Miracle-dz/UniFAR-FTUs huggingface dataset:
MusicSun: A New Approach to Artist Recommendation

MusicSun is a graphical user interface to discover artists. Artists are recommended based on one or more artists selected by the user. The recommendations are computed by combining 3 different aspects of similarity. The users can change the impact of each of these aspects. In addition words are displayed which describe the artists selected by the user. The user can select one of these words to focus the search on a specific direction. In this paper we present the techniques used to compute the recommendations and the graphical user interface. Furthermore, we present the results of an evaluation with 33 users. We asked them, for example, to judge the usefulness of the different interface components and the quality of the recommendations.
Invasive Group B Streptococcal Infections in Infants, France

Clinical features and molecular characterization of 109 group B streptococci causing neonatal invasive infections were determined over an 18-month period in France. Sixty-four percent of the strains were from late-onset infections, and 75% were capsular type III. The hypervirulent clone ST-17 was recovered in 80% of meningitis cases.
Improvisation as a Meta-Counseling Skill

ABSTRACT Counselor education tends to see the development of basic counseling and communication skills as the foundation of clinical training. Improvisation has historically and primarily been connected to theater training and as a performance mechanism. By developing skills in spontaneity and the nature of narrative (or story) one becomes more able to be in-the-moment with a client or clients and thus less anxious and more able to meet the client where they are. As such, improvisation can really be seen as a meta-counseling skill—a skill that can form a firmer foundation for the learning of the basic counseling and communication micro-skills. This article outlines the core concepts of improvisational training for counselors and includes examples of improvisational games that can specifically help in preparing counselor trainees for their future clinical work.
Segmentation of hyperspectral images using phase correlation based on adaptive thresholding

This letter presents hyperspectral image segmentation based on the phase-correlation measure and updating the segments using a post processing operation based on adaptive thresholding. Spectral signature of each pixel is subsampled to gain robustness against noise and spatial variability, and phase correlation is performed to measure spectral similarity. Similar and dissimilar pixels are decided according to the peak value of the phase correlation result to determine pixels that fall into the same segments. An adaptive threshold value that is determined for each segment considering in-segment similarity distribution is used to update the segment. Segmentation accuracy is increased compared to phase correlation based segmentation.
Early Enriched Environment Promotes Neonatal GABAergic Neurotransmission and Accelerates Synapse Maturation

Environmental stimulation is critical for brain development. Here, we report that natural stimulation through enriched environment (EE) rearing during the first 2 weeks of mouse postnatal development promotes GABAergic neurotransmission and accelerates maturation of GABAergic and glutamatergic synapses. Using whole-cell recordings from CA1 pyramidal neurons in acute hippocampal slices, we found that EE-reared mice exhibited higher amplitude of miniature GABAergic postsynaptic currents (mGPSCs) at 1 week of postnatal development, as well as accelerated transition of GABA action from excitation to inhibition, compared with mice reared under standard housing conditions. This enhanced GABAergic synaptic transmission persisted until the end of the second postnatal week, when GABA mostly acts as an inhibitory neurotransmitter. Consistent with these electrophysiological results, we observed elevated levels of GABAA receptors and the K+-Cl− cotransporter KCC2. Similarly, increased levels of excitatory synaptic components, including NMDA and AMPA receptors and the scaffolding protein PSD95, were detected in synaptosomal fractions from the forebrain/hippocampus of EE-reared mice during the first two postnatal weeks. Functional increase in glutamatergic synaptic transmission, as measured by increased amplitude of miniature and spontaneous EPSCs, was also detected during the second postnatal week. Together, these results demonstrate that early environmental stimulation through EE rearing enhances early postnatal GABAergic neurotransmission, which is known to play important trophic functions in many aspects of neural development.
Solving the berth allocation problem with service priority via multi-objective optimization

This paper studies a multi-objective instance of the berth allocation problem (BAP). The BAP involves the determination of exact berthing times and positions of incoming ships in a container port so as to minimize concurrently the three objectives of makespan of the port, total waiting time of the ships, and degree of deviation from a predetermined service priority schedule. These objectives represent the interests of both port and ship operators. Unlike most existing approaches in the literature which are single-objective-based, a multi-objective evolutionary algorithm (MOEA) that incorporates the concept of Pareto optimality is proposed for solving the multi-objective BAP. The multi-objective approach reveals several interesting characteristics of the BAP.
Admission control and power allocation for energy harvesting systems with QoS provisioning

