Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining Features Extracted from Audio, Symbolic and Cultural Sources

This paper experimentally investigates the classification utility of combining features extracted from separate audio, symbolic and cultural sources of musical information. This was done via a series of genre classification experiments performed using all seven possible combinations and subsets of the three corresponding types of features. These experiments were performed using jMIR, a software suite designed for use both as a toolset for performing MIR research and as a platform for developing and sharing new algorithms. The experimental results indicate that combining feature types can indeed substantively improve classification accuracy. Accuracies of 96.8% and 78.8% were attained respectively on 5 and 10-class genre taxonomies when all three feature types were combined, compared to average respective accuracies of 85.5% and 65.1% when features extracted from only one of the three sources of data were used. It was also found that combining feature types decreased the seriousness of those misclassifications that were made, on average, particularly when cultural features were included.
Sequential Decoding of Convolutional Codes

This article surveys many variants of sequential decoding in literature. Rather than introducing them chronologically, this article first presents the Algorithm A, a general sequential search algorithm. The stack algorithm and the Fano algorithm are then described in details. Next, trellis variants of sequential decoding, including the recently proposed maximum-likelihood sequential decoding algorithm, are discussed. Additionally, decoding complexity and error performance of sequential decoding are investigated, followed by a discussion on the implementation of sequential decoding from various practical aspects. Moreover, classes of convolutional codes that are particularly appropriate for sequential decoding are outlined. Keywords: coding; decoding; convolutional codes; convolutional coding; sequential decoding; maximum-likelihood decoding
Hubble Space Telescope observations of globular cluster systems along the Hubble sequence of spiral galaxies

We have studied the globular cluster systems of seven giant, edge-on spiral galaxies using Hubble Space Telescope imaging in V and I. The galaxy sample covers the Hubble types Sa to Sc, allowing us to study the variation of the properties of globular cluster systems along the Hubble sequence. The photometry reaches ∼1.5 mag beyond the turn-over magnitude of the globular cluster luminosity function for each galaxy. Specific frequencies of globular clusters (SN values) were evaluated by comparing the numbers of globular clusters found in our WFPC2 pointings with those in our Milky Way that would be detected in the same spatial region if placed at the distance of the target galaxies. Results from this method were found to be consistent with the more commonly used method of constructing radial distribution functions of globular clusters. The SN values of spirals with B/T≲ 0.3 (i.e. spirals with a Hubble type later than about Sb) are consistent with a value of SN= 0.55 ± 0.25. We suggest that this population of globular clusters represents a ‘universal’, old halo population that is present around each galaxy. Most galaxies in our sample have SN values that are consistent with a scenario in which globular cluster systems are made up of (i) the aforementioned halo population plus (ii) a population that is associated with bulges, which grows approximately linearly with the mass of the bulge. Such scenarios include the ‘merger scenario’ for the formation of elliptical galaxies as well as the ‘multi-phase collapse’ scenario, but it seems inconsistent with the ‘secular evolution’ scenario of Pfenniger & Norman, in which bulges are formed from disc stars by means of the redistribution of angular momentum through bar instabilities and/or minor perturbations. However, there is one bulge-dominated spiral galaxy in our sample (NGC 7814) with a low SN value that is consistent with those of the latest-type spirals. This means that the ‘secular evolution’ scenario can still be viable for some bulge-dominated spirals. Thus, our results suggest that the formation histories of galaxy bulges of early-type spirals can be significantly different from one galaxy to another.
Recent development in bioluminescence tomography

Bioluminescence tomography (BLT) is a new molecular imaging tool. Using a modality fusion approach, we built the first BLT prototype to combine BLI data and micro-CT images for proof of concept, established a theoretical framework for BLT, and reported encouraging preliminary results. In this overview, we highlight our key results and discuss further directions
A preliminary attempt to attribute selection using Split-and-Rank tool

In this paper, some preliminary attempt to attribute selection using Split-and-Rank tool were presented. This approach devotes to using three ways of splitting of data into subsets investigated separately. These methods apply sequential, random and random with repetitions split of dataset. Additionally, two methods for threshold of selection were defined. The first one was based on using SVM weight to find important feature, and the second one uses random forest importance to reduce the feature space. Implemented methods were applied on three datasets from UCI machine learning repository and results of classification and AUROC were mostly better after selection than using original datasets.
A Conceptual Model for Segmentation of Multiple Scleroses Lesions in Magnetic Resonance Images Using Massive Training Artificial Neural Network

