Miracle-dz/UniFAR-FTUs huggingface dataset:
A Bayesian Treatment for Singular Value Decomposition

The traditional Singular Value Decomposition(SVD) based recommendation system suffers from two key challenges, namely, (1) the normal assumption is not an appropriate one since it is sensitive to outliers, which means the predicted mean would be changed a lot from the true value by the presence of outliers, and (2) the penalty terms added on the feature vectors are difficult to be settled in advance and thus an automatic configuring method for setting penalty terms is indispensable. To solve that, we propose a Bayesian based singular value decomposition (BSVD) and its related inference algorithms in this study. Specifically, we impose a T assumption on the ratings and the feature vectors, and propose a Gibbs sampler for the inference part. Besides giving a statistical explanation of the inference part and showing that this procedure is meaningful, we list the results of a series of experiments to further verify the performance of our proposed Bayesian SVD.
Vortex identification-applications in aerodynamics: a case study

An eigenvector method for vortex identification has been applied to recent numerical and experimental studies in external flow aerodynamics. It is shown to be an effective way to extract and visualize features such as vortex cores, spiral vortex breakdowns, vortex bursting, and vortex diffusion. Several problems are reported and illustrated. These include: disjointed line segments, detecting non-vortical flow features, and vortex core displacement. Future research and applications are discussed, such as using vortex cores to guide automatic grid refinement.
Avalanche: an environment for design space exploration and optimization of low-power embedded systems

We present Avalanche, a prototyping framework that addresses the issues of power estimation and optimization for mixed hardware and software embedded systems. Avalanche is based on a generic embedded system architecture consisting of embedded CPU, custom hardware, and a memory hierarchy. For system-level power estimation, given various system parameters like cache sizes, cache policies, and bus width, etc., Avalanche is able to rapidly evaluate/estimate power and performance and thus facilitate comprehensive design space explorations. For system-level power optimization, Avalanche offers different modes reflecting various design scenarios: if no hardware/software partitioning or only partial partitioning has been conducted, Avalanche guides the designer in finding power-aware hardware/software partitioning; when a system has already been partitioned, Avalanche can optimize system parameters such as cache and memory size; if system parameters and partitioning are given, Avalanche applies additional optimizations for power including source-to-source compiler transformations. Avalanche has been deployed during the design phase of real-world applications including an MPEG II encoder in a set-top box design. Extensive design space explorations in terms of power and performance could be conducted within several hours and various optimization techniques led to power reductions of up to 94% without performance losses and only a slight increases in total chip size (i.e., transistor count).
Mid-Adolescent Predictors of Adult Drinking Levels in Early Adulthood and Gender Differences: Longitudinal Analyses Based on the South Australian School Leavers Study

There is considerable public health interest in understanding what factors during adolescence predict longer-term drinking patterns in adulthood. The aim of this study was to examine gender differences in the age 15 social and psychological predictors of less healthy drinking patterns in early adulthood. The study investigates the relative importance of internalising problems, other risky health behaviours, and peer relationships after controlling for family background characteristics. A sample of 812 young people who provided complete alcohol consumption data from the age of 15 to 20 years (5 measurement points) were drawn from South Australian secondary schools and given a detailed survey concerning their psychological and social wellbeing. Respondents were classified into two groups based upon a percentile division: those who drank at levels consistently below NHMRC guidelines and those who consistently drank at higher levels. The results showed that poorer age 15 scores on measures of psychological wellbeing including scores on the GHQ-12, self-esteem, and life-satisfaction as well as engagement in health-related behaviours such as smoking or drug-taking were associated with higher drinking levels in early adulthood. The pattern of results was generally similar for both genders. Higher drinking levels were most strongly associated with smoking and marijuana use and poorer psychological wellbeing during adolescence.
The Patterns of Histone Modifications in the Vicinity of Transcription Factor Binding Sites in Human Lymphoblastoid Cell Lines

