Miracle-dz/UniFAR-FTUs huggingface dataset:
From Heuristics-Based to Data-Driven Audio Melody Extraction

The identification of the melody from a music recording is a relatively easy task for humans, but very challenging for computational systems. This task is known as “audio melody extraction”, more formally defined as the automatic estimation of the pitch sequence of the melody directly from the audio signal of a polyphonic music recording. This thesis investigates the benefits of exploiting knowledge automatically derived from data for audio melody extraction, by combining digital signal processing and machine learning methods. We extend the scope of melody extraction research by working with a varied and realistic set of data, and considering multiple definitions of melody. We first present an extensive overview of the state of the art, and perform an evaluation on a novel symphonic music melody extraction dataset. Results show that most approaches are not able to generalise well to the characteristics of such data, which presents a high pitch range. A pitch salience function based on sourcefilter modelling is found to be specially useful in such context. We then propose its integration with melody tracking methods based on pitch contour characterisation, and evaluate them on a wide range of music genres. Firstly, this salience function is adapted for pitch contour creation by combining it with another one based on harmonic summation. This combination increases the salience of melody pitches and improves melody extraction accuracy over previous approaches, with two different contour-based melody tracking methods: pitch contour selection based on heuristic rules, and supervised pitch contour classification. Secondly, the latter approach is further improved by using novel timbre, tonal and spatial features, which are helpful to discriminate melodic from non-melodic pitch contours. Finally, we also propose a method for the estimation of multiple melodic lines based on pitch contour classification, which exploits continuity within melodic lines. The combination of supervised and unsupervised approaches leads to advancements on melody extraction and shows a promising path for future research and applications.
Fast modeling of structural uncertainty by means of image dilation in the depositional domain

Among various sources of uncertainty in reservoir modeling, structural uncertainty is often underrepresented. Evaluating different faulting scenarios requires gridding each of these scenarios. Preserving the structural geological realism requires careful consideration of structural hierarchy and abutting relationships. Enforcing such relationships often requires manual editing results. In this report, we propose a proxy method to efficiently represent uncertainty in structural modeling by building fault scenarios in the depositional grid, which is often a simple Cartesian grid. In this way accuracy (building actual complex fault models) is traded off for the ability to study uncertainty. A bottleneck in properly modeling structural uncertainty is caused by representation of faults as explicit surfaces. This is resolved in this report with the proxy method by representing a faulting scenario as a fault block map which represents the compartments created in a reservoir by faults as a property on a Cartesian grid. These compartments defined on a Cartesian grid are easier to manipulate, allow for fast generation of geologically consistent fault network realizations. Faults bounding these compartments are represented as transmissibility multipliers on the Cartesian grid taking into account their throw. Another bottleneck associated with structural uncertainty evaluation comes at the stage of simulating flow through a faulted reservoir. Running simulations on physical domain where the grid is deformed with respect to fault throws is hard to achieve due to grid cell geometries around faults. Utilizing state-of the-art flow diagnostics on the Cartesian domain instead of a relatively slow finite element reservoir simulator on the physical domain allows the rapid evaluation and selection of fault networks for uncertainty quantification of forecasts. In order to showcase the main functionalities of the proxy method, first, a small field example is used with small number of faults, where the full exploration of uncertainty is compared with uncertainty derived from the proxy method.
Mutual information network-based support vector machine for identification of rheumatoid arthritis-related genes