Detecting abnormalities in medical images is one application of image segmentation. MRI as an imaging technique sensitive to soft tissues such as brain shows Multiple Scleroses lesions as hyper-intense or hypo-intense signals. As manual segmentation of these lesions is a laborious and time consuming task, many methods for automatic brain lesion segmentation have been proposed. To tackle difficulties of Multiple Scleroses lesion segmentation we have proposed a conceptual model based on MTANN, as a method for training artificial neural networks to detect abnormalities in medical images. The proposed model has three main phases namely, Pre-Processing, Segmentation, and False Positive/Negative Reduction. In the segmentation phase, feature extraction and selection are done automatically using MTANN. The Fuzzy Inference System reduce false positives/negatives in the last phase. As advantage of proposed model, it is supposed to produce accurate lesion mask using just FLAIR MRI that reduce computational time and brings comfort for patients.
Assessing the Correlation Between Task-induced Involvement Load, Word Learning, and Learners’ Regulatory Ability

Abstract The present study, using quantitative and qualitative analyses, aimed at delineating the interrelationship between the knowledge of metacognition and the regulation of metacognition, along with the role of learners’ regulatory ability in mediating the effects of task-induced involvement load on word learning. A total of 60 university EFL students were recruited to the study. They first completed a checklist on metacognition and were then assigned to complete three tasks with varying degrees of involvement load followed by a vocabulary test. Of them, 12 students also participated in an interview. The results showed that the two main components of metacognition, i.e., the knowledge and regulation of metacognition, are closely and significantly correlated. The learners, assigned to four different ability groups (LK/LR, LK/HR, HK/LR, HK/HR), were found to benefit most by engaging in a task with the highest involvement load. Despite the benefits, their regulatory ability mediated the effects of task-induced involvement load on word learning, which was corroborated by the interview results. The relevant implications for teaching and learning words through tasks are further discussed.
Roles of Religion and Spirituality Among Veterans Who Manage PTSD and Their Partners

Traumatic events can have ripple effects on the survivor’s intimate relationships and on his or her religious/spirituality (R/S) beliefs and practices. Although both of these outcomes have been examined independently, research has yet to consider the intersection of trauma, its impacts on partners and intimate relationships, and R/S. This exploratory qualitative study involved individual interviews with 20 participants, including 11 male married veterans with posttraumatic stress disorder (PTSD; or subthreshold PTSD) and 9 female married partners of male veterans with PTSD (or subthreshold PTSD). Interviews explored perceptions of the roles of R/S in how participants coped with the veteran’s PTSD, both individually and as a couple. Participants described a wide array of responses in their R/S beliefs and activities, ranging from withdrawal and avoidance to deeper engagement and growth. Although many participants described drawing upon their R/S beliefs and practices to support their spouses, a few shared how female partners used R/S against their veterans in a hurtful manner. Couples described their spiritual bond with one another as facilitating communication and strengthening their relational bond. Implications for psychotherapy and future research are discussed.
Internet QoS and Regulations

This paper investigates Internet service provider (ISP) incentives with a single-service class and with two-service classes in the Internet. We consider multiple competing ISPs who offer network access to a fixed user base, consisting of end-users who differ in their quality requirements and willingness to pay for the access. We model user-ISP interactions as a game in which each ISP makes capacity and pricing decisions to maximize its profits and the end-users only decide which service to buy (if any) and from which ISP. Our model provides pricing for networks with single- and two-service classes for any number of competing ISPs. Our results indicate that multiple service classes are socially desirable, but could be blocked due to the unfavorable distributional consequences that it inflicts on the existing Internet users. We propose a simple regulatory tool to alleviate the political economic constraints and thus make multiple service classes in the Internet feasible.
Heterozygous Mutation of Opa1 in Drosophila Shortens Lifespan Mediated through Increased Reactive Oxygen Species Production

Optic atrophy 1 (OPA1) is a dynamin-like GTPase located in the inner mitochondrial membrane and mutations in OPA1 are associated with autosomal dominant optic atrophy (DOA). OPA1 plays important roles in mitochondrial fusion, cristae remodeling and apoptosis. Our previous study showed that dOpa1 mutation caused elevated reactive oxygen species (ROS) production and resulted in damage and death of the cone and pigment cells in Drosophila eyes. Since ROS-induced oxidative damage to the cells is one of the primary causes of aging, in this study, we examined the effects of heterozygous dOpa1 mutation on the lifespan. We found that heterozygous dOpa1 mutation caused shortened lifespan, increased susceptibility to oxidative stress and elevated production of ROS in the whole Drosophila. Antioxidant treatment partially restored lifespan in the male dOpa1 mutants, but had no effects in the females. Heterozygous dOpa1 mutation caused an impairment of respiratory chain complex activities, especially complexes II and III, and reversible decreased aconitase activity. Heterozygous dOpa1 mutation is also associated with irregular and dysmorphic mitochondria in the muscle. Our results, for the first time, demonstrate the important role of OPA1 in aging and lifespan, which is most likely mediated through augmented ROS production.
Optimal Peer Selection, Task Assignment and Rate Allocation for P2P Downloading

