Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloning, Expression, and Enzymatic Characterization of Pseudomonas aeruginosaTopoisomerase IV

ABSTRACT The topoisomerase IV subunit A gene, parC homolog, has been cloned and sequenced from Pseudomonas aeruginosa PAO1, with cDNA encoding the N-terminal region of Escherichia coli parC used as a probe. The homolog and its upstream gene were presumed to be parC and parE through sequence homology with the parC and parE genes of other organisms. The deduced amino acid sequence of ParC and ParE showed 33 and 32% identity with that of the P. aeruginosa DNA gyrase subunits, GyrA and GyrB, respectively, and 69 and 75% identity with that of E. coli ParC and ParE, respectively. The putative ParC and ParE proteins were overexpressed and separately purified by use of a fusion system with a maltose-binding protein, and their enzymatic properties were examined. The reconstituted enzyme had ATP-dependent decatenation activity, which is the main catalytic activity of bacterial topoisomerase IV, and relaxing activities but had no supercoiling activity. So, the cloned genes were identified asP. aeruginosa topoisomerase IV genes. The inhibitory effects of quinolones on the activities of topoisomerase IV and DNA gyrase were compared. The 50% inhibitory concentrations of quinolones for the decatenation activity of topoisomerase IV were from five to eight times higher than those for the supercoiling activities ofP. aeruginosa DNA gyrase. These results confirmed that topoisomerase IV is less sensitive to fluoroquinolones than is DNA gyrase and may be a secondary target of new quinolones in wild-typeP. aeruginosa.
Register constrained modulo scheduling

Software pipelining is an instruction scheduling technique that exploits the instruction level parallelism (ILP) available in loops by overlapping operations from various successive loop iterations. The main drawback of aggressive software pipelining techniques is their high register requirements. If the requirements exceed the number of registers available in the target architecture, some steps need to be applied to reduce the register pressure (incurring some performance degradation): reduce iteration overlapping or spilling some lifetimes to memory. In the first part, we propose a set of heuristics to improve the spilling process and to better decide between adding spill code or directly decreasing the execution rate of iterations. The experimental evaluation, over a large number of representative loops and for a processor configuration, reports an increase in performance by a factor of 1.29 and a reduction of memory traffic by a factor of 1.36. In the second part, we analyze the use of backtracking and propose a novel approach for simultaneous instruction scheduling and register spilling in modulo scheduling: MIPS (modulo scheduling with integrated register spilling). The experimental evaluation reports an increase in performance by a factor of 1.46 and a reduction of the memory traffic by a factor of 1.66 (or an additional 1.13 and 1.22 with regard to the proposal in the first part). These improvements are achieved at the expense of a reasonable increase in the compilation time.
Grasping algorithms: exploring toys that teach computational thinking

Computational thinking has received increased attention over the past several years and is considered by many to be a fundamental and necessary literacy for children. One approach to teaching this skill has been through tangible programming since it facilitates intuitive interaction with children. In this paper, we introduce CodeTrain and CodeBox, two motorized toys whose behavior can be programmed through wooden building blocks without the use of a computer, tablet, or screen-based interface. The goal with both these designs is to foster playful exploration of computational thinking in pre-adolescent children through tangible objects. We describe the design process from the conceptual design to the functional prototype. Furthermore, we present first impressions of the prototypes from a pilot study and highlight some lessons learned from our first iteration.
Road Centerline Extraction in Complex Urban Scenes From LiDAR Data Based on Multiple Features

Automatic extraction of roads from images of complex urban areas is a very difficult task due to the occlusions and shadows of contextual objects, and complicated road structures. As light detection and ranging (LiDAR) data explicitly contain direct 3-D information of the urban scene and are less affected by occlusions and shadows, they are a good data source for road detection. This paper proposes to use multiple features to detect road centerlines from the remaining ground points after filtering. The main idea of our method is to effectively detect smooth geometric primitives of potential road centerlines and to separate the connected nonroad features (parking lots and bare grounds) from the roads. The method consists of three major steps, i.e., spatial clustering based on multiple features using an adaptive mean shift to detect the center points of roads, stick tensor voting to enhance the salient linear features, and a weighted Hough transform to extract the arc primitives of the road centerlines. In short, we denote our method as Mean shift, Tensor voting, Hough transform (MTH). We evaluated the method using the Vaihingen and Toronto data sets from the International Society for Photogrammetry and Remote Sensing Test Project on Urban Classification and 3-D Building Reconstruction. The completeness of the extracted road network on the Vaihingen data and the Toronto data are 81.7% and 72.3%, respectively, and the correctness are 88.4% and 89.2%, respectively, yielding the best performance compared with template matching and phase-coded disk methods.
Model Comparison: a Systematic Mapping Study