In this paper, we address the problem of joint admission control and power allocation for energy harvesting (EH)-based communication systems. We consider that the harvested energy from the environment is uncertain and insufficient to satisfy the quality-of-service (QoS) requirement of all the communication devices in the system. Joint admission control and power allocation with QoS provisioning for EH systems under causal information of harvested energy and incomplete CSI is very difficult to solve. We develop an efficient “online” resource allocation policy based on dynamic programming to solve this problem considering the practical constraints of EH systems. We compare our proposed scheme with an “offline” scheme that considers the availability of non-causal information and with a practical “naive” scheme based on instantaneous information and demonstrate the effectiveness of our proposed algorithm.
Logico-semantic Aspects of Children's Knowledge about the Universal Quantifier: New Empirical Evidence

It has been widely assumed that a universal quantifier such as every evokes an asymmetry among entailments in its first argument (i.e., the NP) and its second argument (i.e., the VP). In particular, the first argument of every is downward entailing (henceforth DE), whereas its second argument is non-downward entailing (non-DE). Entailment-sensitive linguistic phenomena, arising as a consequence of these asymmetric entailments, are evident at various levels of representation. This paper discusses the linguistic representation of sentences with universal quantification and the consequences of asymmetric entailment in universal quantification at the logico-semantic level from an acquisition point of view; specifically, is children’s knowledge of the universal quantifier and its asymmetric pattern of entailments, previously examined with respect to within-sentence meanings, also reflected in their computation of logical inferences across universally-quantified sentences? We present a new experimental methodology and results which directly address whether children’s knowledge extends to the computation of across-sentence meaning relations involving every. We begin our discussion by reviewing the consequences of asymmetric entailment for within-sentential and across-sentential meanings.
Detecting Malicious Domains by Massive DNS Traffic Data Analysis

DNS (Domain name System) is one of the most prevalent protocols on modern networks and is essential for the correct operation of many network activities including the malicious operation. Monitoring the DNS traffic is an effective method to detect malicious activities. In this paper, we proposed an approach to detect malicious domains by analyzing massive mobile web traffic data. We used multiple features to classify, including the textual features and the traffic statistics features of domains and presented three typical classifiers to compare the classifying effect of each. Spark framework is leveraged to speed up the calculation of a large-scale DNS traffic. The efficiency of our system makes us believe the approach can help a lot in the field of network security.
A software oriented approach to hardware-software co-design

We present a software oriented approach to hardware/software codesign by applying traditional compiler techniques to the hardware/software partitioning problem and linking a compiler to a state of the art hardware synthesis technology. The system is specified in C or C++. Time critical regions are identified by means of profiling and are automatically implemented in user programmable logic with high level and logic synthesis design tools. The underlying architecture is an add-on board with user programmable logic, connected to a Sparc based workstation via the system bus. We present a novel partitioning technique based on a hierarchical candidate preselection scheme, that utilizes profilers and estimators for performance and cost. Our approach allows (a) efficient collection of profiling data due to the usage of C and C++ as specification languages, (b) fast partitioning due to a candidate preselection scheme, and (c) high complexity of the hardware partition due to a logic emulation system.
Evaluation of the performance of error-correcting codes on a Gilbert channel

We present a combinatorial analysis to derive an explicit expression for the number of transmission errors that occur in a block transmitted through a Gilbert (1960) channel. This expression can be used to investigate the tradeoffs among the decoding error probability, degree of interleaving, and the error-correction ability of a code. We illustrate how a designer may apply our method to determine different combinations of the degree of interleaving and error correction ability to achieve a specified decoding error rate. <<ETX>>
Performance analysis of a self-driven adaptive cold-plate, an experimental approach

Effective thermal management system is critical for the safety, maintainability and reliability of the operation of space vehicles. The objective of the present study is to improve the current space-based active fluid loop (AFL). A self-driven adaptive cold-plate (SDACP) was proposed in this paper. The innovation relies on a novel energy-saving wax-actuated thermal switch assembly (TSA) which is highly integrated and competent in fulfilling multiple missions including temperature sensing, mechanical manipulation and flow regulation, decreasing the required power input in temperature control process and thus enhancing the overall operating economy. Ground-based validation experiments were organized to evaluate its temperature control precisions. Comparative studies were conducted at the same time to investigate the influence of the physical properties of actuators using different waxes on the thermal control performances.
Short Text Classification Using Wikipedia Concept Based Document Representation

