Miracle-dz/UniFAR-FTUs huggingface dataset:
An image analysis approach for transcription of music played on keyboard-like instruments

Music transcription refers to the process of analyzing a piece of music to generate a sequence of constituent notes and their duration. Transcription of music from audio signals is fraught with problems due to auditory interference such as ambient noise, multiple instruments playing simultaneously, accompanying vocals or polyphonic sounds. For several instruments, there exists added information for music transcription which can be derived from a video sequence of the instrument as it is being played. This paper proposes a method to utilize this visual information for the case of keyboard-like instruments to generate a transcript automatically, by analyzing the video frames. We present encouraging results under varying lighting conditions on different song sequences played out on a keyboard.
Trade Without Law: Private-Order Institutions in Mexican California

Trade prospered in absence of law in California during the 1830s and 1840s. Merchants, through intermerchant trade and the partnerships they organized to buy goods abroad, played a central role in trade. This article examines the private-order institution that facilitated intermerchant trade. The hypothesis is that a particular type of private-order institution, a coalition, a reputation mechanism mitigated the commitment problem inherent in having individuals handle goods that they did not own by linking a merchant's past behavior and his future payoff. Evidence from the merchants' business correspondence supports the hypothesis. A game-theoretic model of a coalition is presented. The model provides insight into the punishment merchants imposed on cheaters, the expansion of the coalition in the 1830s, and its collapse around the time of the gold rush in 1848-1849. Copyright 1997 by Oxford University Press.
Using Log Files to Track Students' Model-based Inquiry in Science

We report on the Modeling Across the Curriculum Project (mac.concord.org), a 5-year study funded by the IERI program (IERI # 0115699). In this project we are using qualitative model-based tools for inquiry in three science domains (Genetics, Gas Laws, & Newtonian Mechanics) to promote scientific literacy on a broad scale, namely, content knowledge, process skills, and epistemologies of science (Perkins, 1986). The process skills we focus on in this project are model-based inquiry skills; epistemological constructs of interest here are students' epistemologies of models as a subset of epistemology of science (Gobert & Discenna, 1997; Schwartz & White, 1999). Our technological infrastructure, Pedagogica™ (Horwitz & Burke, 2002) logs all students' interactions with our hypermodels (Horwitz & Christie, 1999). We use students' log files as performance assessments of model-based inquiry on inquiry tasks called "hot spots" and track changes in inquiry skills over time both within and across domains.
The dose–volume constraint satisfaction problem for inverse treatment planning with field segments

The prescribed goals of radiation treatment planning are often expressed in terms of dose–volume constraints. We present a novel formulation of a dose–volume constraint satisfaction search for the discretized radiation therapy model. This approach does not rely on any explicit cost function. Inverse treatment planning uses the aperture-based approach with predefined, according to geometric rules, segmental fields. The solver utilizes the simultaneous version of the cyclic subgradient projection algorithm. This is a deterministic iterative method designed for solving the convex feasibility problems. A prescription is expressed with the set of inequalities imposed on the dose at the voxel resolution. Additional constraint functions control the compliance with selected points of the expected cumulative dose–volume histograms. The performance of this method is tested on prostate and head-and-neck cases. The relationships with other models and algorithms of similar conceptual origin are discussed. The demonstrated advantages of the method are: the equivalence of the algorithmic and prescription parameters, the intuitive setup of free parameters, and the improved speed of the method as compared to similar iterative as well as other techniques. The technique reported here will deliver approximate solutions for inconsistent prescriptions.
Understanding Image Intensities 1

Traditionally, image intensities have been processed to segment an image into regions or to find edge-fragments. Image intensities carry a great deal more information about three-dimensional shape, however. To exploit this information, it is necessary to understand how images are formed and what determines the observed intensity in the image. The gradient space, popularized by Huffman and Mackworth in a slightly different context, is a helpful tool in the development of new methods. 0. Introduction and Motivation The purpose of this paper is to explore some of the puzzling phenomena observed by researchers in computer vision. They range from the effects of mutual illumination to the characteristic appearance of metallic surfaces—subjects which at first glance may seem to take us away from the central issues of artificial intelligence. But surely if artificial intelligence research is to claim victory over the vision problem, then it has to embrace the whole domain, understanding not only the problem solving aspects, but also the physical laws that underlie image formation and the corresponding symbolic constraints that enable the problem solving. One reason for previous neglect of the image itself was the supposition that the work must surely already have been done by researchers in image processing, pattern recognition, signal processing and allied fields. There are several reasons why this attitude was misadvised: Image processing deals with the conversion of images into new images, usually for human viewing. Computer image understanding systems, on the other hand, must work toward symbolic descriptions, not new images. 1 This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's research is provided in part by the Advanced Research Projects Agency of the Department of Defence under Office of Naval Research contract N00014-75-C-0643. Artificial Intelligence 8 (1977), 201-231 Copyright © 1977 by North-Holland Publishing Company UNDERSTANDING IMAGE INTENSITIES ')C\-1
A Feature-based Framework for Model-Driven Engineering

