Miracle-dz/UniFAR-FTUs huggingface dataset:
Master-element vector irradiance for large tessellated models

We propose a new global light simulation method for diffuse (or moderately glossy) scenes comprising highly tesselated models with simple topology (e.g., scanned meshes). By using the topological coherence of the surface, we show how to extend a classic Finite Element method called the Master Element: We generalize this method to efficiently handle tessellated models by using mesh parameterization and mesh extrapolation techniques. In addition, we propose a high-order and hierarchical extension of the Master Element method. Our method computes a compact representation of vector irradiance, represented by high-order wavelet bases. For totally diffuse scenes, the so-computed vector irradiance maps can be transformed into light maps. For moderatly glossy scenes, approximated view-dependent lighting can be computed and displayed in real-time by the GPU from the vector irradiance maps. Using our methods, view-dependent solutions for scenes with over one million polygons are computed in minutes and displayed in real time. As with clustering methods, the time complexity of the method is independent on the number of polygons. By efficiently capturing the lighting signal at a suitable scale, the method is made independent of the geometric discretization and solely depends on the lighting complexity. We demonstrate our method in various settings, with both sharp and soft shadows accurately represented by our hierarchical function basis.
Performance comparison of training sequences for power amplifier linearization systems

The suitable design of a calibration signal for power amplifier (PA) behavioral modeling and digital predistortion design is addressed in this work. The proposed alternatives are a manageable triangular chirp-like waveform or a multisine-type sequence that resembles as much as possible to the transmitted signal. In this research, multisines are generated accordingly to the statistical characteristics of the transmitted signal, whereas chirp sequence is defined by the system transmission parameters. Laboratory tests show that, in spite of the remarkable existing similarities between the transmitted signal and the multisines, the chirp sequence accomplishes the same enhancement in nonlinear distortion reduction than the multisines (up to 16 dB) while reducing the training time needed for computing the predistorter coefficients.
A reconfigurable FTL (flash translation layer) architecture for NAND flash-based applications

In this article, a novel FTL (flash translation layer) architecture is proposed for NAND flash-based applications such as MP3 players, DSCs (digital still cameras) and SSDs (solid-state drives). Although the basic function of an FTL is to translate a logical sector address to a physical sector address in flash memory, efficient algorithms of an FTL have a significant impact on performance as well as the lifetime. After the dominant parameters that affect the performance and endurance are categorized, the design space of the FTL architecture is explored based on a diverse workload analysis. With the proposed FTL architectural framework, it is possible to decide which configuration of FTL mapping parameters yields the best performance, depending on the differing characteristics of various NAND flash-based applications.
Anticipatory translation model adaptation for bilingual conversations

Conversational spoken language translation (CSLT) systems facilitate bilingual conversations in which the two participants speak different languages. Bilingual conversations provide additional contextual information that can be used to improve the underlying machine translation system. In this paper, we describe a novel translation model adaptation method that anticipates a participant’s response in the target language, based on his counterpart’s prior turn in the source language. Our proposed strategy uses the source language utterance to perform cross-language retrieval on a large corpus of bilingual conversations in order to obtain a set of potentially relevant target responses. The responses retrieved are used to bias translation choices towards anticipated responses. On an Iraqi-to-English CSLT task, our method achieves a significant improvement over the baseline system in terms of BLEU, TER and METEOR metrics.
Photoconducting response on bending of individual ZnO nanowires

The bending effect of individual zinc oxide (ZnO) nanowires on photoconducting behavior has been investigated by an in situtransmission electron microscopy (TEM) method. By increasing the nanowire bending, the photocurrent of ZnO nanowire under ultraviolet illumination drops dramatically and the photoresponse time becomes much shorter. A possible mechanism has been proposed and discussed. The improved photo response performance by bending ZnO nanowires could be of significance for their optoelectronics and sensor applications.
Utility Based Scheduling for Downlink OFDMA/SDMA Systems with Multimedia Traffic

