Miracle-dz/UniFAR-FTUs huggingface dataset:
IRAC Observations of Taurus Pre-Main-Sequence Stars

We present infrared photometry obtained with the IRAC camera on the Spitzer Space Telescope of a sample of 82 pre-main-sequence stars and brown dwarfs in the Taurus star-forming region. We find a clear separation in some IRAC color-color diagrams between objects with and without disks. A few "transition" objects are noted, which correspond to systems in which the inner disk has been evacuated of small dust. Separating pure disk systems from objects with remnant protostellar envelopes is more difficult at IRAC wavelengths, especially for objects with infall at low rates and large angular momenta. Our results generally confirm the IRAC color classification scheme used in previous papers by Allen et al. and Megeath et al. to distinguish between protostars, T Tauri stars with disks, and young stars without (inner) disks. The observed IRAC colors are in good agreement with recent improved disk models, and in general accord with models for protostellar envelopes derived from analyzing a larger wavelength region. We also comment on a few Taurus objects of special interest. Our results should be useful for interpreting IRAC results in other, less well studied star-forming regions.
Performance modeling and optimization of 3-D stencil computation on a stream-based FPGA accelerator

In this paper, we discuss user space parameters and performance modeling of 3-D stencil computing on a stream-based FPGA accelerator. We use a heat conduction simulation as a benchmark and evaluate a performance for that developed with MaxCompiler, a kind of high-level synthesis tools for FPGAs, and MaxGenFD, a domain specific framework on the MaxCompiler for finite-difference equations. Performance comparison with multi-threaded and SIMD-enabled CPU implementation shows FPGA design achieved about six times speedup when a user chose the best architectural parameters. Energy consumptions of the FPGA accelerator were measured and it is shown that the best configuration in terms of performance also shows the lowest energy consumption.
Novel SISO Detection Algorithms for Nonlinear Satellite Channels

We propose novel detection algorithms for linear modulations transmitted over nonlinear satellite channels. These algorithms are derived by using a Volterra-series expansion of the useful signal and by applying the sum-product algorithm to a suitably-designed factor graph. Being soft-input soft-output (SISO) in nature, the proposed detectors can be adopted in turbo processing without additional modifications. When compared with the optimal detection algorithm for these channels, whose complexity is exponential in the channel memory, the proposed schemes result very appealing in terms of tradeoff between performance and computational complexity. Particularly, they can approach the optimal performance with a complexity only linear in the channel memory.
Advancing a multivalent ‘Pan-anthelmintic’ vaccine against soil-transmitted nematode infections

The Sabin Vaccine Institute Product Development Partnership is developing a Pan-anthelmintic vaccine that simultaneously targets the major soil-transmitted nematode infections, in other words, ascariasis, trichuriasis and hookworm infection. The approach builds off the current bivalent Human Hookworm Vaccine now in clinical development and would ultimately add both a larval Ascaris lumbricoides antigen and an adult-stage Trichuris trichiura antigen from the parasite stichosome. Each selected antigen would partially reproduce the protective immunity afforded by UV-attenuated Ascaris eggs and Trichuris stichosome extracts, respectively. Final antigen selection will apply a ranking system that includes the evaluation of expression yields and solubility, feasibility of process development and the absence of circulating antigen-specific IgE among populations living in helminth-endemic regions. Here we describe a five year roadmap for the antigen discovery, feasibility and antigen selection, which will ultimately lead to the scale-up expression, process development, manufacture, good laboratory practices toxicology and preclinical evaluation, ultimately leading to Phase 1 clinical testing.
Registration of satellite images based on road network map

This paper presents a novel approach to fully automatic satellite image registration to a local earth coordinate system based on the digital map of the road network. Automatic satellite image co-registration methods typically establish correspondences between points on the target and registered image using local image features such as SIFT, however they are not effective for multi-temporal and multi-sensor registration. As the road network is a prominent feature on the satellite images and is visible in most circumstances, we propose to map it directly to the digital road network topographic map, which is readily available in GIS databases. Our approach starts by detection of road segments in a satellite image, producing a road mask image. Small road mask patches are matched against rasterized road network map to find a set of probable patch locations. Following optimization of translation parameters, each satellite image tile is coarsely located on a road map. In a second fine optimization step, smaller road patches locations are further optimized. The algorithm produces a set of tie points, which include coordinates of satellite image pixels within local metric coordinate system. Experiments were performed on a set of 5 RapidEye images of Slovenia from different periods of the year. The results show that the average error of the points is below 1 pixel for all images, and that the reliability in terms of outlier pixels is very high.
Packet detection scheme using cross correlation and complex multiplication in MB-OFDM UWB system

