Responses of the Southern Ocean mixed layer depth to the eastern and central Pacific El Niño events during austral winter

Based on the Ocean Reanalysis System version 5(ORAS5)and the fifth-generation reanalysis datasets derived from European Centre for Medium-Range Weather Forecasts(ERA5),we investigate the different impacts of the central Pacific(CP)El Niño and the eastern Pacific(EP)El Niño on the Southern Ocean(SO)mixed layer depth(MLD)during austral winter.The MLD response to the EP El Niño shows a dipole pattern in the South Pacific,namely the MLD dipole,which is the leading El Niño-induced MLD variability in the SO.The tropical Pacific warm sea surface temperature anomaly(SSTA)signal associated with the EP El Niño excites a Rossby wave train propagating southeastward and then enhances the Amundsen Sea low(ASL).This results in an anomalous cyclone over the Amundsen Sea.As a result,the anomalous southerly wind to the west of this anomalous cyclone advects colder and drier air into the southeast of New Zealand,leading to surface cooling through less total surface heat flux,especially surface sensible heat(SH)flux and latent heat(LH)flux,and thus contributing to the mix layer(ML)deepening.The east of the anomalous cyclone brings warmer and wetter air to the southwest of Chile,but the total heat flux anomaly shows no significant change.The warm air promotes the sea ice melting and maintains fresh water,which strengthens stratification.This results in a shallower MLD.During the CP El Niño,the response of MLD shows a separate negative MLD anomaly center in the central South Pacific.The Rossby wave train triggered by the warm SSTA in the central Pacific Ocean spreads to the Amundsen Sea,which weakens the ASL.Therefore,the anomalous anticyclone dominates the Amundsen Sea.Consequently,the anomalous northerly wind to the west of anomalous anticyclone advects warmer and wetter air into the central and southern Pacific,causing surface warming through increased SH,LH,and longwave radiation flux,and thus contributing to the ML shoaling.However,to the east of the anomalous anticyclone,there is no statistically significant impact on the MLD.

Training on LSA lifeboat operation using Mixed Reality

Background This work aims to provide an overview of the Mixed Reality(MR)technology’s use in maritime industry for training purposes.Current training procedures cover a broad range of procedural operations for Life-Saving Appliances(LSA)lifeboats;however,several gaps and limitations have been identified related to the practical training that can be addressed through the use of MR.Augmented,Virtual and Mixed Reality applications are already used in various fields in maritime industry,but their full potential have not been yet exploited.SafePASS project aims to exploit MR advantages in the maritime training by introducing a relevant application focusing on use and maintenance of LSA lifeboats.Methods An MR Training application is proposed supporting the training of crew members in equipment usage and operation,as well as in maintenance activities and procedures.The application consists of the training tool that trains crew members on handling lifeboats,the training evaluation tool that allows trainers to assess the performance of trainees,and the maintenance tool that supports crew members to perform maintenance activities and procedures on lifeboats.For each tool,an indicative session and scenario workflow are implemented,along with the main supported interactions of the trainee with the equipment.Results The application has been tested and validated both in lab environment and using a real LSA lifeboat,resulting to improved experience for the users that provided feedback and recommendations for further development.The application has also been demonstrated onboard a cruise ship,showcasing the supported functionalities to relevant stakeholders that recognized the added value of the application and suggested potential future exploitation areas.Conclusions The MR Training application has been evaluated as very promising in providing a user-friendly training environment that can support crew members in LSA lifeboat operation and maintenance,while it is still subject to improvement and further expansion.

Theoretical and Experimental Study on The Speed-up of Freight Train with Mixed Marshaling of Light and Heavy Vehicle

To study the influence of the speed-up of a freight train with mixed marshaling of light and heavy vehicles on the dynamic behavior,a dynamic model of the freight train was established based on the modular method of cyclic variables,and the dynamic behavior of the freight train was simulated and analyzed under different marshaling patterns,speeds and line conditions.On-site speed-up test with different marshaling freight trains was carried out,and the stability and ride-index of the train before and after the speed-up were compared and analyzed.The feasibility of increasing the speed of freight trains with mixed marshaling of light and heavy cars was demonstrated theoretically and experimentally.The results show that the theory is in good agreement with the test,which can effectively reflect the dynamic behavior of the vehicle.The dynamic behavior of the freight train in the study meets the requirements of increasing speed to 90 km/h.This paper provides a theoretical basis and method for railway freight transportation and the speed-up of freight vehicles.