This paper considers the scheduling and resource allocation problem for downlink OFDMA/SDMA systems with the objective to maximize the system capacity and guarantee each user's QoS requirements. A mathematical formulation of the optimization problem is established based on utility function, and then the detailed proof of the equivalent optimal policy is given. The developed scheduling policy can decouple the complex joint space-time-frequency resource allocation problem into simple single-subcarrier optimization problem. Moreover, a low-complexity algorithm according to the spatial separability is proposed for practical implementation. Simulation results show that the proposed algorithm is able to better attain the tradeoff between system throughput and QoS requirement to employ different utility functions.
Recent Improvements on Error Detection for Automatic Speech Recognition

Automatic speech recognition(ASR) offers the ability to access the semantic content present in spoken language within audio and video documents. While acoustic models based on deep neural networks have recently significantly improved the performances of ASR systems, automatic transcriptions still contain errors. Errors perturb the exploitation of these ASR outputs by introducing noise to the text. To reduce this noise, it is possible to apply an ASR error detection in order to remove recognized words labelled as errors. This paper presents an approach that reaches very good results, better than previous state-of-the-art approaches. This work is based on a neural approach, and more especially on a study targeted to acoustic and linguistic word embeddings, that are representations of words in a continuous space. In comparison to the previous state-of-the-art approach which were based on Conditional Random Fields, our approach reduces the classification error rate by 7.2%.
Extractability and leachability of Pb in a shooting range soil amended with poultry litter ash: Investigations for immobilization potentials

The use of agricultural and industrial by-products as a metal immobilizing agent is cost effective for remediation of vast amounts of contaminated soil. The objective of this study was to assess the effect of an amendment (poultry litter ash) on immobilizing Pb in a shooting range soil. For a contaminant transport study, the soil admixed with amendment at the rate of 0 (control), 0.5, 1, 3 and 6%(w/w) was packed into soil columns and eluted solutions were collected through 40 pore volumes. The amendment application significantly reduced the concentrations of water-extractable and toxicity characteristic leaching procedure (TCLP)-extractable Pb by > 96% and > 97% of control, respectively. The contaminant transport study demonstrated that increasing amendment additions up to 3% decreased eluted Pb concentration below 0.5 mg L−1. The X-ray diffraction peaks indicative of chloropyromorphite were observed in the soil of the 1 and 3% treatments, but were less intense in the 0.5 and 6% treatments. The 6% treatment had an eluted Pb concentration of 13 mg L−1 at the first pore volume and significantly increased the total Pb elution (38 mg kg−1), mainly due to a drastic increase of organically complexed Pb as a result of soil alkalinization. These results suggest that poultry litter ash may have potential for immobilizing Pb in shooting range sites, if the soil pH is properly managed.
A Quantification of Aborting Effect for Real-Time Data Accesses

This paper proposes a generic framework to integrate real-time scheduling algorithms, conventional concurrency control algorithms, and aborting algorithms. The schedulability of a transaction system is improved by aborting excessive blocking from lower priority transactions. A schedulability analysis model is proposed to better manage the schedulability of a transaction system.
Inverse kinematics solution for robot manipulator based on adaptive MIMO neural network model optimized by hybrid differential evolution algorithm

In this paper, a new hybrid differential evolution algorithm is proposed, which combines the differential evolution (DE) algorithm and the back-propagation (BP) algorithm. This new hybrid algorithm is used to train an adaptive MIMO neural network (or AMNN) model for identifying the inverse kinematics of the industrial robot manipulator. Simulation results prove that the proposed identification process of the new hybrid algorithm performs faster convergence and better precision than the conventional back-propagation algorithm or the solely differential evolution algorithm. Consequently, the inverse kinematics of the industrial robot manipulator identification based on the AMNM achieves outstanding performance.
Generalized Golomb Codes and Adaptive Coding of Wavelet-Transformed Image Subbands

