Miracle-dz/UniFAR-FTUs huggingface dataset:
Tool support for helping the use of frameworks

Frameworks promote design and code reuse, at a higher level of granularity. The use of frameworks is a hard task though, because usually they lack documentation and instructions on how to use them, thus being, in general, very difficult to understand. The paper addresses some mechanisms to help in object oriented framework usage. It presents SEA-Preceptor, a hyperdocument based tool that sets up the possible paths to be followed by framework users to construct applications. SEA-Preceptor hyperdocuments also allow navigating through design or code of frameworks (or applications), as a way of helping in framework understanding. Frameworks and applications are specified in SEA environment (which hosts SEA-Preceptor and other tools) as sets of diagrammatic models that are views of a semantically checked metamodel repository, which is semi-automatically translated into source code.
Robust Adaptive Beamformers Based on Worst-Case Optimization and Constraints on Magnitude Response

In this paper, novel robust adaptive beamformers are proposed with constraints on array magnitude response. With the transformation from the array output power and the magnitude response to linear functions of the autocorrelation sequence of the array weight, the optimization of an adaptive beamformer, which is often described as a quadratic optimization problem in conventional beamforming methods, is then reformulated as a linear programming (LP) problem. Unlike conventional robust beamformers, the proposed method is able to flexibly control the robust response region with specified beamwidth and response ripple. In practice, an array has many imperfections besides steering direction error. In order to make the adaptive beamformer robust against all kinds of imperfections, worst-case optimization is exploited to reconstruct the robust beamformer. By minimizing array output power with the existence of the worst-case array imperfections, the robust beamforming can be expressed as a second-order cone programming (SOCP) problem. The resultant beamformer possesses superior robustness against arbitrary array imperfections. With the proposed methods, a large robust response region and a high signal-to-interference-plus-noise ratio (SINR) enhancement can be achieved readily. Simple implementation, flexible performance control, as well as significant SINR enhancement, support the practicability of the proposed methods.
The Improvement of Naive Bayesian Classifier Based on the Strategy of Fuzzy Feature Selection

Naive Bayesian classifier (NBC) is a simple and effective classification model. However, the fact that the assumption of independence is often violated in reality makes it perform poorly on some datasets. We give a summary of previous improvement methods of the NBC model. In our study, we attempt to improve the NBC model based on the strategy of the fuzzy feature selection. The main idea of the improvement strategy is to adjust the features' contribution to classification through the feature important factor (FIF) which describes the importance of the features and the relevance between features. This strategy overcomes deficiencies caused by the assumption of independence. Through the experimental comparison and analysis on the UCI datasets, the strategy is proved effective
Probing the Retinol-binding Site of Bovine fl-Lactoglobulin *

The retinol-binding site of P-lactoglobulin has been located by selective modification of amino acid residues which reside in the two putative binding sites. Based upon two separate crystallographic analyses of bovine j3-lactoglobulin, different binding sites for retinol have been proposed one proposal favors an interior cavity, the other a surface cleft. To discriminate between these two models, we have made four separate site-directed mutations introducing a W19A or a K70M in the interior pocket and a F136A or K141M in the surface pocket. The K70M j? -lactoglobulin exhibited a marked decrease in ts binding of retinoic acid compared to the F136A, K141M, and wild-type proteins. Retinylidenepropylamine, a retinyl Schiff base analog of retinol, was synthesized and its absorption spectrum when bound to the wildtype, K70M, and K141M proteins was examined to probe its interaction with the respective lysine residues. The retinylidenepropylamine bound in the K70M p-lactoglobulin exhibited a kinetic red shift as distinct from the blue shift observed when it is bound to either the K141M or wild-type @lactoglobulins. The blue shift indicates protonation of the Schiff base. The r sulting tagged peptide was isolated after cyanogen bromide cleavage and found to be the Alaz6-Met1m peptide, consistent with the Lys” being the residue which interacts with the bound retinol. These results support the proposal that retinol binds to an evolutionarily conserved interior cavity rather than the surface pocket.
Absence of centrioles in the first and second meiotic spindles of mouse oocytes.