Comprehensive Evaluation of Talent Training Model for Modern Rehabilitation Therapy Technology:A Case Study of School Y

The purpose of this study is to comprehensively evaluate the modern training model of rehabilitation therapy technology talents.Selecting the third-year students of the rehabilitation therapy technology program in School Y as the research subject,300 questionnaires were collected and the effective response rate was 92%.The strengths and weaknesses of the modern training model were analyzed through a mixed qualitative and quantitative research method.It was found that 68%of the students thought that the modern model had obvious advantages in practical teaching,but 42%of the students thought that it still needed to be improved in personalized teaching.This study provides an empirical basis and specific suggestions for optimizing the cultivation of rehabilitation therapy technology talents.

Design and Implementation of a Comprehensive Training Program for Software Engineering Talents’ Practical Ability

In the process of cultivating software engineering professionals,the practical teaching of professional courses is an indispensable link.In order to enable students to understand,consolidate and master theoretical knowledge,improve the ability to solve problems by combining theory with practice,and achieve the goal of combining theoretical knowledge with practice.Adopting the planning of through-type training,complete the teaching work of three practical courses of software system design,software system construction,and software product construction.Through the implementation of the plan,the digitization of teaching resources,the virtualization of real enterprises,the intelligentization of teaching guidance,the visualization of teaching process,and the panorama of learning process are realized.By adopting the teaching methods of taskdriven online practice teaching,artificial intelligence-based teaching training support and teaching process,and result big data evaluation,the students’comprehensive practical ability can be improved finally,and the whole practice teaching reform can provide experience for the follow-up reform.

The Optimizing Model and Its Solution for Making Train Working Graph with Computer on Separative Division of Double－Track Lines

The authoros specialize in the field of optunization and automatic programme oftrain working graph. In this peper, at frist, a mixed 0-1 integer progranimingmodel about this problem for duuble-track lines is set up, then the principle andProcess of selution are stated, with an application exaiiiple put forward.

Trainguard MT系统混合运营时的列车追踪

以重庆轨道交通6号线为例,应用主动列车追踪和被动列车追踪原理,对Trainguard MT系统中同一条线路下不同装备的列车混合运营时,列车位置信息确定和后续列车运营安排进行了详细论述,并对其在运营中的作用进行了描述。

基于Train2Vec的消防培训数据分类

为提高消防培训效果,提出一种基于深度神经网络的对混合现实消防培训数据分类的模型。通过Train2Vec将受训人员在混合现实火灾场景中进行消防培训时所产生的过程数据、生理数据构建为多维培训向量;通过对生成的多维培训向量进行相似度求解,实现将受训人员进行分类的功能,即归为专业消防人员、应对火灾经验丰富人员、未经历过火灾心理素质良好人员和未经历过火灾心理素质较差人员中的某类,为其生成个性化的应对火灾建议和消防培训任务,达到提升培训效果的目的。实验结果表明,该Train2Vec模型预测的身份信息的准确率为92.00%,可以实现受训人员的正确分类,从而实现个性化消防培训。

基于临床路径的多元混合教学法在内分泌住院医规范化培训中的探索

目的探讨基于临床路径(CP)的多元混合教学法在内分泌住院医规范化培训中的教学效果。方法对2020年1月-2020年12月内分泌科轮转的内科及全科住院医规范化培训97学员按照入科时间分为对照组(CPL+PBL+CBL)和观察组(CPL+PBL+改良CBL),通过教学效果、学员岗位胜任力、教学满意度三个维度进行定量研究。结果两组间出科考试理论成绩、教学满意度差异无显著性,P>0.05。观察组学员病例分析能力和岗位胜任力(CCMTV住培管理系统中360度评估)优于对照组,P<0.05。结论以CP教学法为基础,联合PBL、CBL教学法的多元混合教学模式适用于内分泌住院医规范化培训,在此基础上改良CBL教学法有利于学员临床思维和岗位胜任力的培养。基于临床路径的混合教学法在内分泌住院医规范化培训中具有良好的应用前景。

新农科背景下“BOPPPS+在线资源”模式在耕作学中的改革与实践

随着国家实施乡村振兴战略,加快推进农业转型升级和农业现代化的建设,对高等农业院校农业人才培养和教育教学提出更高的要求。为有效提高农学专业课程的教学效果,培养适合社会需求的素质高、技能精、实践强、有担当且敢于迎接挑战并坚持创新的新农科人才。该文以农学专业核心课程耕作学教学为对象,设计并实践“BOPPPS+在线资源”的混合式教学模式,该模式将学科文化和学科发展与思政教育结合、理论知识与生产实践结合、线下与线上教育资源结合。该模式能够优化创新学习策略,构建新农科背景下课上“活跃”课下“忙碌”的混合式教学新模式,有效提高耕作学的教学质量,为培养高素质应用型新农科人才提供重要的参考依据。

