Miracle-dz/UniFAR-FTUs huggingface dataset:
Waveform Modeling and Generation Using Hierarchical Recurrent Neural Networks for Speech Bandwidth Extension

This paper presents a waveform modeling and generation method using hierarchical recurrent neural networks (HRNN) for speech bandwidth extension (BWE). Different from conventional BWE methods that predict spectral parameters for reconstructing wideband speech waveforms, this BWE method models and predicts waveform samples directly without using vocoders. Inspired by SampleRNN, which is an unconditional neural audio generator, the HRNN model represents the distribution of each wideband or high-frequency waveform sample conditioned on the input narrowband waveform samples using a neural network composed of long short-term memory (LSTM) layers and feed-forward layers. The LSTM layers form a hierarchical structure and each layer operates at a specific temporal resolution to efficiently capture long-span dependencies between temporal sequences. Furthermore, additional conditions, such as the bottleneck features derived from narrowband speech using a deep neural network based state classifier, are employed as auxiliary input to further improve the quality of generated wideband speech. The experimental results of comparing several waveform modeling methods show that the HRNN-based method can achieve better speech quality and run-time efficiency than the dilated convolutional neural network based method and the plain sample-level recurrent neural network based method. Our proposed method also outperforms the conventional vocoder-based BWE method using LSTM-RNNs in terms of the subjective quality of the reconstructed wideband speech.
One Way or Another: Evidence for Perceptual Asymmetry in Pre-attentive Learning of Non-native Contrasts

Research investigating listeners’ neural sensitivity to speech sounds has largely focused on segmental features. We examined Australian English listeners’ perception and learning of a supra-segmental feature, pitch direction in a non-native tonal contrast, using a passive oddball paradigm and electroencephalography. The stimuli were two contours generated from naturally produced high-level and high-falling tones in Mandarin Chinese, differing only in pitch direction (Liu and Kager, 2014). While both contours had similar pitch onsets, the pitch offset of the falling contour was lower than that of the level one. The contrast was presented in two orientations (standard and deviant reversed) and tested in two blocks with the order of block presentation counterbalanced. Mismatch negativity (MMN) responses showed that listeners discriminated the non-native tonal contrast only in the second block, reflecting indications of learning through exposure during the first block. In addition, listeners showed a later MMN peak for their second block of test relative to listeners who did the same block first, suggesting linguistic (as opposed to acoustic) processing or a misapplication of perceptual strategies from the first to the second block. The results also showed a perceptual asymmetry for change in pitch direction: listeners who encountered a falling tone deviant in the first block had larger frontal MMN amplitudes than listeners who encountered a level tone deviant in the first block. The implications of our findings for second language speech and the developmental trajectory for tone perception are discussed.
Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users’ sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.
Composition Dependent Structural and Optical Properties of Nanocrystallites ZnxCd1-xS

In this work a novel chemical reduction method at room temperature is described to synthesize nanocrystalline ZnS, CdS, ZnxCd1-xS. The method is cheap and cost effective. The grown nanoparticles are characterized by XRD, TEM, EDX, UV-VIS absorption and PL study. CdS formation is supported by the systematic splitting of x-ray diffraction peak at lower angle and the peaks are identified. ZnS peaks are also identified comparing with ICDD data. EDX analysis shows two other phases Zn 0.8 Cd 0.2 S, Zn 0.5 Cd 0.5 S. The particle sizes are in the range 4-8 nm. The band gap changes with change of composition. Also at each composition the band gap is greater compared to bulk band gap. This indicates quantum confinement takes place. The band gap energy of nanoparticles can be tuned to a lower energy by increasing the Cd content, indicating the formation of the alloyed nanoparticles. PL peak shifts towards higher wavelength as Cd content increases. The peak corresponds to transition associated with surface state.
Integrative Pathway-Based Approach for Genome-Wide Association Studies: Identification of New Pathways for Rheumatoid Arthritis and Type 1 Diabetes

Genome-wide association studies (GWAS) led to the identification of numerous novel loci for a number of complex diseases. Pathway-based approaches using genotypic data provide tangible leads which cannot be identified by single marker approaches as implemented in GWAS. The available pathway analysis approaches mainly differ in the employed databases and in the applied statistics for determining the significance of the associated disease markers. So far, pathway-based approaches using GWAS data failed to consider the overlapping of genes among different pathways or the influence of protein–interactions. We performed a multistage integrative pathway (MIP) analysis on three common diseases - Crohn's disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) - incorporating genotypic, pathway, protein- and domain-interaction data to identify novel associations between these diseases and pathways. Additionally, we assessed the sensitivity of our method by studying the influence of the most significant SNPs on the pathway analysis by removing those and comparing the corresponding pathway analysis results. Apart from confirming many previously published associations between pathways and RA, CD and T1D, our MIP approach was able to identify three new associations between disease phenotypes and pathways. This includes a relation between the influenza-A pathway and RA, as well as a relation between T1D and the phagosome and toxoplasmosis pathways. These results provide new leads to understand the molecular underpinnings of these diseases. The developed software herein used is available at http://www.cogsys. cs.uni-tuebingen.de/software/GWASPathwayIdentifier/index.htm.
Roaring High and Low: Composition and Possible Functions of the Iberian Stag's Vocal Repertoire