In a peer to peer file sharing system, there are usually multiple peers which store the copies of a requested file, and these peers may charge different costs for resource sharing. Moreover, the peers in the system are often connected in a network with heterogeneous link bandwidths. We propose two optimal algorithms for P2P file downloading, both based on the network flow theory. The first algorithm guarantees that the requested file can be downloaded in the shortest time,and the second algorithm guarantees that the file downloading can be done in the shortest time with the lowest cost. In both algorithms, the peer selection, task assignment and rate allocation problems are solved jointly, and duplicate downloading is avoided. Finally, we give a complexity analysis of the proposed algorithms.
Author Reply: Illuminating the Health Benefits of Psychological Assets

This reply addresses observations of Drs. Larsen, Kruse, and Sweeny, and Scherer in their reviews of our published work on the link between positive psychological assets and outcomes of physical health. Inspired by Obama’s Precision Medicine Initiative we argue that the interplay between the emotion spectrum and health is likely a complex and heterogeneous amalgam of known and yet unidentified elements melding at the individual level. When exploring the emotion–health link, researchers are challenged to grapple with complex system models by considering multiple hierarchies of information that span individual-level factors, genetic blueprints, and cultural and environmental context. Research is needed to more fully elucidate the mechanism through which emotion influences health, with careful consideration of differences across race/ethnicity, culture, and context.
Exchange Rate Fluctuations and Trade Flows: Evidence from the European Union

This paper analyzes the effects of exchange rate volatility on bilateral trade flows. Through use of a gravity model and panel data from western Europe, exchange rate uncertainty is found to have a negative effect on international trade. The results seem to be robust with respect to the particular measures representing exchange rate uncertainty. Particular attention is reserved for problems of simultaneous causality, stemming from the endogenous behavior of monetary authorities. The negative correlation between trade and bilateral volatility remains significant after controlling for the simultaneity bias.
Democracy : Order out of Chaos Understanding Power-Law in Indonesian Elections

We construct a majority cellular automata based model to explain the power-law signatures in Indonesian general election results. The understanding of second-order phase transitions between two different conditions inspires the model. The democracy is assumed as critical point between the two extreme socio-political situations of totalitarian and anarchistic social system – where democracy can fall into the twos. The model is in multi-party candidates system run for equilibrium or equilibria, and used to fit and analyze the three of democratic national elections in Indonesia, 1955, 1999, and 2004.
A dynamic priority assignment strategy for real-time task

Most of the real-time task scheduling algorithms assign the priorities of tasks according to their three attributes, deadlines, slack times and value(density), but seldom synthetically analyze the effects of the three factors on the priorities of tasks. This paper studies the dynamic value density and urgency of a task by studying its three attributes, and based on which, a dynamic priority assignment strategy, DPA, is proposed. In this strategy, two parameters p and q are used to adjust the weight that the value density and urgency of a task impact on its priority. Finally, the result of simulations shows that a scheduler using DPA strategy could improve the gained-value of the system, reduce the deadline miss ratio.
Querying Schemas With Access Restrictions

We study verification of systems whose transitions consist of accesses to a Web-based data-source. An access is a lookup on a relation within a relational database, fixing values for a set of positions in the relation. For example, a transition can represent access to a Web form, where the user is restricted to filling in values for a particular set of fields. We look at verifying properties of a schema describing the possible accesses of such a system. We present a language where one can describe the properties of an access path, and also specify additional restrictions on accesses that are enforced by the schema. Our main property language, AccLTL, is based on a first-order extension of linear-time temporal logic, interpreting access paths as sequences of relational structures. We also present a lower-level automaton model, A-automata, which AccLTL specifications can compile into. We show that AccLTL and A-automata can express static analysis problems related to "querying with limited access patterns" that have been studied in the database literature in the past, such as whether an access is relevant to answering a query, and whether two queries are equivalent in the accessible data they can return. We prove decidability and complexity results for several restrictions and variants of AccLTL, and explain which properties of paths can be expressed in each restriction.
Studies on Extremal Segments in Random Sequences

