Miracle-dz/UniFAR-FTUs huggingface dataset:
Synergies between Musical Source Separation and Instrument Recognition

ii iii Acknowledgements I would first like to thank Prof. Xavier Serra for giving me the opportunity to join the SMC Master's program at the Pompeu Fabra University, and the whole Music Technology Group for providing an excellent intellectual framework for the completion of this thesis, specially the members and SMC students which have somehow influenced the development of this work. Special thanks to Perfecto Herrera and Ferdinand Fuhrmann for all their ideas, recommendations, revisions, and for the provision of the code and original dataset that I used as a basis for the instrument recognition in this work. Many thanks to thank Ricard Marxer for the clarifications, as well as Yamaha for the opportunity they provided me to work with their separation algorithm. Special thanks as well to Jordi Janer for his supervision, clarifications, suggestions, and patience. I would like to specially thank my family for all their love and support throughout the years, without which I could not have written this thesis. Thanks as well to friends and everyone else that supported me during this year, such as Andrea with her computing hardware (and patience). Many thanks as well to "La Caixa" Fellowship program for their confidence and their financial support during this year. iv Abstract Due to the increasing amount of digital music available, there is a clear need of a proper organization and effective retrieval. Automatic instrument recognition techniques are useful for satisfying such needs, by labeling music pieces with their instrumentation, but also as support to the extraction of other semantic information such as the genre. Source separation has also recently been applied to facilitate the analysis of musical data, as well as to other applications such as karaoke or post production. In contrast with the huge need for both algorithms, the results obtained so far show that there is still much room for improvement. The main purpose of this thesis is to find synergies between instrument recognition and source separation algorithms in two different tasks: 1) the separation of a target instrument from the accompaniment, and 2) the automatic labeling of songs with the predominant music instruments. Several combination strategies are presented, aimed at overcoming some of the limitations of current state-of-the-art algorithms. In the first task, instrument recognition is used to detect the presence of the target instrument in order to apply or bypass the separation algorithms. In the second task, source separation is …
The Value of Being Linked In Yaakov

I semi-empirically study the social networking sites such as LinkedIn. Such sites enable users to maintain contact information of people they know and trust (their first degree connections or friends), and to discover the friends of their friends (their second degree connections), and to access the friends of the friends of their friends (their third degree connections). Connections up to some degree (e.g., third) make up a network. I find the size of such a tree network grows sublinearly with time, even when its owner actively seeks out new friends. Under simplistic assumptions I find that the value of such a network to its owner is three times that of a standard contact list (containing only first degree connection). The total value of a network of N connections up to d degrees of separation to all its members scales as N 1 d . This is less than Metcalfe’s law that states that the value of a fully connected network scales as N, but more than Odlyzko’s law where the scaling is only N log N . On the other hand, the cost of maintaining a large network increases faster than the value, and thus there is an optimal network size from the value point of view. Using models I am able to estimate the average degrees of separation between members of my network, and the size of the strongly connected cluster to which I belong.
Enhanced Topic Identification Algorithm for Arabic Corpora

During the past few years, the construction of digitalized content is rapidly increasing, raising the demand of information retrieval, data mining and automatic data tagging applications. There are few researches in this field for Arabic data due to the complex nature of Arabic language and the lack of standard corpora. In addition, most work focuses on improving Arabic stemming algorithms, or topic identification and classification methods and experiments. No work has been conducted to include an efficient stemming method within the classification algorithm, which would lead to more efficient outcome. In this paper, we propose a new approach to identify significant keywords for Arabic corpora. That is done by implementing advanced stemming and root extraction algorithm, as well as Term Frequency/Inverse Document Frequency (TFIDF) topic identification method. Our results show that combining advanced stemming, root extraction and TFIDF techniques, lead to extracting a highly significant terms represented by Arabic roots. These roots weights higher TFIDF values than terms extracted without the use of advanced stemming and root extraction methods. Decreasing the size of indexed words and improving the feature selection process.
A Blind Interference Canceling Technique for Two-Stage Harmonic Rejection in Down-mixers

