Template‐Free Fabrication of Mesoporous Alumina Nanospheres Using Post‐Synthesis Water‐Ethanol Treatment of Monodispersed Aluminium Glycerate Nanospheres for Molybdenum Adsorption

This work reports the template‐free fabrication of mesoporous Al₂O₃ nanospheres with greatly enhanced textural characteristics through a newly developed post‐synthesis “water‐ethanol” treatment of aluminium glycerate nanospheres followed by high temperature calcination. The proposed “water‐ethanol” treatment is highly advantageous as the resulting mesoporous Al₂O₃ nanospheres exhibit 2–4 times higher surface area (up to 251 m² g^?1), narrower pore size distribution, and significantly lower crystallization temperature than those obtained without any post‐synthesis treatment. To demonstrate the generality of the proposed strategy, a nearly identical post‐synthesis “water treatment” method is successfully used to prepare mesoporous monometallic (e.g., manganese oxide (MnO₂)) and bimetallic oxide (e.g., CuCo₂O₄ and MnCo₂O₄) nanospheres assembled of nanosheets or nanoplates with highly enhanced textural characteristics from the corresponding monometallic and bimetallic glycerate nanospheres, respectively. When evaluated as molybdenum (Mo) adsorbents for potential use in molybdenum‐99/technetium‐99m (⁹⁹Mo/^99mTc) generators, the treated mesoporous Al₂O₃ nanospheres display higher molybdenum adsorption performance than non‐treated Al₂O₃ nanospheres and commercial Al₂O₃, thereby suggesting the effectiveness of the proposed strategy for improving the functional performance of oxide materials. It is expected that the proposed method can be utilized to prepare other mesoporous metal oxides with enhanced textural characteristics and functional performance.     

Greedy versus social: resource-competing oscillator network as a model of amoeba-based neurocomputer

A single-celled amoeboid organism, the true slime mold Physarum polycephalum, exhibits rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. The authors previously created a biocomputer that incorporates the organism as a computing substrate to search for solutions to combinatorial optimization problems. With the assistance of optical feedback to implement a recurrent neural network model, the organism changes its shape by alternately growing and withdrawing its photosensitive branches so that its body area can be maximized and the risk of being illuminated can be minimized. In this way, the organism succeeded in finding the optimal solution to the four-city traveling salesman problem with a high probability. However, it remains unclear how the organism collects, stores, and compares information on light stimuli using the oscillatory dynamics. To study these points, we formulate an ordinary differential equation model of the amoeba-based neurocomputer, considering the organism as a network of oscillators that compete for a fixed amount of intracellular resource. The model, called the “Resource-Competing Oscillator Network (RCON) model,” reproduces well the organism’s experimentally observed behavior, as it generates a number of spatiotemporal oscillation modes by keeping the total sum of the resource constant. Designing the feedback rule properly, the RCON model comes to face a problem of optimizing the allocation of the resource to its nodes. In the problem-solving process, “greedy” nodes having the highest competitiveness are supposed to take more resource out of other nodes. However, the resource allocation pattern attained by the greedy nodes cannot always achieve a “socially optimal” state in terms of the public cost. We prepare four test problems including a tricky one in which the greedy pattern becomes “socially unfavorable” and investigate how the RCON model copes with these problems. Comparing problem-solving performances of the oscillation modes, we show that there exist some modes often attain socially favorable patterns without being trapped in the greedy one.     

Unsupervised WSD by Finding the Predominant Sense Using Context as a Dynamic Thesaurus

We present and analyze an unsupervised method for Word Sense Disambiguation (WSD). Our work is based on the method presented by McCarthy et al. in 2004 for finding the predominant sense of each word in the entire corpus. Their maximization algorithm allows weighted terms (similar words) from a distributional thesaurus to accumulate a score for each ambiguous word sense, i.e., the sense with the highest score is chosen based on votes from a weighted list of terms related to the ambiguous word. This list is obtained using the distributional similarity method proposed by Lin Dekang to obtain a thesaurus. In the method of McCarthy et al., every occurrence of the ambiguous word uses the same thesaurus, regardless of the context where the ambiguous word occurs. Our method accounts for the context of a word when determining the sense of an ambiguous word by building the list of distributed similar words based on the syntactic context of the ambiguous word. We obtain a top precision of 77.54% of accuracy versus 67.10% of the original method tested on SemCor. We also analyze the effect of the number of weighted terms in the tasks of finding the Most Frecuent Sense (MFS) and WSD, and experiment with several corpora for building the Word Space Model.     

