Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating semantics in pattern-based scientific workflow recommender systems: Improving the accuracy of recommendations

Recommender systems are used to enable decision-support. Using them to assist users when designing scientific workflows introduces a number of challenges. These include selecting appropriate components and specifying correct parameter values. Pattern-based workflow recommender systems employ historical usage patterns to generate recommendations. Such systems can intelligently adapt with use. Semantics, on the other hand, can enable recommender systems to intelligently infer new relationships between workflow components. Combining both approaches can help to overcome the drawbacks of each approach and improve the accuracy of the suggestions. To this end, a framework for a hybrid workflow design recommender system is presented in this paper along with the accompanying suggestion generation algorithm. An illustrative example is also presented to demonstrate how the system helps in constructing a workflow. The performance of the framework is compared with an existing pattern-based system using a dataset of neuroimaging workflows. The evaluation results demonstrate that the proposed system outperforms the existing system in a number of different scenarios. The improvement in the performance of the proposed system enhances the usability of the system for users and allows them to more efficiently construct workflows.
TacTical PeriodizaTion : MoUrinho ’ s BesT-kePT secreT ?

“We can differentiate among traditional analytical training where the different factors are trained in isolation, the integrated training, which uses the ball but where the fundamental concerns are not very different from the traditional one; and there is my way of training, which is called Tactical Periodization. It has nothing to do with the previous two even though many people could think so. ” (Mourinho, J. in gaiteiro, 2006)
Analysis of redundant peaks in LC-MS/MS datasets

LC-MS/MS is an analytical technique used for protein identification and biomarker discovery. Typically, each peptide will be measured twice by the MS/MS, resulting in two or more mass-to-charge spectra for each peptide. The current study investigates various ways to combine these replicate measurements to improve the quality of the measured spectra, and in turn, the confidence and accuracy of the protein identification. Sample data was collected using a QSTAR XL hybrid quadrupole-time-of-flight mass spectrometer, given a input standard protein mixture of known composition. Spectrum alignment is used to identify replicate spectra. Various algorithms for combining these replicate measurements are investigated, and are compared to the current industry standard MASCOT algorithm. Results are judged based on protein identification rates following combination of replicate spectra. Algorithms which leverage the fact that mass-to-charge data collected above the parent ion mass are more informative for protein identification appear particularly effective, and warrants further investigation.
A 100-MS/s 8-b CMOS subranging ADC with sustained parametric performance from 3.8 V down to 2.2 V

A 100-MS/s 8-b CMOS analog-to-digital converter (ADC) designed for very low supply voltage and power dissipation is presented. This single-ended-input ADC is based on the unified two-step subranging architecture, which processes the coarse and fine decisions in identical signal paths to maximize their matching. However, to minimize power and area, the coarse-to-fine overlap correction has been aggressively reduced to only one LSB. The ADC incorporates five established design techniques to maximize performance: bottom-plate sampling, distributed sampling, autozeroing, interpolation, and interleaving. Very low voltage operation required for a general purpose ADC was obtained with four additional and new circuit techniques. These are a dual-gain first-stage amplifier, differential T-gate boosting, a supply independent delay generator, and a digital delay-locked-loop controlled output driver. For a clock rate of 100 MS/s, 7.0 (7.3) effective bits for a 50 MHz (10 MHz) input are maintained from 3.8 V down to 2.2 V. At 2.2 V, this 100-MS/s converter dissipates 75 mW plus 9 mW for the reference ladder. For a typical supply of 2.7 V, it consumes just 1 mW per MS/s over the 10-160-MS/s clock frequency range. Differential nonlinearity below 0.5 LSB is maintained from 2.7 V down to 2.2 V, and it degrades only slightly to 0.8 LSB at 3.8-V supply. The converter is implemented in a 0.35-/spl mu/m CMOS process, with double-poly capacitors and no low-threshold devices.
Critical Multimodal Analysis of Digital Discourse Preliminary Remarks

