Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotional States Associated with Music

We present several interrelated technical and empirical contributions to the problem of emotion-based music recommendation and show how they can be applied in a possible usage scenario. The contributions are (1) a new three-dimensional resonance-arousal-valence model for the representation of emotion expressed in music, together with methods for automatically classifying a piece of music in terms of this model, using robust regression methods applied to musical/acoustic features; (2) methods for predicting a listener’s emotional state on the assumption that the emotional state has been determined entirely by a sequence of pieces of music recently listened to, using conditional random fields and taking into account the decay of emotion intensity over time; and (3) a method for selecting a ranked list of pieces of music that match a particular emotional state, using a minimization iteration method. A series of experiments yield information about the validity of our operationalizations of these contributions. Throughout the article, we refer to an illustrative usage scenario in which all of these contributions can be exploited, where it is assumed that (1) a listener’s emotional state is being determined entirely by the music that he or she has been listening to and (2) the listener wants to hear additional music that matches his or her current emotional state. The contributions are intended to be useful in a variety of other scenarios as well.
Ineffectiveness of Use of Software Science Metrics as Predictors of Defects in Object Oriented Software

Software science metrics (SSM) have been widely used as predictors of software defects. The usage of SSM is an effect of correlation of size and complexity metrics with number of defects. The SSM have been proposed keeping in view the procedural paradigm and structural nature of the programs. There has been a shift in software development paradigm from procedural to object oriented (OO) and SSM have been used as defect predictors of OO software as well. However, the effectiveness of SSM in OO software needs to be established. This paper investigates the effectiveness of use of SSM for: a)classification of defect prone modules in OO software b) prediction of number of defects. Various binary and numeric classification models have been applied on dataset kc1 with class level data to study the role of SSM. The results show that the removal of SSM from the set of independent variables does not significantly affect the classification of modules as defect prone and the prediction of number of defects. In most of the cases the accuracy and mean absolute error has improved when SSM were removed from the set of independent variables. The results thus highlight the ineffectiveness of use of SSM in defect prediction in OO software.
Real-Time Coordination of Electric Vehicles to Support the Grid at the Distribution Substation Level

In this paper, the charging stations (CSs) of electric vehicles (EVs) and their coordination at the substation level are presented. It is considered that the EVs of a particular area arrive at the CS in their idle time to charge their batteries. Fuzzy logic controllers (FLCs) have been designed at the substation and the CS level. The FLC at the substation level decides the amount of power to be compensated by the entire CSs, and the FLC at the CS level determines the power to be exchanged by individual CS. The aggregator at the substation level will distribute the power among the CSs connected to different subfeeders. Also, every subfeeder has an aggregator which distributes the power among different CSs connected to the same subfeeder. Batteries of EVs have been modeled which can handle the capacity loss at different charging/discharging rates (Crate). The Crate of the battery is controlled to achieve the desired rate of power flow between the grid and the EV battery. The main focus of this paper is to coordinate the EVs, present at the CSs, and support the grid by peak shaving and valley filling.
Online news creation, trust in the media, and political participation: Direct and moderating effects over time

This article explores the role of trust in professional and alternative media as (a) antecedents of citizen news production, and (b) moderators of the effect of citizen news production on political participation. Using two-wave panel survey data collected in the United States between December 2013 and March 2014, results show that trust in citizen media predicts people’s tendency to create news. In turn, citizen news production is a positive predictor of both offline and online participation. More importantly, trust in the media moderates the effect of citizen news production over online political participation. Overall, this article highlights the importance of trust in the media with respect to citizen news production and how it matters for democracy. Thus, this study casts a much-needed light on how media trust and citizen journalism intertwine in explaining a more engaged and participatory citizenry.
Identifying the most influential topic-sensitive opinion leaders in online review communities

With the successful adoption of Web 2.0 applications, consumers are increasingly voicing their opinions and concerns, and providing suggestions in online review communities. Consumers who significantly influence the opinions and decisions of others through communicative acts are called opinion leaders. These leaders usually capture the most representative opinions and play a crucial role in electronic word-of-mouth. Since opinion leaders have different expertise and interests, they are typically topic sensitive. In this paper, we discuss the challenges of identifying topic-sensitive opinion leaders in online review communities, and present a two-stage approach. In Stage I, we derive opinion leaders' interest from their tags. In Stage II, we rank leaders according to not only the link structure of networks but also opinion leaders' personal expertise and interests. A preliminary experiment on real-world data indicates the proposed approach is effective.
Testing for symmetry and conditional symmetry using asymmetric kernels

