Effects of Berry Anthocyanins on Cognitive Performance,Vascular Function and Cardiometabolic Risk Markers: A Systematic Review of Randomized Placebo-Controlled Intervention Studies in Humans

Supplementation with anthocyanins, which are a type of flavonoids mainly found in various berries, is hypothesized to be a promising approach to lower the risk of developing cognitive decline. The aim of this systematic review was to provide a comprehensive overview of dietary intervention trials describing effects of berry anthocyanins on cognitive performance in humans, while also addressing potential underlying mechanisms. A total of 1197 articles were identified through a systematic search, and 49 studies reporting effects on cognitive performance (n = 18), vascular function (n = 22), or cardiometabolic risk markers (n = 32) were included. Significant improvements were observed on memory, while some of the studies also reported effects on attention and psychomotor speed or executive function. Vascular function markers such as brachial artery flow-mediated vasodilation were also affected and consistent evidence was provided for the beneficial effects of berry anthocyanins on endothelial function. Finally, studies reported improvements in blood pressure, but effects on metabolic risk markers (e.g. carbohydrate and lipid metabolism) were less consistent. In conclusion, this review provides evidence for the beneficial effects of berry anthocyanins on cognitive performance as memory improved. Whether observed anthocyanin-induced improvements in vascular function and blood pressure underlie beneficial effects on cognitive performance warrants further study.     

Computational Problem Solving in Spatial Substrates -- A Cognitive Systems Engineering Approach

The ability to perform spatial tasks is crucial for everyday life and of great importance to cognitive agents such as humans, animals, and autonomous robots. A common artificial intelligence approach to accomplish spatial tasks is to represent spatial configurations and tasks in form of detailed knowledge about various aspects of space and time. Suitable algorithms then use the representations to compute solutions to spatial problems. In comparison, natural embodied and situated agents often solve spatial tasks without detailed knowledge about geometric, topological, or mechanical laws; they directly relate actions to effects that are due to spatio-temporal affordances in their bodies and environments. Accordingly, we propose a paradigm that makes the spatio-temporal substrate an integral part of the engine that drives spatial problem solving. We argue that spatial and temporal structures in body and environment can substantially support (and even replace) reasoning effort in computational processes: physical manipulation and perception in spatial environments substitute formal computation. While the approach is well known – for example, we employ diagrams as spatial substrate for geometric problem solving and maps for wayfinding – the underlying principle has not been systematically investigated or formally analyzed as a paradigm of cognitive processing. Topology, distance, and orientation constraints are all integrated and interdependent in truly 2- or 3-dimensional space. Exploiting this fact may not only help overcome the need for acquiring detailed knowledge about the interrelationships between different aspects of space; it also can point to a way of avoiding exploding computational complexity that occurs when we deal with these aspects of space in complex real-world scenarios. Our approach employs affordance-based object-level problem solving to complement knowledge-level formal approaches. We will assess strengths and weaknesses of the new cognitive systems paradigm.     

认知无线电网络信道交汇研究综述

认知无线电技术被认为是解决目前频谱资源利用率低下问题最有前景的技术,基于该技术,认知无线电网络采用动态频谱接入方式有效地提高了授权频段的利用率.然而,动态变化的信道可用性极大地增加了认知无线电网络组网的难度.信道交汇旨在为用户通信提供公共传输媒介,是实现无线网络组网的基础.介绍了认知无线电网络信道交汇的基本概念和特点,并阐述了信道交汇策略设计面临的挑战以及应考虑的性能指标.提出了信道交汇策略的分类标准和系统模型,根据该分类标准,详细剖析了当前信道交汇策略相关的研究工作.最后,讨论了认知无线电网络信道交汇研究的开放性问题,以期为未来的研究指出可能的方向和重点.     

