A cognitively based simulation of academic science

The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous simulations and to human data are obtained. It is found that while different cognitive settings may affect the aggregate number of scientific articles produced, they do not generally lead to different distributions of number of articles per author. The paper concludes with a discussion of the correspondence between the model and the constructivist view of academic science. It is argued that using more cognitively realistic models in simulations may lead to novel insights. Isaac Naveh obtained a master’s degree in computer science at the University of Missouri. His research interests include hybrid cognitive models and multi-agent learning. Ron Sun is Professor of Cognitive Science at Rensselaer Polytechnic Institute, and formerly the James C. Dowell Professor of Engineering and Professor of Computer Science at University of Missouri-Columbia. He received his Ph.D in 1992 from Brandeis University. His research interest centers around studies of cognition, especially in the areas of cognitive architectures, human reasoning and learning, cognitive social simulation, and hybrid connectionist models. For his paper on integrating rule-based and connectionist models for accounting for human everyday reasoning, he received the 1991 David Marr Award from Cognitive Science Society. He is the founding co-editor-in-chief of the journal Cognitive Systems Research, and also serves on the editorial boards of many other journals. He is the general chair and program chair for CogSci 2006, and a member of the Governing Board of International Neural Networks Society. His URL is: http://www.cogsci.rpi.edu/~rsun     

模糊美学的一种认知结构

美学问题存在大量的模糊性现象。本文分析了建立在处理狭义模糊性的L.A.Zadeh模糊集合论基础上的传统的模糊美学。运用模糊性层次的分析方法探讨了模糊美学问题,提出了模糊美学的一种认知结构,提出了结构性模糊美学的概念,讨论了它的本质、特征、研究对象和范围、研究任务和方法。     

High‐resolution mass spectrometry for bioanalytical applications: Is this the new gold standard?

Liquid chromatography coupled to quadrupole‐based tandem mass spectrometry (QqQ) is termed the “gold standard” for bioanalytical applications because of its unpreceded selectivity, sensitivity, and the ruggedness of the technology. More recently, however, high‐resolution mass spectrometry (HRMS) has become increasingly popular for bioanalytical applications. Nonetheless, this technique is still viewed, either as a screening technology or as a research tool. Although HRMS is actively discussed during scientific conferences, it is yet to be widely utilised in routine laboratory settings and there remains a reluctance to use HRMS for quantitative measurements in regulated environments. This paper does not aim to comprehensively describe the potential of the latest HRMS technology, but rather, it focuses on what results can be obtained and outlines the author's experiences over a period of many years of the routine application of various forms of HRMS instrumentation. Fifteen years ago, some nine different QqQ methods were used in the author's laboratory to analyse a variety of different veterinary drug resides. Today, many more analytes are quantified by seven HRMS methods and just three QqQ methods remain in use for the analysis of a small set of compounds yet to be upgraded to HRMS analysis. This continual upgrading and migration of analytical methods were accompanied by regularly participating in laboratory proficiency tests (PTs). The PT reports (covering a range of analytes and analytical methods) were used to compare the accuracy of HRMS‐ versus QqQ‐based measurements. In the second part of this paper, the particular strengths and limitations of HRMS for both method development and routine measurements are critically discussed. This also includes some anecdotal experiences encountered when replacing QqQ assays with HRMS methods.     

知识体系与认知规律相结合建设分析化学课程教材

阐述教材是提高教学质量重要且必备的条件之一,回顾我国分析化学工作者编写教材的实践历程,提出编写教材应体现＂注重学科基础、关注学科前沿、适当拓展学科交叉,体现知识体系与认知规律相结合＂的特点。     

认知无线网络中基于Sigmoid函数的功率控制算法研究

为了实现认知无线网络中频谱分配公平性以及契合现代化绿色通信的需求,根据非合作博弈论和干扰温度,引入信道状态概念,设计出一种新型功率控制算法,分析了该算法的收敛性、纳什均衡解的存在性和唯一性。该算法不仅可以快速收敛,符合实时通信,而且分布式实施,简单实用。仿真结果表明,相比其他算法,该算法系统干扰小,能源消耗低,具有抗干扰性能,而且在日益多用户网络的情况下,具有低功率、低干扰,提高网络的整体效益,更加符合现代化的绿色通信的需求。     

茶叶中联苯菊酯、毒死蜱残留量的测定能力验证分析

介绍了组织全国多个行业102家实验室参加茶叶中联苯菊酯、毒死蜱残留量的测定能力验证的情况.选用自然基体测试样品,分别采用F检验和t检验法检验样本的均匀性和稳定性,采用稳健统计技术对试验结果进行了分析.时残留量测定的关键技术进行了讨论.     