The invention relates to a method and an apparatus for detecting metal objects in a metal detecting apparatus using impulse techniques. The metal detector comprises a compensation circuit arranged in between the transmitter system (13) and the receiver system (14) in order to compensate the mutual inductance between the transmitter (11) and the receiver (12). The compensation circuit is advantageously operated so that the signal caused by the metal object in this detector is measurable during both at least two measuring sequences (21,22) located within the range of the cut-off peak of the transmitter current and during at least one measuring sequence (23) located outside the range of the cut-off peak of the transmitter current.
Elimination of dietary gluten does not reduce titers of type 1 diabetes-associated autoantibodies in high-risk subjects.

OBJECTIVE Removal of the dietary wheat protein gluten protects against autoimmune diabetes in animal models. Furthermore, elimination of dietary gluten reduces the frequency of type 1 diabetes in patients with celiac disease. Herein we test the hypothesis that gluten is the driving antigen for type 1 diabetes-associated islet autoimmunity. RESEARCH DESIGN AND METHODS Seven autoantibody-positive, first-degree relatives of patients with type 1 diabetes were placed on a gluten-free diet for 12 months followed by gluten reexposure for 12 months. Gliadin antibodies as well as the diabetes-related antibodies insulin autoantibody (IAA), GAD antibody (GADA), and tyrosin phosphatase IA2 antibody (IA-2A) were measured every 3 months; oral glucose tolerance tests were performed every 6 months. Changes in autoantibody titers were compared with those observed in a matched historical cohort. RESULTS A reduction in IgG gliadin antibody titers was observed during the gluten-free period, but titers of diabetes-associated autoantibodies changed independently of gluten exposure. Type 1 diabetes-associated islet autoantibody levels at the end of the gluten-free diet period were not significantly different from those before commencement of the diet (P = 0.2) or at the end of the gluten reexposure period (P = 0.4). Changes in individual subjects were identified, but no differences were noted between the gluten-free and the gluten re-exposure periods, and the changes were similar to those observed in the historical control cohort (P = 1.0). Major titer reductions (>50%) in the gluten-free period were observed in only one subject for all antibodies. Type 1 diabetes developed in this subject and in a second subject during the gluten reexposure period. CONCLUSIONS The findings do not support the hypothesis that gluten is a driving antigen in type 1 diabetes.
Design and Implementation of a Hierarchical Robotic System: A Platform for Artificial Intelligence Investigation

Robots need to act in the real world, but they are constrained by weight, power, and computation capability. Artificial intelligence (AI) techniques try to mimic the clever processing of living creatures, but they lack embodiment and a realistic environment. This thesis introduces a novel robotic architecture that provides slender robots with massive processing and parallel computation potential. This platform allows the investigation and development of AI models (the brain) in interaction with its body and environment. Our robotic system distributes the processing on three biologically correlated layers: the Body, Brainstem, and Cortex; on board the robot, on a local PC, and on a remote parallel supercomputer, respectively. On each layer we have implemented a series of intelligent functions with different computational complexity, including a binaural sound localization technique, a bimodal speech recognition approach using artificial neural networks, and the simulation of biologically realistic spiking neural networks for bimodal speech perception.
Effects of Noise on Identification and Serial Recall of Nonsense Syllables in Older and Younger Adults

ABSTRACT The present experiment investigated the hypothesis that age-related declines in cognitive functioning are partly due to a decrease in peripheral sensory functioning. In particular, it was suggested that some of the decline in serial recall for verbal material might be due to even small amounts of degradation due to noise or hearing loss. Older and younger individuals identified and recalled nonsense syllables in order at a number of different speech-to-noise ratios. Performance on the identification task was significantly correlated with performance on a subsequent serial recall task. However, this was restricted to the case in which the stimuli were presented in a substantial amount of noise. These data show that even small changes in sensory processing can lead to real and measurable declines in cognitive functioning as measured by a serial recall task.
From Total Hits to Unique Visitors Modelfor Election’s Forecasting