In recent years, the underlying roles of significant genes in the pathogenesis of rheumatoid arthritis (RA) have greatly aroused the interest of clinicians and researchers. In the current study, we aimed to identify the potential biomarkers of RA via mutual information network-based support vector machine (SVM) classifier. Firstly,microarray data E-GEOD-45291 was downloaded from ArrayExpress database. Next, differentially expressed genes (DEGs) identification was implemented. The differential pathways genes (DPGs) which were enriched in differential pathways were then screened through attract method. Subsequently, the mutual information network was constructed on the basis of the DPGs through context likelihood of relatedness (CLR) algorithm. Simultaneously, hub genes of the mutual information network were screened, followed by the extraction of the intersection of hub genes and DEGs (named as inter genes). Finally, the classification and evaluation via SVM with linear kernel was performed. Based on the results, we found that a total of 339 DEGs and 448 DPGs were screened. There were 54 hub genes. Then, 8 inter genes were identified such as mitogen-activated protein kinase kinase 2 (MAP2K2), tumor necrosis factor receptor (TNFR)-associated death domain (TRADD), BH3 interacting domain death agonist (BID) and so on. Accordingly, these 8 genes can classify unknown samples from patients with the highest AUC score of 1.00, MCC score of 1.00, specificity of 1.00, and sensitivity of 1.00. Our analysis might provide a novel insight into the pathogenic processes in RA. MAP2K2, TRADD and BID might be attractive biomarkers for the diagnosis and therapeutic intervention of RA.
Initiation of pharmacist–psychiatrist collaborative patient education in ambulatory care settings of a tertiary care teaching hospital in south India

The aim of this study is to initiate the pharmacist–psychiatrist collaborative patient education in ambulatory care settings. A prospective cohort study was conducted in psychiatry out-patient department of a tertiary care teaching hospital over a period of 6 months. All the eligible patients were enrolled, and the necessary information was collected. The collected data were analyzed for medication adherence by using medication adherence rating scale and healthrelated quality of life by using the World Health Organization Quality of Life questionnaire. Student t-test was used to analyze the results at p-value <0.05. A total of 210 patients were analyzed and followed for a period of 6 months. When compared to the baseline values, a significant improvement in medication adherence and quality of life with each follow-up at p-value <0.05 was observed. The study results have evidently proven that pharmacist–psychiatrist collaborative approach could significantly improve patient education and related clinical outcomes.
1 Analysis of the relationship between emotional 2 intelligence , resilience and family functioning in 3 adolescent sustainable use of alcohol and tobacco 4

The use of alcohol and tobacco is related to several variables which act as risk or protective 12 factors, depending on the circumstances. The objectives of this study were to analyze the 13 relationship between emotional intelligence, resilience and family functioning in adolescent use of 14 alcohol and tobacco and to find emotional profiles for their use considering self-concept. The sample 15 was made up of 317 high school students aged 13 to 18 who filled out the Brief Emotional 16 Intelligence Inventory, the Resilience Scale for Adolescents, the APGAR Scale, the Alcohol 17 Expectancy Questionnaire Adolescents and the Five-Factor Self-Concept Questionnaire. The 18 results revealed that emotional intelligence and resilience, specifically, stress management and 19 family cohesion were significant in the group of nonusers. Family functioning acts as a predictor 20 factor for onset of use of tobacco and alcohol. Positive expectancies about drinking alcohol were 21 found to be a risk factor and the intrapersonal factor to be protective. Both stress management and 22 family cohesion were protective factors against smoking. Furthermore, cluster analysis revealed 23 emotional profiles for users of both substances based on self-concept. Finally, the importance of the 24 direction of the relationship between the variables studied for intervention in this problem should 25 be mentioned. Responsible use by improving adolescent decision-making is one of the results 26 expected from this type of intervention. 27
Python Driver Driver SDF 2 Feature Generation Feature Normalization Classification Dimensionality Reduction SDF 1 Filtering and Decimation Detrending PythonLibraries and Middleware Application

