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1.Arsenic mitigation in paddy soils by using microbial fuel cells

Author:Gustave, W;Yuan, ZF;Sekar, R;Chang, HC;Zhang, J;Wells, M;Ren, YX;Chen, Z


Abstract:Arsenic (As) behavior in paddy soils couples with the redox process of iron (Fe) minerals. When soil is flooded, Fe oxides are transformed to soluble ferrous ions by accepting the electrons from Fe reducers. This process can significantly affect the fate of As in paddy fields. In this study, we show a novel technique to manipulate the Fe redox processes in paddy soils by deploying soil microbial fuel cells (sMFC). The results showed that the sMFC bioanode can significantly decrease the release of Fe and As into soil porewater. Iron and As contents around sMFC anode were 65.0%% and 47.0%% of the control respectively at day 50. The observed phenomenon would be explained by a competition for organic substrate between sMFC bioanode and the iron- and arsenic-reducing bacteria in the soils. In the vicinity of bioanode, organic matter removal efficiencies were 10.3%% and 14.0%% higher than the control for lost on ignition carbon and total organic carbon respectively. Sequencing of the 16S rRNA genes suggested that the influence of bioanodes on bulk soil bacterial community structure was minimal. Moreover, during the experiment a maximum current and power density of 0.31 mA and 12.0 mWm(-2) were obtained, respectively. This study shows a novel way to limit the release of Fe and As in soils porewater and simultaneously generate electricity. (C) 2018 Elsevier Ltd. All rights reserved.

2.Expanding roles for immune adaptors in regulation of pro-inflammatory signaling in macrophages

Author:Yang, N


3.Analysis of a new dimension-wise splitting iteration with selective relaxation for saddle point problems

Author:Gander, MJ;Niu, Q;Xu, YX


Abstract:We propose a new dimension-wise splitting with selective relaxation (DSSR) method for saddle point systems arising from the discretization of the incompressible Navier-Stokes equations. Using Fourier analysis, we determine the optimal choice of the relaxation parameter that leads to the best performance of the iterative method for the Stokes and the steady Oseen equations. We also explore numerically the influence of boundary conditions on the optimal choice of the parameter, the use of inner and outer iterations, and the performance for a lid driven cavity flow.

4.Cell-type-specific neuroanatomy of cliques of autism-related genes in the mouse brain

Author:Grange, P;Menashe, I;Hawrylycz, M


Abstract:Two cliques of genes identified computationally for their high co-expression in the mouse brain according to the Allen Brain Atlas, and for their enrichment in genes related to autism spectrum disorder (ASD), have recently been shown to be highly co-expressed in the cerebellar cortex, compared to what could be expected by chance. Moreover, the expression of these cliques of genes is not homogeneous across the cerebellar cortex, and it has been noted that their expression pattern seems to highlight the granular layer. However, this observation was only made by eye, and recent advances in computational neuroanatomy allow to rank cell types in the mouse brain (characterized by their transcriptome profiles) according to the similarity between their spatial density profiles and the spatial expression profiles of the cliques. We establish by Monte Carlo simulation that with probability at least 99%%, the expression profiles of the two cliques are more similar to the density profile of granule cells than 99%% of the expression of cliques containing the same number of genes (Purkinje cells also score above 99%% in one of the cliques). Thresholding the expression profiles shows that the signal is more intense in the granular layer. Finally, we work out pairs of cell types whose combined expression profiles are more similar to the expression profiles of the cliques than any single cell type. These pairs predominantly consist of one cortical pyramidal cell and one cerebellar cell (which can be either a granule cell or a Purkinje cell).

5.Net load-displacement estimation in soil-nail pullout tests

Author:Seo, HJ;Pelecanos, L;Kwon, YS;Lee, IM


Abstract:Soil-nails are used to stabilise a soil mass by exploiting the resistance generated by the skin friction between the ground and grout and the tensile stiffness of the reinforcing material. A load-displacement curve is obtained from in situ pullout load tests performed by considering the elastic shear modulus and ultimate skin friction capacity between the soil and grout. This study determines the shear behaviour between the soils and grout analytically, especially the soil-dilation effect during shearing that is one of the main factors affecting the ultimate skin friction, even though this estimation is rather cumbersome. Many studies assume a full bond between the grout and the steel reinforcing bar, thus neglecting their relative displacement. In this study, the net load-displacement between the ground and grout is obtained by subtracting the nail elongation from the load-displacement of the pullout tests when estimating the shear displacement. Numerous field pullout tests are performed in this study under various ground conditions and through various construction methods. The dilatancy angles are estimated dependent on the soil type by comparing the net load-displacement curve obtained in the field with that obtained theoretically.