Using Internet to predict elections has been a topic of interest for different fields. Researchers from Google have showed an approach employing user’s queries on that search engine [4]. Other site, The Daily Beast, has create an “Election Oracle” [1], scanning 40,000 blogs and social media sites and applying a sentiment analysis to made their predictions. In both these case, the predictions are expressed as a likelihood of winning and not the total amount candidate votes or percent expected. This makes sense because they have applied their methodology to U.S.A elections which are based in a two-party system where one candidate won and the other lose. An multi-party approach was proposed by Tumasjan et al [3], they state that is possible to predict the result by counting the number of Twitter mentions of Political Parties and Candidates. They have tested this idea in 2009 German elections obtaining a similar accuracy of traditional election polls. However, all these methods require an important span of time to be implemented. Moreover, recent studies claim that these kind of techniques could not replace the traditional pools Limits of Electoral Predictions using Social Media Data,[2] setting, among other things, that these algorithms do not offer a methodology to sample data.
Badania koniunktury jako dodatkowe źródło informacji o sytuacji gospodarczej

Uczestnicy działalności gospodarczej na wszystkich szczeblach, działający zarówno w sferze realnej jak i regulacyjnej, nieustannie zgłaszają zapotrzebowanie na informacje. Są one niezbędne dla potrzeb procesów decyzyjnych w celu ograniczania zakresu niepewności i ryzyka. Spośród wszystkich rodzajów informacji, jakie gromadzą podmioty gospodarcze, największe znaczenie mają: prawidłowa diagnoza rzeczywistego przebiegu procesów gospodarczych, trafne prognozy dotyczące przyszłego przebiegu procesów gospodarczych. Przedmiotem rozważań w referacie będzie analiza użyteczności danych, pozyskiwanych w badaniach koniunktury metodą testu dla podmiotów gospodarczych. W szczególności rozważać będziemy użyteczność tych danych dla podmiotów analizujących przebieg procesów gospodarczych i prowadzących politykę gospodarczą. W celu oceny użyteczności tych danych, podejmiemy próbę odpowiedzi na następujące pytania: czy są one w stanie uzupełnić w sposób znaczący zestaw informacji, istotnych zarówno przy podejmowaniu bieżących decyzji gospodarczych jak i rozstrzyganiu dylematów dotyczących przyszłości, czy są one wiarygodne, czy mają własności prognostyczne? W rozważaniach wykorzystane zostaną przede wszystkim doświadczenia z badań prowadzonych w IRG SGH. Ich wyniki były prezentowane zarówno w kraju jak i na arenie międzynarodowej. Za szczególnie inspirujące należy uznać dyskusje prowadzone w gronie członków CIRET-u (Centre for International Research on Economic Tendency Survey), organizacji zrzeszającej główne ośrodki zajmujące się badaniami koniunktury na świecie.
Non-deterministic communication complexity and instance complexity

We study the relationship between non-deterministic communication complexity [8, 9, 4] and instance complexity [7]. For that purpose, the witness of the non-deterministic communication protocol executed by Alice and Bob is interpreted by Alice as a program p that, for t sufficiently large, “corresponds exactly” (see Definition 2) to the instance complexity ic(y : Y1(x)); in the previous expression x and y are the parts of the input known by Alice and Bob respectively and Y1(x) is the set of all values of y such that f(x, y) = 1. The main results of this paper are max|x|=|y|=n{ict(n) yes (y : Y1(x))} = N(f) and max|x|=|y|=n{ic(y : Y1(x))} = N(f) where icyes(a : S) is a variant of instance complexity (see Definition 3) and the non-deterministic communication complexities N(f) and N(f) are defined in [4], Chap. 2. We also present in Sec. 5 a simple inequality relating individual communication complexity with instance complexity.
Rights to Special Services for People with Developmental Disabilities in Sweden

