Miracle-dz/UniFAR-FTUs huggingface dataset:
Eclectic Styles and Classical Performance: Motivation and Self-Efficacy Belief at Two Summer Music Camps

String teachers and scholars have suggested that classically trained students may be motivated to engage in eclectic (e.g., rock, pop, jazz, groove, folk) styles. However, we do not fully understand the ways in which students’ motivation to engage in new styles might be influenced by their perceptions of their ability to perform in those styles. In this mixed-method study, we draw upon quantitative, qualitative, and arts-based data from 120 middle and high school students at two camps (one emphasizing classical music, the other emphasizing eclectic styles), to explore various ways in which students develop self-efficacy beliefs and motivation to perform in a variety of musical approaches. According to analysis of all data, students at both camps generally expressed having positive musical and social experiences. Negative experiences, while less common, stemmed from confusion or frustration with music learning, boredom with music that was too easy or not interesting, and competitive comparison with others. Based on findings from qualitative and arts-based data, we suggest that these students may have benefited from additional teacher support when encountering new musical techniques.
Hepatocellular Carcinoma Growth Is Inhibited by Euphorbia helioscopia L. Extract in Nude Mice Xenografts

Euphorbia helioscopia L. is a traditional Chinese medicine; recently research found that its ethyl acetate extract (EAE) plays an important role on tumor cell proliferation, apoptosis, invasion, and metastasis in vitro. But the effect of EAE for tumor cells in vivo has not been reported. To explore the inhibitory effect of EAE and molecular mechanism on hepatocellular carcinoma (HCC) SMMC-7721 cells in vivo, we utilized the nude mouse xenograft model of HCC. Treated with EAE (50, 100, and 200 μg/mL), the volume of xenograft was measured during the entire process of EAE treatment. In EAE treatment group, the volume of xenograft was significantly reduced compared with the control group (P < 0.05) and the protein expressions of CyclinD1, bcl-2, and MMP-9 were reduced, while those of bax, caspase-3, and nm23-H1 were increased. A significant change trend with increasing EAE concentrations has presented, compared with controls. Moreover, the ultrastructural morphology of xenografts showed significant changes, including nuclear pyknosis and chromatin condensation, We found that EAE could effectively inhibit tumor growth, induce apoptosis, and inhibit tumor invasion and metastasis in vivo; it is suggested that EAE is a potential candidate for as a new anticancer agent.
Incremental Data Uncertainty Handling Using Evidence Combination: A Case Study on Maritime Data Reasoning

Semantic incompatibility is a conflict that occurs in the meanings of data. In this paper, we propose an approach for data cleaning by resolving semantic incompatibility. Our approach applies a dynamic and incremental enhancement of data quality. It checks the coherency/conflict of the newly recorded facts/relations against the existing ones. It reasons over the existing information and comes up with new discovered facts/relations. We choose maritime data cleaning as a validation scenario.
Boosting multi-feature visual texture classiffiers for the authentication of Jackson Pollock's drip paintings

Early attempts at authentication Jackson Pollock's drip paintings based on computer image analysis were restricted to a single "fractal" or "multi-fractal" visual feature, and achieved classification nearly indistinguishable from chance. Irfan and Stork pointed out that such Pollock authentication is an instance of visual texture recognition, a large discipline that universally relies on multiple visual features, and showed that modest, but statistically significant improvement in recognition accuracy can be achieved through the use of multiple features. Our work here extends such multi-feature classification by training on more image data and images of higher resolution of both genuine Pollocks and fakes. We exploit methods for feature extraction, feature selection and classiffier techniques commonly used in pattern recognition research including Support Vector Machines (SVM), decision trees (DT), and AdaBoost. We extract features from the fractality, multifractality, pink noise patterns, topological genus, and curvature properties of the images of candidate paintings, and address learning issues that have arisen due to the small number of examples. In our experiments, we found that the unmodified classiffiers like Support Vector Machines or Decision Tree alone give low accuracies (60%), but that statistical boosting through AdaBoost leads to accuracies of nearly 75%. Thus, although our set of observations is very small, we conclude that boosting methods can improve the accuracy of multi-feature classiffication of Pollock's drip paintings.
Technology comparison for large last-level caches (L3Cs): Low-leakage SRAM, low write-energy STT-RAM, and refresh-optimized eDRAM