In this paper, we introduce a low power consumption packet detection scheme based on cross correlation and complex multiplication for MB-OFDM UWB system. The proposed scheme compares received signal power and calculated value explained later. The received signal is filtered by a correlator and then output of the correlator is multiplied with delayed output of the correlator and then we get the calculated value which is absolute value of output of complex multiplier. Filter tap coefficient of the correlator is given as sign value of known preamble. This scheme improves packet detection performance in multi-path fading channel model for MB-OFDM UWB system. Through the simulation for 4 block-fading channels, we describe that the proposed scheme can shrink degradation of packet detection performance due to any sampling timing offset and the fading channel model environment for MB-OFDM UWB system.
Research of text clustering based on fuzzy granular computing

The typical algorithm of text clustering is a “Hard Partition” one, Actually, Chinese text is better to treat with “Soft Partition” for its diversity and largeness. The fuzzy-set theory supply a powerful analyzing tool to this “Soft partition”. Traditional fuzzy text clustering methods mostly are getting the fuzzy equivalent matrix or fuzzy division by iterating the matrix of membership degree, huge storage space is necessary for that process. The text clustering based on fuzzy granular computing will work as: first provide a normalized distance function in the fuzzy granularity space of text set, then use the function to do a dynamic clustering work to text who has a less distance than granularity. Approved by the test, this method has such advantages on reducing the computing complexity and space complexity, suitable for the status that many samples need to be processed.
A Sociological Approach to the Rights of Children in Greek Primary Education

The aim of this research paper is the investigation of the rights of children concerning education, as they are set out in the International Convention on the Rights of the Child (1989), and as they are perceived by pupils through the pedagogical practices of their teachers in the primary schools. At the same time the degree of differentiation of the teachers’ pedagogical practices regarding the application of these rights is investigated. In order to carry out this research, in which pupils in year six of Greek primary schools participated, the tool of the semi-structured interview for the collection of research data was used. The main findings of this study revealed that two of the four rights of the children (the right to rest, leisure and play, and the right to freedom of expression and participation) were significantly restricted through the visible pedagogical practices that the teachers applied at the micro-level of the school classroom. In addition, the pedagogical practices applied, concerning the right to primary consideration of the pupils’ best interests and the right to equal treatment, tend towards the rules of an invisible pedagogy, which favours more the common processes of knowledge uptake amongst all the pupils.
SRMC: A Model for Web Services Registry with Multilevel Caches

In order to improve the efficiency of service discovery and release the load of service registry, this paper proposes a service registry model named as SRMC (Service Registry with Multilevel Caches) which clusters the service consumers into groups according to their searching similarity and sets up a multilevel cache for all groups to improve the performance of service discovery. The multilevel caches of SRMC are refreshed by a hybrid mechanism which includes event-based refreshing and periodical refreshing. The basis of refreshing and clustering is the history records of service discovery requests issued by service consumers. The running results of an instance of SRMC deployed in an experimental environment have shown that SRMC is effective to reduce the times of accessing global storage and the amount of data searched in service discovery.
Feature Selection with Hybrid Mutual Information and Genetic Algorithm

During past years, various metrics have been proposed to measure the relevance between different features. Mutual information is nonlinear and can effectively represent the dependencies of features. In this paper, we proposed a combinatorial algorithm that uses the powerful metric mutual information and genetic algorithm. In this method, relevant features search with genetic algorithm by mutual information as fitness function. Totally, this method has better results than original mutual information in more situation and some of them the result of Hybrid Mutual Information and Genetic Algorithm 1 is equal with original mutual information.
Creation of digital terrain models using an adaptive lidar vegetation point removal process