Several major pieces of legislation in Sweden have been developed and enacted during the twentieth century to enable people with disabilities to live as normal a life as possible. The legal instrument is not supposed to depend on political economic trends. Important changes in the new Act on Special Services for Developmentally Disabled Persons from 1986 include qualitative demands and the right to self-determination for these individuals. The special services covered by the law are called social rights. The implementation of these rights is under the jurisdiction of politically appointed councils in counties or municipalities. The decisions made by these authorities can be appealed in administrative courts. Judicial review is supposed to be an instrument for the protection of citizens from the authorities responsible for services. In theory, at least, when one disabled person wins a case in court, the precedent should trickle down to all individuals in similar predicaments. But this does not always occur. One problem is that the law has no sanctions to force local authorities to follow the precedents or to execute court decisions. This article focuses on the Act and on the interplay between court cases and precedents and the decisions made by local authorities.
Learning and Activity Patterns in OSS Communities and their Impact on Software Quality

This paper presents a framework to identify and analyse learning and activity patterns that characterise participation and collaboration of individuals in Open Source Software (OSS) communities. It first describes how participants’ activities enable and drive a learning process that occurs in individual participants as well as in the OSS project community as a whole. It then explores how to identify and analyse learning patterns at both individual level and community level. The objective of such analysis is to determine the impact of these patterns on the quality of the OSS product and define a descriptive approach to quality that is concerned less with standards than with the facts of OSS peer-review and peer-production.
Glomus Tumor of the Trachea Managed by Spiral Tracheoplasty

Patient: Female, 58 Final Diagnosis: Glomus tutor of trachea Symptoms: Hemopthysis Medication: — Clinical Procedure: — Specialty: Otolaryngology Objective: Rare disease Background: Glomus tumors are usually found over the dermis of the extremities, particularly over the subungual region of the fingers, and occurrence in the trachea is an extremely rare event. To date, only 29 cases of tracheal and 2 main bronchus glomus tumors have been reported in the English literature. Our patient is the first ever reported case in Taiwan that was managed by spiral tracheoplasty. Case Report: A 58-year-old woman was admitted to our hospital because of hemoptysis. Computed tomographic (CT) scan revealed a mass over the posterior wall of the trachea. Surgical resection with spiral tracheoplasty was performed due to uncontrolled bleeding and airway compromise. Histopathology and immunostaining confirmed a glomus tumor. Postoperative course was unremarkable and she was discharged in improved condition after 9 days of hospital stay. Conclusions: Although chronic symptom presentation is the rule for tracheal glomus tumors, airway obstruction and bleeding are life-threatening presentations. Histopathological examination and staining are important to differentiate it from hemangiopericytoma or carcinoid tumors. Spiral tracheoplasty after tangential resection may be tried, as this preserves more tracheal tissue, decreases tension, and prevents postoperative leakage at the anastomotic site.
Diversity and adaptive evolution of Saccharomyces wine yeast: a review

Saccharomyces cerevisiae and related species, the main workhorses of wine fermentation, have been exposed to stressful conditions for millennia, potentially resulting in adaptive differentiation. As a result, wine yeasts have recently attracted considerable interest for studying the evolutionary effects of domestication. The widespread use of whole-genome sequencing during the last decade has provided new insights into the biodiversity, population structure, phylogeography and evolutionary history of wine yeasts. Comparisons between S. cerevisiae isolates from various origins have indicated that a variety of mechanisms, including heterozygosity, nucleotide and structural variations, introgressions, horizontal gene transfer and hybridization, contribute to the genetic and phenotypic diversity of S. cerevisiae. This review will summarize the current knowledge on the diversity and evolutionary history of wine yeasts, focusing on the domestication fingerprints identified in these strains.
Embedding Finite Metric Spaces in Low Dimension

