韵味悠长 上海镛舍酒店

正作为太古酒店屡获殊荣的居舍系列(The House Collective)全球第四间酒店,上海镛舍坐落于繁华的静安区,同时毗邻潮流街区南京西路。上海镛舍延续居舍系列一贯的品牌理念,致力于为宾客打造申城繁华中心的雅致居舍。室内设计由意大利著名设计师Piero Lissoni操刀主理,他从上海悠久深厚的工艺文化中汲取灵感,将标志性的简约风格与经典的上海元素完美融合。清晰现代的线条、精心挑选的材料和微妙大胆的色彩,搭配以海派文化、艺     

A combined approach for characterisation of fresh and brined vine leaves by X-ray powder diffraction,NMR spectroscopy and direct infusion high resolution mass spectrometry

X-ray powder diffraction was combined, for the first time, with Nuclear Magnetic Resonance spectroscopy and direct infusion mass spectrometry to characterise fresh and brined grape leaves. Covariance analysis of data generated by the three techniques was performed with the aim to correlate information deriving from the solid part with those obtained for soluble metabolites. The results obtained indicate that crystalline components can be correlated to the metabolites contained in the grape leaves, paving the way to the use of X-ray diffraction analysis for food fingerprinting purposes. Moreover it was ascertained that, differently from most of the metabolites present in the fresh vine leaves, linolenic acid (an omega-3-fatty acid) and quercetin-3-O-glucuronide (a polyphenol metabolite) do not undergo sensible degradation during the brining process, which is used as preservative method for the grape leaves.     

Effects of aerosol scattering phase function formulation on point-spread-function calculations

The quality of the image produced by an outdoor optical system is affected by the presence of atmospheric aerosols between object and receiver. The properties of the point-spread function that result from aerosol particles were calculated by a new Monte Carlo code called MEDIA (an acronym for Modélisation des Effets de Diffusion Inhérents à l'Atmosphère). The influence of the scattering phase function's angular dependence on the irradiance of the focal plane of a detector was studied. Calculations were performed by use of Mie theory and of the Henyey-Greenstein formulation for the same asymmetry parameter and various detector optical characteristics and atmospheric conditions. Major variations were observed for strong forward-peaked scattering phase functions and a large detector field of view.     

Toward overcoming culture, skill and situation hurdles in Human-Computer Interaction

This paper proposes a new effective strategy for designing and implementing interactive systems overcoming culture, skill and situation hurdles in Human-Computer Interaction (HCI). The strategy to identify and reduce these hurdles is developed in the framework of a methodology based on a recently introduced model of HCI, and exploits the technological innovations of XML (Extensible Markup Language). HCI is modelled as a cyclic process in which the user and the interactive system communicate by materializing and interpreting a sequence of messages. The interaction process is formalized by specifying both the physical message appearance and the computational aspect of the interaction. This formalization allows the adoption of notation traditionally adopted by users in their workplaces as the starting point of the interactive system design. In this way, the human–system interaction language takes into account the users’ culture. Moreover, the methodology permits user representatives to build a hierarchy of systems progressively adapted to users’ situations, skills and habits, according to the work organization in the domain considered. The strategy is proved to be effective by describing how to implement it using BANCO (Browsing Adaptive Network for Changing user Operativity), a feasibility prototype based on XML, which allows the hierarchy implementation and system adaptations. Several examples from an environmental case under study are used throughout the paper to illustrate the methodology and the effectiveness of the technology adopted. Published online: 4 June 2002     

MARS: A mergers and acquisitions reasoning system

Mergers and acquisitions (M&A) are currently revolutionizing the structure of corporate U.S.A. and annually involve deals totalling billions of dollars. Consequently, it is an area of intense activity and interest within the financial community. The process of planning an M&A is enormously complex and involves sophisticated reasoning and planning, by several parties such as the raider, the target company, investment banks, etc. Computer based tools are often invaluable for planning several stages of an M&A, such as generating forecasted cash flows. Current computer aids for M&A however do not provide adequate support for many essential features such as real time planning, reasoning under uncertainty, nonmonotonic inference, case-based reasoning, etc. MARS is a prototype M&A reasoning tool developed at General Electric Corporate R&D that attempts to provide such features in an integrated environment. MARS both simulates and provides advice regarding the complex reasoning and planning involved in an M&A deal. In doing so, it provides an excellent test bed architecture for the testing, development and integration of several ideas from artificial intelligence. MARS is implemented in COMMON LISP using RUM [15] on top of KEE [18]. RUM, a development environment for reasoning under uncertainty is based on Bonissone's theory of plausible reasoning [2–4] and was also developed at General Electric Corporate R&D.     

A classification and regression technique to handle heterogeneous and imperfect information

Imperfect information inevitably appears in real situations for a variety of reasons. Although efforts have been made to incorporate imperfect data into learning and inference methods, there are many limitations as to the type of data, uncertainty and imprecision that can be handled. In this paper, we propose a classification and regression technique to handle imperfect information. We incorporate the handling of imperfect information into both the learning phase, by building the model that represents the situation under examination, and the inference phase, by using such a model. The model obtained is global and is described by a Gaussian mixture. To show the efficiency of the proposed technique, we perform a comparative study with a broad baseline of techniques available in literature tested with several data sets.     

Erratum to: Reasoning with infinite stable models [Artificial Intelligence 156 (1) (2004) 75-111]

Theorem 16 in [Piero A. Bonatti, Reasoning with infinite stable models, Artificial Intelligence 156 (1) (2004) 75-111] states that ground skeptical and credulous inferences under the stable model semantics are decidable when the given normal logic program is finitary. Giovanni Criscuolo and Nicola Leone independently observed in personal communications that the proof of this theorem relies on an unproved assumption that—at the best of our current knowledge—might turn out to be false. In this note we correct Theorem 16 by adding the set of odd-cyclic atoms to the inputs of the computation, and argue that this change has no impact on the current applications of the theory of finitary programs.