Commercial small-footprint lidar remote sensing has become an established tool for the creation of digital terrain models (DTMs). Unfortunately, even after the application of lidar vegetation point removal algorithms, vertical DTM error is not uniform and varies according to land cover. This paper presents the results of the application of an adaptive lidar vegetation removal process to a raw lidar dataset of a small area in North Carolina. This process utilized an existing lidar vegetation point removal algorithm in which the parameters were adaptively adjusted based on a vegetation map. The vegetation map was derived through the exclusive use of the lidar dataset, making the process independent of ancillary data. The vertical error and surface form of the resulting DTM were then compared to DTMs created using traditional techniques. The results indicate that the adaptive method produces a superior DTM.
Extending BPMN Business Process Model with SBVR Business Vocabulary and Rules

Despite the fact that business process (BP) modeling has its long-lasting traditions in various areas of application, this discipline remains in the constant process of improvement and issue-solving. The possibilities of synergy among business process models and business vocabularies & rules are analyzed in this paper. The authors emphasize the existing gap between business process modeling and specification of business vocabularies & rules. Such situation may lead to misunderstandings while reading and interpreting business models and also miscommunication issues within among the organizations. Some of these issues could be resolved by realizing the integration of BP modeling standards with business vocabularies & rules. The paper presents some argumentation to back such statements. Later, basic principles of the approach for BPMN Business process model integration with SBVR business vocabulary & rules are presented and briefly described in this paper. DOI: http://dx.doi. org/10.5755/j01.itc. 41.4. 2013
Wheel torque control for a rough terrain rover

Navigating in rough terrain is a complex task that requires the robot to be considered as a holistic system. Algorithms, which don't consider the physical dimensions and capabilities of the mobile robot lead to inefficient motion and suffer from a lack of robustness. A physical model of the robot is necessary for trajectory control. In this paper, quasi-static modeling of a six-wheeled robot with a passive suspension mechanism is presented together with a method for selecting the optimal torques considering the system constraints: maximal and minimal torques, positive normal forces. The aim of this method is to limit wheel slip and to improve climbing capabilities. The modeling and the optimization are applied to the shrimp rover.
Extractive evidence based medicine summarisation based on sentence-specific statistics

We present an approach for extracting 3-sentence evidence-based summaries relevant to clinical questions. We approach this task as one of query-focused, extractive, single-document summarisation using sentencespecific statistics for each target sentence. We incorporate simple statistics and domain knowledge and show that such an approach is effective for identifying informative sentences from medical abstracts. Our system is evaluated automatically using ROUGE, and we compare our results with several baselines. The ROUGE-L F-scores of our system outperform all baselines. In addition, our approach is computationally efficient, and, on a percentile rank measure, our system achieves a percentile rank of 97.3%.
Realistic synthetic off-line signature generation based on synthetic on-line data

A novel method for the generation of synthetic offline signatures is presented. The proposed algorithm follows a two steps scheme: first, the raw synthetic dynamic functions of the synthetic signature are generated; second, several ink and paper models are applied to transform the on-line data to realistic static signatures. The novel approach is validated using four different publicly available databases both real and synthetic. The experimental protocol includes the comparison of both types of signatures in terms of: i) performance evaluation of two competitive and totally different verification systems; and ii) visual appearance according to human observers. The experimental results show the high similarity existing between synthetically generated and humanly produced samples, and the potential of the proposed method for the study of the signature trait.
Conflict Experiences and Household Expectations on Recovery: Survey Evidence From Northern Uganda

We analyse the role of mass violent conflict in influencing individual expectations. We hypothesise that individuals are likely to report negative expectations if they were exposed to conflict events in the past. We combine individual and household level data from the Northern Uganda Livelihood Survey of 2007 with a disaggregated conflict exposure index based on the Armed Conflict Locations Events Data (ACLED). We run logistic regression models to study the strength of the association between conflict and expectations. Results indicate that conflict intensity is correlated with a decrease in the probability of expecting economic recovery. The effect of conflict on general welfare however is less robust.
PERFORMANCE ANALYSIS OF IDMA SCHEME USING DIFFERENT CODING TECHNIQUES WITH RECEIVER DIVERSITY USING RANDOM INTERLEAVER