Cross-layer design based hybrid MAC protocol for cognitive radio network

A minimal interrupted communication link setup is the primary objective of the MAC layer. The MAC layer is responsible for accessing the communication channel. At MAC, a control channel is used in the selection of collision free paths for data transfer. Therefore, the design of the control channel plays a pivotal role in achieving desired QoS in cognitive radio (CR) technology. Various schemes of control channel design help the CR network (CRN) to obtain better performance. The reported work focuses on a hybrid MAC protocol. The novelty of the scheme lies in the process of hybridization. A cross-layer framework is proposed for hybridization. The cross-layering has been done between network and MAC layer to achieve hybridization between different control channel design approaches. The broad categorization of control channel designs is between licensed in-band and dedicated unlicensed out-band approaches. In the in-band control channel design approach, the opportunistic use of data channel as control channel fulfills the decorum of CR technology. As soon as the primary user activity rises in the data channels, the in-band approach suffers from poor performance. On the other hand, the dedicated unlicensed out-band control channel design approach provides global coverage and all-time availability but suffers from channel saturation and intruder attacks. Interference in the control channel limits the use of out-band design. This motivates authors to develop a hybrid MAC protocol that can float between licensed in-band design and unlicensed out-band design to access the control channel. The hybridization is possible by sharing a primary user free channel list (PCL) among CR nodes. In conventional hybrid MAC protocols, the PCL is shared as a control beacon in the channel. Extra packet requirement as control beacon affects the performance of CR scenario. The proposed cross-layer design based hybrid MAC protocol avoids the need of an extra control beacon for PCL transmission. Further, the hybridization helps in achieving advantages of both in-band and out-band control channel design approaches. The simulation results show that the proposed hybrid MAC protocol performs satisfactorily in terms of packet delivery ratio, average throughput, average delay and control overhead. The performances are also tested in the worst scenarios.     

Optimal Channel Selection algorithm for CRahNs

As the data traffic is increasing, the spectrum bands are getting congested. It causes low latency and unreliable communication. Additional spectrum can be utilized to solve this problem but moving towards higher frequency means higher power requirement and increased cost. Cognitive radio network is another solution to this problem. It helps the nodes of a network to use the channels of the nearby bands which are not being used at that time. However, it has several challenges. One of these challenges is the transmission collision with the primary users of the network. Researchers have been working on this problem. However, it is still a major concern for the researchers. This paper proposes an algorithm that selects the optimal cognitive channel for the data transmission by the secondary user in such a way so that the transmission collision with the PU is minimized. After comparison with the existing latest similar protocol, the proposed protocol has shown 5.6% improvement in the throughput, 5.3% improvement in PDR. The delay is decreased by 0.6% and the transmission collision with PUs is reduced by 2.5%.     

Blockchain based Scalable model for Secure Dynamic Spectrum Access

Conventional Cooperative spectrum sensing techniques either suffer from single point of failure attack or lack in providing incentives to users which makes them incompatible for Wireless Service Provider (WSP). We propose a dynamic spectrum access framework for WSP which gives prominence to automated sensing and sharing with the use of blockchain. In this system, the opportunity of spectrum access is first examined by sensor nodes and the access right is then allocated to the users when their transactions to WSP are authenticated in a decentralized manner. Apart from using blockchain as a reliable platform for automatic enforcement of spectrum sensing, we propose a novel mechanism for securing our network from the threats designed primarily for Cognitive Radio Networks. In addition to this, our proposed approach enhances the scalability of blockchain networks by using the sidechains for storing data and checkpointing it onto main chain after periodic intervals of time. Extensive simulations in Octave indicate superior performance offered by our proposed model.     

Gandouling alleviates cognitive dysfunction by regulates the p62/Nrf2 signaling pathway to reduce oxidative stress and autophagy in mice models of Wilson’s disease

Cognitive impairment is a neurological manifestation of Wilson's disease (WD). Gandouling (GDL), a traditional Chinese medicine, protects against WD-related brain damage. However, the mechanisms underlying its protective effect have not been elucidated. Therefore, we explored the neuroprotective effects of GDL on cognitive abilities to understand the underlying molecular mechanisms using a toxic milk mouse model of WD. We employed the Morris water maze test and open field test to assess the effects of GDL on spatial memory, learning abilities and exploratory behavior in these mice. GDL treatment reduced the escape latency and increased the number of times mice crossed the platform to reach the target zone, indicative of alleviated WD-associated cognitive dysfunction. It also ameliorated the histopathological changes in the hippocampus via downregulation of IL-1β, IL-6, and TNF-α expression, reduced oxidative stress, and increased cell vigor. GDL treatment increased the protein and mRNA levels of Nrf2 and OH-1 protein while lowering p62, Beclin1, and LC3 expression in the hippocampus. Collectively, GDL improves cognitive dysfunction in mice with WD by regulating the Nrf2/p62 signaling pathway by reducing oxidative stress and autophagy. Based on its anti-inflammatory, antioxidant, and autophagy-inhibiting effects, we believe GDL is a promising therapy for WD-related cognitive dysfunction.