We provide a detailed description of the rutting vocalisations of free-ranging male Iberian deer (Cervus elaphus hispanicus, Hilzheimer 1909), a geographically isolated and morphologically differentiated subspecies of red deer Cervus elaphus. We combine spectrographic examinations, spectral analyses and automated classifications to identify different call types, and compare the composition of the vocal repertoire with that of other red deer subspecies. Iberian stags give bouts of roars (and more rarely, short series of barks) that are typically composed of two different types of calls. Long Common Roars are mostly given at the beginning or at the end of the bout, and are characterised by a high fundamental frequency (F0) resulting in poorly defined formant frequencies but a relatively high amplitude. In contrast, Short Common Roars are typically given in the middle or at the end of the bout, and are characterised by a lower F0 resulting in relatively well defined vocal tract resonances, but low amplitude. While we did not identify entirely Harsh Roars (as described in the Scottish red deer subspecies (Cervus elaphus scoticus)), a small percentage of Long Common Roars contained segments of deterministic chaos. We suggest that the evolution of two clearly distinct types of Common Roars may reflect divergent selection pressures favouring either vocal efficiency in high pitched roars or the communication of body size in low-pitched, high spectral density roars highlighting vocal tract resonances. The clear divergence of the Iberian red deer vocal repertoire from those of other documented European red deer populations reinforces the status of this geographical variant as a distinct subspecies.
Noradrenergic enhancement of reconsolidation in the amygdala impairs extinction of conditioned fear in rats—a possible mechanism for the persistence of traumatic memories in PTSD

Background: Posttraumatic stress disorder (PTSD) is associated with enhanced noradrenergic activity. Animal and human studies demonstrate that noradrenergic stimulation augments consolidation of fear learning. Retrieval of well‐established memories by presenting a learned fear cue triggers reconsolidation processes during which memories may be updated, weakened, or strengthened. We previously reported that noradrenergic blockade in the rat amygdala impairs reconsolidation of fear memories. Here we investigated the effects of noradrenergic enhancement on reconsolidation of learned fear. Methods: Using auditory fear conditioning in rats, we tested the effects of postretrieval intraamygdala infusion of the β‐adrenergic receptor agonist isoproterenol or the antagonist propranolol on conditioned fear in the amygdala. Results: A single intraamygdala infusion of isoproterenol following a retrieval of a well‐consolidated memory enhanced fear memory elicited by the learned fear stimulus and impaired extinction of this memory 48 hr later. Intraamygdala infusion of the β‐adrenergic receptor antagonist propranolol following a consecutive retrieval trial blocked the enhancing effects of isoproterenol on fear memory. Conclusions: Postretrieval β‐adrenergic stimulation in the amygdala enhances reconsolidation of fear memories, making them resistant to extinction. Noradrenergic augmentation during retrieval of fear memories may thus contribute to persistence and severity of traumatic memories. Reconsolidation may be a useful tool in understanding the pathology of PTSD and may thus help in developing new and in modifying existing treatments of traumatic memories. Depression and Anxiety 28:186–193, 2011. © 2011 Wiley‐Liss, Inc.
A Systematic Review and Meta-Analysis of Mindfulness-Based (Baduanjin) Exercise for Alleviating Musculoskeletal Pain and Improving Sleep Quality in People with Chronic Diseases

Objective: we performed the first systematic review with meta-analyses of the existing studies that examined mindfulness-based Baduanjin exercise for its therapeutic effects for individuals with musculoskeletal pain or insomnia. Methods: Both English- (PubMed, Web of Science, Elsevier, and Google Scholar) and Chinese-language (CNKI and Wangfang) electronic databases were used to search relevant articles. We used a modified PEDro scale to evaluate risk of bias across studies selected. All eligible RCTS were considered for meta-analysis. The standardized mean difference was calculated for the pooled effects to determine the magnitude of the Baduanjin intervention effect. For the moderator analysis, we performed subgroup meta-analysis for categorical variables and meta-regression for continuous variables. Results: The aggregated result has shown a significant benefit in favour of Baduanjin at alleviating musculoskeletal pain (SMD = −0.88, 95% CI −1.02 to −0.74, p < 0.001, I2 = 10.29%) and improving overall sleep quality (SMD = −0.48, 95% CI −0.95 to −0.01, p = 004, I2 = 84.42%). Conclusions: Mindfulness-based Baduanjin exercise may be effective for alleviating musculoskeletal pain and improving overall sleep quality in people with chronic illness. Large, well-designed RCTs are needed to confirm these findings.
Real-time navigation for indoor environment