We describe a class of prefix-free codes for the nonnegative integers. We apply a family of codes in this class to the problem of runlength coding, specifically as part of an adaptive algorithm for compressing quantized subbands of wavelettransformed images. On test images, our adaptive coding algorithm is shown to give compression effectiveness comparable to the best performance achievable by an alternate algorithm that has been previously implemented.
Extracting rules from neural networks for time series prediction

A significant limitation of neural networks is that the representations they learn are usually incomprehensible to humans. There have been a number of research works that focused on how to extract rules from trained neural networks. Recently, Kamruzzaman et al. have developed an efficient algorithm, called REANN, for extracting rules from trained neural networks for classification problem. Given a trained network, REANN produces a set of rules that approximates the function represented by the network. In this paper, we investigate a case study in which we apply REANN to neural networks used in a more complex context: time series prediction. We devise some modifications to REANN to adapt this algorithm to the problem of time series prediction. Experimental results on three real world time series datasets demonstrate the effectiveness of the proposed approach in generating accurate rules from neural networks for time series prediction.
Tree Modeling with Real Tree-Parts Examples

We introduce a 3D tree modeling technique that utilizes examples of real trees to enhance tree creation with realistic structures and fine-level details. In contrast to previous works that use smooth generalized cylinders to represent tree branches, our method generates realistic looking tree models with complex branching geometry by employing an exemplar database consisting of real-life trees reconstructed from scanned data. These trees are sliced into representative parts (denoted as tree-cuts), representing trunk logs and branching structures. In the modeling process, tree-cuts are positioned in space in an intuitive manner, serving as efficient proxies that guide the creation of the complete tree. Allometry rules are taken into account to ensure reasonable relations between adjacent branches. Realism is further enhanced by automatically transferring geometric textures from our database onto tree branches as well as by guided growing of foliage. Our results demonstrate the complexity and variety of trees that can be generated with our method within few minutes. We carry a user study to test the effectiveness of our modeling technique.
Integration of X3D geospatial in a data driven web application

The Monterey Bay Aquarium Research Institute designed the Spatial Temporal Oceanographic Query System (STOQS) [MBARI 2014] to create new capabilities for scientists to gain insight from their data. STOQS employs open standards and is a 100% free and open source project. It includes a web-based graphical user interface where X3D Geospatial has been integrated to enable 3D geospatial data visualization.
Variable-bit-rate HDTV codec with ATM-cell-loss compensation

A variable-bit-rate coding algorithm based on motion-adaptive discrete cosine transform (DCT) is investigated for asynchronous transfer mode (ATM) environments in broadband integrated-services digital networks (B-ISDN). The algorithm effectively reduces the bit rate, in particular, for HDTV-picture sources with little motion. Adaptive two-layered coding, an ATM cell matrix for error correction, and a block interleave for error concealment are proposed to keep picture quality high by compensating for ATM cell loss. A feedforward control scheme for variable-length coding (VLC), a multimode quantization that restricts peak bit rate and average bit rate, is also proposed for traffic control. Experimental hardware is shown to reduce the coding bit rate for pictures of HDTV conference applications to peak bit rate of 65-Mb/s and an average bit rate of 10-20-Mb/s in ATM environments. >
First Functional and Mutational Analysis of Group 3 N-Acetylneuraminate Lyases from Lactobacillus antri and Lactobacillus sakei 23K

N-acetyl neuraminate lyases (NALs) catalyze the reversible aldol cleavage of N-acetyl neuraminic acid (Neu5Ac) to pyruvate and N-acetyl-D-mannosamine (ManNAc). Previous phylogenetic studies divided NALs into four different groups. Groups 1 and 2 have been well characterized at both kinetic and molecular levels, but no NAL from group 3 has been studied to date. In this work, a functional characterization of two group 3 members was performed using the recombinant NALs from Lactobacillus antri and Lactobacillus sakei 23K, revealing an optimal pH of between 6.0 and 7.0, low stability at basic pHs (>8.0), low optimal temperatures and, especially, low catalytic efficiency compared with their counterparts in group 1 and 2. The mutational analysis carried out showed that a plausible molecular reason for the low activity shown by Lactobacillus antri and Lactobacillus sakei 23k NALs compared with group 1 and 2 NALs could be the relatively small sugar-binding pocket they contain. A functional divergence analysis concluding that group 3 is more closely related to group 2 than to group 1.
Prevalence of Anxiety and Depression among Outpatients with Type 2 Diabetes in the Mexican Population