Large last-level caches (L3Cs) are frequently used to bridge the performance and power gap between processor and memory. Although traditional processors implement caches as SRAMs, technologies such as STT-RAM (MRAM), and eDRAM have been used and/or considered for the implementation of L3Cs. Each of these technologies has inherent weaknesses: SRAM is relatively low density and has high leakage current; STT-RAM has high write latency and write energy consumption; and eDRAM requires refresh operations. As future processors are expected to have larger last-level caches, the goal of this paper is to study the trade-offs associated with using each of these technologies to implement L3Cs. In order to make useful comparisons between SRAM, STTRAM, and eDRAM L3Cs, we model them in detail and apply low power techniques to each of these technologies to address their respective weaknesses. We optimize SRAM for low leakage and optimize STT-RAM for low write energy. Moreover, we classify eDRAM refresh-reduction schemes into two categories and demonstrate the effectiveness of using dead-line prediction to eliminate unnecessary refreshes. A comparison of these technologies through full-system simulation shows that the proposed refresh-reduction method makes eDRAM a viable, energy-efficient technology for implementing L3Cs.
Scalable RF MEMS Switch Matrices: Methodology and Design

This paper proposes new solutions for implementing wideband large switch matrices. These solutions are based on crossbar and L-shaped topologies. This paper introduces a high-performance wideband switch cell to build up scalable NtimesN switch matrices and gives an account of the design, fabrication, and characteristics of the switch cell and a 3times3 crossbar switch matrix. The chosen design procedure is seen to be appropriate since it produces valid measured results. In addition, this paper presents an RF microelectromechanical systems L-shaped switch matrix, which indicates less variation of characteristics for certain types of connectivity. It also demonstrates that for a 4times4 switch matrix, there is a 50% improvement in insertion loss and phase-shift variation.
Fowler mega-scale glacial lineations The formation of subglacial streams and

References html#ref-list-1 http://rspa.royalsocietypublishing. org/content/466/2123/3181.full. This article cites 30 articles, 3 of which can be accessed free Subject collections (17 articles) glaciology  (81 articles) mathematical modelling  Articles on similar topics can be found in the following collections Email alerting service here the box at the top right-hand corner of the article or click Receive free email alerts when new articles cite this article sign up in
Sleep symptoms and polysomnographic architecture in advanced Parkinson's disease after chronic bilateral subthalamic stimulation

Objective: To evaluate the sleep symptoms and polysomnographic architecture in advanced Parkinson's disease after chronic bilateral subthalamic stimulation (STN-DBS). Methods: Sleep was studied in 11 patients (six women and five men; mean (SD) age 63.6 (7.8) years) who underwent STN-DBS. Subjective sleep evaluation was assessed by clinical sleep interview and the Pittsburgh sleep quality index (PSQI) questionnaire, and sleep architecture by polysomnography with audiovisual recording. Nocturnal mobility was evaluated. Results: Before surgery, eight patients rated their sleep quality as unsatisfactory; seven of these had a marked improvement after surgery, and the PSQI questionnaire showed significantly improved sleep quality. After surgery, polysomnography showed an increase in the longest period of uninterrupted sleep and a decrease in the arousal index. There was an increase in nocturnal mobility after surgery, but no change in REM sleep behaviour disorder. Conclusions: In advanced Parkinson's disease, chronic STN-DBS is associated with subjective improvement in sleep quality, probably through increased nocturnal mobility and reduction of sleep fragmentation.
A Semi-Supervised Ensemble Approach for Multi-label Learning