Model-Driven Engineering (MDE) improves software engi- neering by providing an appropriate level of abstraction for an early review of a system design. Model transformations can be used to estab- lish a well-regulated development process. But existing transformation approaches still lack in connecting system requirements to the models realizing them. Furthermore, it is still dicult to integrate existing tools for particular tasks in MDE to an all-embracing environment. This paper presents a framework for MDE by defining required compo- nents and data structures to establish such an environment. It combines concepts of a UML-based MDE with feature modelling from Product Line Engineering. Feature models capture characteristics of existing sys- tem components as well as requirements of a planned application. They are used to control all parts of the engineering process.
A learning classifier system for emergent team behavior in real-time POMDP

Often the only solution for many complex and dynamic real-world situations is a crucial concurrent cooperation and coordination divided into tasks and subtasks, i.e. team behavior [1]. This research focus on such problems under real-time constraints, distributed control and decentralized knowledge. Existent frameworks and simulation systems were designed relying heavily on a priori knowledge of experts and introducing little or nothing of Machine Learning (ML). Therefore, the goal here is to develop a team of agents inspired by team behavior as found in Nature - emergent and adaptive - applying only ML on the action-selection decision process. Such team would reduce time and resources in the design of autonomous teamwork while keeping equivalent performance in comparison to a heuristic-based approach. Applying unbiased methods and a divide and conquer strategy, we achieved individual actions that emerge into the aimed collective behavior, not once requiring plans, common beliefs or agreed intentions.
The Social Dimensions of Entrepreneurship

Conventional ways of viewing the social aspects of entrepreneurship are considered unsatisfactory; hence, this emphasis is recast in terms of the "entrepreneurial event. " The entrepreneurial event is shaped by groupings of social variables (such as ethnic groups) and the social and cultural environment. The entrepreneurial event is denoted by initiative-taking, consolidation of resources, management, relative autonomy, and risk-taking. The proposed paradigm attempts to include all versions of the entrepreneurial event and all variables (situational, social, and individual) identified with the event. The paradigm will answer two basic questions: what brought about the life-changing event? and why this particular event? Negative information, events, or displacements often lead to entrepreneurial events. The particular action taken depends upon (1) perceptions of desirability (values), and (2) perceptions of feasibility. The utility of the paradigm lies in its application to questions of policy, historical examples, and future research. (TNM)
Pointed lips, thumbs up, and cheek puffs: some emblematic gestures in social interactional and ethnographic context

Emblematic gestures from three distinct locations, the Kuna pointed-lip gesture, the Brazilian thumbs-up gesture, and French breath, lip, and cheek gestures, are studied from the combined perspectives of social interaction and discours analysis and the ethnography of speaking/communication and more general social, political and economic context
Data‐Parallel Decompression of Triangle Mesh Topology

We propose a lossless, single‐rate triangle mesh topology codec tailored for fast data‐parallel GPU decompression. Our compression scheme coherently orders generalized triangle strips in memory. To unpack generalized triangle strips efficiently, we propose a novel parallel and scalable algorithm. We order vertices coherently to further improve our compression scheme. We use a variable bit‐length code for additional compression benefits, for which we propose a scalable data‐parallel decompression algorithm. For a set of standard benchmark models, we obtain (min: 3.7, med: 4.6, max: 7.6) bits per triangle. Our CUDA decompression requires only about 15% of the time it takes to render the model even with a simple shader.
Inferring Relevance from Eye Movements: Feature Extraction

We organize a PASCAL EU Network of Excellence challenge for inferring relevance from eye movements, beginning 1 March 2005. The aim of this paper is to provide background material for the competitors: give references to related articles on eye movement modelling, describe the methods used for extracting the features used in the challenge, provide results of basic reference methods and to discuss open questions in the field.
Intermediate and normal sized CGG repeat on the FMR1 gene does not negatively affect donor ovarian response.