Transcription factor (TF) binding at specific DNA sequences is the fundamental step in transcriptional regulation and is highly dependent on the chromatin structure context, which may be affected by specific histone modifications and variants, known as histone marks. The lack of a global binding map for hundreds of TFs means that previous studies have focused mainly on histone marks at binding sites for several specific TFs. We therefore studied 11 histone marks around computationally-inferred and experimentally-determined TF binding sites (TFBSs), based on 164 and 34 TFs, respectively, in human lymphoblastoid cell lines. For H2A.Z, methylation of H3K4, and acetylation of H3K27 and H3K9, the mark patterns exhibited bimodal distributions and strong pairwise correlations in the 600-bp region around enriched TFBSs, suggesting that these marks mainly coexist within the two nucleosomes proximal to the TF sites. TFs competing with nucleosomes to access DNA at most binding sites, contributes to the bimodal distribution, which is a common feature of histone marks for TF binding. Mark H3K79me2 showed a unimodal distribution on one side of TFBSs and the signals extended up to 4000 bp, indicating a longer-distance pattern. Interestingly, H4K20me1, H3K27me3, H3K36me3 and H3K9me3, which were more diffuse and less enriched surrounding TFBSs, showed unimodal distributions around the enriched TFBSs, suggesting that some TFs may bind to nucleosomal DNA. Besides, asymmetrical distributions of H3K36me3 and H3K9me3 indicated that repressors might establish a repressive chromatin structure in one direction to repress gene expression. In conclusion, this study demonstrated the ranges of histone marks associated with TF binding, and the common features of these marks around the binding sites. These findings have epigenetic implications for future analysis of regulatory elements.
A context dependency relation pattern based algorithm for term similarity calculation

In this paper, we put forward a new term similarity algorithm which automatically extracts context patterns by sentence dependency analysis, and then calculates term similarity by mapping those patterns. The algorithm provides better way to extract term context patterns with stronger context expression ability than current algorithms. Meanwhile, the length of patterns is modest, which makes it convenient to be matched. We also evaluate the algorithm on the basis of gene engineering field experiment data set. Experiment result shows that the algorithm evidently improves the calculating performance.
A comparison of three electrode channels selection methods applied to SSVEP BCI

There has been increasing interest in using steady-state visual evoked potential (SSVEP) in brain-computer interface systems (BCIs). The electrode channels usually used in SSVEP classification are O1, O2 and Oz. However, optimal results of SSVEP recognition could not be obtained from the same electrode setting (O1, O2 and Oz), which was caused by subject variation. In this paper, three methods (Sequential floating forward selection (SFFS), discrete particle swarm optimization (DPSO) and F-score) were employed to select the optimal electrode channels. The electrode channels obtained by SFFS, DPSO and F-score were compared with traditional electrode channels (i.e., O1, O2 and Oz), which are usually used in SSVEP BCI. The results show that SFFS and DPSO can obtain higher classification accuracy than traditional approach. The results also show that SFFS is superior to DPSO in terms of calculating time, and F-score is not good compared to other two methods. Channel selection can not only reduce features for data analysis but also reduce the time for channel installation.
Object Recognition based on local feature trajectories

This paper presents a novel approach for extracting discriminative descriptions of 3-D objects using spatio-temporal information. In particular, local features are tracked in image sequences leading to local trajectories containing dynamic information. These trajectories are judged with respect to their quality and robustness and finally each of them is assigned a single local descriptor from a key-frame in order to obtain an object description. Extensive experiments compare this novel approach for selecting key-points to state-of-the-art view-based methods and show that it outperforms existing methods although the obtained representations are much sparser.
Design and analysis of an asynchronous checkpoint-based redundant multithreading architecture

