cancer(CRC)according to the National Comprehensive Cancer Network guidelines,but both have limited efficacy.Several phase 2 trials have indicated that R or F combined with immune checkpoint inhibitors can reverse immunosuppression and achieve promising efficacy for microsatellite stable or proficient mismatch repair(MSS/pMMR)CRC.Due to the lack of studies comparing the efficacy between F,R,F plus programmed death-1(PD-1)inhibitor,and R plus PD-1 inhibitors(RP),it is still unclear whether the combination therapy is more effective than monotherapy.AIM To provide critical evidence for selecting the appropriate drugs for MSS/pMMR metastatic CRC(mCRC)patients in clinical practice.METHODS A total of 2639 CRC patients were enrolled from January 2018 to September 2022 in our hospital,and 313 MSS/pMMR mCRC patients were finally included.RESULTS A total of 313 eligible patients were divided into F(n=70),R(n=67),F plus PD-1 inhibitor(FP)(n=95)and RP(n=81)groups.The key clinical characteristics were well balanced among the groups.The median progression-free survival(PFS)of the F,R,FP,and RP groups was 3.5 months,3.6 months,4.9 months,and 3.0 months,respectively.The median overall survival(OS)was 14.6 months,15.7 months,16.7 months,and 14.1 months.The FP regimen had an improved disease control rate(DCR)(P=0.044)and 6-month PFS(P=0.014)and exhibited a better trend in PFS(P=0.057)compared with F,and it was also significantly better in PFS than RP(P=0.030).RP did not confer a significant survival benefit;instead,the R group had a trend toward greater benefit with OS(P=0.080)compared with RP.No significant differences were observed between the R and F groups in PFS or OS(P>0.05).CONCLUSION FP is superior to F in achieving 6-month PFS and DCR,while RP is not better than R.FP has an improved PFS and 6-month PFS compared with RP,but F and R had similar clinical efficacy.Therefore,FP may be a highly promising strategy in the treatment of MSS/pMMR mCRC.

Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.

Assessment of programmed death-ligand 1 expression in primary tumors and paired lymph node metastases of gastric adenocarcinoma

BACKGROUND Anti-programmed death-1/programmed death-ligand 1(PD-1/PD-L1)immuno-therapy has demonstrated promising results on gastric cancer(GC).However,PD-L1 can express differently between metastatic sites and primary tumors(PT).AIM To compare PD-L1 status in PT and matched lymph node metastases(LNM)of GC patients and to determine the correlation between the PD-L1 status and clinicopathological characteristics.METHODS We retrospectively reviewed 284 GC patients who underwent D2-gastrectomy.PD-L1 was evaluated by immunohistochemistry(clone SP142)using the com-bined positive score.All PD-L1+PT staged as pN+were also tested for PD-L1 expression in their LNM.PD-L1(-)GC with pN+served as the comparison group.RESULTS Among 284 GC patients included,45 had PD-L1+PT and 24 of them had pN+.For comparison,44 PD-L1(-)cases with pN+were included(sample loss of 4 cases).Of the PD-L1+PT,54.2%(13/24 cases)were also PD-L1+in the LNM.Regarding PD-L1(-)PT,9.1%(4/44)had PD-L1+in the LNM.The agreement between PT and LNM had a kappa value of 0.483.Larger tumor size and moderate/severe peritumoral inflammatory response were associated with PD-L1 positivity in both sites.There was no statistical difference in overall survival for PT and LNM according to the PD-L1 status(P=0.166 and P=0.837,respectively).CONCLUSION Intra-patient heterogeneity in PD-L1 expression was observed between the PT and matched LNM.This disagreement in PD-L1 status may emphasize the importance of considering different tumor sites for analyses to select patients for immunotherapy.