BACKGROUND Fragile X syndrome is associated with low ovarian reserve and poor ovarian response. The aim of this study was to investigate whether CGG repeats on the fragile X mental retardation 1 (FMR1) gene have predictive value for ovarian response to stimulation with gonadotrophins and for clinical outcome in our oocyte donation program. METHODS Oocyte donor candidates were selected according to Instituto Bernabeu oocyte donation program requirements. Fragile X genetic screening was performed in 204 oocyte donors, defining 141 controls and 63 cases: 35-39 repeats (n = 34), 40-45 (n = 12) and >45 (n = 17). All the patients underwent ovarian stimulation using a GnRH antagonist protocol and received a GnRH agonist trigger. The main factors used to measure outcome were oocyte yields, days of stimulation, gonadotrophin dosages, biochemical pregnancy, ongoing pregnancy and miscarriage rates. RESULTS No differences between the study group and controls were reported in oocyte yields (17.5 versus 18.9) or days of stimulation (11.40 versus 9.82). The control group used significantly more gonadotrophin (2212 versus 1850 IU) than the study group. Clinical outcome was not affected by the CGG repeats on the FMR1 gene in oocyte donors. CONCLUSIONS No negative effect was observed for intermediate-sized CGG repeats on ovarian stimulation and clinical outcome using a non-confounding model of oocyte donation. These results disagree with previous studies performed on infertility patients. Owing to the present study, fragile X genetic screening should not be considered for prediction of response to ovarian stimulation.
Neuropsychological and dimensional behavioral trait profiles in Costa Rican ADHD sib pairs: Potential intermediate phenotypes for genetic studies

Attention deficit hyperactivity disorder (ADHD) is associated with substantial functional impairment in children and in adults. Many individuals with ADHD have clear neurocognitive deficits, including problems with visual attention, processing speed, and set shifting. ADHD is etiologically complex, and although genetic factors play a role in its development, much of the genetic contribution to ADHD remains unidentified. We conducted clinical and neuropsychological assessments of 294 individuals (269 with ADHD) from 163 families (48 multigenerational families created using genealogical reconstruction, 78 affected sib pair families, and 37 trios) from the Central Valley of Costa Rica (CVCR). We used principal components analysis (PCA) to group neurocognitive and behavioral variables using the subscales of the Child Behavior Checklist (CBCL) and 15 neuropsychological measures, and created quantitative traits for heritability analyses. We identified seven cognitive and two behavioral domains. Individuals with ADHD were significantly more impaired than their unaffected siblings on most behavioral and cognitive domains. The verbal IQ domain had the highest heritability (92%), followed by auditory attention (87%), visual processing speed and problem solving (85%), and externalizing symptoms (81%). The quantitative traits identified here have high heritabilities, similar to the reported heritability of ADHD (70–90%), and may represent appropriate alternative phenotypes for genetic studies. The use of multigenerational families from a genetically isolated population may facilitate the identification of ADHD risk genes in the face of phenotypic and genetic heterogeneity. © 2015 Wiley Periodicals, Inc.
Stretching DNA with a receding meniscus: Experiments and models.

A detailed experimental and theoretical analysis of the alignment of grafted DNA molecules by a moving meniscus is presented. The existence and extent of the stretching (up to 2.14 times the unstretched length) depends critically on the properties of the surface. Molecules grafted at both ends exhibit a looplike shape which is scale invariant. An elastic model of this process, which we have called molecular combing, is introduced which (a) yields the extension force on various surfaces, ( b) yields a value for the tensile strength of DNA, 476 6 84 pN, and (c) describes the shape of the loops with no fitting parameters.
Improved adaptive ing of coherent interference without spatial smoothing

A new scheme for adaptive nulling in the presence of coherent interference is proposed that finds the weight vector using a nonsquare correlation matrix without spatial smoothing. Conventional schemes, which use square matrices, correspond to specific cases of the new method. It allows us to increase the dimension of the weight vector such that the nulling capability is enhanced. Theoretic performance analysis is made, showing that the output signal-to-interference ratio (SINR) of such a beamformer is proportional to the weight dimension for sidelobe interference. Simulation results confirm this.
GeoMix: scalable geoscientific array data management