Context: Model comparison plays a central role in many software engineering activities. However, a comprehensive understanding about the state-of-art is still required. Goal: This paper, therefore, aims at classifying, identifying publication fora, and performing thematic analysis of the current literature in model comparison for creating an extensive and detailed understanding about this area, thereby determining gaps by graphing and pinpointing in which research areas and for which study types a shortage of publications still exits. Method: We have conducted a systematic mapping study to scrutinize those contributions produced over time, which research topics have most investigated, and which research methods that have been applied. For this, we have followed well-established empirical guidelines to define and apply a systematic mapping study. Results: The results are: (1) majority of studies (14 out of 40) provide generic model comparison techniques, rather than comparison techniques for UML diagrams; (2) a categorization and quantification of the current studies in a variety of dimensions; and (3) an overview of current research topics and trends.
Negotiating Parent-Adolescent Conflict: A Behavioral-Family Systems Approach

Introduction. Theoretical Orientation. Empirical Evaluation of Behavioral-Family Systems Theory. Assessment-Overview and Interviewing. Questionnaire and Observational Assessment. Conceptualizing and Integrating Assessment Data. Treatment-Overview and Problem-Solving Training. Communication Training. Cognitive Restructuring. Functional/Structural Interventions. Sequencing Intervention. Resistance. Case Studies. Treatment Outcome Research. Future Directions.
Improving the locality of the sparse matrix-vector product on shared memory multiprocessors

We extend a model of locality and the subsequent process of locality improvement previously developed for the case of sparse algebra codes in monoprocessors to the case of NUMA shared memory multiprocessors (SMPs). In particular the product of a sparse matrix by a dense vector (SpM/spl times/V) is studied. In the model, locality is established at run-time considering parameters that describe the structure of the sparse matrix involved in the computations. The problem of increasing the locality is formulated as a graph problem, whose solution indicates some appropriate reordering of rows and columns of the sparse matrix. The reordering algorithms were tested for a broad set of matrices. We have also performed a comparison with other reordering algorithms. The results lead to general conclusions about improving SMP performance for other sparse algebra codes.
An Algorithmic Framework for Estimating Rumor Sources With Different Start Times

We study the problem of identifying multiple rumor or infection sources in a network under the susceptible-infected model, and where these sources may start infection spreading at different times. We introduce the notion of an abstract estimator that, given the infection graph, assigns a higher value to each vertex in the graph it considers more likely to be a rumor source. This includes several of the single-source estimators developed in the literature. We introduce the concepts of a quasi-regular tree and a heavy center, which allows us to develop an algorithmic framework that transforms an abstract estimator into a two-source joint estimator, in which the infection graph can be thought of as covered by overlapping infection regions. We show that our algorithm converges to a local optimum of the estimation function if the underlying network is a quasi-regular tree. We further extend our algorithm to more than two sources, and heuristically to general graphs. Simulation results on both synthetic and real-world networks suggest that our algorithmic framework outperforms several existing multiple-source estimators, which typically assume that all sources start infection spreading at the same time.
Objections in Research Interviewing

In this article the author argues that research interviewing can be a form of research practice in which the subjects of study can object to the researcher's questions and the interview's theme. Researchers performing qualitative interviews should pay particular attention to situations where interviewees object to what we think, say, and write about them. The author draws on empirical examples where the objections and hesitations voiced by the interviewees toward the interviewer's questions became part of reconsidering the initial theoretical concepts guiding the research process. She argues that the interviewer should not provoke such situations but, rather, be sensitive enough to remain open to the possibility that the interviewee might feel a need to object to or refuse the researcher's interpretations. When this happens, it can allow for a fruitful exploration of the theme of conversation and the researcher's agenda.
Cell-Based Therapy of Myocardial Infarction

Cell-based therapy is a promising option for treatment of ischemic diseases. Several cell types have experimentally been shown to increase the functional recovery of the heart after ischemia by physically forming new blood vessels, differentiating to cardiac myocytes and—additionally or alternatively—by providing proangiogenic and antiapoptotic factors promoting tissue repair in a paracrine manner. Clinical studies preferentially used adult bone marrow–derived cells for the treatment of patients with acute myocardial infarction. Most of the studies suggested that cell therapy reduced the infarct size and improved cardiac contractile function. However, cell therapy is in its early stages, and various questions remain. For example, the identification of those patients who benefit most from cell therapy, the optimal cell type and number for patient with acute and chronic diseases, the best time and way of cell delivery, and the mechanisms of action by which cells exhibit beneficial effects, need to be further evaluated. Although no major safety concerns were raised during the initial clinical trials, several potential side effects need to be carefully monitored. The present review article summarizes the results of the clinical studies and discusses the open issues.
Rater bias patterns in an EFL writing assessment