In this paper, we present a new ensemble approach for semi-supervised multi-label classification which exploits both the dependencies between the class labels and the unlabeled instances to enhance the multi-label classification performance. Our approach combines both data resampling (bagging) and label random subspace strategies for generating a committee of multi-label models in a co-training style algorithm. The key ideas behind this approach are to i) promote and maintain diversity in the multi-label base-classifiers committee, ii) define a new cost oriented metric to estimate the prediction confidence for each label, and iii) use a new multi-label out-of-bag feature importance measure that makes full use of labeled and unlabeled in the semi-supervised setting. Experimental results on various benchmark data sets approved that the proposed approach outperforms recent state-of-the-art supervised and semi-supervised multi-label algorithms over different multi-label metrics.
Hybrid MPI-OpenMP Paradigm on SMP Clusters: MPEG-2 Encoder and N-Body Simulation

Clusters of SMP nodes provide support for a wide diversity of parallel programming paradigms. Combining both shared memory and message passing parallelizations within the same application, the hybrid MPI-OpenMP paradigm is an emerging trend for parallel programming to fully exploit distributed shared-memory architecture. In this paper, we improve the performance of MPEG-2 encoder and n-body simulation by employing the hybrid MPI-OpenMP programming paradigm on SMP clusters. The hierarchical image data structure of the MPEG bit-stream is eminently suitable for the hybrid model to achieve multiple levels of parallelism: MPI for parallelism at the group of pictures level across SMP nodes and OpenMP for parallelism within pictures at the slice level within each SMP node. Similarly, the work load of the force calculation which accounts for upwards of 90% of the cycles in typical computations in the n-body simulation is shared among OpenMP threads after ORB domain decomposition among MPI processes. Besides, loop scheduling of OpenMP threads is adopted with appropriate chunk size to provide better load balance of work, leading to enhanced performance. With the n-body simulation, experimental results demonstrate that the hybrid MPI-OpenMP program outperforms the corresponding pure MPI program by average factors of 1.52 on a 4-way cluster and 1.21 on a 2-way cluster. Likewise, the hybrid model offers a performance improvement of 18% compared to the MPI model for the MPEG-2 encoder.
Easy Knowledge Engineering and Usability Evaluation of Longan Knowledge-Based System

Longan has been regarded as an important economic fruit for export of Thailand. In order to support Thai longan growers, the Thai government has set a strategic plan to enhance longan production and knowledge distribution by funding research and development, and constructing of Longan Knowledge-based System (LKS). This paper presents the construction process of LKS called ‘easy’ knowledge engineering, involving ontology modeling for construction of longan knowledge structure and preparation of data instances. LKS provides (1) unsophisticated tools with usability for searching some related knowledge concepts, and (2) ‘easy’ knowledge that was compiled, according to the designed ontology, into different basic core data representation. In addition, this paper demonstrates a usability study in evaluation of LKS based on ISO 9241 usability standard. The results show that LKS has a usability, and users highly satisfy with searching interaction and retrieving ‘easy’ knowledge.
Recent progress in translational research on neurovascular and neurodegenerative disorders

The already established and widely used intravenous application of recombinant tissue plasminogen activator as a re-opening strategy for acute vessel occlusion in ischemic stroke was recently added by mechanical thrombectomy, representing a fundamental progress in evidence-based medicine to improve the patient’s outcome. This has been paralleled by a swift increase in our understanding of pathomechanisms underlying many neurovascular diseases and most prevalent forms of dementia. Taken together, these current advances offer the potential to overcome almost two decades of marginally successful translational research on stroke and dementia, thereby spurring the entire field of translational neuroscience. Moreover, they may also pave the way for the renaissance of classical neuroprotective paradigms. This review reports and summarizes some of the most interesting and promising recent achievements in neurovascular and dementia research. It highlights sessions from the 9th International Symposium on Neuroprotection and Neurorepair that have been discussed from April 19th to 22nd in Leipzig, Germany. To acknowledge the emerging culture of interdisciplinary collaboration and research, special emphasis is given on translational stories ranging from fundamental research on neurode- and -regeneration to late stage translational or early stage clinical investigations.
A Study on the Effect of Stroop Test on the Formation of Students Discipline by Using the Heart Rate Variability (HRV) Technique