This paper presents novel techniques that allow the solution to several open problems regarding embedding of finite metric spaces into Lp. We focus on proving near optimal bounds on the dimension with which arbitrary metric spaces embed into Lp. The dimension of the embedding is of very high importance in particular in applications and much effort has been invested in analyzing it. However, no previous result improved the bound on the dimension which can be derived from Bourgain’s embedding. We prove that any metric space on n points embeds into Lp with distortion O(log n) in dimension O(log n). This provides an optimal bound on the dimension of the embedding. Somewhat surprisingly, we show that a further small improvement is possible at a small price in the distortion, obtaining an embedding with distortion O(log n) in optimal dimension O(θ−1 log n/ log log n), for any θ > 0. It is worth noting that with the small loss in the distortion this improves upon the best known embedding of arbitrary spaces into Euclidean space, where dimension reduction is used. Our techniques also allow to obtain the optimal distortion for embedding into Lp with nearly optimal dimension. For any 1 ≤ p ≤ ∞ and any 1 ≤ k ≤ p, we give an embedding into Lp with distortion O(dlog n/ke) in dimension 2 log n.
Kinesio® Taping in Stroke: Improving Functional Use of the Upper Extremity in Hemiplegia

Abstract The purpose of this article is to present the Kinesio® taping method used to improve the upper extremity function in the adult with hemiplegia. The article discusses various therapeutic methods used in the treatment of stroke patients to achieve a functional upper extremity. The only taping technique for various upper extremity conditions that has been described in the literature is the athletic taping technique. In this article, some interpretation is offered on proper assessment of the nonfunctional upper extremity, including the emphasis on postural alignment, trunk control, and scapula alignment. The Kinesio® taping method in conjunction with other therapeutic interventions may facilitate or inhibit muscle function, support joint structure, reduce pain, and provide proprioceptive feedback to achieve and maintain preferred body alignment. Restoring trunk and scapula alignment after the stroke is critical in an effective treatment program for the upper extremity in hemiplegia.
Electrophysiological Properties of Mutant Nav1.7 Sodium Channels in a Painful Inherited Neuropathy

Although the physiological basis of erythermalgia, an autosomal dominant painful neuropathy characterized by redness of the skin and intermittent burning sensation of extremities, is not known, two mutations of Nav1.7, a sodium channel that produces a tetrodotoxin-sensitive, fast-inactivating current that is preferentially expressed in dorsal root ganglia (DRG) and sympathetic ganglia neurons, have recently been identified in patients with primary erythermalgia. Nav1.7 is preferentially expressed in small-diameter DRG neurons, most of which are nociceptors, and is characterized by slow recovery from inactivation and by slow closed-state inactivation that results in relatively large responses to small, subthreshold depolarizations. Here we show that these mutations in Nav1.7 produce a hyperpolarizing shift in activation and slow deactivation. We also show that these mutations cause an increase in amplitude of the current produced by Nav1.7 in response to slow, small depolarizations. These observations provide the first demonstration of altered sodium channel function associated with an inherited painful neuropathy and suggest that these physiological changes, which confer hyperexcitability on peripheral sensory and sympathetic neurons, contribute to symptom production in hereditary erythermalgia.
Experimental study to elicit effective multimodal behaviour in pedagogical agents

This paper describes a small experimental study into the use of avatars to remediate the lecturer's absence in voice-over-slide material. Four different avatar behaviours are tested. Avatar A performs all the upper-body gestures of the lecturer, which were recorded using a 3D depth sensor. Avatar B is animated using few random gestures in order to create a natural presence that is unrelated to the speech. Avatar C only performs the lecturer's pointing gestures, as these are known to indicate important parts of a lecture. Finally, Avatar D performs "lecturer-like" gestures, but these are desynchronised with the speech. Preliminary results indicate students' preference for Avatars A and C. Although the effect of avatar behaviour on learning did not prove statistically significant, students' comments indicate that an avatar that behaves quietly and only performs some of the lecturer's gestures (pointing) is effective. The paper also presents a simple empirical method for automatically detecting pointing gestures in Kinect recorded lecture data.