激波结构对喷射器工作特性的影响

喷射制冷循环系统因其采用水作为工质不仅节能环保而且可以实现循环利用.本文采用数值仿真方法,对喷射制冷系统核心部件——喷射器内部的激波结构进行了讨论和详细划分.首次给出了伪激波区域、混合区域、激波串区域以及正激波位置的判定依据.讨论了激波结构对喷射器工作特性的影响.研究结果表明,正激波的位置受喷射器出口背压的影响;伪激波区域是决定喷射器引射效率的直接因素;激波串对降低喷射器内部流动速度和压力恢复起到重要作用.激波混合层的存在将工作蒸汽与引射蒸汽的流道分开.工作蒸汽通过激波混合层来携带和加速引射蒸汽的流动.激波混合层的面积大小受喷射器的几何结构和工作蒸汽的工作条件所影响.因此,了解和掌握激波结构对于理解喷射器内部流体流动规律,提高喷射器工作效率,进一步改进和优化喷射器的几何结构,具有参考价值.

人工智能时代成人高等教育教学发展路径探究

成人高等教育教学是我国教育体系的一大分支,在培养卓越人才、建设终身学习型社会中发挥着重要作用。随着信息技术的发展,人工智能思维深刻影响着“教”与“学”方式,将人工智能与教育融合既是历史缘起与现实所需,也是政策支持与国家计划,更是时代呼唤与机械革命。故此,成人高等教育教学应在人工智能的带动下努力实现教育内容长效化、教育评价全景化、师资培养现代化、教学模式个性化,以此促进传统教学方式的变革,满足不同学习需求,促进教育资源均衡配置,为成人高等教育教学发展注入引擎新动能。

考虑训练样本分布不均衡的超短期风电功率概率预测

提出一种考虑训练样本分布不均衡的超短期风电概率预测方法。首先构建深度信念混合密度网络,通过深度信念网络独特的预训练和微调机制提取输入变量的隐特征,利用Beta混合概率分布的有界性准确表征风电预测功率的概率分布,实现隐特征与预测功率概率分布参数之间的非线性映射;然后引入训练样本分布平滑策略,其中特征分布平滑技术用于校准输入特征,标签分布平滑技术用于对各样本误差赋予差异化权重,从输入和输出两方面改善训练样本分布不均衡现象对预测结果的不利影响。实际算例结果表明,与常见风电功率概率预测模型相比,所提模型在点预测和概率预测方面均能获得较高的预测精度,尤其能有效提高低密度样本区域的预测精度。

既有铁路开行市域(郊)列车开行方案优化

研究目的:在利用既有铁路资源发展市域(郊)铁路的背景下,本文研究旨在提高市域(郊)铁路的运营效率,以满足乘客的出行需求。通过分析不同到达模式下的乘客行为,提出一种适应混合到达模式的市域(郊)客流分配方式。基于“线路国有、国铁与地方共营”管理模式,构建一个多目标优化模型,综合考虑乘客出行时间、运营成本和地方政府成本,并采用遗传粒子群优化算法求解,优化列车开行方案。研究结论:(1)通过对某条市域(郊)铁路线路早高峰时段客流数据的实证分析表明,构建的市域(郊)列车开行方案优化模型能够显著提高运营效率;(2)该模型早高峰时段缩短了乘客总旅行时间34.8%,降低了铁路局运营成本10.2%,减少地方政府成本11.5%,并节省了10%的车辆购置费用;(3)本研究成果可为利用既有铁路开行市域(郊)列车的项目规划决策和运营优化提供参考。

黑龙江省准对称混合训练期MOS气温预报性能分析

本文选取ECMWF细网格地面2 m气温要素预报产品作为预报因子,选取中国气象局陆面数据同化系统(CLDAS-V2.0)地面2 m气温格点实况数据作为预报量,应用准对称混合训练期MOS方法,建立黑龙江省格点气温MOS方法,并对MOS方法在24 h预报时效内间隔3 h的格点气温预报性能进行检验分析。结果表明:MOS平均绝对误差≤1.5℃;MOS夏半年≤2℃预报准确率为84.1%,比ECMWF提高7.6%;冬半年预报准确率为71.5%,比ECMWF提高18.3%;预报技巧夏半年为14.2%,冬半年为29.8%。MOS夏半年预报效果好于冬半年,冬半年预报改善效果好于夏半年。大、小兴安岭和东南部山区MOS预报效果不如平原地区好,但是MOS改善效果明显好于平原地区。