Discipline refers to self-control and individual behaviour. Other than that, discipline is an important element in the formation of integrity level. The objective of the study is to assess the effects of using the Stroop test of biofeedback protocol in order to evaluate individual level of discipline. A clinical study has been conducted on 50 participants which is the participants is a undergraduate student from Universiti Malaysia Pahang, who were divided into two groups. First group is students get high achiever and second group is students get low achierver in academic. The Heart Rate Variability (HRV) technique has been used in the assessment of this protocol. The findings show that there was a positive relationship between the Stroop test and the students discipline that those who excelled managed to get higher score of LF spectrum as compared to HF and VLF, while the students with lower achievement showed higher score of VLF and HF spectrum than LF. In conclusion, this test is one of the tests that can be used in increasing the level of individual discipline.
Search diversion, rent extraction and competition

This paper studies search diversion by competing intermediaries connecting consumers with third-party stores. First, we show that endogenizing store entry leads to more search diversion when intermediaries cannot price discriminate among stores because the intermediaries’ incentives are aligned with the marginal stores. Second, competition among intermediaries may lead to more or less search diversion relative to monopoly, depending on whether consumers multihome and stores singlehome or vice-versa.
An Equation for the Prediction of Oxygen Consumption in a Brazilian Population

Background: The equations predicting maximal oxygen uptake (VO2max or peak) presently in use in cardiopulmonary exercise testing (CPET) softwares in Brazil have not been adequately validated. These equations are very important for the diagnostic capacity of this method. Objective: Build and validate a Brazilian Equation (BE) for prediction of VO2peak in comparison to the equation cited by Jones (JE) and the Wasserman algorithm (WA). Methods: Treadmill evaluation was performed on 3119 individuals with CPET (breath by breath). The construction group (CG) of the equation consisted of 2495 healthy participants. The other 624 individuals were allocated to the external validation group (EVG). At the BE (derived from a multivariate regression model), age, gender, body mass index (BMI) and physical activity level were considered. The same equation was also tested in the EVG. Dispersion graphs and Bland-Altman analyses were built. Results: In the CG, the mean age was 42.6 years, 51.5% were male, the average BMI was 27.2, and the physical activity distribution level was: 51.3% sedentary, 44.4% active and 4.3% athletes. An optimal correlation between the BE and the CPET measured VO2peak was observed (0.807). On the other hand, difference came up between the average VO2peak expected by the JE and WA and the CPET measured VO2peak, as well as the one gotten from the BE (p = 0.001). Conclusion: BE presents VO2peak values close to those directly measured by CPET, while Jones and Wasserman differ significantly from the real VO2peak.
A perceptual memory system for grounding semantic representations in intelligent service robots

This paper addresses the problem of grounding semantic representations in intelligent service robots. In particular, this work contributes to addressing two important aspects, namely the anchoring of object symbols into the perception of the objects and the grounding of object category symbols into the perception of known instances of the categories. The paper discusses memory requirements for storing both semantic and perceptual data and, based on the analysis of these requirements, proposes an approach based on two memory components, namely a semantic memory and a perceptual memory. The perception, memory, learning and interaction capabilities, and the perceptual memory, are the main focus of the paper. Three main design options address the key computational issues involved in processing and storing perception data: a lightweight, NoSQL database, is used to implement the perceptual memory; a thread-based approach with zero copy transport of messages is used in implementing the modules; and a multiplexing scheme, for the processing of the different objects in the scene, enables parallelization. The system is designed to acquire new object categories in an incremental and open-ended way based on user-mediated experiences. The system is fully integrated in a broader robot system comprising low-level control and reactivity to high-level reasoning and learning.
Collocation translation based on sentence alignment and parsing

