Miracle-dz/UniFAR-FTUs huggingface dataset:
High quality, lightweight and adaptable TTS using LPCNet

We present a lightweight adaptable neural TTS system with high quality output. The system is composed of three separate neural network blocks: prosody prediction, acoustic feature prediction and Linear Prediction Coding Net as a neural vocoder. This system can synthesize speech with close to natural quality while running 3 times faster than real-time on a standard CPU. The modular setup of the system allows for simple adaptation to new voices with a small amount of data. We first demonstrate the ability of the system to produce high quality speech when trained on large, high quality datasets. Following that, we demonstrate its adaptability by mimicking unseen voices using 5 to 20 minutes long datasets with lower recording quality. Large scale Mean Opinion Score quality and similarity tests are presented, showing that the system can adapt to unseen voices with quality gap of 0.12 and similarity gap of 3% compared to natural speech for male voices and quality gap of 0.35 and similarity of gap of 9 % for female voices.
Exponential convergence to equilibrium for the $d$-dimensional East model

Kinetically constrained models (KCMs) are interacting particle systems on $Z^d$ with a continuous-time constrained Glauber dynamics, which were introduced by physicists to model the liquid-glass transition. One of the most well-known KCMs is the one-dimensional East model. Its generalization to higher dimension, the d-dimensional East model, is much less understood. Prior to this paper, convergence to equilibrium in the d-dimensional East model was proven to be at least stretched exponential, by Chleboun, Faggionato and Martinelli in 2015. We show that the d-dimensional East model exhibits exponential convergence to equilibrium in all settings for which convergence is possible.
Measuring and Predicting Temperature Distributions on FPGAs at Run-Time

In the next decades, hybrid multi-cores will be the predominant architecture for reconfigurable FPGA-based systems. Temperature-aware thread mapping strategies are key for providing dependability in such systems. These strategies rely on measuring the temperature distribution and redicting the thermal behavior of the system when there are changes to the hardware and software running on the FPGA. While there are a number of tools that use thermal models to predict temperature distributions at design time, these tools lack the flexibility to autonomously adjust to changing FPGA configurations. To address this problem we propose a temperature-aware system that empowers FPGA-based reconfigurable multi-cores to autonomously predict the on-chip temperature distribution for pro-active thread remapping. Our system obtains temperature measurements through a self-calibrating grid of sensors and uses area constrained heat-generating circuits in order to generate spatial and temporal temperature gradients. The generated temperature variations are then used to learn the free parameters of the system's thermal model. The system thus acquires an understanding of its own thermal characteristics. We implemented an FPGA system containing a net of 144 temperature sensors on a Xilinx Virtex-6 LX240T FPGA that is aware of its thermal model. Finally, we show that the temperature predictions vary less than 0.72 degree C on average compared to the measured temperature distributions at run-time.
Big Data in IoT Systems

Big Data in IoT is a large and fast-developing area where many different methods and techniques can play a role. Due to rapid progress in Machine Learning and new hardware developments, a dynamic turnaround of methods and technologies can be observed. This overview therefore tries to be broad and highlevel without claiming to be comprehensive. Its approach towards Big Data and IoT is predicated on a distinction between the digital economy and the characteristics of what Robin Milner has described as the Ubiquitous Computing System.
Perihematomal Edema After Spontaneous Intracerebral Hemorrhage.

