Lack of tolerance development to tumor necrosis factor α inside the central nervous system

Tumor necrosis factor (TNF) was repeatedly microinfused into the lateral ventricle of guinea pig brains at a dose of 200 ng, 4 times within 150 min, at intervals of 3 days. In comparison to guinea pigs infused with solvent according to the same time schedule, the animals responded to TNF with pronounced fevers. The quantity of the fever response was the same after each of the 4 microinfusions of TNF. Three days after the last infusion of TNF or solvent all animals received an intramuscular injection of bacterial lipopolysaccharide (LPS). The fever in response to LPS was the same in both groups. Thus, the reported development of tolerance to repeated systemic administration of TNF^1–3 does not develop inside the blood-brain barrier. Also, the febrile response to LPS is not influenced by repeated central pre-treatment with TNF, whereas repeated peripheral treatment does have an effect.     

框架与框剪结构建筑工程量计算要领

在框架与框剪结构建筑工程量计算中,用本文赋予新概念的基线“外（墙）梁柱中心线”,“内（墙）梁柱净长线”,“外（墙）梁柱外边线”和基面（各楼层楼板面积）来统筹其工程量计算,并以柱、梁、板项目力主导展于各分项计算程序,能使繁杂而易混淆不清的工程量计算问题得以简明、准确、完整地解决。     

构成基本串联与并联非线性系统结构模型的必要条件

在Ｖｏｌｔｅｒｒａ理论和Ｗｉｅｎｅｒ理论的基础上,利用相关分析方法,研究并给出了构成基本串联与并联非线性系统结构模型的必要条件,它们能够为辩识一大类可表示成这些模型的“黑箱”非线性系统提供一种重要的判别依据．文中还给出了计算机模拟算例．     

Cephalopod myocardial receptors: Pharmacological studies on the isolated heart ofSepia officinalis (L.)

Summary This paper presents a synopsis of the information available about the pharmacological action of various substances on the cephalopod heart, with special emphasis on the central heart ofSepia officinalis. Threshold concentrations, EC₅₀ values and maximum effective concentrations have been experimentally determined. Studies with various transmitter substances, analogous compounds and antagonists have led to the following picture: Acetylcholine is the natural inhibitory transmitter substance; it acts via receptors with nicotinic properties which can be blocked by d-tubocurarine and -bungarotoxin. The probable excitatory transmitter system is represented by a noradrenergic innervation. Noradrenaline has a positive inotropic and a positive chronotropic action on in vitro heart preparations. A positive inotropic response can also be evoked by serotonin (5-HT); this effect is not due to stimulation of the catecholamine receptor, as is shown by cross-over experiments with specific blocking agents. Furthermore, a peptidergic receptor system has been described which reacts with the molluscan cardioactive peptide FMRF amide most effectively. It is assumed that cardioactive peptides may reach the central heart in the circulating blood; the sites of synthesis and release are still unknown. Possibly the NSV-layer of the vena cava is involved in hormonal cardiovascular regulation processes.     

采用变长梁单元的柔性平面连杆机构的KED分析

本文采用变长梁单元来处理机构中的所谓“导杆”构件,在弹性小变形范围内,导出了考虑弯曲、剪切及轴向三种变形型式和计及截面转动惯量、端点集中质量、纵向弯曲影响的柔性平面连杆机构系统最一般的弹性运动微分方程式,不仅使其与全转动副柔性平面连杆机构KED分析在形式上得到了完全统一,而且更简明地给出了求其稳态解的Four柏r级数系数方程式.作为算例,文中给出了一转动导杆机构相应数值计算结果.     

凸轮转子叶片马达的过渡曲线中心角参数优化

提出了针对凸轮转子外轮廓过渡曲线段的参数优化设计方法.通过对马达关键参数解析式推导及分析,得出了压力角、叶片干扰转矩、流量脉动、泄漏量与过渡曲线中心角之间的关系.通过解析计算及仿真,得出了该类型叶片马达凸轮转子设计的理论依据和优化参数.经过实验验证,基于该中心角优化参数设计的凸轮转子叶片马达取得了良好的伺服精度,证明了凸轮转子过渡曲线段中心角参数优化设计的正确性和可行性.     

一种改进的B样条网络学习算法应用于非线性时间序列预测

将一种关于一维输入的改进B样条网络学习算法推广到二维输入情形，并应用到一个非线性时间序列预测问题中，计算机仿真结果表明该算法比现有的B样条网络学习算法更有效。     

多重Taylor级数在C~n上的零级

分析了传统教学模式的弊端,介绍了这种教学模式的意义、建设和效果,研究了这种教学模式的优越性和局限性,探索了新型的教学方法。     

扩展安全区求解孔系坐标尺寸链

在孔系坐标尺寸换算过程中，首选设定了孔心距综合公差带安全区，并按不同的边界条件对安全区进行扩展，最后导出坐标尺寸公差的计算公式。     

Forecasting Australia's real house price index: A comparison of time series and machine learning methods

We employ 47 different algorithms to forecast Australian log real house prices and growth rates, and compare their ability to produce accurate out-of-sample predictions. The algorithms, which are specified in both single- and multi-equation frameworks, consist of traditional time series models, machine learning (ML) procedures, and deep learning neural networks. A method is adopted to compute iterated multistep forecasts from nonlinear ML specifications. While the rankings of forecast accuracy depend on the length of the forecast horizon, as well as on the choice of the dependent variable (log price or growth rate), a few generalizations can be made. For one- and two-quarter-ahead forecasts we find a large number of algorithms that outperform the random walk with drift benchmark. We also report several such outperformances at longer horizons of four and eight quarters, although these are not statistically significant at any conventional level. Six of the eight top forecasts (4 horizons × 2 dependent variables) are generated by the same algorithm, namely a linear support vector regressor (SVR). The other two highest ranked forecasts are produced as simple mean forecast combinations. Linear autoregressive moving average and vector autoregression models produce accurate olne-quarter-ahead predictions, while forecasts generated by deep learning nets rank well across medium and long forecast horizons.