Bien que de nombreux efforts aient été déployés pour extraire des collocations à partir de corpus de textes, seule une minorité de travaux se préoccupent aussi de rendre le résultat de l’extraction prêt à être utilisé dans les applications TAL qui pourraient en bénéficier, telles que la traduction automatique. Cet article décrit une méthode précise d’identification de la traduction des collocations dans un corpus parallèle, qui présente les avantages suivants : elle peut traiter des collocation flexibles (et pas seulement figées) ; elle a besoin de ressources limitées et d’un pouvoir de calcul raisonnable (pas d’alignement complet, pas d’entraînement) ; elle peut être appliquée à plusieurs paires des langues et fonctionne même en l’absence de dictionnaires bilingues. La méthode est basée sur l’information syntaxique provenant du parseur multilingue Fips. L’évaluation effectuée sur 4000 collocations de type verbe-objet correspondant à plusieurs paires de langues a montré une précision moyenne de 89.8% et une couverture satisfaisante (70.9%). Ces résultats sont supérieurs à ceux enregistrés dans l’évaluation d’autres méthodes de traduction de collocations.
Suma Qamaña as a strategy of power: politicizing the Pluriverse

The “pluriverse” has recently gained momentum in International Relations among scholars focused on ontological pluralism. Nevertheless, theoretical debates may obscure several political tensions observed in local experience. In this paper, I analyze narratives on Suma Qamana , which synthesizes Aymara cosmology and is both reproduced and criticized by political actors in Bolivia. I argue that the discourse on Suma Qamana entails a strategy of power by both Aymara people and the government. The paper is developed in three parts: first, I examine the term`s framing in literature, Suma Qamana `s risen in Bolivian society and its connection to the reconstruction of Aymara identity. Then, I analyze Suma Qamana `s insertion into governmental discourse. Finally, I stress power disputes over Suma Qamana . I suggest that the emphasis attributed by IR academics to its ontological potential without considering this strategic facet might lead them to depoliticize the term, reproducing a similar pattern advanced by other theorists and the government.
Algorithm xxx : NOMAD : Nonlinear Optimization with the MADS algorithm

NOMAD is software that implements the MADS algorithm (Mesh Adaptive Direct Search) for blackbox optimization under general nonlinear constraints. Blackbox optimization is about optimizing functions that are usually given as costly programs with no derivative information and no function values returned for a significant number of calls attempted. NOMAD is designed for such problems and aims for the best possible solution with a small number of evaluations. The objective of this paper is to describe the underlying algorithm, the software’s functionalities, and its implementation.
Incremental HLA-based distributed simulation cloning

Distributed simulation cloning technology is designed to analyze alternative scenarios of a distributed simulation concurrently within the same execution session. The goal is to optimize the execution time for evaluating different scenarios by avoiding repeated computation. In terms of high level architecture (HLA) based simulations, a federate may make clones to explore different scenarios at decision points. It is desirable to use an incremental cloning mechanism to replicate only those federates, whose states will be affected. This paper discusses the theory and issues involved in incremental distributed simulation cloning, which employs an event checking algorithm to ensure accurate sharing and initiates cloning only when absolutely necessary. Experiments have been performed to compare the performance of entire cloning and incremental cloning mechanisms. The experimental results indicate that cloning technologies can effectively reduce the time of executing multiple scenarios, and the incremental cloning mechanism significantly surpasses entire cloning in execution efficiency.
Imaging of through-silicon vias using X-Ray computed tomography

X-Ray computed tomography (CT) can be useful in evaluating defects in through-silicon vias (TSVs). X-Ray CT images of two different TSV processes are presented; copper TSVs used for stacked memory on logic and tungsten TSVs used for power amplifiers. It is found that TSVs in the edge exclusion region are susceptible to defects from the TSV etch and TSV metallization processes.