Mechanical disruption of adjacent neurons and glia after intracerebral hemorrhage (ICH) can result in both immediate and delayed neurological injury, with the eventual consequences of long-term functional impairment and mortality. In patients who survive the initial injury, inflammatory and cytotoxic responses to the hematoma and its breakdown components cause further damage to the surrounding parenchyma in the ensuing days to weeks, which represents a potential window for therapeutic intervention. In addition to attempts at surgically reducing the immediate mass effect of the hematoma, efforts to identify novel therapies that target secondary injury pathways are ongoing. As the common end point for thrombin accumulation, influx of inflammatory mediators, and erythrocyte lysis, perihematomal edema (PHE) represents a promising surrogate marker of secondary brain injury after ICH. The temporal course of PHE development correlates with the manifestation of secondary injury, and PHE can be readily quantified on neuroimaging studies. Although some studies have found an association between PHE and clinical outcomes, others have reported no such relationship. These inconsistent findings may be influenced by heterogeneous PHE quantification methods, an incomplete understanding of the natural history of PHE, and selection bias from retrospective studies. To serve as a reliable indicator of secondary brain injury in ICH clinical trials, an improved understanding of PHE is necessary. Here, we critically assess the pathogenesis, quantification, and natural history of PHE, as well as its impact on clinical outcome in ICH patients.
Potent vasodilator activity of calcitonin gene-related peptide in human skin.

We have recently shown that the novel neuropeptide calcitonin gene-related peptide, CGRP, is a potent vasodilator. In this paper we report a detailed study of the effects of CGRP in human skin. CGRP induces a clearly defined, long-lasting erythema. We have measured the effect of CGRP on blood flow in human skin using a laser Doppler technique and have demonstrated increased local blood flow that persists for a number of hours. We compared the response of CGRP with other known vasodilators [histamine, prostaglandin (PG) E2, PGI2, substance P, and vasoactive intestinal peptide (VIP)] in the skin, and in all subjects the erythema induced by CGRP was more persistent than that induced by the other mediators tested. Except at high doses the local vasodilatation induced by CGRP was not associated with a wheal and flare as seen with histamine, substance P, and VIP. CGRP is an extremely potent vasodilator and if released into the circulation, or locally from peripheral nerve endings, it could have a role in the regulation of blood flow in both physiologic and pathologic conditions; CGRP may be the endogenous mediator of the flare in the triple response. A deficiency in CGRP secretion or action could be an important component of peripheral vascular disease. Some flushing reactions (e.g., those associated with medullary thyroid carcinoma) may result from circulating CGRP.
An Intention-Based Account of Perspective-Taking

Perspective-taking often increases generosity in behavior and attributions. We present an intentions-based account to explain how perspective-taking can both decrease and increase moral condemnation. Consistent with past research, we predicted perspective-taking would reduce condemnation when the perspective-taker initially attributed benevolent intent to a transgressor. However, we predicted perspective-taking would increase condemnation when malevolent intentions were initially attributed to the wrongdoer. We propose that perspective-taking amplifies the intentions initially attributed to a transgressor. Three studies measured and manipulated intention attributions and found that perspective-taking increased condemnation when malevolent intentions were initially attributed to a transgressor. Perspective-taking also increased costly punishment of a transgressor, an effect mediated by malevolent intentions. In contrast, empathy did not increase punitive responses, supporting its conceptual distinction from perspective-taking. Whether perspective-taking leads to forgiveness or condemnation depends on the intentions the perspective-taker initially attributes to a transgressor.
A general algorithm for output-sensitive visibility preprocessing

Occlusion culling based on precomputed visibility information is a standard method for accelerating the rendering in real-time graphics applications. In this paper we present a new general algorithm that performs the visibility precomputation for a group of viewcells in an output-sensitive fashion. This is achieved by exploiting the directional coherence of visibility between adjacent viewcells. The algorithm is independent of the underlying from-region visibility solver and is therefore applicable to exact, conservative and aggressive visibility solvers in both 2D and 3D.
Multi-slot Spectrum Sensing in Fading Channels for a Cooperative Cognitive Radio Network

The performance of cooperative spectrum sensing (CSS) with multi-slot sensing has been investigated. A number of cognitive radio (CR) enabled users sense the primary user (PU) spectrum in multiple sensing mini-slots and the decision of each slot is combined using OR rule to evaluate the local decision about PU. All the CRs send their local decisions over faded reporting channels (R-channel) to fusion centre (FC). FC takes the final decision about PU on the basis of majority logic fusion rule. The performance of spectrum sensing has been investigated in terms of detection probability and missed detection probability for different sensing parameters such as sensing threshold, number of mini-slots and sensing channel SNR (S-SNR) etc.
Genetics and penile cancer: recent developments and implications.