High-performance cone beam reconstruction using CUDA compatible GPUs

Compute unified device architecture (CUDA) is a software development platform that allows us to run C-like programs on the nVIDIA graphics processing unit (GPU). This paper presents an acceleration method for cone beam reconstruction using CUDA compatible GPUs. The proposed method accelerates the Feldkamp, Davis, and Kress (FDK) algorithm using three techniques: (1) off-chip memory access reduction for saving the memory bandwidth; (2) loop unrolling for hiding the memory latency; and (3) multithreading for exploiting multiple GPUs. We describe how these techniques can be incorporated into the reconstruction code. We also show an analytical model to understand the reconstruction performance on multi-GPU environments. Experimental results show that the proposed method runs at 83% of the theoretical memory bandwidth, achieving a throughput of 64.3 projections per second (pps) for reconstruction of 512³-voxel volume from 360 512²-pixel projections. This performance is 41% higher than the previous CUDA-based method and is 24 times faster than a CPU-based method optimized by vector intrinsics. Some detailed analyses are also presented to understand how effectively the acceleration techniques increase the reconstruction performance of a naive method. We also demonstrate out-of-core reconstruction for large-scale datasets, up to 1024³-voxel volume.     

Visual simulation of mixed-motion avalanches with interactions between snow layers

In the field of computer graphics, simulation of fluids, including avalanches, is an important research topic. In this paper, we propose a method to simulate a kind of avalanche, mixed-motion avalanche, which is usually large and travels down the slope fast, often resulting in impressive visual effects. The mixed-motion avalanche consists of snow smokes and liquefied snow which form an upper suspension layer and a lower dense-flow layer, respectively. The mixed-motion avalanche travels down the surface of the snow-covered mountain, which is called accumulated snow layer. We simulate a mixed-motion avalanche taking into account these three snow layers. We simulate the suspension layer using a grid-based approach, the dense-flow and accumulated snow layer using a particle-based approach. An important contribution of our method is an interaction model between these snow layers that enables us to obtain the characteristic motions of avalanches, such as the generation of the snow smoke from the head of the avalanche.     

An Algorithm for Minimum Cost Arc-Connectivity Orientations

Given a 2k-edge-connected undirected graph, we consider to find a minimum cost orientation that yields a k-arc-connected directed graph. This minimum cost k-arc-connected orientation problem is a special case of the submodular flow problem. Frank (1982) devised a combinatorial algorithm that solves the problem in O(k ² n ³ m) time, where n and m are the numbers of vertices and edges, respectively. Gabow (1995) improved Frank’s algorithm to run in O(kn ² m) time by introducing a new sophisticated data structure. We describe an algorithm that runs in O(k ³ n ³+kn ² m) time without using sophisticated data structures. In addition, we present an application of the algorithm to find a shortest dijoin in O(n ² m) time, which matches the current best bound.     

Discharge properties and chemical stability of SrZrO films

Abstract— MgO thin film is currently used as a surface protective layer for dielectric materials because MgO has a high resistance during ion sputtering and exhibits effective secondary electron emission. The secondary‐electron‐emission coefficient γ of MgO is high for Ne ions; however, it is low for Xe ions. The Xe content of the discharge gas of PDPs needs to be raised in order to increase the luminous efficiency. Thus, the development of high‐γ materials replacing MgO is required. The discharge properties and chemical surface stability of SrO containing Zr (SrZrO) as the candidate high‐γ protective layer for noble PDPs have been characterized. SrZrO films have superior chemical stability, especially the resistance to carbonation because of the existence of a few adsorption sites due to their amorphous structure. The firing voltage is 60 V lower than that of MgO films for a discharge gas of Ne/Xe = 85/15 at 60 kPa.     

Deformation characteristics of ultra-thin liquid film considering temperature and film thickness dependence of surface tension

Thermocapillary deformations of an ultra-thin liquid film caused by temperature distribution were three-dimensionally analyzed using the unsteady and linearized long wave equation considering the temperature and film thickness dependence of surface tension. The temperature and film thickness dependence equation for the surface tension of a liquid was firstly established. The temperature dependence of the surface tension was obtained experimentally using a surface tensiometer and the film thickness dependence was obtained theoretically from the corrected van der Waals pressure equation for a symmetric multilayer system. Time evolutions of depression and groove of the ultra-thin liquid film caused by local heating were obtained quantitatively.     

A robust automatic crack detection method from noisy concrete surfaces

In maintenance of concrete structures, crack detection is important for the inspection and diagnosis of concrete structures. However, it is difficult to detect cracks automatically. In this paper, we propose a robust automatic crack-detection method from noisy concrete surface images. The proposed method includes two preprocessing steps and two detection steps. The first preprocessing step is a subtraction process using the median filter to remove slight variations like shadings from concrete surface images; only an original image is used in the preprocessing. In the second preprocessing step, a multi-scale line filter with the Hessian matrix is used both to emphasize cracks against blebs or stains and to adapt the width variation of cracks. After the preprocessing, probabilistic relaxation is used to detect cracks coarsely and to prevent noises. It is unnecessary to optimize any parameters in probabilistic relaxation. Finally, using the results from the relaxation process, a locally adaptive thresholding is performed to detect cracks more finely. We evaluate robustness and accuracy of the proposed method quantitatively using 60 actual noisy concrete surface images.