6.Discontinuous finite volume element method for a coupled Navier-Stokes-Cahn-Hilliard phase field model

Author:Li, R;Gao, YL;Chen, J;Zhang, L;He, XM;Chen, ZX


Abstract:In this paper, we propose a discontinuous finite volume element method to solve a phase field model for two immiscible incompressible fluids. In this finite volume element scheme, discontinuous linear finite element basis functions are used to approximate the velocity, phase function, and chemical potential while piecewise constants are used to approximate the pressure. This numerical method is efficient, optimally convergent, conserving the mass, convenient to implement, flexible for mesh refinement, and easy to handle complex geometries with different types of boundary conditions. We rigorously prove the mass conservation property and the discrete energy dissipation for the proposed fully discrete discontinuous finite volume element scheme. Using numerical tests, we verify the accuracy, confirm the mass conservation and the energy law, test the influence of surface tension and small density variations, and simulate the driven cavity, the Rayleigh-Taylor instability.

7.The Transient Receptor Potential Ankyrin Type 1 Plays a Critical Role in Cortical Spreading Depression

Author:Jiang, LW;Wang, Y;Xu, YW;Ma, DQ;Wang, MY


Abstract:The transient receptor potential ankyrin type-1 (TRPA1) channels have been proposed as a potential target for migraine therapy. Yet the role of cortical TRPA1 channels in migraine mechanism has not been fully understood. Cortical spreading depression (CSD) is known as an underlying cause of migraine aura. The aim of this study is to investigate if cortical TRPA1 activity is required for CSD genesis and propagation. A mouse brain slice CSD model with intrinsic optical imaging was applied for TRPA1 signaling pharmacology. The results showed that the TRPA1 agonist, umbellulone, facilitated the propagation of submaximal CSD. Correspondingly, an anti-TRPA1 antibody and two selective TRPA1 antagonists, A967079 and HC-030031, prolonged the CSD latency and reduced magnitude, indicating a reduced cortical susceptibility to CSD under TRPA1 deactivation. Furthermore, the TRPA1 agonist, allyl-isothiocyanate (AITC), reversed the suppression of CSD by HC-030031, but not by A967079. Interestingly, the inhibitory action of A967079 on CSD was reversed by exogenous calcitonin-gene-related peptide (CGRP). Consistent to TRPA1 deactivation, the prolonged CSD latency was observed by an anti-CGRP antibody in the mouse brain slice, which was reversed by exogenous CGRP. We conclude that cortical TRPA1 is critical in regulating cortical susceptibility to CSD, which involves CGRP. The data strongly suggest that deactivation of TRPA1 channels and blockade of CGRP would have therapeutic benefits in preventing migraine with aura. (C) 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

8.RingText: Dwell-Free and Hands-Free Text Entry for Mobile Head-Mounted Displays Using Head Motions (vol 25, pg 1991, 2019)

Author:Xu, WG;Liang, HN;Zhao, YX;Zhang, TY;Yu, DF;Monteiro, D


Abstract:© 2019 IEEE. YONG Yue was also a contributing author for this article [1] and, unfortunately, his name was inadvertently not included. He is with the Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, China. The authors of the paper should have been: Wenge Xu, Hai-Ning Liang, Yuxuan Zhao, Tianyu Zhang, Difeng Yu, Diego Monteiro, and Yong Yue.