Centrioles are present in oogonia and oocytes of hamsters, mice, rats, gerbils and man up to the pachytene stage. In subsequent meiotic stages, centrioles are absent. At the time of germinal vesicle breakdown in the mouse several foci composed of electron-dense fibrillar material from which microtubules radiate appear near the nucleus. These fibrillar aggregates, referred to as microtubule foci, form small asters and collectively perform the role of the spindle pole during the two meiotic divisions. There are multiple centres at each pole and their number may vary. Thus, centrioles are not obligatory organelles of the spindle apparatus.
Incorrect estimates and false reports: How framing modifies truth

Nearly all framing studies to date presuppose unbiased estimates. If an expert says that “programme A will save 200 people”, it is tacitly assumed that this prediction is correct. In real life this is rarely the case. In the present study people were asked to evaluate such claims that eventually turned out to be incorrect. Participants in five experiments were asked to rate how correct, and how true, are predictions and reports that either overstate or understate the facts. Overall, understatements were considered more accurate than overstatements, and pessimistic statements were better than overly optimistic ones. Thus predictions of an outcome that turns out better than expected should preferably have been presented in a positive frame (e.g., money saved), whereas outcomes that turn out worse than expected will appear less “wrong” if predictions were presented in a negative frame (e.g., money lost). Parallel studies were performed with wrong predictions and incorrect factual claims (lies). In all studies, correctness ratings were affected by the way the statements were framed.
Multidetector computed tomography for acute pulmonary embolism: diagnosis and risk stratification in a single test.

AIMS In patients with acute pulmonary embolism (PE), right ventricular dysfunction at echocardiography is associated with increased in-hospital mortality. The aims of this study in patients with acute PE were to identify a sensitive and simple criterion for right ventricular dysfunction at multidetector computed tomography (MDCT) using echocardiography as the reference standard and to evaluate the predictive value of the identified MDCT criterion for in-hospital death or clinical deterioration. METHODS AND RESULTS Right ventricular dysfunction at MDCT was defined as the right-to-left ventricular dimensional ratio and was centrally assessed by a panel unaware of clinical and echocardiographic data. A right-to-left ventricular dimensional ratio ≥0.9 at MDCT had a 92% sensitivity for right ventricular dysfunction [95% confidence interval (CI) 88-96]. Overall, 457 patients were included in the outcome study: 303 had right ventricular dysfunction at MDCT. In-hospital death or clinical deterioration occurred in 44 patients with and in 8 patients without right ventricular dysfunction at MDCT (14.5 vs. 5.2%; P< 0.004). The negative predictive value of right ventricular dysfunction for death due to PE was 100% (95% CI 98-100). Right ventricular dysfunction at MDCT was an independent predictor for in-hospital death or clinical deterioration in the overall population [hazard ratio (HR) 3.5, 95% CI 1.6-7.7; P= 0.002] and in haemodynamically stable patients (HR 3.8, 95% CI 1.3-10.9; P= 0.007). CONCLUSION In patients with acute PE, MDCT might be used as a single procedure for diagnosis and risk stratification. Patients without right ventricular dysfunction at MDCT have a low risk of in-hospital adverse outcome.
Emotion-memory effects in bilingual speakers: A levels-of-processing approach*

Emotion-memory effects occur when emotion words are more frequently recalled than neutral words. Bilingual speakers report that taboo terms and emotional phrases generate a stronger emotional response when heard or spoken in their first language. This suggests that the basic emotion-memory will be stronger for words presented in a first language. Turkish–English bilinguals performed a deep processing task (emotional-intensity rating) or shallow processing task (counting letter features) and two additional deep processing tasks (translation and word association) on five categories of words (taboo words, reprimands, positive words, negative words, and neutral words), followed by a surprise recall task. Reprimands had the highest recall in English (L2), which may be a novelty effect. If reprimands are set aside, then overall emotion-memory effects were similar in the two languages, with taboo words having the highest recall, followed by positive words. Negative words had no recall advantage over neutral words, an unexpected finding. Results indicate that emotional attributes of words are equally available to boost memory in a first and second language in both shallow and deep processing tasks, athough some task-specific effects did occur.
Autoregressive hidden Markov model with missing data for modelling functional MR imaging data

Functional Magnetic Resonance Imaging (fMRI) has opened ways to look inside active human brain. However, fMRI signal is an indirect indicator of underlying neuronal activity and has low-temporal resolution due to acquisition process. This paper proposes autoregressive hidden Markov model with missing data (AR-HMM-md) framework which aims at addressing aforementioned issues while allowing accurate capturing of fMRI time series characteristics. The proposed work models unobserved neuronal activity over time as sequence of discrete hidden states, and shows how exact inference can be obtained with missing fMRI data under the "Missing not at Random" (MNAR) mechanism. This mechanism requires explicit modelling of the missing data along with the observed data. The performance is evaluated by observing convergence characteristic of log-likelihoods and classification capability of the proposed model over existing models for two fMRI datasets. The classification is performed between real fMRI time series from a task-based experiment and randomly-generated time series. Another classification experiment is performed between children and elder subjects using fMRI time series from resting-state data. The proposed model captured the fMRI characteristics efficiently and thus converged to better posterior probability resulting into higher classification accuracy over existing models for both the datasets.
Student Teaching Feedback and Evaluation: Results From a Seven-State Survey