PURPOSE OF REVIEW We summarize the recent developments in the molecular landscape of penile squamous cell carcinoma (PSCC). RECENT FINDINGS Recent genomic studies have demonstrated a molecular convergence of PSCC with other squamous cell carcinomas (SCCs) from different organ sites. Similarly, human papillomavirus (HPV)-related PSCCs appear to have epigenetic and genomic similarities with other HPV-related cancers. This could have implications on future HPV-related cancer trial design. Growing efforts to characterize recurrent gene alterations in PSCC have expanded our understanding over the past years, showing a predominance of tumor suppressor gene alterations such as TP53 and NOTCH1. In addition, these studies have demonstrated that at least 30% of PSCC cases have targetable gene alterations. Further, the similar tumor mutational burden with other SCCs and the relatively high rates of programmed death-1 (PD-1) positive expression in PSCC constitute the rationale for investigation of PD-1 inhibition in ongoing clinical trials. Multiple studies have identified potential epigenetic and RNA signatures predictive of metastasis or survival, but these still require validation in larger cohorts. SUMMARY PSCC appears to be genomicaly similar to other SCCs and HPV-related cancers. This provides the rationale and opportunity to include a rare tumor like PSCC in future 'basket type' trials using novel agents targeting multiple SCCs that may exhibit similar biology.
Predictive factors for the development of renal insufficiency following partial nephrectomy and subsequent renal function recovery

Abstract Patients who undergo partial nephrectomy (PN) may exhibit renal function insufficiency, and a subset of these patients achieves renal function recovery. We evaluated the predictors of renal insufficiency and subsequent renal function recovery following PN. Data on 393 patients who underwent PN for solid renal tumors between March 2001 and November 2013, obtained from 6 institutions, were retrospectively reviewed. Renal insufficiency was defined as new onset of chronic kidney disease stage ≥3 postoperatively on the second of 2 consecutive tests. Renal function recovery was defined as an estimated glomerular filtration rate ≥60 ml/minute/1.73 m2 following renal insufficiency. Tumor complexity was stratified according to the RENAL classification system. The median (interquartile range) age, tumor size, and follow-up period were 53 (45–63) years, 2.6 (1.9–3.8) cm, and 36 (12–48) months, respectively. Tumors were of low complexity in 258/393 (65.6%) of cases. Renal insufficiency developed in 54/393 (13.5%) patients, in which age ≥60 years and preoperative creatinine ≥1.1 mg/ml were independent predictors. Tumor complexity, clamp type, and operative method were not significant prognostic factors. Among patients with newly developed renal insufficiency, 18/54 (33.3%) patients exhibited renal function recovery within a median period of 18 months, of which preoperative creatinine <1.1 mg/ml was an independent predictor. Age ≥60 years and preoperative creatinine ≥1.1 mg/ml were risk factors for renal insufficiency following PN. Patients with renal insufficiency whose preoperative creatinine was <1.1 mg/ml were likely to have renal function recovery.
Adaptive detection for spread spectrum audio watermarking

This paper presents an adaptive detection algorithm for spread-spectrum-based audio watermarking. Aiming at the watermark adaptively embedded in the audio signal, our improvements to the correlation-based detection algorithms include the adaptive normalization coefficients for correlation calculating and the adaptive threshold for decision comparing. Experimental results show that the proposed detector has high robustness to normal attacks, such as cropping, low pass filtering, noise addition, re-quantization, re-sampling, MPEG compression, and so on.
Quorum sensing between bacterial species on the skin protects against epidermal injury in atopic dermatitis