Redundant multithreading (RMT) architectures detect errors by comparing the result of each instruction of the master and slave threads, which leads to large overhead caused by comparison and communication. To address this problem, several enhanced architectures were proposed. However, some of them have lower performance and lower error detection coverage. This paper presents an asynchronous checkpoint-based redundant multithreading (AC-RMT) architecture, in which two contexts saving rooms are set aside for each thread, one for detecting faults, the other for saving the last checkpoint used for fault restoration. In AC-RMT, enhanced load value queue (LVQ) and store buffer (STB) are setup for committing store results in time. It can avoid the waiting of master threads at checkpoints, so resources can be released timely. Experiments show that AC-RMT can reduce more number of comparisons than that of SRTR and boost performance efficiently with lower overhead than that of register value queue free recovery scheme (RVQ_F).
Slit2 Regulates the Dispersal of Oligodendrocyte Precursor Cells via Fyn/RhoA Signaling*

Background: Secreted by nervous system midline cells Slits regulate neurodevelopmental processes through binding to roundabout receptors (Robos). Results: Slit2 causes dispersal of oligodendrocyte precursor cells (OPCs) by inducing the association between Robo1 and Fyn. Conclusion: Robo1 interacts with Fyn to repel the migration of OPCs through RhoA activation. Significance: Learning how Slit/Robo signaling regulates OPC dispersal is crucial for understanding the distribution of OPCs during central nervous system development. Oligodendrocyte precursor cells (OPCs) are a unique type of glia that are responsible for the myelination of the central nervous system. OPC migration is important for myelin formation during central nervous system development and repair. However, the precise extracellular and intracellular mechanisms that regulate OPC migration remain elusive. Slits were reported to regulate neurodevelopmental processes such as migration, adhesion, axon guidance, and elongation through binding to roundabout receptors (Robos). However, the potential roles of Slits/Robos in oligodendrocytes remain unknown. In this study, Slit2 was found to be involved in regulating the dispersal of OPCs through the association between Robo1 and Fyn. Initially, we examined the expression of Robos in OPCs both in vitro and in vivo. Subsequently, the Boyden chamber assay showed that Slit2 could inhibit OPC migration. RoboN, a specific inhibitor of Robos, could significantly attenuate this effect. The effects were confirmed through the explant migration assay. Furthermore, treating OPCs with Slit2 protein deactivated Fyn and increased the level of activated RhoA-GTP. Finally, Fyn was found to form complexes with Robo1, but this association was decreased after Slit2 stimulation. Thus, we demonstrate for the first time that Slit2 regulates the dispersal of oligodendrocyte precursor cells through Fyn and RhoA signaling.
Enhanced Striatal Dopamine Transmission and Motor Performance with LRRK2 Overexpression in Mice Is Eliminated by Familial Parkinson's Disease Mutation G2019S

PARK8/LRRK2 (leucine-rich repeat kinase 2) was recently identified as a causative gene for autosomal dominant Parkinson's disease (PD), with LRRK2 mutation G2019S linked to the most frequent familial form of PD. Emerging in vitro evidence indicates that aberrant enzymatic activity of LRRK2 protein carrying this mutation can cause neurotoxicity. However, the physiological and pathophysiological functions of LRRK2 in vivo remain elusive. Here we characterize two bacterial artificial chromosome (BAC) transgenic mouse strains overexpressing LRRK2 wild-type (Wt) or mutant G2019S. Transgenic LRRK2-Wt mice had elevated striatal dopamine (DA) release with unaltered DA uptake or tissue content. Consistent with this result, LRRK2-Wt mice were hyperactive and showed enhanced performance in motor function tests. These results suggest a role for LRRK2 in striatal DA transmission and the consequent motor function. In contrast, LRRK2-G2019S mice showed an age-dependent decrease in striatal DA content, as well as decreased striatal DA release and uptake. Despite increased brain kinase activity, LRRK2-G2019S overexpression was not associated with loss of DAergic neurons in substantia nigra or degeneration of nigrostriatal terminals at 12 months. Our results thus reveal a pivotal role for LRRK2 in regulating striatal DA transmission and consequent control of motor function. The PD-associated mutation G2019S may exert pathogenic effects by impairing these functions of LRRK2. Our LRRK2 BAC transgenic mice, therefore, could provide a useful model for understanding early PD pathological events.
Minimum unit selection error training for HMM-based unit selection speech synthesis system