大规模认知无线电网络的时延分析

时延作为无线网络的最基本的性能之一,对网络信息分发、路由协议设计、节点部署等都具有重要意义。与传统的无线网络不同,认知无线电网络的频谱资源具有动态变化性,该特性会对网络时延产生极大的影响。因此,如何对动态频谱环境下的大规模认知无线电网络进行时延分析,是一项很具挑战性的课题。为此,首先对动态频谱环境进行建模,将认知用户的频谱接入过程建模为一个连续时间的马尔可夫链,并建立认知用户的生存函数来量化授权用户活动以及信道数量对频谱环境的影响;其次,将上述模型与首次通过渗流理论结合起来,研究了大规模认知无线电网络时延的伸缩规律,并获取了更为精确的时延与距离比的上限值。理论分析及仿真结果表明,动态频谱环境与密度一样会对时延产生极大影响。研究结论对认知无线电网络的设计具有重要的指导意义。     

基于重加权快速交替方向法的频谱感知

在认知无线电网络中,由于深衰落和低信噪比的影响,单个认知用户的宽带频谱检测性能较差,且算法复杂度较高。针对该问题,提出一种基于重加权快速交替方向法的频谱感知算法。利用目标函数的凸性,通过求导简化辅助变量的更新过程。对目标函数进行线性化处理,增加一个二次项,使待估变量更新时部分项线性化的增广拉格朗日函数成为严格凸函数,并使用迭代软阈值算法进行求解。在目标项中增加大权值抑制信号中的非零元素,获得接近于最小?0范数的解。实验结果表明,该算法能有效提高低信噪比环境下的检测概率和检测速度。     

认知无线网络动态频谱感知决策安全协议框架研究

对认知网络频谱感知安全研究现状进行了分析, 提出了一个频谱感知决策安全协议框架。对认知无线网络模型中相关组件、符号进行了定义, 并对其结构和安全性进行了详细描述。通过与相关方案比较, 结果表明该协议框架能够用来抵御频谱感知所面临的潜在威胁, 使之进行正确的频谱决策。     

浅谈绿色无线通信技术

目前,移动通信正朝着绿色通信的方向发展,网络中的基站节能是绿色无线通信的重点。该文简要介绍了网络节能的相关技术,包括认知无线电、协作中继、小区缩放及云计算等,这些技术将在绿色通信的发展中起到巨大的作用。     

认知无线电中对干扰信号源的定位

当认知用户接入主用户系统时将对主用户产生干扰。确定产生干扰的认知用户的位置能更好地进行基站布署,从而最大限度地避免这种干扰,使频谱得到有效利用。本文主要给出了一种改进的MUSIC算法对相干的干扰认知用户进行定位,即利用前后向空间平滑的修正矩阵进行矩阵的重构,再分解其重构矩阵,最后利用波束空间的MUSIC算法减少谱峰搜索中的计算量。通过计算机仿真证明了此方法的有效性。     

OFDM信号循环谱分析及参数估计*

针对在无线电监测和认知无线电系统中,信号参数估计这一重要问题,证明了OFDM信号具有循环平稳性的必要条件是加循环前缀或有非矩形脉冲成型,并以线性周期时变变换(LPTV)模型为基础,推导了OFDM信号的循环谱表达式。通过对连续信号和离散信号进行计算机仿真,都得到了相同的OFDM信号循环谱图,实现了OFDM信号符号周期的估计,结果与理论分析相吻合。     

认知无线电网络中基于检测概率的主用户定位算法

为了解决认知无线电网络中次用户对主用户进行定位的问题,提出了一种加权最小二乘的迭代定位算法。采用两状态马尔可夫模型作为主用户头像模型,能量检测作为次用户的感知模型。该算法可以在不干扰主用户正常工作的情况下,利用次用户之间的合作感知结果进行定位,并估计出主用户的三维地理位置位置信息。提出了一种可以降低定位算法复杂度的简化算法。通过对定位问题进行了理论分析,求出了均方误差的Cramer-Rao理论下界。仿真结果表明,算法的均方误差非常接近理论下界,能有效地估计主用户的三维位置信息,提高定位精度。