Mobile robots have been widely used in exploration and navigation from the starting position to the desired goal where static, dynamic and unknown environment is involved. The environment is distinguished by variable terrain and obstacles that may block the movement of the robot in reaching the desired destination. Mobile robot relies on sensors to get information about their surroundings. The proposed system has been implemented with the help of an overhead camera acting as a Positioning System or a 2D real time terrain mapping sensor node and the robot connected to this sensor node wirelessly thus acquiring its own position along with the position of the dynamic obstacles and the path to be followed. It uses Lego Mindstorms NXT V2 for the robot and MATLAB for the image processing and programming. The system designed is capable of static as well as dynamic obstacle avoidance.
Epidemics of Community-Associated Methicillin-Resistant Staphylococcus aureus in the United States: A Meta-Analysis

Staphylococcus aureus is the most frequent cause of skin and soft tissue infections in humans. Methicillin-resistant strains of S. aureus (MRSA) that emerged in the 1960s presented a relatively limited public health threat until the 1990s, when novel community-associated (CA-) MRSA strains began circulating. CA-MRSA infections are now common, resulting in serious and sometimes fatal infections in otherwise healthy people. Although some have suggested that there is an epidemic of CA-MRSA in the U.S., the origins, extent, and geographic variability of CA-MRSA infections are not known. We present a meta-analysis of published studies that included trend data from a single site or region, and derive summary epidemic curves of CA-MRSA spread over time. Our analysis reveals a dramatic increase in infections over the past two decades, with CA-MRSA strains now endemic at unprecedented levels in many US regions. This increase has not been geographically homogeneous, and appears to have occurred earlier in children than adults.
Fibroblast growth factor 23 serum level in type 2 diabetic italian subjects with peripheral arterial disease and critical limb ischemia.

OBJECTIVE Fibroblast growth factor 23 (FGF23) was demonstrated to be involved in the occurrence and development of cardiovascular disease (CVD). The aim of this study was to investigate the potential role of FGF23 on presence and severity of peripheral arterial disease (PAD) in type 2 diabetic patients. PATIENTS AND METHODS In this study, we analyzed FGF23 serum levels in 413 type 2 diabetic patients with PAD and in 598 diabetic controls without lower limbs atherosclerosis. RESULTS We found that FGF23 median serum levels were significantly higher in patients than in diabetic controls (69.3 (58.8-75.1) pg/mL in PAD and 42.98 (37.1-49.8) pg/mL in subjects without PAD (p < 0.001) and were significantly and independently associated with critical limb ischemia (CLI) [OR, 7.69 (2.64-16.31); p = 0.001]. CONCLUSIONS We have found, for the first time, that FGF23 could be associated with presence and severity of PAD in Italian patients with type 2 diabetes.
Application of Monte-Carlo tree search in a fighting game AI

This paper describes an application of Monte-Carlo Tree Search (MCTS) in a fighting game AI. MCTS is a best-first search technique that uses stochastic simulations. In this paper, we evaluate its effectiveness on FightingICE, a game AI competition platform at Computational Intelligence and Games Conferences. Our results confirm that MCTS is an effective search for controlling a game AI in the aforementioned platform.
Two Curvelets variational Models Depend on Decomposition Spaces

Wavelet has become an appealing image processing technique, due to the fact that the sparseness of wavelet expansion is equivalent to smoothness measure in Besov spaces so that the regularization of image can be performed by manipulating its wavelet coefficients. Unfortunately, wavelets have good performance especially at representing point singularities, but they fail to efficiently represent object edges. As one of computational harmonic analysis tools, curvelets have an essentially optimal representation of objects which is C2 away from a C2 edge. In this paper, we first apply constraint of curvelet-type decomposition spaces as a regularizing term to variational model for image denoising. Based on the equivalent relationship between semi-norm of curvelet-type decomposition spaces and the weighted curvelet coefficients, solution to the proposed model approximately equals to different curvelet shrinkages. As a second contribution, we also propose another image restoration model from image decomposition point of view. Furthermore, an equivalent theorem of two proposed models is given. Finally, the experiment results show the superiority of proposed models over traditional wavelet-based ones.
Social Capital and Usefulness of External Knowledge: The Moderating Role of Group Affiliation