We derive nonparametric tests of symmetry using asymmetric kernels with either vanishing or fixed bandwidths. The idea is to split the sample around the symmetry point and then test whether the distributions to the right and to the left are the same. We show how to extend the approach to examine conditional symmetry by deriving conditions under which our tests are applicable to residuals from semiparametric models with a (sufficiently smooth) nonparametric link function. The latter setting is general enough to entertain as a particular case a unknown symmetry point, which we duely estimate by the sample median. The conditions we derive ensure that the resulting estimation error is asymptotically negligible. Simulations show that the asymptotic tests perform well even in very small samples, entailing better size and power properties than some of the existing symmetry tests.
A Cluster Based Model for Resource Management and Fault Tolerance in Distributed Real-time Systems

We propose a distributed system model based on clusters of processors and processes to manage the resources and provide fault tolerance in a distributed real-time system. At the lowest level, time is managed in a distributed clock synchronization module by a leader process that provides agreement on a common clock value among the representatives of the clusters which then dictate this value to the individual members of each cluster. For fault tolerance in such a system, process groups are used to manage replicates of processes using a similar concept where the ordering of the events is managed by the leader and representatives of process groups of each cluster which then dictate this ordering to every process group member in each cluster. Finally, the static load balancing is performed in two phases; rst the real-time tasks are allocated to clusters of processors and then scheduled within individual clusters to meet deadline constraints
The Costs and Cost-Effectiveness of Mass Treatment for Intestinal Nematode Worm Infections Using Different Treatment Thresholds

Background It is estimated that almost a half of all of people living in developing countries today are infected with roundworms, hookworms, or whipworms or combinations of these types of intestinal nematode worms. They can all be treated using safe, effective, and inexpensive single-dose generic drugs costing as little as USD 0.03 per person treated when bought in bulk. The disease caused by intestinal nematodes is strongly related to the number of worms in the gut, and it is typical to find that worms tend to be aggregated or clumped in their distribution so that <20% of people may harbour >80% of all worms. This clumping of worms is greatest when the prevalence is low. When the prevalence rises above 50%, the mean worm burden increases exponentially, worms are less clumped, and more people are likely to have moderate to heavy infections and may be diseased. Children are most at risk. For these reasons, the World Health Organization (WHO) currently recommends mass treatment of children ≥1 year old without prior diagnosis when the prevalence is ≥20% and treatment twice a year when the prevalence is ≥50%. Methods and Findings The risk of moderate to heavy infections with intestinal nematodes was estimated by applying the negative binomial probability distribution, then the drug cost of treating diseased individuals was calculated based on different threshold numbers of worms. Based on this cost analysis, a new three-tier treatment regime is proposed: if the combined prevalence is >40%, treat all children once a year; >60% treat twice a year; and >80% treat three times a year. Using average data on drug and delivery costs of USD 0.15 to treat a school-age child and USD 0.25 to treat a pre-school child (with provisos) the cost of treating children aged 2–14 years was calculated for 105 low- and low-middle-income countries and for constituent regions of India and China based on estimates of the combined prevalence of intestinal nematode worms therein. The annual cost of the three-tier threshold was estimated to be USD 224 million compared with USD 276 million when the current WHO recommendations for mass treatment were applied. Conclusion The three-tier treatment thresholds were less expensive and more effective as they allocated a greater proportion of expenditures to treating infected individuals when compared with the WHO thresholds (73% compared with 61%) and treated a larger proportion of individuals with moderate to heavy worm burdens, arbitrarily defined as more than 10 worms per person (31% compared with 21%).
SOCIAL SECURITY AND SAVING: NEW TIME SERIES EVIDENCE

This paper reexamines the results of my 1974 paper on Social Security and saving with the help of an additional 21 years of data. The estimates presented here reconfirm that each dollar of Social Security wealth (SSW) reduces private saving by between two and three cents. The parameter estimates for the postwar period and for the entire sample since 1930 are very similar. The correction of the error in the original SSW series between 1958-1971 therefore does not significantly affect the original results. The estimated effect of SSW is robust with respect to the addition of a variety of variables that have been suggested in previous critiques of the original study. In the aggregate, the parameter values imply that the Social Security program currently reduces overall private saving by nearly 60 percent.
Computational Model of Membrane Fission Catalyzed by ESCRT-III