This paper presents a minimum unit selection error (MUSE) training method for HMM-based unit selection speech synthesis system, which selects the optimal phone-sized unit sequence from the speech database by maximizing the combined likelihood of a group of trained HMMs. Under MUSE criterion, the weights and distribution parameters of these HMMs are estimated to minimize the number of different units between the selected phone sequences and the natural phone sequences for the training sentences. The optimization is realized by discriminative training using generalized probabilistic descent (GPD) algorithm. Results of our experiment show that this proposed method is able to improve the performance of the baseline system where model weights are set manually and distribution parameters are trained under maximum likelihood criterion.
An FPGA-based distributed IP watermarking method

An FPGA (Field Programmable Gate Array) based distributed IP (Intellectual Property) watermarking method is presented for reusable IP protection. The signature is encrypted by the hash algorithm MD5, generating 128 bits digital digest. The digest is then transformed into watermark positions and watermark bits with high security. The watermark bits is finally embedded into the LUTs(Lookup Table) of FPGA design by identical logic configuration. The normal function of original design will not change and the actual embedded watermark is reduced drastically due to the transformation. The experimental results on Xilinx Virtex II Pro XC2VP4 FPGA show low resource and timing overhead and high security by comparing with other method.
Short Paper : Challenges and Novelties while using Mobile Phones as ICT Devices for Indian Masses

Mobile phones have emerged as truly pervasive and affordable Information and Communication Technology (ICT) platform in the last decade. Large penetration of cellular networks and availability of advanced hardware platforms have inspired multiple innovative research opportunities in mobile computing domain. However, most of the research challenges have focused on typical scenarios existing in the developed economies. In this paper, we present research challenges and novelties in mobile computing domain that take account for differences between developing in particular India and developed economies. Our research is based on commonly available mobile platforms, communication cost, differences in user behavior and acceptable societal norms, among others.
Sensitivity of Cloud-radiation Interactions to Cloud Microphysics

Unrealistic parameterizations are the Achilles' heel of climate models. When a single-column model (SCM), which consists of one isolated column of a global atmospheric model, is forced with observational estimates of horizontal advection terms, the parameterizations within the SCM produce timedependent fields which can be compared directly with measurements. In the case of cloud microphysical schemes, these fields include cloud altitude, cloud amount, liquid and ice content, particle size spectra, and radiative fluxes at the surface and the top of the atmosphere. Comparisons with data from the Atmospheric Radiation Measurement (ARM) Program show conclusively that prognostic cloud algorithms with detailed microphysics are far more realistic than simpler diagnostic approaches. Long-term comparisons of quantities strongly modulated by clouds, such as monthly mean downwelling surface shortwave radiation, clearly demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and radiative interactions. These results also demonstrate the critical need for more and better in situ observations of cloud microphysical variables.
Example-based motion manipulation

This paper introduces an idea of imitating camera movements and shooting styles from an example video and reproducing the effects on another carelessly shot video. Our goal is to compute a series of transformations so that we can warp the input video and make the flow of the output video resemble the example flow. We formulate and solve an optimization problem to find the required transformation for each video frame. By enforcing the resemblance between flow fields, our method can recreate different shooting styles and camera movements, from simple effect of video stabilization, to more complicated ones like anti-blur panning, smooth zoom, tracking shot, and dolly zoom.
Calibrating a triaxial accelerometer-magnetometer - using robotic actuation for sensor reorientation during data collection

A kinematic model and kinematic maneuver to calibrate a triaxial accelerometer and magnetometer was derived. The calibration was accomplished by implementing the maneuver on a six-degrees-of-freedom robotic arm. Analysis of the accuracy of the experimental results was performed by generating simulated data and formulating two least-squares optimization problems. By first calibrating the accelerometers with simulated data, the possibility of inconsistency in the estimator was evaluated. By calibrating the accelerator and the magnetometer separately, discrepancies in the data and model were checked. The simultaneous calibrations produced smaller errors for both the magnetometer and accelerometer compared to the separate calibrations.
Immunophenotyping in BK Virus Allograft Nephropathy Distinct from Acute Rejection