Background Depression and anxiety are common in diabetic patients; however, in recent years the frequency of these symptoms has markedly increased worldwide. Therefore, it is necessary to establish the frequency and factors associated with depression and anxiety, since they can be responsible for premature morbidity, mortality, risk of developing comorbidities, complications, suffering of patients, as well as escalation of costs. We studied the frequency of depression and anxiety in Mexican outpatients with type 2 diabetes and identified the risk factors for depression and anxiety. Methods and Findings We performed a study in 820 patients with type 2 diabetes. The prevalence of depression and anxiety was estimated using the Hamilton Depression Rating Scale and the Hamilton Anxiety Rating Scale, respectively. We calculated the proportions for depression and anxiety and, after adjusting for confounding variables, we performed multivariate analysis using multiple logistic regressions to evaluate the combined effect of the various factors associated with anxiety and depression among persons with type 2 diabetes. The rates for depression and anxiety were 48.27% (95% CI: 44.48–52.06) and 55.10% (95% CI: 51.44–58.93), respectively. Occupation and complications in diabetes were the factors associated with anxiety, whereas glucose level and complications in diabetes were associated with depression. Complications in diabetes was a factor common to depression and anxiety (p<0.0001; OR 1.79, 95% CI 1.29–2.4). Conclusions Our findings demonstrate that a large proportion of diabetic patients present depression and/or anxiety. We also identified a significant association between complications in diabetes with depression and anxiety. Interventions are necessary to hinder the appearance of complications in diabetes and in consequence prevent depression and anxiety.
Bayesian Analysis of Behaviors and Interactions for Situation Awareness in Transportation Systems

In large and crowded transportation sites such as ports, parking lots, or busy streets, the unsafe actions of a moving object (such as a pedestrian, a ship, or a car) may compromise the safety and security of the entire infrastructure. It follows that a full comprehension of the situations taking place in the area could significantly decrease the amount of work performed by human administrators and operators in charge of the zone, reducing also the impact of human errors. The idea behind this paper is to use trajectory data to analyze behaviors (atomic actions without any external influence) and interactions (actions inducted by the presence of another entity) of each target in the scene. Probabilistic techniques applied on a topological map of the scene allow tackling the problem in a robust way, handling the uncertainties arising in such environments. The system is tested in a real maritime scenario, where trajectory data of ships and vessels are used to determine normal and abnormal situations occurring in a canal.
Microgrid's operation-management containing distributed generation system

As an effective way of power industry's sustainable development, microgrid technology provides flexible and high efficiency platform for distributed generation and renewable energy generation's integration and utilization. And research of its operation-control and management-modes has been a key part. In this paper, on the basis of summarizing microgrid's development status all over the world, according to the differences and relations between microgrid and large power system, and considering two operating modes of microgrid, the key issues of microgrid operation-management are studied. It is pointed out that microgrid's stable operation and optimal management depend on advanced unit-level control technology and system-level integration control technology, among which the dispatch of distributed energy storage and design of dynamic microgrid should be paid more attention.
The role of endoplasmic reticulum‐related BiP/GRP78 in interferon gamma‐induced persistent Chlamydia pneumoniae infection