9.Functionalization of diketopyrrolopyrrole with dendritic oligothiophenes: Synthesis, photophysical properties, and application in solar cells

Author:Gao, W;Wang, JK;Lin, Y;Luo, Q;Ma, YC;Dou, JY;Tan, HW;Ma, CQ;Cui, Z


Abstract:Diketopyrrolopyrrole (DPP) is one of the most widely used organic dye moieties in conjugated organic semiconductors for use in organic electronics. To enrich the library of DPP based organic semiconductors and to further understand the structure-property-performance relationship of this type materials, in this paper, the diketopyrrolopyrrole moiety was functionalized with three-dimensional (3D) pi-conjugated dendritic oligothiophenes (DOTs), and four diketopyrrolopyrrole compounds decorated with dendritic oligothiophenes (DOT-c-DPPs) were obtained and characterized in detailed. Results show that all these four compounds are monodisperse with defined molecular structure. Spectroscopy and cyclic voltammetry measurement results showed that the introduction of dendritic oligothiophene unit on the DPP unit improves the light absorption ability over 350-500 nm, and decreases the optical band gap slightly, which are in good accordance with theoretical calculation results that the frontier molecular orbitals are mainly located at the central DPP unit. Solution processed organic solar cells using these DOT-c-DPPs as the electron donor were fabricated and tested. Improved device performance was found for the bigger molecule for its less aggregation tendency. (C) 2017 Elsevier B.V. All rights reserved.

10.Sentiment analysis through recurrent variants latterly on convolutional neural network of Twitter

Author:Abid, F;Alam, M;Yasir, M;Li, C


Abstract:Sentiment analysis has been a hot area in the exploration field of language understanding, however, neural networks used in it are even lacking. Presently, the greater part of the work is proceeding on recognizing sentiments by concentrating on syntax and vocabulary. In addition, the task identified with natural language processing and for computing the exceptional and remarkable outcomes Recurrent neural networks (RNNs) and Convolutional neural networks (CNNs) have been utilized. Keeping in mind the end goal to capture the long-term dependencies CNNs, need to rely on assembling multiple layers. In this Paper for the improvement in understanding the sentiments, we constructed a joint architecture which places of RNN at first for capturing long-term dependencies with CNNs using global average pooling layer while on top a word embedding method using GloVe procured by unsupervised learning in the light of substantial twitter corpora to deal with this problem. Experimentations exhibit better execution when it is compared with the baseline model on the twitter's corpora which tends to perform dependable results for the analysis of sentiment benchmarks by achieving 90.59%% on Stanford Twitter Sentiment Corpus, 89.46%% on Sentiment Strength Twitter Data and 88.72%% on Health Care Reform Dataset respectively. Empirically, our work turned to be an efficient architecture with slight hyperparameter tuning which capable us to reduce the number of parameters with higher performance and not merely relying on convolutional multiple layers by constructing the RNN layer followed by convolutional layer to seizure long-term dependencies. (C) 2019 Elsevier B.V. All rights reserved.

11.Hybridized Nanogenerators for Multifunctional Self-Powered Sensing: Principles, Prototypes, and Perspectives

Author:Zhang, TT;Wen, Z;Liu, YN;Zhang, ZY;Xie, YL;Sun, XH


Abstract:Sensors are a key component of the Internet of Things (IoTs) to collect information of environments or objects. Considering the tremendous number and complex working conditions of sensors, multifunction and self-powered feathers are two basic requirements. Nanogenerators are a kind of devices based on the triboelectric, piezoelectric, or pyroelectric effects to harvest ambient energy and then converting to electricity. The hybridized nanogenerators that combined multiple effects in one device have great potential in multifunctional self-powered sensors because of the unique superiority such as generating electrical signals directly, responding to diverse stimuli, etc. This review aims at introducing the latest advancements of hybridized nanogenerators for multifunctional self-powered sensing. Firstly, the principles and sensor prototypes based on TENG are summarized. To avoid signal interference and energy insufficiently, the multi-functional self-powered sensors based on hybridized nanogenerators are reviewed. At last, the challenges and future development of multifunctional selfpowered sensors have prospected.