Differentiating BK virus nephropathy (BKVN) from acute rejection (AR) is crucial in clinical practice, as both of them have interstitial inflammation in the grafts. The purpose of the study is to describe the inflammatory cellular constituents of BKVN and to determine the clinical utility of immunophenotyping findings in distinguishing BKVN from AR. In addition, the expression of the HLA-DR was investigated. Sixty-five renal allograft recipients were included in this study, including 22 cases of BKVN, 31 cases of AR, and 12 cases of stable allograft. Immunostaining for infiltrating lymphocytes showed that the number of CD20 cells (P < 0.001) and the percentages of CD3 (P < 0.001), CD4 (P = 0.004), CD8 (P = 0.005), and CD20 (P = 0.002) cells were all significantly different between BKVN and AR. Moreover, there were no statistically significant differences in tubule cell HLA-DR expression (P = 0.156). This observation suggests that the number of CD20 cells and the percentages of CD3, CD4, CD8, and CD20 cells in renal biopsies would aid the distinction between BKVN and AR. On the other hand, the presence of HLA-DR upregulation may not only be specific for acute rejection but also be a response to BKVN.
How we move is universal: Scaling in the average shape of human activity

Human motor activity is constrained by the rhythmicity of the 24 hours circadian cycle, including the usual 12-15 hours sleep-wake cycle. However, activity fluctuations also appear over a wide range of temporal scales, from days to a few seconds, resulting from the concatenation of a myriad of individual smaller motor events. Furthermore, individuals present different propensity to wakefulness and thus to motor activity throughout the circadian cycle. Are activity fluctuations across temporal scales intrinsically different, or is there a universal description encompassing them? Is this description also universal across individuals, considering the aforementioned variability? Here we establish the presence of universality in motor activity fluctuations based on the empirical study of a month of continuous wristwatch accelerometer recordings. We study the scaling of average fluctuations across temporal scales and determine a universal law characterized by critical exponents , and . Results are highly reminiscent of the universality described for the average shape of avalanches in systems exhibiting crackling noise. Beyond its theoretical relevance, the present results can be important for developing objective markers of healthy as well as pathological human motor behavior. Received: 18 October 2015, Accepted: 10 November 2015; Edited by: E. Mizraji; Reviewed by: J. Lin, Department of Physics, Washington College, Maryland, USA. ; DOI: http://dx.doi. org/10.4279/PIP.070017 Cite as: D R Chialvo, A M Gonzalez Torrado, E Gudowska-Nowak, J K Ochab, P Montoya, M A Nowak, E Tagliazucchi, Papers in Physics 7, 070017 (2015) This paper, by D R Chialvo, A M Gonzalez Torrado, E Gudowska-Nowak, J K Ochab, P Montoya, M A Nowak, E Tagliazucchi , is licensed under the Creative Commons Attribution License 3.0 .
Ozz-E3 Ubiquitin Ligase Targets Sarcomeric Embryonic Myosin Heavy Chain during Muscle Development

Muscle contractile proteins are expressed as a series of developmental isoforms that are in constant dynamic remodeling during embryogenesis, but how obsolete molecules are recognized and removed is not known. Ozz is a developmentally regulated protein that functions as the adaptor component of a RING-type ubiquitin ligase complex specific to striated muscle. Ozz−/− mutants exhibit defects in myofibrillogenesis and myofiber differentiation. Here we show that Ozz targets the rod portion of embryonic myosin heavy chain and preferentially recognizes the sarcomeric rather than the soluble pool of myosin. We present evidence that Ozz binding to the embryonic myosin isoform within sarcomeric thick filaments marks it for ubiquitination and proteolytic degradation, allowing its replacement with neonatal or adult isoforms. This unique function positions Ozz within a system that facilitates sarcomeric myosin remodeling during muscle maturation and regeneration. Our findings identify Ozz-E3 as the ubiquitin ligase complex that interacts with and regulates myosin within its fully assembled cytoskeletal structure.