ESCRT-III proteins catalyze membrane fission during multi vesicular body biogenesis, budding of some enveloped viruses and cell division. We suggest and analyze a novel mechanism of membrane fission by the mammalian ESCRT-III subunits CHMP2 and CHMP3. We propose that the CHMP2-CHMP3 complexes self-assemble into hemi-spherical dome-like structures within the necks of the initial membrane buds generated by CHMP4 filaments. The dome formation is accompanied by the membrane attachment to the dome surface, which drives narrowing of the membrane neck and accumulation of the elastic stresses leading, ultimately, to the neck fission. Based on the bending elastic model of lipid bilayers, we determine the degree of the membrane attachment to the dome enabling the neck fission and compute the required values of the protein-membrane binding energy. We estimate the feasible values of this energy and predict a high efficiency for the CHMP2-CHMP3 complexes in mediating membrane fission. We support the computational model by electron tomography imaging of CHMP2-CHMP3 assemblies in vitro. We predict a high efficiency for the CHMP2-CHMP3 complexes in mediating membrane fission.
Characteristics of early vocabulary and grammar development in Slovenian-speaking infants and toddlers: a CDI-adaptation study*

A large body of research shows that vocabulary does not develop independently of grammar, representing a better predictor of the grammatical complexity of toddlers' utterances than age. This study examines for the first time the characteristics of vocabulary and grammar development in Slovenian-speaking infants and toddlers using the Slovenian adaptation of the MacArthur-Bates Communicative Development Inventories (CDI). The sample included 512 Slovenian-speaking infants and toddlers aged 0 ; 8 to 2 ; 6. The findings suggest that between age 0 ; 8 and 2 ; 6 the development of vocabulary is best described using a quadratic function. The results also show that nouns predominate in the vocabularies of infants and toddlers of various ages; as they age and with the increasing size of their vocabularies, the share of interjections decreases and the share of verbs and adjectives increases. The size of vocabulary was also found to be related to the grammatical structure of toddlers' utterances.
BUSSOLA: A Cloud Collaborative Platform of Oriented Services to Passengers

BUS Services Mobilizing Living Lab, namely BUSSOLA, focuses on means of transport for people to make a living lab on the move upon which to design, implement and test innovative services that uses and feeds platform SmartDataNet. In particular, thanks to several sensors and devices, the system pays attention on three main macro-areas: air quality monitoring, passengers monitoring and safety on board the vehicles. A distributed and modular architecture has been adopted, to communicate and manage heterogeneous information. The solution is based on cloud technology for a better flexibility and scalability system and an easier adaptation at future requirements in term of computational resource and storage. It allows to experiment and adopt paradigms typical of the world of the Internet of Things and the Internet of Services, it made available by the platform SmartDataNet starting from the processing of big data and open-data.
A heuristic for widest edge-disjoint path pair lexicographic optimization

Telecommunication services are pervasive in today's human activity and are required to offer reliable and quality-of-service(QoS)-aware guaranteed services. In global path protection, the working path between a source and a destination can be protected by a backup path, which ensures data transfer in the event of a failure that makes the working path to be unavailable. Multipath and disjoint routing may require the calculation of disjoint paths maximizing the total bandwidth of the path pair (or set of paths) or the calculation of maximum-bandwidth disjoint paths. In this paper, a lexicographic optimization problem for obtaining maximum-bandwidth disjoint paths, and then maximizing the bandwidth of the widest path in the pair, is formalized. An effective heuristic for addressing this problem is presented.
Intranet Threat Detection Technology Based on Non-frequent Pattern

The existing network information security is mainly focused on the classification of gateway or network perimeter and so on. The lack of measures relevant to security threat from intranet hosts leads to information divulging with great loss. The intranet should be of high security. And it's a latent threat when the intranet users visit the website with illegal motives. In view of these, the security threat mainly from the intranet is analyzed in the paper. Kripke structure is adopted to describe the mathematical model for intranet security system. Non-frequent pattern discovery algorithm based on matrix is designed. And a new intranet-threat monitoring model, which is suitable for dense network, is proposed. Thus the problem of effective monitoring and warning for intranet security is solved.
CGAS: comparative genomic analysis server

Summary: Comparative approach is one of the most essential methods for extracting functional and evolutionary information from genomic sequences. So far, a number of sequence comparison tools have been developed, and most are either for on-site use, requiring program installation but providing a wide variety of analyses, or for the online search of user's sequences against given databases on a server. We newly devised an Asynchronous JavaScript and XML (Ajax)-based system for comparative genomic analyses, CGAS, with highly interactive interface within a browser, requiring no software installation. The current version, CGAS version 1, provides functionality for viewing similarity relationships between user's sequences, including a multiple dot plot between sequences with their annotation information. The scrollbar-less ‘draggable’ interface of CGAS is implemented with Google Maps API version 2. The annotation information associated with the genomic sequences compared is synchronously displayed with the comparison view. The multiple-comparison viewer is one of the unique functionalities of this system to allow the users to compare the differences between different pairs of sequences. In this viewer, the system tells orthologous correspondences between the sequences compared interactively. This web-based tool is platform-independent and will provide biologists having no computational skills with opportunities to analyze their own data without software installation and customization of the computer system. Availability and Implementation: CGAS is available at http://cgas.ist.hokudai.ac.jp/. Contact: watanabe@ist.hokudai.ac.jp
Service science facing Big Data