Th e theme to which the language section of LEA is dedicated this year – that is the relationship between Human Studies and new technologies – is a very relevant issue in the contemporary scenario. Indeed, it is an item of shared knowledge that the spreading of new technologies, along with phenomena like globalization and localization, have led to the pervasive creation and to the massive sharing of very complex digitally mediated texts that not only present varied semiotic compositions, but also feature multiple (and often hybridized) references to diff erent socio-cultural contexts. In addition to that, many of these texts are frequently produced, exchanged and “experienced” without the mediation of traditional signifying (or normative) agencies. In such settings, an awareness of how diff erent semiotic systems concur to make meaning, together with the knowledge of the diff erent linguistic and socio-cultural communities that may take part in a communicative act, constitute invaluable tools to help decoding both the instances of distributed textuality and the eco-social experiences signifi ed in the same acts. Moreover – as the New London Group envisioned in the distant 1990s (Cazden, Fairclough et al. 1996) – these competences are the founding tiles of a “broader view of literacy”, a “multiliterate” (ivi, 60) pedagogical process aimed at creating citizens able to cope with heterogeneous medial (and un-mediated) environments. As a matter of fact, many and multidisciplinary are the skills that people are nowadays required to have if they wish to fully express their citizenship: at fi rst, they need to be able to “crack codes”, that is to recognize the diff erent modal aff ordances used in multi-semiotic texts. Th en – in order to use those artifacts functionally – they need to understand their compositional meaning (that is obviously infl uenced by the particular socio-cultural contexts out of which they originate), as well as the diff erent cultural and social functions performed by the same texts in environments that tend to converge more and more. Finally, since “changes in discourse are dialectically interconnected with changes in other non-discursive social elements” (Fairclough 2011, 11), people need to develop a critical conscience if they want to detect and decode the worldviews that are entexted in such semiotic artifacts.
Functional NMDA Receptors Are Transiently Active and Support the Survival of Purkinje Cells in Culture

Conflicting evidence exists concerning the activity of NMDA receptors (NMDARs) in cerebellar Purkinje cells and their possible functions. To investigate the activity of NMDARs, we used whole-cell recording on immunocytochemically identified Purkinje cells in primary culture. In addition, we used mice with a disrupted NMDAR1 gene that lack functional NMDARs (NR1−/−) to assess the physiological role of NMDARs. In cultures from normal mice, NMDA-mediated currents were detected in all identified Purkinje cells at 4 d in vitro (div). After 14 d, however, NMDA responses were reduced in amplitude, whereas the responses to kainate and glutamate increased steadily in amplitude. In addition, the NMDA-induced current displayed a pronounced desensitization at these later stages; peak current declined to zero during steady application of NMDA. At 7 div, the number of surviving Purkinje cells was less in cultures treated with NMDA antagonists, and their survival was dose-dependent. Purkinje cell survival was correspondingly poorer in cultures from the NR1−/− mice than in wild-type controls, suggesting that NMDAR activity enhances the survival of Purkinje cells in vitro. The addition of moderate doses of NMDA promoted the survival of wild-type Purkinje cells in the presence of tetrodotoxin. Feeder layers of cerebellar granule cells derived from wild-type or NR1−/− mice promoted survival of Purkinje cells to a similar degree, suggesting that the NMDAR in Purkinje cells, but not in other cells, is directly involved in Purkinje cell viability. The results demonstrate that NMDARs transiently produce membrane current in Purkinje cells and may serve as one of the epigenetic factors that support the survival of Purkinje cells in vitro.
Possibility Theory Ii Conditional Possibility

It is shown that the notion of conditional possibility can be consistently introduced in possibility theory, in very much the same way as conditional expectations and probabilities are deened in the measure-and integral-theoretic treatment of probability theory. I write down possibilistic integral equations which are formal counterparts of the integral equations used to deene conditional expectations and probabilities, and use their solutions to deene conditional possibilities. In all, three types of conditional possibilities, with special cases, are introduced and studied. I explain why, like conditional expectations, conditional possibilities are not uniquely deened, but can only be determined up to almost everywhere equality, and I assess the consequences of this nondeterminacy. I also show that this approach solves a number of consistency problems, extant in the literature.
Factor analyses of the Pediatric Symptom Checklist-17 with African-American and Caucasian pediatric populations.

OBJECTIVES To validate a three-factor model for the Pediatric Symptom Checklist-17 (PSC-17) and evaluate its diagnostic accuracy with African-American and Caucasian children with and without a chronic illness. METHODS Mothers of 723 youth diagnosed with either type I diabetes (n = 210) or sickle cell disease (n = 191) and a nonill peer group (n = 322) completed a demographic questionnaire, the PSC-17, and the Child Behavior Checklist (CBCL). RESULTS Confirmatory factor analyses and tests of measurement invariance validated a three-factor structure for the PSC-17 with African-American and Caucasian youth with and without a chronic illness. Receiver operating characteristic curves revealed optimal cut-off scores that are similar to published reports. CONCLUSIONS A three-factor solution was replicated for the PSC-17 with African-American and Caucasian children with and without a chronic illness. Cut-off scores for identifying children at risk for emotional/behavioral problems were evaluated using the CBCL as the gold standard and are discussed.
Maximizing as a predictor of job satisfaction and performance: A tale of three scales