Knowledge is the most important firm asset and studies show that social capital facilitates access to internal and external knowledge and in turn increases business value. In that respect, studies show that companies sharing some similarities such as organizational values and practices may benefit more than companies differing in various aspects. In particular, group affiliations have been shown to influence performance in specific contexts but results are mixed at best. In addition, the question of how the influence of social capital on transferring useful external knowledge might be moderated by closer affiliations between companies is virtually not addressed. Employing a survey among manufacturing companies, this paper contributes to extant research by demonstrating a moderating effect of group affiliations on the relationship between social capital and useful external knowledge.
Dompletion: DOM-aware JavaScript code completion

JavaScript is a scripting language that plays a prominent role in modern web applications. It is dynamic in nature and interacts heavily with the Document Object Model (DOM) at runtime. These characteristics make providing code completion support to Java- Script programmers particularly challenging. We propose an auto- mated technique that reasons about existing DOM structures, dynamically analyzes the JavaScript code, and provides code completion suggestions for JavaScript code that interacts with the DOM through its APIs. Our automated code completion scheme is implemented in an open source tool called DOMPLETION. The results of our empirical evaluation indicate that (1) DOM structures exhibit patterns, which can be extracted and reasoned about in the con- text of code completion suggestions; (2) DOMPLETION can pro- vide code completion suggestions with a recall of 89%, precision of 90%, and an average time of 2.8 seconds.
LiFiX: A fully bidirectional CMOS light communication device: Multichannel dedicated device for high bandwidth secured wireless data transmission

LiflX, is a fully integrated Li-Fi CMOS device. It contains 64 emission-reception cells and architectured in a similar way as a memory array with bitlines and wordlines to read and write data via access transistor of each cell. Each row in the array is specific in terms of commutation frequency and each column is specific in terms of wavelength. Individual cells contain one LED for light emission and one photodiode for light reception. Device is fully bi-directional, can reach bandwidth of 26 Gb/s for 64 cells and has high level of data transmission security via frequency hopping.
Cone opsin mislocalization in Rpe65-/- mice: a defect that can be corrected by 11-cis retinal.

PURPOSE In retinal degenerative diseases, rod photoreceptors typically deteriorate more rapidly than cone photoreceptors. In the Rpe65(-/-) mouse, a model for Leber's congenital amaurosis, cones degenerate much more rapidly than rods. In this model, the retinoid processing pathway in the retinal pigment epithelium is disrupted, and 11-cis retinal is not generated. This study was designed to investigate the feasibility of restoring functional cones with exogenous 11-cis retinal. METHODS Rpe65(-/-)::Rho(-/-) mice were used to remove any interference of rods and compared with wild-type (wt) mice. Pups were injected intraperitoneally with 11-cis retinal, starting at postnatal day (P)10, and were maintained in complete darkness. At P25, cone function was assessed with photopic single-flash and flicker ERGs. Cone survival was determined immunohistochemically with cone-specific antibodies, and cone opsin levels were obtained by quantitative RT-PCR. RESULTS At P25, cone density and transcript levels of cone opsins were drastically reduced, but a minute cone electroretinogram was detected, indicating that the cones were functional. Confocal microscopy revealed that the cone opsins were mislocalized, suggesting that their transport to the outer segments was impaired. Intraperitoneal administrations of 11-cis retinal before P25 led to increased transport of cone opsins to the outer segments and preserved cones anatomically and functionally. CONCLUSIONS The results suggest that the ligand is required during cone opsin synthesis for successful opsin trafficking and that without 11-cis retinal, cones may degenerate because of opsin mislocalization. These results may have important consequences for the treatment of cone dystrophies.
Sales Forecasting with Partial Recurrent Neural Networks: Empirical Insights and Benchmarking Results

Partial Recurrent Neural Networks (PRNN) belong to the family of Artificial Neural Networks. Due to their specific architecture, PRNN are well-suited to forecast time series data. Their ability to outperform well-known statistical forecasting models has been demonstrated in some application domains. However, the potential of PRNN in business decision support and sales forecasting in particular has received relatively little attention. The paper strives to close this research gap. In particular, the paper provides a managerial introduction to PRNN and assesses their forecasting performance vis-à-vis challenging statistical benchmarks using real-world sales data. The sales time series are selected such that they encompass several characteristic patterns (e.g., Seasonality, trend, etc.) and differ in shape and length. Such heterogeneity is commonly encountered in sales forecasting and facilitates a holistic assessment of PRNN, and their potential to generate operationally accurate forecasts.