12.Attention-based Recurrent Neural Network for Traffic Flow Prediction

Author:Chen, Q;Wang, W;Huang, X;Liang, HN


Abstract:Traffic flow prediction is an important while complex problem in transportation modeling and management. Many uncertain, non-linear and stochastic factors could have large influence on the prediction performance. With the recent development in deep learning, researchers have applied deep neural networks for the traffic flow prediction problem and achieved promising results. However, existing studies still have some issues unaddressed, e.g., the models only predict the traffic flow at next time step while travelers may need a sequence of predictions to make better, long-term decisions; temporal factors are (e.g., day of the week, national holiday) usually not well considered during prediction. To address these limitations, this paper proposed an attention-based recurrent neural network architecture for multi-step traffic flow prediction. Experimental results demonstrate that the proposed method has superior performance compared to the existing models. We also show how the method can be used to develop traffic anomaly detection systems.

13.A Novel Deep Density Model for Unsupervised Learning

Author:Yang, X;Huang, KZ;Zhang, R;Goulermas, JY


Abstract:Density models are fundamental in machine learning and have received a widespread application in practical cognitive modeling tasks and learning problems. In this work, we introduce a novel deep density model, referred to as deep mixtures of factor analyzers with common loadings (DMCFA), with an efficient greedy layer-wise unsupervised learning algorithm. The model employs a mixture of factor analyzers sharing common component loadings in each layer. The common loadings can be considered to be a feature selection or reduction matrix which makes this new model more physically meaningful. Importantly, sharing common components is capable of reducing both the number of free parameters and computation complexity remarkably. Consequently, DMCFA makes inference and learning rely on a dramatically more succinct model and avoids sacrificing its flexibility in estimating the data density by utilizing Gaussian distributions as the priors. Our model is evaluated on five real datasets and compared to three other competitive models including mixtures of factor analyzers (MFA), MFA with common loadings (MCFA), deep mixtures of factor analyzers (DMFA), and their collapsed counterparts. The results demonstrate the superiority of the proposed model in the tasks of density estimation, clustering, and generation.

14.Quantification of Microbial Source Tracking and Pathogenic Bacterial Markers in Water and Sediments of Tiaoxi River (Taihu Watershed)

Author:Vadde, KK;McCarthy, AJ;Rong, R;Sekar, R


Abstract:Taihu Lake is one of the largest freshwater lakes in China, serving as an important source of drinking water; >60%% of source water to this lake is provided by the Tiaoxi River. This river faces serious fecal contamination issues, and therefore, a comprehensive investigation to identify the sources of fecal contamination was carried out and is presented here. The performance of existing universal (BacUni and GenBac), human (HF183-Taqman, HF183-SYBR, BacHum, and Hum2), swine (Pig-2-Bac), ruminant (BacCow), and avian (AV4143 and GFD) associated microbial source tracking (MST) markers was evaluated prior to their application in this region. The specificity and sensitivity results indicated that BacUni, HF183-TaqMan, Pig-2-Bac, and GFD assays are the most suitable in identifying human and animal fecal contamination. Therefore, these markers along with marker genes specific to selected bacterial pathogens were quantified in water and sediment samples of the Tiaoxi River, collected from 15 locations over three seasons during 2014 and 2015. Total/universal Bacteroidales markers were detected in all water and sediment samples (mean concentration 6.22 log(10) gene copies/100 ml and 6.11 log(10) gene copies/gram, respectively), however, the detection of host-associated MST markers varied. Human and avian markers were the most frequently detected in water samples (97 and 89%%, respectively), whereas in sediment samples, only human-associated markers were detected more often (86%%) than swine (64%%) and avian (8.8%%) markers. The results indicate that several locations in the Tiaoxi River are heavily polluted by fecal contamination and this correlated well with land use patterns. Among the five bacterial pathogens tested, Shigella spp. and Campylobacter jejuni were the most frequently detected pathogens in water (60%% and 62%%, respectively) and sediment samples (91%% and 53%%, respectively). Shiga toxin-producing Escherichia coli (STEC) and pathogenic Leptospira spp. were less frequently detected in water samples (55%% and 33%%, respectively) and sediment samples (51%% and 13%%, respectively), whereas E. coli O157:H7 was only detected in sediment samples (11%%). Overall, the higher prevalence and concentrations of Campylobacter jejuni, Shigella spp., and STEC, along with the MST marker detection at a number of locations in the Tiaoxi River, indicates poor water quality and a significant human health risk associated with this watercourse.