We review our main findings on the size distribution of the largest neutral segments in a sequence of N randomly charged monomers. Upon mapping to one– dimensional random walks (RWs), this corresponds to finding the probability distribution for the size L of the largest segment that returns to its starting position in an N–step RW. Using analytical, exact enumeration, and Monte Carlo methods, we reveal the complex structure of the probability distribution in the large N limit. In particular, the size of the longest neutral segment has a distribution with a square-root singularity at ` ≡ L/N = 1, an essential singularity at ` = 0, and a discontinuous derivative at ` = 1/2.
CP-recursion and the derivation of verb second in Germanic main and embedded clauses

his paper will give an overview of the verb second (V2) phenomenon, as found in both main and embedded clauses in Germanic, and it will also explore a particular derivation of (embedded) V2, in terms of a cP/CP-distinction. All the Germanic languages except modern English (but including e. g. Old English) are V2, i. e. in all declarative main clauses and in all wh-questions, the inite verb is in the second position, regardless of whether the irst position is occupied by the subject or by some other constituent. his can be extended to yes/no-questions, provided it is assumed that the irst position in such questions is empty (and such an assumption is supported by the fact that it allows an account for Greenberg’s 1963: 83 “Universal 11”, cf. Vikner 2007). No particular type of embedded clause in Germanic ever requires V2, and although V2 is optionally possible in many embedded clauses, this is normally not the case for all types of embedded clauses, as e. g. embedded questions (almost) never allow V2 (Julien 2007, Vikner 2001, though see McCloskey 2006 and Biberauer 2015). As in Nyvad et al. (2016), I will explore a particular derivation of (embedded) V2, in terms of a cP/ CP-distinction, which may be seen as a version of the CP-recursion analysis (deHaan & Weerman 1986, Vikner 1995 and many others). he idea is that because embedded V2 clauses do not allow extraction, whereas other types of CP-recursion clauses do (Christensen et al. 2013a; Christensen et al. 2013b; Christensen & Nyvad 2014), CP-recursion in embedded V2 is assumed to be fundamentally diferent from other kinds of CP-recursion, in that main clause V2 and embedded V2 involve a CP (“big CP”), whereas other clausal projections above IP are instances of cP (“litle cP”).
Projective Quantum Spaces

Associated to the standard SUq(n) R-matrices, we introduce quantum spheres S q , projective quantum spaces CP n−1 q , and quantum Grassmann manifolds Gk(C n q ). These algebras are shown to be homogeneous spaces of standard quantum groups and are also quantum principle bundles in the sense of T. Brzeziński and S. Majid [1].
Ar Source Modeling Based on Spatiotemporally Diverse Multichannel Outputs and Application to Multimicrophone Dereverberation

In this paper, we consider the blind multichannel dereverberation problem for a single source. The multichannel reverberation impulse response is assumed to be stationary enough to allow estimation of the correlations it induces from the received signals. It is well-known that a single-input multi-output (SIMO) filter can be equalized blindly by applying multichannel linear prediction (LP) to its output when the input is white. When the input is colored, the multichannel linear prediction will both equalize the reverberation filter and whiten the source. We exploit the channel's spatiotempo- ral diversity to estimate the source correlation structure, which can hence be used to determine a source whitening filter. Multichannel linear prediction is then applied to the sensor signals filtered by the source whitening filter, to obtain pure source dereverberation. A key parameter in this dereverberation scheme is the order of the source whitening filter. It determines the tradeoff between the modeling error (limited source whitening) and the estimation error (due to the blind estimation of the source correlations). In this paper we propose, using a statistical room reverberation model, a design to optimize the whitening order (function of the room characteristics, and the number of sub-channels).
Lightning response to smoke from Amazonian fires

The effect of anthropogenic aerosols on clouds has the potential to be a key component for climate change predictions, yet is one of the least understood. It is possible that high aerosol loading can change the convection intensity and hence the electrical activity of thunderstorm clouds. Focusing on the Amazon dry season, where thousands of man‐made forest fires inject smoke into the atmosphere, we studied the aerosol effects on thunderclouds. We used the ground‐based World‐Wide Lightning Location Network (WWLLN) lightning measurements together with Aqua‐MODIS aerosol and cloud data to show evidence for the transition between two opposing effects of aerosols on clouds. The first is the microphysical effect which is manifested in an increase in convective intensity (and electrical activity), followed by the radiative effect that becomes dominant with the increase in aerosol loading leading to a decrease in convective intensity.
Using DVFS to optimize time Warp simulations

Some emerging high performance many-core chips have support to enable software control of an individual core's operating frequency (and voltage). These controls can potentially be used to optimize execution for either performance (accelerating the critical path) or power savings (green computing). In Time Warp parallel simulators using the Virtual Time synchronization paradigm, some cores may be executing events that are well off the critical path and likely to be undone. In this work, we explore the adjustment of operating frequencies of cores executing on and off the critical path to reduce rollback and power consumption, while maintaining or, in some cases, enhancing performance.