Research on individual differences in maximizing (versus satisficing) has recently proliferated in the Judgment and Decision Making literature, and high scores on this construct have been linked to lower life satisfaction as well as, in some cases, to worse decision-making performance. The current study exported this construct to the organizational domain and evaluated the utility of the three most widely used measures of maximizing in predicting several criteria of interest to organizational researchers: job satisfaction, intentions to quit the organization, performance in the job role, and income. Moreover, this study used relative weight analyses to determine the relative importance of maximizing and two dispositional variables (conscientiousness and core self-evaluations) that are traditionally used to predict these criteria in the organizational literature. Results indicate that relationships between maximizing and these criteria are influenced by the way in which maximizing is measured. Yet, regardless of how it is measured, maximizing is not a particularly strong predictor of these criteria compared to traditional organizational predictors. Limitations and future research directions are discussed.
An Alternative Theoretical Explanation and Empirical Insights into Overordering Behavior in Supply Chains

The beer game and the supply line underweighting theory are central to our knowledge of decision making in dynamic environments such as supply chains. The core of these theories is that people are incapable of recognizing the pipeline inventory and this is the main cause of overordering and dysfunctional behavior. This article identifies lacunae in the theoretical and empirical foundations of extant literature and proposes an alternate explanation, a “correction model,” explaining why overreactions occur. We adopt a multi-method research design, comprising a field case study and laboratory experiments, to ground our findings. [Submitted: July 19, 2010. Revisions received: December 8, 2010; March 14, 2011. Accepted: March 28, 2011. ]
An SVM Based Automatic Segmentation Method for Brain Magnetic Resonance Image Series

To segment magnetic resonance image series is an interdisciplinary topic that involves both medical and computer science. It is one of the most important steps for medical diagnosis and quantitative analysis. This paper proposes an automatic segmentation method based on support vector machine (SVM). Feature vectors are generated according to both grayscale value and texture pattern of MR brain images. To speed up, some results are acquired directly from the segmentation model trained in adjacent layers. Further more, morphological image processing is introduced to refine the image contour. The experiment shows that our method can achieve good segmentation results in a fast way.
A Modular Rewriting Semantics for CML

This paper presents a modular rewriting semantics (MRS) specification for Reppy's Concurrent ML (CML), based on Peter Mosses' modular structural operational semantics specification for CML. A modular rewriting semantics specification for a programming language is a rewrite theory in rewriting logic written using techniques that support the modular development of the specification in the precise sense that every module extension is conservative. We show that the MRS of CML can be used to interpret CML programs using the rewrite engine of the Maude system, a high- performance implementation of rewriting logic, and to verify CML programs using Maude's built-in LTL model checker. It is assumed that the reader is familiar with basic concepts of structural operational semantics and algebraic specifications.
A Quantitative Evaluation of the Multi-Disciplinary Approach to Prevention Services (MAPS) Program to Protect Children and Strengthen Families

ABSTRACT This article presents the results from an evaluation of a state-funded, prevention-based, pilot program called the Multi-Disciplinary Approach to Prevention Services that was designed to reduce the potential for child abuse and neglect. The program served 64 families of various races and ethnicities over two years. A quantitative pretest–posttest design was used to analyze existing program data related to client outcomes including parenting skills, parenting satisfaction, and the use of non-family resources to assist in improving skills and satisfaction. Means comparisons were used to assess the relationship between three standardized instruments (the Parenting Scale, the Eyberg Child Behavior Inventory and the Kansas Parental Satisfaction Scale). Findings indicated a statistically significant improvement regarding resource engagement by families, parenting behaviors and perceptions, and involvement with Child Protective Services. The results from this study offer insight into how to improve parenting behaviors and increase child protective factors for youth who are at risk of maltreatment. In addition, these findings contribute to strengthen the legitimacy of Weiner's Attribution Theory while providing the social work profession with additional data in areas of research targeting the intersection of financially viable prevention programs, family stability, parental education, resources engagement, and the reduction of child abuse and neglect. If additional research supports the efficacy of prevention programs such as MAPS, funding similar programs could lead to improved parenting and decreases in child maltreatment.
Expression of Olfactory Signaling Genes in the Eye

Purpose To advance our understanding how the outer eye interacts with its environment, we asked which cellular receptors are expressed in the cornea, focusing on G protein-coupled receptors. Methods Total RNA from the mouse cornea was subjected to next-generation sequencing using the Illumina platform. The data was analyzed with TopHat and CuffLinks software packages. Expression of a representative group of genes detected by RNA-seq was further analyzed by RT-PCR and in situ hybridization using RNAscope technology and fluorescent microscopy. Results We generated more than 46 million pair-end reads from mouse corneal RNA. Bioinformatics analysis revealed that the mouse corneal transcriptome reconstructed from these reads represents over 10,000 gene transcripts. We identified 194 GPCR transcripts, of which 96 were putative olfactory receptors. RT-PCR analysis confirmed the presence of several olfactory receptors and related genes, including olfactory marker protein and the G protein associated with olfaction, Gαolf. In situ hybridization showed that mRNA for olfactory marker protein, Gαolf and possibly some olfactory receptors were found in the corneal epithelial cells. In addition to the corneal epithelium, Gαolf was present in the ganglionic and inner nuclear layers of the retina. One of the olfactory receptors, Olfr558, was present primarily in vessels of the eye co-stained with antibodies against alpha-smooth muscle actin, indicating expression in arterioles. Conclusions Several species of mRNA encoding putative olfactory receptors and related genes are expressed in the mouse cornea and other parts of the eye indicating they may play a role in sensing chemicals in the ocular environment.
Structured Named Entity Retrieval in Audio Broadcast News

