All-for-One and One-For-All: Deep learning-based feature fusion for Synthetic Speech Detection

Recent advances in deep learning and computer vision have made the synthesis and counterfeiting of multimedia content more accessible than ever, leading to possible threats and dangers from malicious users. In the audio field, we are witnessing the growth of speech deepfake generation techniques, which solicit the development of synthetic speech detection algorithms to counter possible mischievous uses such as frauds or identity thefts. In this paper, we consider three different feature sets proposed in the literature for the synthetic speech detection task and present a model that fuses them, achieving overall better performances with respect to the state-of-the-art solutions. The system was tested on different scenarios and datasets to prove its robustness to anti-forensic attacks and its generalization capabilities.Comment: Accepted at ECML-PKDD 2023 Workshop "Deep Learning and Multimedia Forensics. Combating fake media and misinformation

A Data-Driven Approach to Violin Making

Of all the characteristics of a violin, those that concern its shape are probably the most important ones, as the violin maker has complete control over them. Contemporary violin making, however, is still based more on tradition than understanding, and a definitive scientific study of the specific relations that exist between shape and vibrational properties is yet to come and sorely missed. In this article, using standard statistical learning tools, we show that the modal frequencies of violin tops can, in fact, be predicted from geometric parameters, and that artificial intelligence can be successfully applied to traditional violin making. We also study how modal frequencies vary with the thicknesses of the plate (a process often referred to as {\em plate tuning}) and discuss the complexity of this dependency. Finally, we propose a predictive tool for plate tuning, which takes into account material and geometric parameters

TIMIT-TTS: a Text-to-Speech Dataset for Multimodal Synthetic Media Detection

With the rapid development of deep learning techniques, the generation and counterfeiting of multimedia material are becoming increasingly straightforward to perform. At the same time, sharing fake content on the web has become so simple that malicious users can create unpleasant situations with minimal effort. Also, forged media are getting more and more complex, with manipulated videos that are taking the scene over still images. The multimedia forensic community has addressed the possible threats that this situation could imply by developing detectors that verify the authenticity of multimedia objects. However, the vast majority of these tools only analyze one modality at a time. This was not a problem as long as still images were considered the most widely edited media, but now, since manipulated videos are becoming customary, performing monomodal analyses could be reductive. Nonetheless, there is a lack in the literature regarding multimodal detectors, mainly due to the scarsity of datasets containing forged multimodal data to train and test the designed algorithms. In this paper we focus on the generation of an audio-visual deepfake dataset. First, we present a general pipeline for synthesizing speech deepfake content from a given real or fake video, facilitating the creation of counterfeit multimodal material. The proposed method uses Text-to-Speech (TTS) and Dynamic Time Warping techniques to achieve realistic speech tracks. Then, we use the pipeline to generate and release TIMIT-TTS, a synthetic speech dataset containing the most cutting-edge methods in the TTS field. This can be used as a standalone audio dataset, or combined with other state-of-the-art sets to perform multimodal research. Finally, we present numerous experiments to benchmark the proposed dataset in both mono and multimodal conditions, showing the need for multimodal forensic detectors and more suitable data

Arrhythmic risk in elderly patients candidates to transcatheter aortic valve replacement. predicative role of repolarization temporal dispersion

Degenerative aortic valve stenosis (AS) is associated to ventricular arrhythmias and sudden cardiac death, as well as mental stress in specific patients. In such a context, substrate, autonomic imbalance as well as repolarization dispersion abnormalities play an undoubted role. Aim of the study was to evaluate the increase of premature ventricular contractions (PVC) and complex ventricular arrhythmias during mental stress in elderly patients candidate to the transcatheter aortic valve replacement (TAVR). In eighty-one elderly patients with AS we calculated several short-period RRand QT-derived variables at rest, during controlled breathing and during mild mental stress, the latter being represented by a mini-mental state evaluation (MMSE). All the myocardial repolarization dispersion markers worsened during mental stress (p < 0.05). Furthermore, during MMSE, low frequency component of the RR variability increased significantly both as absolute power (LFRR) and normalized units (LFRRNU) (p < 0.05) as well as the low-high frequency ratio (LFRR/HFRR) (p < 0.05). Eventually, twenty-four (30%) and twelve (15%) patients increased significantly PVC and, respectively, complex ventricular arrhythmias during the MMSE administration. At multivariate logistic regression analysis, the standard deviation of QTend (QTesd), obtained at rest, was predictive of increased PVC (odd ratio: 1.54, 95% CI 1.14–2.08; p = 0.005) and complex ventricular arrhythmias (odd ratio: 2.31, 95% CI 1.40–3.83; p = 0.001) during MMSE. The QTesd showed the widest sensitive-specificity area under the curve for the increase of PVC (AUC: 0.699, 95% CI: 0.576–0.822, p < 0.05) and complex ventricular arrhythmias (AUC: 0.801, 95% CI: 0.648–0.954, p < 0.05). In elderly with AS ventricular arrhythmias worsened during a simple cognitive assessment, this events being a possible further burden on the outcome of TAVR. QTesd might be useful to identify those patients with the highest risk of ventricular arrhythmias. Whether the TAVR could led to a QTesd reduction and, hence, to a reductionof thearrhythmicburdenin thissettingofpatients isworthytobe investigated

SARS-CoV-2-Associated ssRNAs Activate Human Neutrophils in a TLR8-Dependent Fashion

