重复性经颅磁刺激对吗啡依赖小鼠条件性位置偏爱表达的影响

通过检测重复性经颅磁刺激（rTMS）对吗啡依赖小鼠条件性位置偏爱（CPP）表达的影响,探讨rTMS对吗啡依赖小鼠的治疗效应。30只雄性ICR小鼠随机分为对照组、CPP模型组和rTMS治疗组。CPP模型组与rTMS治疗组通过交替注射吗啡和生理盐水建立CPP模型;对照组皮下注射等量生理盐水替代吗啡。在成功建立CPP模型的基础上,rTMS治疗组采用频率为1Hz的低频脉冲磁场进行治疗,每天治疗15min,连续7d;CPP模型组进行假电磁刺激操作;对照组不作任何处理。在rTMS治疗后分别检测三组小鼠的CPP表达并进行比较。结果显示在rTMS治疗的前3d内,rTMS治疗组小鼠的CPP值显著低于CPP模型组（P < 0.01）,且维持在相对稳定的范围内。结果表明1Hz rTMS能有效抑制吗啡依赖小鼠的CPP表达,可能成为戒毒治疗的新方法。     

某多级压气机畸变传递过程中相关参数影响研究

进口畸变是诱发航空压气机内部流动失稳的关键因素,极大地限制了压气机的性能及稳定运行范围.在畸变条件下采用数值模拟及模型分析相结合的方法,建立了一个模型,以某型三级压气机为研究对象,研究畸变传递过程中相关参数影响,计算了畸变强度和畸变范围沿压气机轴向的分布情况.结果表明在进口总压畸变相同的条件下,转速越小,压气机出口畸变强度越小,出口总压分布相对较均匀,出口畸变范围也越小;总压总温畸变,进口畸变范围越大,压气机出口畸变强度越大.不论是总压畸变还是总温畸变,对于该三级压气机,径向畸变的衰减程度比周向畸变衰减程度大.     

长沙市商业街区单向交通组织的适应性评价

城市单向交通作为缓解城市交通拥堵问题的有效途径,在各大城市得到了广泛的应用,但是商业街区单行线的设置也产生了诸多负面影响.在分析城市商业街区交通组织中存在的主要问题的基础上,运用模糊综合评价法,对长沙市商业街区单向交通组织的商业适应性进行评价.认为城市交通管理部门应该从全局把握,慎重考虑单行线设置的必要性和可行性,使单行线设置的正面效应高于负面影响.对于商业利益的主体来说,应积极主动采取一定的措施来降低单行线的负面影响,适应商业新格局.     

满足各种矿岩配车需求的露天矿车流规划模型

将汽车运输露天矿的运输设备与物料匹配关系分为统一运输、独立运输、组合运输3种类型,分析了难度最大的组合运输的车流特点,并充分考虑统一运输、独立运输的兼容性,提出了满足各种矿岩配车需求的通用车流规划数学模型.讨论了模型在3种类型下的应用差别,论述了简化模型计算步骤及提高模型计算速度的办法.实验结果不仅验证了模型的通用性,而且还证明在卸矿点与装岩点或卸岩点与装矿点的距离较近时,矿岩混运具有明显优势,对露天矿车流规划具有评价和指导价值.     

另类元素周期表

为帮助学生理解元素排列规律,综述了长式、螺旋式和三维式元素周期表,讨论了各自的优缺点和辅助教学作用.介绍的周期表在提高学生学习兴趣,开阔学生眼界,培养学生创造性思维和想象力等方面有重要的参考价值.     