Direct interaction of Chlamydiae with the endoplasmic reticulum (ER) is essential in intracellular productive infection. However, little is known about the interplay between Chlamydiae and the ER under cellular stress conditions that are observed in interferon gamma (IFN‐γ) induced chlamydial persistent infection. ER stress responses are centrally regulated by the unfolded protein response (UPR) under the control of the ER chaperone BiP/GRP78 to maintain cellular homeostasis. In this study, we could show that the ER directly contacted with productive and IFN‐γ‐induced persistent inclusions of Chlamydia pneumoniae (Cpn). BiP/GRP78 induction was observed in the early phase but not in the late phase of IFN‐γ‐induced persistent infection. Enhanced BiP/GRP78 expression in the early phase of IFN‐γ‐induced persistent Cpn infection was accompanied by phosphorylation of the eukaryotic initiation factor‐2α (eIF2α) and down‐regulation of the vesicle‐associated membrane protein‐associated protein B. Loss of BiP/GRP78 function resulted in enhanced phosphorylation of eIF2α and increased host cell apoptosis. In contrast, enhanced BiP/GRP78 expression in IFN‐γ‐induced persistent Cpn infection attenuated phosphorylation of eIF2α upon an exogenous ER stress inducer. In conclusion, ER‐related BiP/GRP78 plays a key role to restore cells from stress conditions that are observed in the early phase of IFN‐γ‐induced persistent infection.
A pilot study of rimantadine for patients with chronic hepatitis C unresponsive to interferon therapy

OBJECTIVE:Therapeutic options are limited for chronic hepatitis C patients who have not responded to a course of interferon therapy. Recently, a 6-month course of amantadine was shown to result in a sustained virological response in chronic hepatitis C patients who were unresponsive to interferon therapy. The aim of this study was to evaluate the effect of rimantadine on chronic hepatitis C patients who had not responded to interferon therapy.METHODS:This was an open label trial involving 17 patients who were treated with rimantadine 100 mg b.i. d. for 6 months. Changes in serum aminotransferase activities and HCV-RNA levels were determined.RESULTS:Mean alanine aminotransferase activities and HCV RNA levels did not change significantly during therapy. HCV RNA remained detectable in all patients throughout therapy. Neurologic symptoms (headaches, nervousness, and dizziness) developed in 29% of patients. A total of 12% of patients required dose reduction after 12 wk of therapy because of dizziness.CONCLUSION:Rimantadine has no significant antiviral activity against HCV.
High Throughput Transcriptome Profiling of Lithium Stimulated Human Mesenchymal Stem Cells Reveals Priming towards Osteoblastic Lineage

Human mesenchymal stem cells (hMSCs) present in the bone marrow are the precursors of osteoblasts, chondrocytes and adipocytes, and hold tremendous potential for osteoregenerative therapy. However, achieving directed differentiation into osteoblasts has been a major concern. The use of lithium for enhancing osteogenic differentiation has been documented in animal models but its effect in humans is not clear. We, therefore, performed high throughput transcriptome analysis of lithium-treated hMSCs to identify altered gene expression and its relevance to osteogenic differentiation. Our results show suppression of proliferation and enhancement of alkaline phosphatase (ALP) activity upon lithium treatment of hMSCs under non-osteogenic conditions. Microarray profiling of lithium-stimulated hMSC revealed decreased expression of adipogenic genes (CEBPA, CMKLR1, HSD11B1) and genes involved in lipid biosynthesis. Interestingly, osteoclastogenic factors and immune responsive genes (IL7, IL8, CXCL1, CXCL12, CCL20) were also downregulated. Negative transcriptional regulators of the osteogenic program (TWIST1 and PBX1) were suppressed while genes involved in mineralization like CLEC3B and ATF4 were induced. Gene ontology analysis revealed enrichment of upregulated genes related to mesenchymal cell differentiation and signal transduction. Lithium priming led to enhanced collagen 1 synthesis and osteogenic induction of lithium pretreated MSCs resulted in enhanced expression of Runx2, ALP and bone sialoprotein. However, siRNA-mediated knockdown of RRAD, CLEC3B and ATF4 attenuated lithium-induced osteogenic priming, identifying a role for RRAD, a member of small GTP binding protein family, in osteoblast differentiation. In conclusion, our data highlight the transcriptome reprogramming potential of lithium resulting in higher propensity of lithium “primed” MSCs for osteoblastic differentiation.