COVID-19 disease is characterized by a dysregulation of the innate arm of the immune system. However, the mechanisms whereby innate immune cells, including neutrophils, become activated in patients are not completely understood. Recently, we showed that GU-rich RNA sequences from the SARS-CoV-2 genome (i.e., SCV2-RNA1 and SCV2-RNA2) activate dendritic cells. To clarify whether human neutrophils may also represent targets of SCV2-RNAs, neutrophils were treated with either SCV2-RNAs or, as a control, R848 (a TLR7/8 ligand), and were then analyzed for several functional assays and also subjected to RNA-seq experiments. Results highlight a remarkable response of neutrophils to SCV2-RNAs in terms of TNFα, IL-1ra, CXCL8 production, apoptosis delay, modulation of CD11b and CD62L expression, and release of neutrophil extracellular traps. By RNA-seq experiments, we observed that SCV2-RNA2 promotes a transcriptional reprogramming of neutrophils, characterized by the induction of thousands of proinflammatory genes, similar to that promoted by R848. Furthermore, by using CU-CPT9a, a TLR8-specific inhibitor, we found that SCV2-RNA2 stimulates neutrophils exclusively via TLR8-dependent pathways. In sum, our study proves that single-strand RNAs from the SARS-CoV-2 genome potently activate human neutrophils via TLR8, thus uncovering a potential mechanism whereby neutrophils may contribute to the pathogenesis of severe COVID-19 disease

OxCOVID19 Database, a multimodal data repository for better understanding the global impact of COVID-19

Oxford COVID-19 Database (OxCOVID19 Database) is a comprehensive source of information related to the COVID-19 pandemic. This relational database contains time-series data on epidemiology, government responses, mobility, weather and more across time and space for all countries at the national level, and for more than 50 countries at the regional level. It is curated from a variety of (wherever available) official sources. Its purpose is to facilitate the analysis of the spread of SARS-CoV-2 virus and to assess the effects of non-pharmaceutical interventions to reduce the impact of the pandemic. Our database is a freely available, daily updated tool that provides unified and granular information across geographical regions

Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

BACKGROUND: The tetraploid durum wheat (Triticum turgidum L. ssp. durum Desf. Husnot) is an important crop which provides the raw material for pasta production and a valuable source of genetic diversity for breeding hexaploid wheat (Triticum aestivum L.). Future breeding efforts to enhance yield potential and climate resilience will increasingly rely on genomics-based approaches to identify and select beneficial alleles. A deeper characterisation of the molecular and functional diversity of the durum wheat transcriptome will be instrumental to more effectively harness its genetic diversity. RESULTS: We report on the de novo transcriptome assembly of durum wheat cultivar 'Svevo'. The transcriptome of four tissues/organs (shoots and roots at the seedling stage, reproductive organs and developing grains) was assembled de novo, yielding 180,108 contigs, with a N50 length of 1121\u2009bp and mean contig length of 883\u2009bp. Alignment against the transcriptome of nine plant species identified 43% of transcripts with homology to at least one reference transcriptome. The functional annotation was completed by means of a combination of complementary software. The presence of differential expression between the A- and B-homoeolog copies of the durum wheat tetraploid genome was ascertained by phase reconstruction of polymorphic sites based on the T. urartu transcripts and inferring homoeolog-specific sequences. We observed greater expression divergence between A and B homoeologs in grains rather than in leaves and roots. The transcriptomes of 13 durum wheat cultivars spanning the breeding period from 1969 to 2005 were analysed for SNP diversity, leading to 95,358 non-rare, hemi-SNPs shared among two or more cultivars and 33,747 locus-specific (diploid inheritance) SNPs. CONCLUSIONS: Our study updates and expands the de novo transcriptome reference assembly available for durum wheat. Out of 180,108 assembled transcripts, 13,636 were specific to the Svevo cultivar as compared to the only other reference transcriptome available for durum, thus contributing to the identification of the tetraploid wheat pan-transcriptome. Additionally, the analysis of 13 historically relevant hallmark varieties produced a SNP dataset that could successfully validate the genotyping in tetraploid wheat and provide a valuable resource for genomics-assisted breeding of both tetraploid and hexaploid wheats

Care pathways models and clinical outcomes in disorders of consciousness

Objective: Patients with Disorders of consciousness, are persons with extremely low functioning levels and represent a challenge for health care systems due to their high needs of facilitating environmental factors. Despite a common Italian health care path-way for these patients, no studies have analyzed information on how each region have implemented it in its welfare system correlating data with patients’ clinical outcomes. Materials and Methods: A multicenter observational pilot study was realized. Clinicians collected data on the care pathways of patients with Disorder of consciousness by ask-ing 90 patients’ caregivers to complete an ad hoc questionnaire through a structured phone interview. Questionnaire consisted of three sections: sociodemographic data, description of the care pathway done by the patient, and caregiver evaluation of health services and information received.Results: Seventy- three patients were analyzed. Length of hospital stay was different across the health care models and it was associated with improvement in clinical diag-nosis. In long- term care units, the diagnosis at admission and the number of caregivers available for each patient (median value=3) showed an indirect relationship with worsening probability in clinical outcome. Caregivers reported that communication with professionals (42%) and the answer to the need of information were the most critical points in the acute phase, whereas presence of Non- Governmental Organizations (25%) and availability of psychologists for caregivers (21%) were often missing during long-term care. The 65% of caregivers reported they did not know the UN Convention on the Rights of Persons with Disabilities. Conclusion: This study highlights relevant differences in analyzed models, despite a recommended national pathway of care. Future public health considerations and ac-tions are needed to guarantee equity and standardization of the care process in all European countries