Brain activity is more and more used for innovative applications like Brain Computer Interfaces (BCIs). However, in order to be able to use the brain activity, the related psychophysiological data has to be processed and analyzed with sophisticated signal processing and machine learning methods. Usually these methods have to be calibrated with subject-specific data before they can be used. Since future systems that implement these methods need to be portable to be applied more flexible tight constraints regarding size, power consumption and computing time have to be met. Field Programmable Gate Arrays (FPGAs) are a promising solution, which are able to meet all the constraints at the same time. Here, we present an FPGA-based mobile system for signal processing and classification. In addition to other systems, it is able to be calibrated and adapt at runtime, which makes the acquisition of training data unnecessary.
Working Papers / Documents de travail WP 2014-Nr 04 Liquidity Constraints , Fiscal Externalities and Optimal Tuition Subsidies

A large body of theoretical and empirical research focuses on two very different rationales for government subsidies to college students: positive fiscal externalities from greater human capital accumulation and a larger income tax base, and the existence of liquidity constraints among student borrowers. This paper provides a first attempt to gauge the relative importance of these two mechanisms. I use two different modelling approaches, both of which use US data on the effects of income and tuition subsidies on college enrollment to discipline the analysis: calibration of a simple structural model of human capital accumulation, and a “sufficient statistics” approach that employs behavioral elasticities within a social welfare optimality condition. The results imply optimal subsidies that are quite large, of a magnitude similar to median tuition at public universities. This finding is almost entirely driven by the fiscal externality channel, indicating that optimal tuition subsidy policy is not sensitive to the extent of liquidity constraints among students.
Source ! Target Incorrect Predicted aunt ! тетя бабушка ( Grandmother ) uruguay ! уругвая аргентины ( Argentina ) regiments ! полков кавалерийские

Recent work on bilingual lexicon induction (BLI) has frequently depended either on aligned bilingual lexicons or on distribution matching, often with an assumption about the isometry of the two spaces. We propose a technique to quantitatively estimate this assumption of the isometry between two embedding spaces and empirically show that this assumption weakens as the languages in question become increasingly etymologically distant. We then propose Bilingual Lexicon Induction with Semi-Supervision (BLISS) — a semi-supervised approach that relaxes the isometric assumption while leveraging both limited aligned bilingual lexicons and a larger set of unaligned word embeddings, as well as a novel hubness filtering technique. Our proposed method obtains state of the art results on 15 of 18 language pairs on the MUSE dataset, and does particularly well when the embedding spaces don’t appear to be isometric. In addition, we also show that adding supervision stabilizes the learning procedure, and is effective even with minimal supervision. ⇤
TVA 8 immobilised by adsorption on optical fibre

Physico–chemical models of the interactions of cells with solid surfaces, which use contact angles and zeta potentials, indicated more facile adsorption of cells of Pseudomonas putida TVA8 on the quartz surface after its treatment with 3-aminopropyltriethoxysilane (APTES). A whole-cell optical fibre sensor of toluene was prepared by the adsorption of P. putida TVA8, bacteria producing light in contact with toluene on the wider end of APTEStreated quartz tapered optical fibre. The results of the measurements of luminescence from both sides of the layer of adsorbed cells were compared. Over the 135 days trial, the fibre biosensor was repetitively induced with toluene solution (26.5 mg L−1) 68 times. The intensities of bioluminescence gradually decreased due to release of the adsorbed cells and they were only temporarily restored by the addition of nutrients. The intensities of bioluminescence induced with contaminated ground water were lower than in the mineral medium (MSM) with the same content of toluene. c © 2016 Institute of Chemistry, Slovak Academy of Sciences
Gangsters and Pranksters : The Art of Thievery “ : A Multiplayer Stealth Game in the Context of the Generation of Dynamic Replay Videos