Quorum sensing peptides produced by commensal skin staphylococci protect against skin injury and inflammation induced by Staphylococcus aureus toxins. Skin-soothing bacteria Staphylococcus aureus is both a normal skin-resident species and a common bad actor in inflammatory skin conditions. Williams et al. showed that S. aureus relies on quorum sensing to secrete certain toxins and proteases that can cause epithelial barrier damage. Coagulase-negative staphylococci (CoNS) normally present on human skin, however, secreted autoinducing peptides that inhibited quorum sensing in S. aureus and hence secretion of these virulence factors. A CoNS autoinducing peptide also reduced S. aureus–induced skin inflammation in mice. Analysis of the skin microbiome of patients with atopic dermatitis suggested that the ratio of protective CoNS to S. aureus may be a factor in the pathogenesis of this condition. Colonization of the skin by Staphylococcus aureus is associated with exacerbation of atopic dermatitis (AD), but any direct mechanism through which dysbiosis of the skin microbiome may influence the development of AD is unknown. Here, we show that proteases and phenol-soluble modulin α (PSMα) secreted by S. aureus lead to endogenous epidermal proteolysis and skin barrier damage that promoted inflammation in mice. We further show that clinical isolates of different coagulase-negative staphylococci (CoNS) species residing on normal skin produced autoinducing peptides that inhibited the S. aureus agr system, in turn decreasing PSMα expression. These autoinducing peptides from skin microbiome CoNS species potently suppressed PSMα expression in S. aureus isolates from subjects with AD without inhibiting S. aureus growth. Metagenomic analysis of the AD skin microbiome revealed that the increase in the relative abundance of S. aureus in patients with active AD correlated with a lower CoNS autoinducing peptides to S. aureus ratio, thus overcoming the peptides’ capacity to inhibit the S. aureus agr system. Characterization of a S. hominis clinical isolate identified an autoinducing peptide (SYNVCGGYF) as a highly potent inhibitor of S. aureus agr activity, capable of preventing S. aureus–mediated epithelial damage and inflammation on murine skin. Together, these findings show how members of the normal human skin microbiome can contribute to epithelial barrier homeostasis by using quorum sensing to inhibit S. aureus toxin production.
Onyx: Describing Emotions on the Web of Data

There are several different standardised and widespread formats to represent emotions. However, there is no standard semantic model yet. This paper presents a new ontology, called Onyx, that aims to become such a standard while adding concepts from the latest Semantic Web models. In particular, the ontology focuses on the representation of Emotion Analysis results. But the model is abstract and inherits from previous standards and formats. It can thus be used as a reference representation of emotions in any future application or ontology. To prove this, we have translated resources from EmotionML representation to Onyx. We also present several ways in which developers could benefit from using this ontology instead of an ad-hoc representation. Our ultimate goal is to foster the use of semantic technologies for Emotion Analysis while following the Linked Data ideals.
An emergent integrated aging process conserved across primates.

Aging is a complex process emerging from integrated physiological networks. Recent work using principal component analysis (PCA) of multisystem biomarkers proposed a novel fundamental physiological process, "integrated albunemia", which was consistent across human populations and more strongly associated with age and mortality risk than individual biomarkers. Here we tested for integrated albunemia and associations with age and mortality across 6 diverse nonhuman primate species and humans. PCA of 13 physiological biomarkers recovered in all species a primary axis of variation (PC1) resembling integrated albunemia, which increased with age in all but one species but was less predictive of mortality risk. Within species, PC1 scores were often reliably recovered with a minimal biomarker subset and usually stable between sexes. Even among species, correlations in PC1 structure were often strong, but the effect of phylogeny was inconclusive. Thus, integrated albunemia likely reflects an evolutionarily conserved process across primates and appears to be generally associated with aging but not necessarily with negative impacts on survival. Integrated albunemia is unlikely to be the only conserved emergent physiological process; our findings hence have implications both for the evolution of the aging process and of physiological networks more generally.
Detection of Single Grapevine Berries in Images Using Fully Convolutional Neural Networks