Geoscientific array data, such as satellite imagery, geoscientific model, and weather prediction model data, are a significant subset of scientific array data that use geolocation information as index. The sharp growth in the availability of such data demands new data management infrastructures. The traditional relational DBs has problems managing such spatial-array-oriented data due to the limitations of relational algebra(RA) and SQL. In this paper, we investigate this problem and summarize the basic requirements for big geoscientific array data management. Following the requirements, we propose a novel data model in which the geoscientific arrays are modeled as spatial array objects supported by a two-level spatial index. Based on the data model, we implement GeoMix, a geoscientific database system inside IBM Informix, aiming to provide middleware-level support for data management on geoscientific array data. It provides users with a SQL insert/select interface as well as a set of APIs enabling direct data access by native arrays. Last, we show, by a series of experimentations, the power of GeoMix to provide middleware-level support for complex analytics on real satellite imagery and model data.
Networking the political: On the dynamic interrelations that create publics in the digital age

This article argues that the definition of the political and its role in on- and offline public spheres calls for a conceptualization that takes into account the networked connections established between lay and professional political actors, mass media and mobile media. While acknowledging the importance of popular and mass media’s impact on participatory and democratic processes, this article focuses on the cultural citizen and proposes that a rethinking of publics affords a new understanding of the idea of networks as a series of connection points fostering a dynamic and relational view on the political. We illustrate this conceptualization through a case study mapping the agonistic and antagonistic frontiers in communication in a variety of publics and counter-publics in the context of Danish minority culture and politics.
Meningococcal group C conjugate vaccines

In November 1999 the Department of Health introduced a national vaccination programme using newly licensed meningococcal serogroup C conjugate vaccines (MenC). 1 In the largest national mass vaccination campaign ever undertaken in the UK, all people under the age of 18 years are being offered vaccination: three doses for infants as part of the primary vaccination schedule at 2, 3, and 4 months of age; two doses for infants age 4–12 months; and one dose for individuals aged 1–18 years. The cost to the government has not been made public. Vaccination started a year earlier than originally planned and the UK is the only country thus far to have licensed and introduced the vaccine. Prior to the campaign there was no experience of using the vaccine outside the setting of a clinical trial. What is the rationale behind this ambitious programme and what unanswered questions remain? Every paediatrician knows the severity of invasive meningococcal disease and the speed at which previously healthy children can become prostrate. Five major serogroups (A, B, C, Y, and W135) are responsible for the majority of disease, the serogroup being determined by the nature of the capsular polysaccharide. The prevalence of different serogroups varies in different regions and in different age groups. Globally the greatest burden of disease comes from serogroup A which is responsible for massive epidemics in the “meningitis belt” of sub-Saharan Africa and an endemic rate which is more than 10 times that in industrialised countries.2 In much of Western Europe including the UK, more than 90% of disease is caused by serogroups B and C. Serogroup C accounts for 25–40% of cases, with the relative proportion varying in a cyclical manner from year to year. In 1995, there were 1890 reported cases of invasive meningococcal disease, an increase of 43% …
Multiple Representations and Algorithms for Sequence Learning

Kenji Doya, Hiroyuki Nakahara, Raju S. Bapi, and Okihide Hikosaka doya@erato.atr. co.jp, hiro@brain.riken. go.jp, bapics@uohyd.ernet. in, hikosaka@med.juntendo. ac.jp Kawato Dynamic Brain Project, ERATO, Japan Science and Technology Corporation 2-2 Hikaridai, Seika, Soraku, Kyoto 619-0288, Japan Laboratory for Information Synthesis, RIKEN Brain Science Institute, Japan Department of Computer/Information Sciences, University of Hyderabad, India Department of Physiology, School of Medicine, Juntendo University, Japan
2 Decays of the Tau Lepton and Charged Kaon in the Standard Model

From an analysis of the current world averages of the K→ ν̄l l (γ) and τ→ντ K − branching fractions, we derive, within the framework of type II Higgs doublets models such as the Minimal Supersymmetric Extension of the Standard Model, tanβ/mH < 0.21 GeV at a 90% confidence limit.
On Double Domination in Graphs

In a graph G, a vertex dominates itself and its neighbors. A subset S µ V (G) is a double dominating set of G if S dominates every vertex of G at least twice. The minimum cardinality of a double dominating set of G is the double domination number ∞£2(G). A function f(p) is deflned, and it is shown that ∞£2(G) = minf(p), where the minimum is taken over the n-dimensional cube C n = fp = (p1;:::;pn) j pi 2 IR;0 • pi • 1;i = 1;:::;ng. Using this result, it is then shown that if G has order n with minimum degree ‐ and average degree d, then ∞£2(G) • ((ln(1 + d) + ln‐ + 1)=‐)n.