Generalized resolution and cutting planes

This paper illustrates how the application of integer programming to logic can reveal parallels between logic and mathematics and lead to new algorithms for inference in knowledge-based systems. If logical clauses (stating that at least one of a set of literals is true) are written as inequalities, then the resolvent of two clauses corresponds to a certain cutting plane in integer programming. By properly enlarging the class of cutting planes to cover clauses that state that at least a specified number of literals are true, we obtain a generalization of resolution that involves both cancellation-type and circulant-type sums. We show its completeness by proving that it generates all prime implications, generalizing an early result by Quine. This leads to a cutting-plane algorithm as well as a generalized resolution algorithm for checking whether a set of propositions, perhaps representing a knowledge base, logically implies a given proposition. The paper is intended to be readable by persons with either an operations research or an artificial intelligence background.This report was prepared as part of the activities of the Management Sciences Research Group, Carnegie-Mellon University. Reproduction in whole or in part is permitted for any purpose of the U.S. Government.     

A review of expert systems

Expert systems have recently become popular and are attracting more and more attention. The high quality performance achieved by some systems in areas previously not considered practical for computational solutions has lead to great interest from many different disciplines. Most expert systems use a subset of techniques from the general area of computer science research known as artificial intelligence. However, some expert systems have been developed that incorporate more traditional mathematical modeling techniques. The combination of artificial intelligence techniques and more traditional mathematical techniques has been shown to be quite effective in developing several high quality performance computer software systems. The techniques used in expert systems may be what is needed to bridge the gap between classical operational research modeling and human decision making processes. This paper addresses how expert systems techniques are being used in problem solving and why someone in operational research might want to use them.     

The professional voice: Part III. Common diagnoses and treatments

Common problems that are of little consequence to other patients may be disabling to professional singers. Laryngologists must recognize even subtle manifestation of these ailments and be familiar with techniques to treat them without creating undesirable side effects. It is not usually necessary to restrict the trained professional from performing, and absolute voice rest is rarely necessary. Laryngeal surgery should be avoided whenever possible.     

Novel ultrasound contrast agents

As a novel ultrasound diagnostic contrast agent, the preparation, characterization and ultrasound imaging in the body of dog about poly(lactic acid) (PLLA) microcapsules have been studied. The behavior of this kind of contrast agent in the microcirculation was also investigated. Prepared by (water/oil/water) emulsion-solvent evaporation protocol, the PLLA microcapsules with hollow structure can enhance the ultrasound image both in vitro and in vivo, and the enduring time can last as long as 3 h. The microcirculation examination shows that the PLLA microcapsules with a diameter ranging from 2 to 8 μm could pass through the pulmonary capillaries without retention. All the results prove the PLLA microcapsules for potential use for the clinical application.     

小分子级联自组装/解组装策略在精准癌症诊疗中的应用

“智能”识别及靶向癌细胞是精确诊断与高效治疗的关键。目前的策略中,使用小分子共价前体探针（或药物）存在机体代谢速度快及对其他器官毒副作用大的局限;使用纳米探针（或载药）体系则存在分子量不明确、生物穿透性低和易被网状内皮系统捕获等问题。肿瘤“原位自组装”策略兼具了小分子和纳米体系的优点,利用小分子作为前体可提高药物分子在肿瘤组织的生物穿透性,?而自组装形成的纳米结构则提供了更好的生物利用度、更高的代谢稳定性和更长的滞留时间。在此基础上,研究者们通过设计多个肿瘤特异性生物分子顺次激活分子前体,进一步开发了小分子顺次级联自组装/解组装策略,以实现肿瘤组织的精准定位和肿瘤细胞的高选择性。在癌症的诊疗应用中,该策略可有效提高诊断信号的灵敏度,时空追踪癌细胞内的系列动态生物过程,同时实现药物的有效富集,并降低对正常细胞的副作用。该文概述了当前增强型级联自组装、级联自组装/解组装策略的研究进展,为癌症诊疗提供了新见解。     