Yield estimation and forecasting are of special interest in the field of grapevine breeding and viticulture. The number of harvested berries per plant is strongly correlated with the resulting quality. Therefore, early yield forecasting can enable a focused thinning of berries to ensure a high quality end product. Traditionally yield estimation is done by extrapolating from a small sample size and by utilizing historic data. Moreover, it needs to be carried out by skilled experts with much experience in this field. Berry detection in images offers a cheap, fast and non-invasive alternative to the otherwise time-consuming and subjective on-site analysis by experts. We apply fully convolutional neural networks on images acquired with the Phenoliner, a field phenotyping platform. We count single berries in images to avoid the error-prone detection of grapevine clusters. Clusters are often overlapping and can vary a lot in the size which makes the reliable detection of them difficult. We address especially the detection of white grapes directly in the vineyard. The detection of single berries is formulated as a classification task with three classes, namely 'berry', 'edge' and 'background'. A connected component algorithm is applied to determine the number of berries in one image. We compare the automatically counted number of berries with the manually detected berries in 60 images showing Riesling plants in vertical shoot positioned trellis (VSP) and semi minimal pruned hedges (SMPH). We are able to detect berries correctly within the VSP system with an accuracy of 94.0 % and for the SMPH system with 85.6 %.
A new multiparameter flow cytometric method for human semen analysis.

BACKGROUND The objectives of this study were (i) to evaluate whether the combined use of Syto 16 and 7-amino-actinomycin-D (7-AAD) allows the detection of sperm apoptosis and (ii) to describe a new multiparameter flow cytometric method to assess simultaneously sperm concentration (SC), viability and apoptosis as well as leukocyte concentration. METHODS Semen samples from 68 patients were evaluated according to World Health Organization (WHO) criteria (normal, n=26; abnormal, n=42). The detection of activated caspases before and after betulinic acid (BA) incubation was carried out in 13 semen samples by flow cytometry using fluorescein-labelled inhibitors of caspases (FLICA). A multiparameter flow cytometric analysis was performed in 55 semen samples. Fluorescent microspheres were used to assess SC. Sperm apoptosis was detected by staining sperm with Syto 16 and 7-AAD. Leukocytes were counted using monoclonal anti-CD45. RESULTS A significant correlation between the percentage of the spermatozoa with low Syto 16 fluorescence and the percentage of spermatozoa containing activated caspases was found (r=0.68, P=0.0106; n=13). After incubation with BA, an increase of the percentage of apoptotic cells was observed in all samples, using both the Syto 16/7-AAD and the caspase activation methods. There was a good correlation between flow cytometry and optical microscopy for sperm (r=0.98, P < 0.0001) and leukocyte counting (r=0.64, P <0.0001). The percentage of apoptotic sperm was inversely correlated with both SC (r=-0.303, P=0.0246) and morphology (r=-0.384, P=0.0050) but not with motility. CONCLUSIONS The combination of Syto 16/7-AAD provides a sensitive assay to detect sperm apoptosis. The multiparameter flow cytometric method described offers the possibility of a simultaneous, simple, rapid and accurate assessment of several semen parameters.
Likelihood-ratio empirical kernels for i-vector based PLDA-SVM scoring

Likelihood ratio (LR) scoring in PLDA speaker verification systems only uses the information of background speakers implicitly. This paper exploits the notion of empirical kernel maps to incorporate background speaker information into the scoring process explicitly. This is achieved by training a scoring SVM for each target speaker based on a kernel in the empirical feature space. More specially, given a test i-vector and the identity of the target under test, a score vector is constructed by computing the LR scores of the test i-vector with respect to the target-speaker's i-vectors and a set of background-speakers' i-vectors. While in most situations, only one target-speaker i-vector is available for training the SVM, this paper demonstrates that if the enrollment utterance is sufficiently long, a number of target-speaker i-vectors can be generated by an utterance partitioning and resampling technique, resulting in much better scoring SVMs. Results on NIST 2010 SRE suggests that the idea of incorporating background speaker information into PLDA scoring through training speaker-dependent SVMs together with the utterance partitioning techniques can boost the performance of i-vector based PLDA systems significantly.