Short text classification is a difficult and challenging task in information retrieval systems since the text data is short, sparse and multidimensional. In this paper, we represent short text with Wikipedia concepts for classification. Short document text is mapped to Wikipedia concepts and the concepts are then used to represent document for text categorization. Traditional methods for classification such as SVM can be used to perform text categorization on the Wikipedia concept document representation. Experimental evaluation on real Google search snippets shows that our approach outperforms the traditional BOW method and gives good performance. Although it's not better than the state-of-the-art classifier (see e.g. Phan et al. WWW '08), our method can be easily implemented with low cost.
Guidelines and Caveats for Manipulating Expectancies in Experiments Involving Human Participants

In a number of domains involving decision making under high time pressure, the appearance of an unexpected critical event can startle operators causing errors that may potentially lead to a chain reaction of unfavorable events. Simulating such situations in a laboratory requires overcoming several challenges tied to human responses to unexpected and rare critical events. We discuss cases of experimental studies that have incorporated simulations, critical events, interruptions, predictive displays and ecological displays involving naïve and expert participants. We spell out guidelines and caveats pertaining to training, expertise, temporal variables, critical event frequencies, scenario design, mediator and moderator variables to name a few. The guidelines and caveats may inform researchers in the design of generalizable and reproducible experiments and in the analysis of data.
Strengths-based positive psychology interventions: a randomized placebo-controlled online trial on long-term effects for a signature strengths- vs. a lesser strengths-intervention

Recent years have seen an increasing interest in research in positive psychology interventions. There is broad evidence for their effectiveness in increasing well-being and ameliorating depression. Intentional activities that focus on those character strengths, which are most typical for a person (i.e., signature strengths, SS) and encourage their usage in a new way have been identified as highly effective. The current study aims at comparing an intervention aimed at using SS with one on using individual low scoring (or lesser) strengths in a randomized placebo-controlled trial. A total of 375 adults were randomly assigned to one of the two intervention conditions [i.e., using five signature vs. five lesser strengths (LS) in a new way] or a placebo control condition (i.e., early memories). We measured happiness and depressive symptoms at five time points (i.e., pre- and post-test, 1-, 3-, and 6-months follow-ups) and character strengths at pre-test. The main findings are that (1) there were increases in happiness for up to 3 months and decreases in depressive symptoms in the short term in both intervention conditions; (2) participants found working with strengths equally rewarding (enjoyment and benefit) in both conditions; (3) those participants that reported generally higher levels of strengths benefitted more from working on LS rather than SS and those with comparatively lower levels of strengths tended to benefit more from working on SS; and (4) deviations from an average profile derived from a large sample of German-speakers completing the Values-in-Action Inventory of Strengths were associated with greater benefit from the interventions in the SS-condition. We conclude that working on character strengths is effective for increasing happiness and discuss how these interventions could be tailored to the individual for promoting their effectiveness.
A safe regression test selection technique for database-driven applications

Regression testing is a widely-used method for checking whether modifications to software systems have adversely affected the overall functionality. This is potentially an expensive process, since test suites can be large and time-consuming to execute. The overall costs can be reduced if tests that cannot possibly be affected by the modifications are ignored. Various techniques for selecting subsets of tests for re-execution have been proposed, as well as methods for proving that particular test selection criteria do not omit relevant tests. However, current selection techniques are focused on identifying the impact of modifications on program state. They assume that the only factor that can change the result of a test case is the set of input values given for it, while all other influences on the behavior of the program (such as external interrupts or hardware faults) will be constant for each re-execution of the test. This assumption is impractical in the case of an important class of software system, i.e. systems which make use of an external persistent state, such as a database management system, to share information between application invocations. If applied naively to such systems, existing regression test selection algorithms will omit certain test cases which could in fact be affected by the modifications to the code. In this paper, we show why this is the case, and propose a new definition of safety for regression test selection that takes into account the interactions of the program with a database state. We also present an algorithm and associated tool that safely performs test selection for database-driven applications, and (since efficiency is an important concern for test selection algorithms) we propose a variant that defines safety in terms of database state alone. This latter form of safety allows more efficient regression testing to be performed for applications in which program state is used only as a temporary holding space for data from the database. The claims of increased efficiency of both forms of safety are supported by the results of an empirical comparison with existing techniques.
SemSLATES: Improving enterprise 2.0 information systems using semantic Web technologies