专业认证背景下资源勘查工程专业建设研究

在工程教育认证的推动下,对资源勘查工程专业建设进行了系统研究和实践。基于OBE理念和新工科建设制定面向需求的人才培养目标,建立163递进式人才培养模式;基于学生应用能力培养,优化调整课程体系;利用互联网技术,搭建以学生为中心的线上线下混合教学模式;加强师资队伍和实践基地建设,构建产教融合人才培养体系;基于持续改进,建立面向产出的融入课程思政和创新的课程质量评价体系。这些研究实践将有利于提高我校资源勘查工程专业人才培养质量、提升专业竞争力。

基于混合式教学的纺织文化创意产品设计教学改革

文章研究了混合式教学在纺织文化创意产品设计课程中的应用和改革路径。通过分析教学改革中存在的平台和资源缺乏统一规范、过分强调技能而忽视理论学习、校企合作等问题,提出利用智能终端进行自主学习,以技能竞赛促进教学改革与企业合作提升实践教学质量、探索建立创新工作室、提高对实践教学重视度、突出混合式教学内容及资源、拓宽实践平台等解决措施,从而更好地结合区域市场需求,增强学生的创新意识和实际操作能力。

虚拟编组条件下城轨列车单元灵活运用方法

基于虚拟编组运输组织模式,本文考虑客流时间和空间特征与列车单元实时动态编组之间的耦合关系,协调不同运营方向列车之间的虚拟联挂和虚拟摘解操作,研究虚拟编组条件下城市轨道交通列车单元灵活运用问题。具体地,将列车单元数量分配和周转衔接作为主要决策变量,以极小化总乘客等待时间和系统运营成本为目标,考虑虚拟编组列车单元分配、列车单元周转和乘客分配等约束条件,构建可用CPLEX等软件直接求解的混合整数线性规划模型。最后,以某城市轨道交通线路为例设计数值实验以验证所提方法的有效性。实验结果表明:相较于固定编组(6编组)方案,本文方法可降低约32.8%的总乘客等待时间,同时降低20.9%的系统运营成本;相较于固定编组(8编组)方案,本文方法在仅增加0.3%的总乘客等待时间情况下,降低40.7%的系统运营成本。上述实验结果表明,虚拟编组技术在提升城市轨道交通效率方面的潜在优势,且具有一定的实用价值。

探索中文预训练模型的混合粒度编码和IDF遮蔽

目前大多数中文预训练语言模型采用字级别编码,因为字符级编码序列长而产生大量计算开销。词级别编码尽管能够缓解这一问题,但也会带来其他问题,如词典外词、数据稀疏等。针对中文不同粒度的编码,该文提出使用混合粒度编码的中文预训练模型。这一编码所用的词表在大规模预训练语料上得到,因此缓解了词典外词和数据稀疏问题。为了更进一步增强模型性能,该文提出了一种选择性的遮蔽语言建模训练策略——IDF遮蔽。这一策略基于词在大规模预训练语料上统计的逆文档频率。实验表明,与之前的中文预训练语言模型相比,该文所提出方法预训练的模型在多个中文自然语言数据集上取得了更好或相当的性能,并且能更高效地编码文本。

潮汐客流需求驱动的地铁列车不成对运行图节能优化方法

针对城市轨道交通客流潮汐现象引起的大客流方向乘客滞留和小客流方向运力虚靡且牵引能耗高的问题,本文提出一种结合快慢车和变编组的不成对运输组织策略,并结合变编组技术提升运力供给灵活度的同时减少运能浪费,此外,开行部分跨站快车加速车底周转。基于此,构建开行方案、时刻表与车底运用计划协同优化模型,决策列车的双向开行频率、编组类型、停站方案、首站发车时刻及车底周转计划,从而最小化乘客的总旅行时间和全线总牵引能耗成本;并设计定制的变邻域搜索算法求解混合整数非线性规划模型。广州地铁14号线案例结果表明:与实际的成对运输方案相比,本文不成对运行方案可以将乘客总旅行时间减少6.52%,全线总牵引能耗降低34.20%,总目标函数减少11.40%;快车的开行加速了车底周转,减少了6列上线列车单元数量,可以更好地实现不成对运输组织;变编组技术可以进一步提升不成对运输计划的灵活性,大幅缩减上线列车单元数量,使线路的平均满载率提升约20%,线路总牵引能耗优化率提升约33%。结合快慢车和变编组技术的不成对运输策略实现运力精准灵活配置的同时节约列车运行能耗成本,达到运营降本增效的目的。