六台轧机热轧钢板在线测长及产品统计微机系统

本论文选用Apple-Ⅱ作主机,开发了一套外设接口扩展箱和相应的应用软件,用于实现在钢厂中对六台单轧机的热轧钢板长度在线检测和现场显示,同时对钢板的长度按照合格、超长、超短进行分类统计,打印生产报表。此外还提供随时修改钢板长度(标尺)设定值和随机查询各台轧机产质量状况的功能。在接口扩展箱中,采用了包括光电耦合在内的若干抗干扰措施,保证系统能在钢厂恶劣环境中正常运行。本系统已在工厂轧机上试用成功。     

关于振动模态参数识别的注记

回顾了关于整体拟合的分母多项式系数的争议,论证了Richardson文献中所提供的参数精度不高的原因并非源于Richardson的错误.指出一个经典考核算例的仿真传递函数生成公式不同于复模态理论提供的公式,讨论了两者之间的关系.表1,参9.     

咪唑季铵盐棉纤维制备及其对DOSO_3~-吸附性能研究

本文用20%的NaOH溶液对棉纤维的预处理、醚化、接枝合成工艺进行了优化;在不同条件下,研究了咪唑季铵盐棉纤维对DOSO~-_3的吸附性能.结果表明,用NaOH预处理棉纤维后,在适当的条件下醚化棉纤维素,再用氢氧化钠作催化剂,按3 g环氧基纤维素醚与10 mL甲基咪唑配比接枝,得到白色味唑季铵盐纤维素.用咪唑季铵盐棉纤维对DOSO~-_3进行吸附,吸附率可达91.8%,吸附效果令人满意.     

“互动分层合作学习”对田径运动成绩的影响

在田径教学实践中运用“互动合作学习法”对学生进行合理、适宜的分类或分组，确立相应的层次目标．做好课的设计，包括实践操作、课外作业、课内外的教学指导、协调学生组内及组间的合作交流等各个教学环节，使教学过程体现出系统性、层次性，使每位学生都能在各自力所能及的范围内，通过相互帮助和互相协作学习而收到良好的成效．同时能更好地促进学生主动、积极地学习，更好地完成教学任务与教学目标，提高教与学的双边效果．     

Method of Homomorphic Encryption

The existing homomorphie eneryption scheme is based on ring of the integer, and the possible operators are restricted to addition and multiplication only. In this paper, a new operation is defined Similar Modul. Base on the Similar Modul, the number sets of the homomorphic encryption scheme is extended to real number, and the possible operators are extended to addition, subtraction, multiplication and division. Our new approach provides a practical ways of implementation because of the extension of the operators and the number sets.     

一种基于段的基音检测算法

作为语音信号处理领域一项基本、关键的技术,基音检测在语音信号处理中扮演着重要的角色,一直是语音信号处理的一个研究热点.首先对传统的基于短时自相关函数法的基音检测进行了研究;在此基础上提出了一种能同时检测一段语音信号基音周期的方法,有效地克服了传统基音检测算法只能检测一帧语音信号基音的缺点.进行了实验仿真,结果表明通过去野点,中值平滑等后处理的基于段的基音检测算法比传统的基于帧的基音检测算法具有更好的抗噪性.     

葛根素治疗不稳定性心绞痛71例临床观察

目的 探讨在常规治疗基础上应用葛根素注射液治疗不稳定性心绞痛(UA)的疗效.方法 对于入院确诊为不稳定性心绞痛的患者,随机分为两组:对照组为常规抗凝组,低分子肝素5000 u皮下注射,1次/12 h,共5 d,阿斯匹林肠溶片0.3 g,1次/d,3 d后改为0.1 g,1次/d,长期服用;治疗组为葛根素组,葛根素300 mg静脉滴注,1次/d,其余治疗同对照组.结果 治疗组控制症状及改善异常心电图方面均优于对照组,并使C-反应蛋白(CRP)浓度更快下降,与对照组相比,差异有显著性(P＜0.05).结论 在抗凝及抗血小板基础上加用葛根素,治疗UA疗效优于常规抗凝治疗.     

The Difference of the Pulmonary-Artery Pressure of the Migrants from Difference Elevation at the 4636 - 4907 m Altitude

Study Objective： To compare and analyze the changes of the pulmonary-artery pressure of the migrants coming from different elevation in the hypoxic environment of 4636 - 4907 m extreme altitude. To explore the susceptibility to hypoxic pulmonary-artery hypertension （PH） in the subjects from different altitude and profession. Methods： By using Color Doppler Ultmsonography （CDU）, measuring the pulmonary-artery pressure of 207 healthy men, who had continuously being lived and worked at the extreme altitude for more than six months, and then were divided into three groups according to their profession and the altitude of original living place. Results： There was a significant difference in the outcomes of pulmonary-artery pressure from the 3 groups. Conclusions： Altitude of original living place, labor intensity are some of factors that impact the pulmonary-artery pressure of the people who exposure to a hypoxic environment. The pulmonary- artery pressure of person without strenuously physical work experience was more sensitive to hypoxic surroundings than that of labor workers. It was not always the fact at an extreme altitude that the moderate altitude mountaineers were superior to other migrants from a lower altitude or plain. The higher PH was found in the groups of the moderate altitude mountaineers and labor workers. It is unlikely certain that one with PH would surfer from HAPE.     

中浓纸浆在反应器内的流动特性研究

中浓纸浆是一种非常特殊的介质,中浓纸浆在升流式反应器中的运动特性关系到反应器的反应效率和反应质量.为探求中浓纸浆在升流式反应器内的流动规律,作者利用自行研制的中浓纸浆漂白试验系统采用示踪法进行了研究.结果证明:中浓纸浆在升流塔内流动时的运动和塔器的截面形状,流动速度相关.对其中气体的运移也进行了一定深度的研究.     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.