The present study employed multi-faceted Rasch measurement (MFRM) to explore the rater bias patterns of native English-speaker (NES) raters when they rate EFL essays. Forty NES raters rated 40 essays written by female Japanese university students on a single topic adapted from the TOEFL Test of Written English (TWE). The essays were assessed using a six-category rating scale (Content, Organization, Style and Quality of Expression, Language Use, Mechanics, and Fluency). MFRM revealed several recurring bias patterns among rater subgroups. In rater—category bias interactions, if Content and/or Organization were rated severely, then Language Use and/or Mechanics were rated leniently, and vice versa. In rater—writer bias interactions, there tended to be more severe or lenient bias towards higher ability writers than lower ability writers. Some raters also rated higher ability writers more severely and lower ability writers more leniently than expected. This study has implications for issues of rater training in L2 writing assessment.
Micrographia in Parkinson’s disease: the effect of providing external cues

OBJECTIVE To investigate whether micrographia in patients with Parkinson’s disease is lessened either by giving visual targets or by continually reminding them that they should write with a normal amplitude. METHODS Eleven patients with Parkinson’s disease (mean age 65.4 years) were compared with 14 control subjects (mean age 67.1 years). The subjects wrote with a stylus on a graphics tablet. There were three conditions: free writing, writing with dots to indicate the required size, and writing with continuous verbal reminders (“big”). Each condition was performed twice. RESULTS The patients wrote with a more normal amplitude when given either the visual cues or the auditory reminders. This improvement persisted when, shortly afterwards, the patients wrote freely without external cues. The increase in amplitude was achieved mainly by an increase in movement time rather than in peak velocity. CONCLUSION Whereas the visual cues directly specified the required amplitude the auditory reminders did not. One effect of external cues is that they draw attention to the goal, and thus encourage the patients to write less automatically.
The Impact of College Education on Rape Myth Acceptance, Alcohol Expectancies, and Bystander Attitudes

The purpose of this study was to examine the impact of education on rape myth acceptance, alcohol expectancies, and bystander attitudes. A sample of 126 community members and college students who had consumed alcohol within the past 90 days were administered surveys. College experience was unrelated to rape myth acceptance, alcohol expectancies, and bystander intentions. In line with previous research, two rape myth subscales were inversely related to bystander attitudes. In regard to alcohol expectancies and bystander attitudes, only one subscale was marginally significant. Ancillary analysis indicated that rape myth acceptance varied as a function of age, with older individuals less likely to support rape myths.
Automatic annotation of geo-information in panoramic street view by image retrieval

Panoramic street view is now becoming a popular service in digital map due to its expedient of virtual walking through. Recently, some geo-tagged photos have been added into street view as additional illustration images for the same scenes. However, these images come directly from certain photo sharing websites where users manually tag the locations of their uploaded images; the quality of annotated location is very poor. In this paper, we propose a system to annotate the location tags of users' images in panoramic street view only with visual features. By searching the exemplar region which mostly matches the query image, the system can annotate the query image with geo-information provided by the matched exemplar image. In order to boost matching performance, various techniques such as the motion estimation, visual clustering and feature matching are implemented in our system. The experiments show satisfactory performance and promising results.
Capacity versus Speed in Intelligence and Ageing

Abstract Contemporary explanations of both cognitive ageing and individual differences in cognitive abilities stress both the role of capacity (e.g., working memory) and speed of mental processing. However, researchers frequently lay a particular emphasis on one or the other. In the area of intelligence, those theorists who emphasise a general factor tend to favour speed whereas multiple intelligence theorists favour capacity explanations. In the area of ageing, general slowing (i.e., speed) appears to be the preferred explanation for cognitive decline. This paper will review these arguments and present evidence favouring the role of capacity rather than speed in both ageing and intelligence.
Young children’s communication and expression of values during play sessions in preschool

