《西洋杂志》是[曾门四弟子]的桐城派著名作家黎庶昌任驻英、法、德、西使馆参赞五年闻关于欧洲的记述，通过细致的观察、深刻的体会与明洁动人的描写，作者翔实广泛地介绍日、德、意、奥、比、瑞士等西洋诸国经济发展、生产方式、政治制度、文化教育、科学技术、风俗民情等国情，呈现给人们一幅生动的西方社会全景，勾勒出近代中国人刚刚睁开双眼看世界时的认知过程与内心感受。全书共八卷，向国人详细介绍西洋各国实况，以其独特的史料价值和浓郁的文化兴味，并因顺应当时历史潮流，而深受国内外有识之士好评。

The word
means rebirth, and the most obvious example of this phenomenon was the regeneration of Europe's classical Roman roots. The Renaissance began in northern Italy in the late 14th century and culminated in England in the early 17th century. Emphasis on the dignity of man
(though not of woman) and on human potential distinguished the Renaissance from the previous Middle Ages. In poetry and literature, individual thought and action were prevalent, while depictions of the human form became a touchstone of Renaissance art. In science and medicine the macrocosm and
microcosm of the human condition inspired remarkable strides in research and discovery, and the Earth itself was explored, situating Europeans within a wider realm of possibilities. Organized thematically, the
covers all aspects of life in Renaissance Europe:
History; religion; art and visual culture; architecture; literature and language; music; warfare; commerce; exploration and travel; science and medicine; education; daily life.

The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market

This book presents a unique synthesis of the current neuroscience of cognition by one of the world's authorities in the field. The guiding principle to this synthesis is the tenet that the entirety of our knowledge is encoded by relations, and thus by connections, in neuronal networks of our cerebral cortex. Cognitive networks develop by experience on a base of widely dispersed modular cell assemblies representing elementary sensations and movements. As they develop cognitive networks organize themselves hierarchically by order of complexity or abstraction of their content. Because networks intersect profusely, sharing commong nodes, a neuronal assembly anywhere in the cortex can be part of many networks, and therefore many items of knowledge. All cognitive functions consist of neural transactions within and between cognitive networks. After reviewing the neurobiology and architecture of cortical networks (also named cognits), the author undertakes a systematic study of cortical dynamics in each of the major cognitive functions - perception, memory, attention, language, and intelligence. In this study, he makes use of a large body of evidence from a variety of methodologies, in the brain of the human as well as the nonhuman primate. The outcome of his interdisciplinary endeavor is the emergence of a structural and dynamic order in the cerebral cortex that, though still sketchy and fragmentary, mirrors with remarkable fidelity the order in the human mind.

In Memory in the Cerebral Cortex, Joaquin M. Fuster presents the insights of more than three decades of empirical research on the neural processes by which memory is formed, stored, and retrieved. Spanning the field from neuroanatomy to modeling, this book brings together all that we presently know about the role of the cerebral cortex of the primate in memory.

This important new text and reference for researchers and students in machine learning, game theory, statistics and information theory offers the first comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections. Old and new forecasting methods are described in a mathematically precise way in order to characterize their theoretical limitations and possibilities.