The Big Data is a modification of the traditional view of information organization, particularly view of the data warehouses and databases. Nowadays, business organizations must address a mix of structured, unstructured and streaming data that supports queries and reports. Business recognized the wealth of untapped information in open social media data. Therefore, the goal of this paper is to present the procedural approach on how to cope with massive data sets' management. The proposal included in this paper covers service science application.
Hardware Trends: Challenges and Opportunities in Distributed Computing

This article is about three trends in computer hardware, and some of the challenges and opportunities that I think they provide for the distributed computing community. A common theme in all of these trends is that hardware is moving away from assumptions that have often been made about the relative performance of different operations (e.g., computation versus network communication), the reliability of operations (e.g., that memory accesses are reliable, but network communication is not), and even some of the basic properties of the system (e.g., that the contents of main memory are lost on power failure). Section 1 introduces "rack-scale" systems and the kinds of properties likely in their interconnect networks. Section 2 describes challenges in systems with shared physical memory but without hardware cache coherence. Section 3 discusses non-volatile byte-addressable memory. The article is based in part on my talk at the ACM PODC 2014 event in celebration of Maurice Herlihy's sixtieth birthday.
Bioinformatic and Genetic Association Analysis of MicroRNA Target Sites in One-Carbon Metabolism Genes

One-carbon metabolism (OCM) is linked to DNA synthesis and methylation, amino acid metabolism and cell proliferation. OCM dysfunction has been associated with increased risk for various diseases, including cancer and neural tube defects. MicroRNAs (miRNAs) are ∼22 nt RNA regulators that have been implicated in a wide array of basic cellular processes, such as differentiation and metabolism. Accordingly, mis-regulation of miRNA expression and/or activity can underlie complex disease etiology. We examined the possibility of OCM regulation by miRNAs. Using computational miRNA target prediction methods and Monte-Carlo based statistical analyses, we identified two candidate miRNA “master regulators” (miR-22 and miR-125) and one candidate pair of “master co-regulators” (miR-344-5p/484 and miR-488) that may influence the expression of a significant number of genes involved in OCM. Interestingly, miR-22 and miR-125 are significantly up-regulated in cells grown under low-folate conditions. In a complementary analysis, we identified 15 single nucleotide polymorphisms (SNPs) that are located within predicted miRNA target sites in OCM genes. We genotyped these 15 SNPs in a population of healthy individuals (age 18–28, n = 2,506) that was previously phenotyped for various serum metabolites related to OCM. Prior to correction for multiple testing, we detected significant associations between TCblR rs9426 and methylmalonic acid (p = 0.045), total homocysteine levels (tHcy) (p = 0.033), serum B12 (p < 0.0001), holo transcobalamin (p < 0.0001) and total transcobalamin (p < 0.0001); and between MTHFR rs1537514 and red blood cell folate (p < 0.0001). However, upon further genetic analysis, we determined that in each case, a linked missense SNP is the more likely causative variant. Nonetheless, our Monte-Carlo based in silico simulations suggest that miRNAs could play an important role in the regulation of OCM.
On the sum-capacity of the cognitive interference channel with cognitive-only message sharing

Motivated by the ongoing discussion of spectrum scarcity, this paper considers the K-user cognitive interference channel with K - 1 primary/licensed users and one cognitive/secondary user who has non-causal knowledge of the messages of all primary users. This message sharing mechanism is referred to as cognitive-only message sharing. For certain parameter regimes, the sum-capacity of the symmetric Gaussian noise channel is characterized to within an additive constant gap from an outer bound originally derived for a channel model with cumulative message sharing, which consists of one primary user and K-1 cognitive users where cognitive transmitter i ∈ [2 : K] has non-causal knowledge of the messages of the users with index less than i. The approximately optimal achievability scheme is a combination of simultaneous interference neutralization at the primary receivers, dirty-paper coding to remove the effect of interference at the cognitive receiver, and rate-splitting, where the power splits are chosen such that the signals treated as noise are received below the noise floor of the receiver. This shows that “distributed cognition” may not be necessary in the considered network model since (approximately) the same sum-capacity can be achieved by having only one “globally cognitive” user whose role is to manage all the interference in the network.