Recent surveys have provided some guidance and recommendations for the student teaching component in early childhood teacher preparation, but specific information on the focus of supervision and evaluation of student teachers is limited. The current study surveyed 128 early childhood programs in 2- and 4-year institutions of higher education across seven states. The study collected data in areas such as which students receive feedback, how students are supervised and evaluated, and what types of assessment tools contribute to the evaluation. Results indicate that across 2- and 4-year institutions, language and literacy are a strong focus of feedback for student teachers, as well as child development, planning, and adult–child interactions. Student teachers are typically supervised through on-site visits that range in number and length fairly dramatically across 2- and 4-year institutions. Finally, the use of specific tools for evaluation varies across programs; about a quarter of programs surveyed use a published tool to evaluate student teachers. The majority of programs use an evaluation tool that is based on local, state, or national standards. Findings are discussed in terms of early childhood teacher preparation programs and the continuing discussions of recommendations for student teaching.
Learning to blend rankings: a monotonic transformation to blend rankings from heterogeneous domains

There have been great needs to develop effective methods for combining multiple rankings from heterogeneous domains into one single rank list arising from many recent web search applications, such as integrating web search results from multiple engines, facets, or verticals. We define this problem as Learning to blend rankings from multiple domains. We propose a class of learning-to-blend methods that learn a monotonically increasing transformation for each ranking so that the rank order in each domain is preserved and the transformed values are comparable across multiple rankings. The transformation learning can be tackled by solving a quadratic programming problem. The novel machine learning method for blending multiple ranking lists is evaluated with queries sampled from a commercial search engine and a promising improvement of Discounted Cumulative Gain has been observed.
A Novel Method for Reducing Computational Complexity of Whole Genome Sequence Alignment

National Institute of Advanced Industrial Science and Technology,Computational Biology Research Center,2-42 Aomi, Koto-ku, Tokyo 135-0064, JapanGenomic sequence alignment is a powerful tool for ﬁnding com mon subsequence patterns sharedby the input sequences and identifying evolutionary relationships between the species. However, therunning time and space requirement of genome alignment have often been very extensive. In thisresearch, we propose a novel algorithm called Coarse-Grained AlignmenT (CGAT) algorithm, forreducing computational complexity necessary for cross-species whole genome sequence alignment.The CGAT ﬁrst divides the input sequences into ”blocks” with a ﬁxed length and aligns these blocksto each other. The generated block-level alignment is then reﬁned at the nucleotide level. This two-stepprocedure can drastically reduce the overall computational time and space necessary for an alignment.In this paper, we show the effectiveness of the proposed algorithm by applying it to whole genomesequences of several bacteria.Keywords: Genome Alignment; Multiple Alignment; Sequence Analysis; Comparative Genomics.
Ant Colony System Based Mobile Robot Path Planning

Ant colony optimization (ACO) is a new evolvement algorithm that is proposed by Dorigo M. , and solves some task allocation and target search problems to program the motion path searching food. The topic of the article uses the ant colony optimization algorithm to mobile robot system, and solve the problem of mobile robot path planning such that the target point in a collision free space. The simulated results presents that ACO can finds the optimization motion path for mobile robot moving to the target position (food) from the start position (nest) in a collision-free environment.
First-Person Locomotion in 3D Virtual Environments: a Usability Analysis

D Virtual Environments (VE) are becoming popular as a tool for cog- nitive, functional and psychological assessment. Navigation in these environments is recognized as one of the most difficult activities in 3D Virtual Environments (VE). Users unfamiliar to 3D games, specially elder persons, get puzzled when they try to virtually move an avatar through these environments. Their inability to navigate pre- vents them from concentrating in the task and even to finish it. In this paper, we analyze the influence of different factors in locomotion control. We investigate the impact of having the cursor fixed at the camera center or leaving it free inside the current view. We also analyze the influence of the pitch angle on the camera control. In addition, we have designed an automatic locomotion system that we compare to user-controlled locomotion. We describe a virtual scenario and a test task that we have implemented to evaluate these different methods with users of diverse profiles. We conclude that, for non-casual gamers, automatic locomotion is the faster and preferred mode, whereas gamers prefer to control locomotion themselves. For non- automatic locomotion, the performance is better when the cursor is fixed in the view center point during locomotion. On the contrary, for still positions, a free-cursor is preferable. Finally, restriction of the pitch angle in a solid angle that encompasses the objects related to the task is better than a free pitch angle rotation for still po- sitions. During locomotion, fixing the pitch angle at the horizontal level enhances the locomotion.
Tunable N-Path Notch Filters for Blocker Suppression: Modeling and Verification