The projekt “Gangsters and Pranksters: The Art of Thievery“, which I worked on in cooperation with colleague Alexander Bayer, has two goals: On the one hand, it shall work at its own as an entertaining multiplayer stealth game for up to four human players, on the other hand it was planned from scratch to be fully compatible with the „Surveillance System“ developed by Peter Mindek and his colleagues for automatically generating dynamic replay videos. This thesis concentrates on the topics user interface, virtual architecture, level design, texturing and creation of an event hierarchy.
Headache patients ’ satisfaction with telemedicine : a 12-month follow-up randomized non-inferiority trial

doi:10.1111/ene.13294 Background and purpose: We investigated non-acute headache patients’ longterm satisfaction with a telemedicine consultation and consultation preferences in northern Norway. We hypothesized that patients were not less satisfied with telemedicine than traditional consultations. We also examined the influence of gender, age and education on satisfaction. Methods: For 2.5 years, patients were consecutively screened, recruited and randomly assigned to telemedicine or traditional visits with a consultation at a neurological outpatient department. The primary endpoint was frequency of satisfied patients at 3 and 12 months. Secondary endpoints were satisfaction with consultation, communication, information, diagnosis, advice and prescriptions, and preferred visit form at 12 months. Results: Of 402 participants, 279 (69.4%) answered questionnaires at both 3 and 12 month, and 291 (72.4%) responded at 12 months. The long-term satisfaction of telemedicine patients was 124/145 (85.5%) compared with 118/134 (88.1%) in the traditional group (P = 0.653). The groups did not differ with respect to secondary endpoints, but females were more satisfied with telemedicine communication (P = 0.027). In the telemedicine group, 99/147 (67.3%) were indifferent to the type of consultation. Age and education did not alter the primary results. Conclusions: At 1 year after a specialist evaluation for headache, telemedicine patients did not express less satisfaction than those with traditional consultation. Telemedicine specialist consultations may be a good alternative for headache patients in secondary care.
Spiny-tailed Iguanas , Insular Evolution , and Seri Indians : How Long Does it Take to Make a New Species and Does it Matter Who Makes it ?

The purpose of this application is to conserve the long used and well known specific name of Sauromalus obesus (Baird, 1858) for the chuckwalla (family IGUANIDAE) from the southwest of North America by giving it precedence over the little used name S. ater Duméril, 1856.
4 o Ecological boundary detection using Bayesian areal wombling

The study of ecological boundaries and their dynamics is of fundamental importance to much of ecology, biogeography, and evolution. Over the past two decades, boundary analysis (of which wombling is a subfield) has received considerable research attention, resulting in multiple approaches for the quantification of ecological boundaries. Nonetheless, few methods have been developed that can simultaneously (1) analyze spatially homogenized data sets (i.e., areal data in the form of polygons rather than point-reference data); (2) account for spatial structure in these data and uncertainty associated with them; and (3) objectively assign probabilities to boundaries once detected. Here we describe the application of a Bayesian hierarchical framework for boundary detection developed in public health, which addresses these issues but which has seen limited application in ecology. As examples, we analyze simulated spread data and the historic pattern of spread of an invasive species, the hemlock woolly adelgid (Adelges tsugae), using county-level summaries of the year of first reported infestation and several covariates potentially important to influencing the observed spread dynamics. Bayesian areal wombling is a promising approach for analyzing ecological boundaries and dynamics related to changes in the distributions of native and invasive species.
Market Centered Model of the Early Phases of SW Product Development

How to apply user centeredness in the early phases of software product development? How to make the process of innovating new products more efficient and at the same time finding better fit with the product and the possible user needs? A new model is introduced for the early phases of product development of software products. It is based on a generic phase model ideas from (physical) product development complementing it with the special features of software development. The model is leaning on three inductively derived core concepts. Development processes are seen as continuing processes compared to one time design phase of physical products. The model of market development of technology adoption is used as a strategic tool. And finally, the development of a software product is seen as a process of concretising the vision of the product. The model is needed in order to start research on the interaction between different stakeholders during these early phases of software product development.
Quantum Alice and Silent Bob: Qubit-Based Quantum Key Recycling With Almost No Classical Communication