Author:Chen, AY;Li, JP;Chen, YQ;Zhou, DX


Abstract:We consider the uniqueness and extinction properties of the interacting branching collision process (IBCP), which consists of two strongly interacting components: an ordinary Markov branching process and a collision branching process. We establish that there is a unique IBCP, and derive necessary and sufficient conditions for it to be nonexplosive that are easily checked. Explicit expressions are obtained for the extinction probabilities for both regular and irregular cases. The associated expected hitting times are also considered. Examples are provided to illustrate our results.


Author:Zhang, Q;Ye, SK


Abstract:A compact polyhedron X is said to have the Bounded Index Property for Homotopy Equivalences (BIPHE) if there is a finite bound B such that for any homotopy equivalence f : X -> X and any fixed point class F of f, the index vertical bar ind(f, F)vertical bar <= B. In this note, we consider the product of compact polyhedra, and give some sufficient conditions for it to have BIPHE. Moreover, we show that products of closed Riemannian manifolds with negative sectional curvature, in particular hyperbolic manifolds, have BIPHE, which gives an affirmative answer to a special case of a question asked by Boju Jiang.

17.Robust object detection with real-time fusion of multiview foreground silhouettes

Author:Xu, M;Ren, J;Chen, DY;Smith, JS;Liu, ZC;Jia, TY


Abstract:An object detection algorithm using multiple cameras is proposed. The information fusion is based on homography mapping of the foreground information from multiple cameras and for multiple parallel planes. Unlike the most recent algorithms, which transmit and project foreground bitmaps, it approximates each foreground silhouette with a polygon and projects the polygon vertices only. In addition, an alternative approach to estimating the homographies for multiple parallel planes is presented. It is based on the observed pedestrians and does not resort to vanishing-point estimation. The ability of this algorithm to remove cast shadows in moving object detection is also investigated. The results on open video datasets are presented as well. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.4.047202]

18.Cellular automata in architectural design: From generic systems to specific design tools

Author:Herr, CM;Ford, RC


Abstract:In this paper we examine the adaptations cellular automata (CA) are typically subjected to when they are applied to architectural designing. We argue that, despite a number of earlier studies that portrayed CA as generic generative design tools, the transition from CA as generic systems to specific design tools for the purposes of design is not yet well understood. To describe this transition, we first examine CA adaptations in a number of previous studies relating CA to architectural design. We then analyze an applied design case study in detail and trace similarities between findings made in the literature review to findings made in the case study. We conclude with a summary of challenges and opportunities met by architectural designers employing and developing CA as design tools. (C) 2016 Elsevier B.V. All rights reserved.

19.Geometrical invariability of transformation between a time series and a complex network

Author:Zhao, Y;Weng, TF;Ye, SK

Source:PHYSICAL REVIEW E,2014,Vol.90

Abstract:We present a dynamically equivalent transformation between time series and complex networks based on coarse geometry theory. In terms of quasi-isometric maps, we characterize how the underlying geometrical characters of complex systems are preserved during transformations. Fractal dimensions are shown to be the same for time series (or complex network) and its transformed counterpart. Results from the Rossler system, fractional Brownian motion, synthetic networks, and real networks support our findings. This work gives theoretical evidences for an equivalent transformation between time series and networks.

20.Photoluminescence and Raman mapping characterization of WS2 monolayers prepared using top-down and bottom-up methods

Author:Wang, XH;Ning, JQ;Zheng, CC;Zhu, BR;Xie, L;Wu, HS;Xu, SJ


Abstract:Two kinds of tungsten disulfide (WS2) monolayers, respectively prepared using top-down and bottom-up approaches, were studied with Raman and photoluminescence (PL) mapping techniques. By mapping the intensities of the two characterized phonon modes of WS2, the monolayer region can be quickly selected. Such selection by mapping the intensities is more conclusive than by comparing the small shift in phonon peak position. Also, PL mapping yields more information regarding the uniformity and quality of the monolayers than does Raman mapping. We also show that the focused laser may cause substantial damage to the crystal lattice of monolayers for long-duration mappings.
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