基于仿真驱动的高速公路主动限速效用评价与推荐

传统的路侧被动限速方式对于特定的惩处区域以外缺少管控,间接导致车辆行为在时空上的不一致性甚至突变,影响了交通的通行效率与安全性。从车侧主动限速方式入手,提出主动限速效用评价与推荐方法,结合道路线形、交通流量、车型比例,开展多情景主动、被动限速交通仿真,利用安全间接分析模型及交通流运行状态,从安全与效率2个层面提取效用评价指标及其权重,采用集成学习方法进行预测分析。结果显示：主动限速方式相较于被动限速方式更有利于提高安全性和调节效率,而在主动限速方面,GBDT(gradient boosting decision tree)回归模型的预测稳定性和准确率更高(R²=0.984)。     

基于CPN的智能合约交易顺序依赖漏洞的验证

智能合约的形式化验证工作主要集中在编程语言层面的漏洞研究,而交易顺序依赖作为区块链层面的漏洞更不易被检测。基于着色Petri网对智能合约中潜在的交易顺序依赖漏洞进行形式化验证。以Decode悬赏合约为对象,分析合约中潜在的漏洞,自顶向下地对合约本身及其执行环境建立着色Petri网模型,并引入攻击者模型来考虑合约遭受攻击的情况。通过运行模型以验证合约存在交易顺序依赖漏洞,最后基于Remix平台在以太坊网络中证实结论的正确性。     

信号交叉口人机混驾交通流速度控制策略建模

为分析人机混驾交通流下网联自动驾驶车辆（connected and autonomous vehicles,CAV）速度控制策略对交通流运行特征的影响,构建了考虑驾驶员对行车信息获取不确定性的人工驾驶车辆交叉口通行决策模型。提出考虑前车速度影响的自动驾驶速度控制策略,构建信号交叉口连续型元胞自动机更新规则,通过引入不同CAV渗透率、道路饱和度、控制区长度参数,研究CAV速度控制策略对信号交叉口交通流运行特征的影响。结果表明：CAV能显著提高交叉口通行能力,且车流通过交叉口区域的延误显著降低;同时速度控制策略的实施效果还受控制区长度的影响,呈现出随着控制区长度的增加,车均延误逐渐降低并趋于稳定。     

Space use by two arboreal rodent species in a Neotropical cloud forest

Studying animal space use patterns can help increase our understating of ecological processes such as competition and community dynamics. To quantify space and habitat use in an isolated and patchy cloud forest community in Mexico, we evaluate the vertical stratification, home range and habitat selection of two arboreal rodents: Habromys schmidlyi and Reithrodontomys microdon. Using live-traps at ground level and different forest strata, we radio-equipped nine individuals of H. schmidlyi and seven of R. microdon, and evaluated fine-scale space use and broad-scale habitat selection between cloud forest and oak forest. We found an average home range of 0.24 ha for R. microdon males and 0.72 ha for females, with a preference for higher canopy in the cloud forest. For H. schmidlyi the home range was 0.83 ha for males and 0.29 ha for females, with a preference for the understory level in the cloud forest. Home range is three-dimensional for these rodents, so we estimate that on average, individuals of both species used eight trees in the time they were tracked. We characterised the vegetation at the trap sites, and used recursive partitioning to relate the presence of different plants with the probability of finding these two species and Peromyscus aztecus, a third rodent species also present in the area and considered in our analysis of habitat use. The highest probability of finding R. microdon (96%) was related to the presence of Brachythecium occidentale and Renauldia mexicana, while H. schmidlyi (95%) was found in close proximity to Fabronia ciliaris and Everniastrum. We highlight the importance of arboreal trapping in biodiversity assessments, and the role of arboreal rodents in maintaining tropical forest ecosystems. We suggest that these rodent species could avoid or reduce competition by using the vertical strata differentially, and that H. schmidlyi and R. microdon can be biological indicators for cloud forest management and conservation.     

Long Memory of Financial Time Series and Hidden Markov Models with Time‐Varying Parameters

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time‐varying behavior have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time varying. It is shown that a two‐state Gaussian hidden Markov model with time‐varying parameters is able to reproduce the long memory of squared daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time‐varying behavior of the parameters also leads to improved one‐step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations. Copyright © 2016 John Wiley & Sons, Ltd.