The article explores how young children between one and three years old communicate and prioritise values in order to create and be a part of a community during play sessions in an Icelandic preschool. Furthermore, it aims to investigate the value conflicts that might occur and how the children resolve such conflicts. The study adopts the phenomenological approach of Merleau-Ponty emphasising human bodily existence. Data consist mainly of video recordings. The findings show three main categories that illustrate the values that the children prioritised and found meaningful to their interaction in their play: the value of ownership of toys, the value of others’ well-being and the value of belonging to the community. The values could also be in opposition to values that were either prioritised within the group of children or emphasised by the educators. The study implies that play situations are a valuable arena for children’s learning of values. The value conflicts appeared to be especially important, including children’s confrontations with each other’s perspectives and requiring the children to clarify their views. Thus, children’s positions and possibilities within the group became visible and influenced the resolution of the conflicts.
NN C+SVM: An empirical study for fast classification

This paper proposes a hybrid learning method to speed up classification procedure of Support Vector Machines (SVM). Comparing most algorithms trying to decrease the support vectors in an SVM classifier, we focus on reducing the data points that need SVM for classification, and reduce the number of support vectors for each SVM classification. The system uses a nearest neighbor classifier(NNC) to treat data points attentively. In the training phase, the NNC selects data near partial decision boundary, and then train sub SVMs for each prototype pair. For classification, most non-boundary data points are classified by NNC directly, while remaining boundary data points are passed to an expert SVMs, which is much simpler than a general SVM. Experimental results show that the proposed method significantly accelerates the testing speed on several generated data sets.
A Performance Modeling System for Message-Passing Parallel Programs

We present a new performance modeling system for message-passing parallel programs that is based around a Performance Evaluating Virtual Parallel Machine (PEVPM). We explain how a PEVPM model for a particular message-passing program can be developed by inserting PEVPM performance directives that describe the serial segments of computation and the message-passing events that the program contains. This is a novel bottom-up approach to performance modeling, which aims to accurately model when processing and message-passing occurs during program execution. Since the times at which these functions are performed are dynamic because they are affected by network contention and data dependencies, we use a virtual machine to simulate program execution. This simulation is done by executing PEVPM performance directives rather than executing the code itself, so it is very fast. However, it is still very accurate because enough information is stored by the PEVPM to dynamically create detailed submodels of processing and communication. Another novel feature of our approach is that the submodels used for communication allow completion time for individual message-passing calls to be sampled from a probability distribution that describes the performance variability exhibited by communication subject to contention. These performance distributions can be empirically measured using a suite of highly accurate message-passing benchmarks that we have developed. This approach provides a Monte Carlo analysis that can give very accurate results for the average and the variance (or even the probability distribution) of program execution time. In this paper, we introduce the ideas underpinning the PEVPM technique, describe the syntax of the modeling language and virtual machine that supports it, and discuss the power of the methodology.
Phonological Characteristics of Developmental Verbal Dyspraxia

~lthough much controversy surrounds the concept of developmental verbal dyspraxia (DVD), there is common acknowledgment that a primary symptom of this communication disorder is a severe phonological deficit. Regardless of their orientation, most published articles on this topic refer to, or describe, significant phonological limitations as a major focus of DVD. However, despite the focal nature of the phonological impairment in DVD, only a few studies have tried systematically to delineate the types of phonological errors observed in these children (Morle~, 1967; Rosenbek and Wertz, 1972; Yoss and Darley, 1974; Aram and Glasson, 1979). Although each of these reports proceeded from a slightly different orientation, they agreed that the phonological deficit in DVD is severe. Furthermore, there was considerable overlap among their findings. The following is a summary of the findings common among these reports:
Near-optimal Sleep Scheduling of a Rechargeable Sensor under Temporal Correlations

In this brief survey, we review and summarize our recent work on efficient sleep scheduling of a rechargeable sensor deployed to detect events that exhibit temporal correlations. We pose the dynamic sensor sleep scheduling question in a stochastic optimization framework. Under complete state observability, we show that the optimal sleep scheduling policy has a very simple structure. In a more realistic scenario where a sleeping sensor cannot observe the system state, we show that a simple policy using an appropriately chosen fixed sleep duration attains near-optimal performance. Finally, we argue that an aggressive wakeup policy is optimal if and only if there are no temporal correlations in the event process.
Tagrank - Measuring tag importance for image annotation

Traditional image annotation approaches are only applicable for datasets with small and limited lexicon. Besides, annotation words are treated equally without considering the importance of each word in the real world. To address these problems, we propose TagRank, a method to model the relative importance of every candidate word. By exploiting tag clusters on Flickr, TagRank could be modeled as random walk with restarts, which incorporates both word frequency and word correlation information. As a result, a ranked annotation vocabulary could be built. By utilizing the tag importance in a real image annotation experiment, we show that TagRank is helpful for improving the performance of image annotation.