We answer an open question about Quantum Key Recycling (QKR): Is it possible to put the message entirely in the qubits without increasing the number of qubits compared to existing QKR schemes? We show that this is indeed possible. We introduce a prepare-and-measure QKR protocol where the communication from Alice to Bob consists entirely of qubits. As usual, Bob responds with an authenticated one-bit accept/reject classical message. Compared to Quantum Key Distribution (QKD), QKR has reduced round complexity. Compared to previous qubit-based QKR protocols, our scheme has far less classical communication. We provide a security proof in the universal composability framework and find that the communication rate is asymptotically the same as for QKD with one-way postprocessing.
Cerebral abnormalities in infants with myelomeningocele Nieprawid 3 owoœci mózgu u niemowl 1 t z przepuklin 1 oponowo-rdzeniow 1

Background and purpose: We evaluated brain abnormalities associated with myelomeningocele in infants. Material and methods: Between June 1995 and June 2008, 42 patients with myelomeningocele were treated in our hospital. Only 24 patients (13 males, 11 females, mean age 1.5 months, range 1 day – 11 months) were evaluated by both spinal and brain magnetic resonance imaging (MRI) and were enrolled in the study. Results: Brain MRI revealed: hydrocephalus in 21 (87.5%) patients, all of whom required immediate shunting. Total agenesis of the corpus callosum was observed in 2 (8.3%) patients, partial agenesis was seen in 4 (17%) patients and 8 (34%) patients had dysplasia of the corpus callosum. Absence of the septum pellucidum was observed in 2 (8%) patients. Widening of the interhemispheric fissure and colpocephaly were noted in 10 (41%) and in 3 (12%) patients, respectively. Abnormal white matter maturation was observed in 2 (8%) patients. Small posterior fossa was observed in 18 (74%) patients, Chiari malformation in 16 (67%) patients, cerebellar and brain stem hypoplasia in 3 (12%) and 7 (30%) patients, respectively. Conclusions: MRI examination of the myelomeningocele site is not sufficient. Clinicians should consider obtaining imaging studies of the entire neuraxis in patients with myelomeningocele.
Ondulé: Designing and Controlling 3D Printable Springs

We present Ondulé-an interactive design tool that allows novices to create parameterizable deformation behaviors in 3D-printable models using helical springs and embedded joints. Informed by spring theory and our empirical mechanical experiments, we introduce spring and joint-based design techniques that support a range of parameterizable deformation behaviors, including compress, extend, twist, bend, and various combinations. To enable users to design and add these deformations to their models, we introduce a custom design tool for Rhino. Here, users can convert selected geometries into springs, customize spring stiffness, and parameterize their design with mechanical constraints for desired behaviors. To demonstrate the feasibility of our approach and the breadth of new designs that it enables, we showcase a set of example 3D-printed applications from launching rocket toys to tangible storytelling props. We conclude with a discussion of key challenges and open research questions.
Operating System Support for Virtual Machines

A virtual-machine monitor (VMM) is a useful technique for adding functionality below existing operating system and application software. One class of VMMs (called Type II VMMs) builds on the abstractions provided by a host operating system. Type II VMMs are elegant and convenient, but their performance is currently an order of magnitude slower than that achieved when running outside a virtual machine (a standalone system). In this paper, we examine the reasons for this large overhead for Type II VMMs. We find that a few simple extensions to a host operating system can make it a much faster platform for running a VMM. Taking advantage of these extensions reduces virtualization overhead for a Type II VMM to 14-35% overhead, even for workloads that exercise the virtual machine intensively.
Background subtraction with convolutional neural network and oversegmentation

Background subtraction in video is an important computer vision problem as it serves as a first step in many video analysis algorithms, yet it cannot be considered to be fully solved due to complexity and variety of input data from surveillance cameras. In this work we propose a background subtraction method based on a random sample background model [14] using a convolutional neural network to compare image patches with the background model. To improve the quality of stopped objects detection we utilize oversegmentation of input frames, obtained superpixels are also used at postprocessing step. Experimental evaluation on ChangeDetection.net dataset shows superiority of the proposed algorithm compared to analogues.