Molecularly imprinted monoliths: Recent advances in the selective recognition of biomacromolecules related biomarkers

Biomarkers are significant indicators to assist the early diagnosis of diseases and assess the therapeutic response. However, due to the low abundance of biomarkers in complex biological fluids, it is highly desirable to explore efficient techniques to attain their selective recognition and capture before the detection. Molecularly imprinted monoliths integrate the high selectivity of imprinted polymers and the rapid convective mass transport of monoliths, and as a result, are promising candidates to achieve the specific enrichment of biomarkers from complex samples. This review summarizes the various imprinting approaches for the preparation of molecularly imprinted monoliths. The state-of-art advances as an effective platform for applications in the selective capture of biomacromolecules related biomarkers were also outlined.     

Electrical sensing of volatile organic compounds in exhaled breath for disease diagnosis

In recent years, electrical sensors toward breath volatolomics have attracted increasing interest owing to their wide feasibility in noninvasive disease diagnostics. In this article, the working principles of active nanomaterials (e.g. metal oxides, polymers, and nanocarbon) toward volatile organic compounds are presented, with a special focus on the influence of surface chemistry and structural feature of these nanomaterials on the sensing performance. The latest and representative achievements on the direct analysis of three typical exhaled volatile organic compounds, including acetone, ammonia, and hydrogen sulfide, that are recognized as important disease biomarkers, are highlighted, indicating the capability of the electrical sensors in enabling noninvasive diagnosis and real-time monitoring. The opportunities and challenges in this field are provided in the end, with an emphasis on the background interference and data recognition which are key factors in developing prospective electrical sensors toward volatolomics analysis.     

MRI检查神经根沉降征诊断LSS患者的价值及其危险因素分析

本研究探讨磁共振成像(MRI)检查神经根沉降征(NRS)在腰椎管狭窄症(LSS)患者发生中的相关因素及其诊断学价值。选取接受腰椎MRI检查的262例(511个腰椎节段)患者进行研究,根据MRI结果患者腰椎节段分为狭窄组(172例患者,348个腰椎节段)和非狭窄组(90例患者,163个腰椎节段)。狭窄组硬膜囊面积(CSA)<100 mm²患者占比、椎管正中矢状径(PDA)≤15 mm患者占比、侧隐窝矢状径≤5 mm患者占比、神经根沉降征(NRS)阳性率均显著高于非狭窄组(P<0.05);NRS诊断LSS的曲线下面积(AUC)值为0.714;172例LSS患者,NRS阳性患者108例、NRS阴性患者64例,NRS阳性组的糖尿病率、硬膜囊CSA<100 mm²患者占比、椎管PDA≤15 mm患者占比、侧隐窝矢状径≤5 mm患者占比均高于阴性组患者,差异均具有统计学意义(P<0.05);硬膜囊CSA<100 mm²、椎管PDA≤15 mm、侧隐窝矢状径≤5 mm是LSS患者发生NRS的独立危险因素(P<0.05)。NRS对于诊断LSS具有较高的特异度,但是灵敏度一般,患者椎管狭窄越严重,其NRS发生的风险越高。     

可视化智能融合导航系统

本文以提高导航系统的精度、可靠性、智能化和可视化程度为目标，利用智能工程的思想与方法将信息融合、人工智能和可视化技术综合应用于多传感器组合导航系统中，提出了面向２１世纪控制与导航技术的新一代导航系统概念—可视化智能融合导航系统，并对其功能、组成及关键技术进行了研究。     

用多传感器融合系统识别摩擦副的磨损状态

用于机械摩擦副磨损状态监测的多传感器融合系统，是本世纪８０年代末问世的一项新技术．在讨论了融合系统的构成和不同传感器信息的预处理之后，提出了一种基于自组织神经网络的多传感器融合系统．将这种融合系统用于实际机械摩擦副磨损状态监测的结果证明，其正确识别率明显地比单一传感器的高，容错能力强，而且由于自组织神经网络有在线学习的功能，系统可以用于在线监测