This paper focuses on the role of structures in named entity retrieval inside audio transcription. We consider the transcription documents structures that guide the parsing process, and from which we deduce an optimal hierarchical structure of the space of concepts. Therefore, a concept (named entity) is represented by a node or any sub-path in this hierarchy. We show the interest of such structure in the recognition of the named entities using the Conditional Random Fields (CRFs). The comparison of our approach to the Hidden Markov Model (HMM) method shows an important improvement of recognition using Combining CRFs. We also show the impact of time axis in the prediction process.
Open-ended waveguide antenna for microwave breast cancer detection

Microwave imaging techniques for breast cancer detection have attacked many research groups recently. The key element for the microwave imaging system is the antenna. In this paper, a small flanged open-ended rectangular waveguide antenna (ORWA) is proposed for breast cancer detection. WR 62 waveguide which has cut-off frequency of 9.5 GHz is used in the design process. A 16-element antenna array plane is proposed for operation at a frequency of 12.6 GHz. Measurement and simulation results show that the designed single ORWA can obtain a return loss less than -60 dB at frequency of 12.12 GHz. The scattered field detection capability is also tested under our developed holographic microwave imaging array (HMIA) system for breast phantom detection. The experimental results show that the proposed ORWA has the ability to detect tumour as small as 2.5 mm within the breast phantom.
Utrecht Multi-Person Motion ( UMPM ) benchmark

Analyzing human motion, including tracking and pose estimation, is a major topic in computer vision for several decades. Many methods have been and will be developed further in the future. To have a systematic and quantitative evaluation of such methods, ground truth data of the 3D human motion is scientifically required. For scenes limited to only a single person, there exist some publicly available data sets like HumanEva that provide synchronized video sequences together with detailed ground truth 3D data. However, for multiple persons, such a data set currently does not exist. In this report, we present the Utrecht Multi-Person Motion (UMPM) benchmark, which includes synchronized motion capture data and video sequences from multiple viewpoints for multi-person motion including multi-person interaction. The data set is available to the research community via http://www.projects. science.uu. nl/umpm/including documentation and software to promote further research in multi-person articulated human motion analysis. This report gives a detailed literature survey on publicly available data sets, describes the details of the data acquisition, the format of the provided data and the accompanying software.
Memory for biopsychology material presented in comic book format

This study investigated the influence of format of presentation on memory for undergraduate level biopsychology material. Ninety participants read either seven comic book pages explaining the rudiments of sleep, the same material presented in text-only format or seven pages where the original images were replaced with random incongruous images. Participants were tested on the material using ten multiple-choice questions. Results showed significantly higher memory scores in the comic condition compared with both the text-only and the incongruous comic condition. Furthermore, the text-only version showed significantly higher memory scores than the incongruous comic condition. It was concluded, that while there were some limitations to the study, the findings provided preliminary evidence to support the general idea of using comic books to create instructional materials. Results also provided some support for dual coding theory as a theoretical basis for the use of comics in educational contexts.
Data gathering in wireless sensor networks through intelligent compressive sensing

The recently emerged compressive sensing (CS) theory provides a whole new avenue for data gathering in wireless sensor networks with benefits of universal sampling and decentralized encoding. However, existing compressive sensing based data gathering approaches assume the sensed data has a known constant sparsity, ignoring that the sparsity of natural signals vary in temporal and spatial domain. In this paper, we present an adaptive data gathering scheme by compressive sensing for wireless sensor networks. By introducing autoregressive (AR) model into the reconstruction of the sensed data, the local correlation in sensed data is exploited and thus local adaptive sparsity is achieved. The recovered data at the sink is evaluated by utilizing successive reconstructions, the relation between error and measurements. Then the number of measurements is adjusted according to the variation of the sensed data. Furthermore, a novel abnormal readings detection and identification mechanism based on combinational sparsity reconstruction is proposed. Internal error and external event are distinguished by their specific features. We perform extensive testing of our scheme on the real data sets and experimental results validate the efficiency and efficacy of the proposed scheme. Up to about 8dB SNR gain can be achieved over conventional CS based method with moderate increase of complexity.