冷能利用片冰机海水淡化动态仿真

介绍了一种新型的冷冻海水淡化技术。到2019年末,液化天然气（LNG）生产能力已达4.3亿吨/年。LNG从再气化过程中释放出的巨大冷能量可用于冷冻脱盐过程,以最大限度地降低总能耗。本文采用HYSYS软件设计并仿真了利用LNG冷能的片冰机冷冻海水淡化（FD）过程。采用片冰机上的制冰桶作为海水结晶器,主要是由于其连续制冰和除冰无热源。利用gPROMS软件建立了冻结段的动态模型并进行了仿真。结果表明,用1kg当量液化天然气冷能可获得1.9~2.1kg的冰融水,该混合工艺的制冷剂泵功率能耗为3.725Wh/100kg,可忽略不计。     

Approximate variational inference based on a finite sample of Gaussian latent variables

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower bound on the desired integral to be approximated, e.g. marginal likelihood. The lower bound is then optimised with respect to its free parameters, the so-called variational parameters. However, this is not always possible as for certain integrals it is very challenging (or tedious) to come up with a suitable lower bound. Here, we propose a simple scheme that overcomes some of the awkward cases where the usual variational treatment becomes difficult. The scheme relies on a rewriting of the lower bound on the model log-likelihood. We demonstrate the proposed scheme on a number of synthetic and real examples, as well as on a real geophysical model for which the standard variational approaches are inapplicable.     

High pressure cell for neutron reflectivity measurements up to 2500 bar

The design of a high pressure (HP) cell for neutron reflectivity experiments is described. The cell can be used to study solid-liquid interfaces under pressures up to 2500 bar (250 MPa). The sample interface is based on a thick silicon block with an area of about 14 cm(2). This area is in contact with the sample solution which has a volume of only 6 cm(3). The sample solution is separated from the pressure transmitting medium, water, by a thin flexible polymer membrane. In addition, the HP cell can be temperature-controlled by a water bath in the range 5-75°C. By using an aluminum alloy as window material, the assembled HP cell provides a neutron transmission as high as 41%. The maximum angle of incidence that can be used in reflectivity experiments is 7.5°. The large accessible pressure range and the low required volume of the sample solution make this HP cell highly suitable for studying pressure-induced structural changes of interfacial proteins, supported lipid membranes, and, in general, biomolecular systems that are available in small quantities, only. To illustrate the performance of the HP cell, we present neutron reflectivity data of a protein adsorbate under high pressure and a lipid film which undergoes several phase transitions upon pressurization.     

Diffraction contrast STEM of dislocations: imaging and simulations

The application of scanning transmission electron microscopy (STEM) to crystalline defect analysis has been extended to dislocations. The present contribution highlights the use of STEM on two oppositely signed sets of near-screw dislocations in hcp α-Ti with 6wt% Al in solid solution. In addition to common systematic row diffraction conditions, other configurations such as zone axis and 3g imaging are explored, and appear to be very useful not only for defect analysis, but for general defect observation. It is demonstrated that conventional TEM rules for diffraction contrast such as g·b and g·R are applicable in STEM. Experimental and computational micrographs of dislocations imaged in the aforementioned modes are presented.     

The Price of Anarchy in Network Creation Games Is (Mostly) Constant

We study the price of anarchy and the structure of equilibria in network creation games. A network creation game is played by n players {1,2,…,n}, each identified with a vertex of a graph (network), where the strategy of player i, i=1,…,n, is to build some edges adjacent to i. The cost of building an edge is α>0, a fixed parameter of the game. The goal of every player is to minimize its creation cost plus its usage cost. The creation cost of player i is α times the number of built edges. In the SumGame variant, the usage cost of player i is the sum of distances from i to every node of the resulting graph. In the MaxGame variant, the usage cost is the eccentricity of i in the resulting graph of the game. In this paper we improve previously known bounds on the price of anarchy of the game (of both variants) for various ranges of α, and give new insights into the structure of equilibria for various values of α. The two main results of the paper show that for α>273?n all equilibria in SumGame are trees and thus the price of anarchy is constant, and that for α>129 all equilibria in MaxGame are trees and the price of anarchy is constant. For SumGame this answers (almost completely) one of the fundamental open problems in the field—is price of anarchy of the network creation game constant for all values of α?—in an affirmative way, up to a tiny range of α.     

Examining the dimensionality of genuine multipartite entanglement

Entanglement in high-dimensional many-body systems plays an increasingly vital role in the foundations and applications of quantum physics. In the present paper, we introduce a theoretical concept which allows to categorize multipartite states by the number of degrees of freedom being entangled. In this regard, we derive computable and experimentally friendly criteria for arbitrary multipartite qudit systems that enable to examine in how many degrees of freedom a mixed state is genuine multipartite entangled.     

Privacy-enhanced architecture for smart metering

The recent deployment of smart grids promises to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more transparent and instantaneous measurement of electricity consumption through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy usage. Nevertheless, it also has associated drawbacks related to the privacy of customers, since such management might reveal their personal habits, which electrical appliances they are using at each moment, whether they are at home or not, etc. In this work, we present a privacy-enhanced architecture for smart metering aimed at tackling this threat by means of encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values.     

Figure-ground separation by cue integration

This letter presents an improved cue integration approach to reliably separate coherent moving objects from their background scene in video sequences. The proposed method uses a probabilistic framework to unify bottom-up and top-down cues in a parallel, "democratic" fashion. The algorithm makes use of a modified Bayes rule where each pixel's posterior probabilities of figure or ground layer assignment are derived from likelihood models of three bottom-up cues and a prior model provided by a top-down cue. Each cue is treated as independent evidence for figure-ground separation. They compete with and complement each other dynamically by adjusting relative weights from frame to frame according to cue quality measured against the overall integration. At the same time, the likelihood or prior models of individual cues adapt toward the integrated result. These mechanisms enable the system to organize under the influence of visual scene structure without manual intervention. A novel contribution here is the incorporation of a top-down cue. It improves the system's robustness and accuracy and helps handle difficult and ambiguous situations, such as abrupt lighting changes or occlusion among multiple objects. Results on various video sequences are demonstrated and discussed. (Video demos are available at http://organic.usc.edu:8376/ approximately tangx/neco/index.html .).     

Rapid convergence to feature layer correspondences

We describe a neural network able to rapidly establish correspondence between neural feature layers. Each of the network's two layers consists of interconnected cortical columns, and each column consists of inhibitorily coupled subpopulations of excitatory neurons. The dynamics of the system builds on a dynamic model of a single column, which is consistent with recent experimental findings. The network realizes dynamic links between its layers with the help of specialized columns that evaluate similarities between the activity distributions of local feature cell populations, are subject to a topology constraint, and can gate the transfer of feature information between the neural layers. The system can robustly be applied to natural images, and correspondences are found in time intervals estimated to be smaller than 100 ms in physiological terms.