While the use of Web 2.0 tools and principles in organizations — a practice commonly known as Enterprise 2.0 — helps knowledge workers to collaboratively build and exchange information more easily, it introduces several issues in terms of efficiently integrating and retrieving this information. In this paper, we describe how Semantic Web technologies can be efficiently deployed to solve these issues and to enhance such ecosystems. We detail the SemSLATES methodology, a middleware architecture for Enterprise 2.0 that combines Social Web principles and Semantic Web technologies in a novel and innovative way for the benefit of end users. Since the work presented here has been applied in an industrial context, we emphasize our motivations and the benefits of the approach through a complete and real-world case study.
Generating Conference Linked Open Data in One Click

In this paper we describe cLODg2 (conference Linked Open Data generator version 2), a tool to collect, refine and produce Linked Data about scientific conferences with their associated publications, participants and events. Conference metadata collected from different unstructured and semi-structured resources must be expressed with appropriate vocabularies to be exposed as Linked Data. cLODg2 facilitates this task by providing a one-click workflow to generate data which is ready to be integrated in the ScholarlyData.org dataset. cLODg2 is an open source project, which has the aim to foster the publication of scholarly Linked Open Data and encourage collaborative efforts in this direction between researchers and publishers.
Controller-based Routing Scheme for Named Data Network

Named Data Network (NDN) routing schemes must learn routes to named data locations, so routers know where to send interest packets. These routing schemes are based on IP routing schemes, therefore they inherit characteristics such as prefix dissemination and routing based prefix longest match. As the amount of named data and non-aggregated prefixes increase, routers store more routes and exchange more control messages, which results in high control overhead and possible Forwarding Information Base explosion. We address these issues with a novel Controller-based Routing Scheme (CRoS) for NDN. CRoS introduces special controllers which have two main functions: i) acquire topology and calculate routes, and ii) store named data locations. Named data locations are registered in controllers. On interest packets to an unknown prefix, routers request controllers for installation of a new route. CRoS controllers implement distributed hash tables to distribute the storage of named data locations efficiently. Furthermore, as CRoS runs on top of the NDN, it preserves NDN features such congestion control, network problem detection and path diversity.
A Fire and Smoke Simulation for Mobile Game

In the field of computer graphics, fluid-like motion is an important and challenging problem with many applications. Currently, the graphical performance and resolution of the mobile handset is highly improved; therefore, mobile 3D games and physically based animations are also more and more popular items in the mobile services. Yet interactive physically-based fluid simulation is still challenging for mobile games. We studied and implemented physically-based models based on Navier-Stokes equation for fire and smoke effects on mobile 3D games. To make an efficient fire effects on mobile games, we implemented billboard based 2D fluid simulation and gradient based coloring effects. We also implemented external forces on billboard for interactive fire simulation with game characters. The mobile platform of our system is WIPI, which is the standard mobile platform in Korea and NF3D for our 3D programming API. All the simulations have also been adopted for our mobile 3D game, “Rupee Story”.
Translational approaches to studying reward-based purposive behaviours

Within classical economics, an agent is deemed “rational” if their preferences are both consistent and maximize utility of positive, subjective experience. Violations from this norm may occur as a result of utility devaluation (proceeding from risk or delay) or when an imbalance occurs between ‘liking’ and ‘wanting’. The current studies investigate how changes in reward-contingencies, delay before reward receipt, and reinforcer devaluation contribute to such utility-based decision-making in human and rodent models. I examined the effects of devaluation through pre-exposure and outcome-contingency on the development and maintenance of sign- and goal-tracking responses in rats (chapter three) and humans (chapter four). Chapter four presents a novel, translational, eye-tracking procedure and correlates of such behaviour, including trait-impulsivity and discounting performance. In chapter five I presented probability- and temporal discounting using a mouse model, exploring the consequences of satiety-based devaluation, and changes in outcome-contingencies- and delays. In Chapter six I presented the same factors in a human sample using a novel laboratory-based procedure and sought to explore the impact of trait and state impulsivity and correlates of rapid discounting. Finally, in chapter seven I considered the relationship between trait impulsivity, alcohol use, smoking and discounting behaviour using a more conventional online questionnaire. The results represent some of the first to present probability discounting using a mouse model and characterisation of reliable sign- and goal-tracking performance in humans. The results of the latter studies broadly support previous findings in rats showing that lowered reward contingency diminishes goal-oriented, but enhances sign-oriented, responding. Chapter six establishes a human equivalent to rodent discounting paradigms through implicit learning that will allow future controlled studies in humans. Finally, chapter seven presents evidence for an association between delay discounting and trait impulsivity. The results of these studies support the assertion that irrational decision-making arises, in part, from changes in reward utility as a function of delay, probability, devaluation and individual differences. Furthermore the translational-homologous models presented allow for future biopsychological research into mechanisms underlying such behaviours.