N-path switched-RC circuits can realize filters with very high linearity and compression point while they are tunable by a clock frequency. In this paper, both differential and single-ended N-path notch filters are modeled and analyzed. Closed-form equations provide design equations for the main filtering characteristics and nonidealities such as: harmonic mixing, switch resistance, mismatch and phase imbalance, clock rise and fall times, noise, and insertion loss. Both an eight-path single-ended and differential notch filter are implemented in 65-nm CMOS technology. The notch center frequency, which is determined by the switching frequency, is tunable from 0.1 to 1.2 GHz. In a 50-Ω environment, the N-path filters provide power matching in the passband with an insertion loss of 1.4-2.8 dB. The rejection at the notch frequency is 21-24 dB, P1 dB > +2 dBm, and IIP3 > +17 dBm.
Force control in a parallel manipulator through virtual foundations

An overwhelming controller provides robustness against uncertain parameters, disturbances and un-modelled dynamics. A simplified inverse dynamics model is used in the present paper to develop an overwhelming controller for a parallel manipulator (a Stewart platform), where the controller accommodates modelling uncertainties such as the simplifications made for development of the inverse model in order to improve the computational efficiency. Such a control strategy leads to good trajectory tracking accuracy in the presence of unknown disturbances. However, in addition to trajectory tracking performance, the controller for a Stewart platform should also be able to control or limit the interaction forces in applications such as robot assisted surgery and low-impact docking. The environmental forces can be accommodated during the interaction period by modulating the impedance at the interface of manipulator and environment through virtual flexible foundations. The positional error induced during the force control phase can be recovered during the free flight or idle phase. While this approach has been used successfully in the past to control serial manipulators, the closed loop kinematic architecture in a parallel manipulator introduces many difficulties. This paper proposes a modified overwhelming control scheme for parallel manipulators with compensations for interaction force control and positional error recovery. Bond graph modelling is used as an integrated model and controller development tool. Force controlled machining on a spherical surface, which is akin to a surgical operation, is considered as an example application of the developed control strategy. The simulation results from the bond graph model of the controlled Stewart platform are presented to demonstrate the performance of the developed hybrid position force controller.
The Subjective Present and Its Modulation in Clinical Contexts

Time is a basic dimension in psychology, underlying behavior and experience. Timing and time perception constitute implicit processes that are often inaccessible to the individual person. Research in this field has shown that timing is involved in many areas of clinical significance. In the projects presented here, we combine timing with seemingly different fields of research, such as psychopathology, perceptual grouping, and embodied cognition. Focusing on the time scale of the subjective present, we report findings from three different clinical studies: (1) We studied perceived causality in schizophrenia patients, finding that perceptual grouping (‘binding’, ‘Gestalt formation’), which leads to visual causality perceptions, did not distinguish between patients and healthy controls. Patients however did integrate context (provided by the temporal distribution of auditory context stimuli) less into perceptions, in significant contrast to controls. This is consistent with reports of higher inaccuracy in schizophrenia patients’ temporal processing. (2) In a project on auditory Gestalt perception we investigated auditory perceptual grouping in schizophrenia patients. The mean dwell time was positively related to how much patients were prone to auditory hallucinations. Dwell times of auditory Gestalts may be regarded as operationalizations of the subjective present; findings thus suggested that patients with hallucinations had a shorter present. (3) The movement correlations of interacting individuals were used to study the non-verbal synchrony between therapist and patient in psychotherapy sessions. We operationalized the duration of an embodied ‘social present’ by the statistical significance of such associations, finding a window of roughly 5.7 seconds in conversing dyads.We discuss that temporal scales of nowness may be modifiable, e.g., by mindfulness. This yields promising goals for future research on timing in the clinical context: psychotherapeutic techniques may alter binding processes, hence the subjective present of individuals, and may affect the social present in therapeutic interactions.
Optimized Min-Sum Decoding Algorithm for Low Density Parity Check Codes

Low Density Parity Check (LDPC) code approaches Shannon-limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min- sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min- sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.