In this paper performance analysis of IDMA systems is determined using different coding techniques. In this paper we use a receiver diversity approach which is useful in combating the fading in the IDMA scheme. In the transmitter section a single antenna is used where as in the receiver section two antennas are used. A comparative study has been performed between convolutional coding and zigzag coding with and without receiver diversity. Use of receiver diversity improves the bit error performance of the IDMA scheme. Random interleaver has been used in this paper.
Building a Memetic Algorithm Based Support Vector Machine for Imbalaced Classification

Classification analysis is one of core research topics in pattern recognition field. According to the distribution of samples, algorithms like artificial network (ANN) and support vector machine (SVM) have been proposed to perform binary classification. But these traditional classification algorithms hardly work well for imbalanced dataset. In this study, a novel model on the basis of memetic algorithm (MA) and support vector machine (SVM) is proposed to perform the classification for large imbalanced dataset. It is named MSVC (memetic support vector classification) model. Memetic Algorithm is recently proposed and used as a heuristic framework for the large imbalanced classification. Because of the high performance of SVM in balanced binary classification, support vector classification (SVC) is combined with MA to improve the classification accuracy. G-mean is used to check the final result. Compared with some conventional models, the results showed that this model is a proper alternative for imbalanced dataset classification, and it expends the applications of memetic algorithm.
Explaining the presence of political content in football fans’ antagonistic communication in Cyprus

Abstract The landscape of football fan culture in Cyprus contains a good deal of antagonistic communicative actions of explicit political content. We attempt to explain this phenomenon by focusing on two analytical dimensions. First, we ask to what extent are political elements in fans’ antagonistic communication guided by politics, in the narrower sense, that is, political ideology, party affiliation, historical narratives, etc.—the political–historical dimension. Second, we ask to what extent are these political elements means of performance in an intense game of identity reaffirmation—the game dimension. We address these questions qualitatively, using data from 20 field observations of first division football games and from 38 in-depth interviews, predominantly with football fans. We conclude that both dimensions are meaningful and useful in explaining football fans’ antagonistic communication.
Collective Problem Solving in Networks

Many complex problems in science, business, and engineering require a trade-off between exploitation of known solutions and exploration of new possibilities. When complex problems are solved by collectives rather than individuals, this explore-exploit trade-off is complicated by the presence of communication networks, which can accelerate collective learning, but can also lead to convergence on suboptimal solutions. In this paper, we report on a series of 195 web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. We found that network structure affected collective performance indirectly, via its impact on individual search strategies, as well as directly, by impacting the speed of information diffusion. We also found that networks in general suppress individual exploration, but greatly amplify the benefits of the exploration that takes place. Finally, we identified two ways in which individual and collective performance were in tension, consistent with longstanding theoretical claims.
Enhancing teaching competence through bidirectional mentoring and structured on-the-job training model

ABSTRACT This study employed conventional and reverse mentoring to form the theoretical basis for bidirectional mentoring. Using the analytic hierarchy process, the relative weights of bidirectional mentoring functions were measured and analyzed. A focus group method was employed to plan a structured on-the-job training course framework for bidirectional mentoring. Analysis of research data indicated that role modeling is the most crucial bidirectional mentoring function, followed by psychosocial support and career development. Psychosocial support, role modeling, teaching, teamwork, and communication skills were the most crucial elements of career development. This paper proposes seven training courses, totaling 59 h, based on the mentoring development plan. This study intends to use the proposed structured on-the-job training framework for bidirectional mentoring to promote career development and psychosocial support for new teachers, to improve role modeling for senior teachers, and to enhance the teaching skills of new and senior teachers.
Complexity control of HEVC based on region-of-interest attention model

In this paper, we present a novel complexity control method of HEVC to adjust its encoding complexity. First, a region-of-interest (ROI) attention model is established, which defines different weights for various regions according to their importance. Then, the complexity control algorithm is proposed with a distortion-complexity optimization model, to determine the maximum depth of the largest coding units (LCUs) according to their weights. We can reduce the encoding complexity to a given target level at the cost of little distortion loss. Finally, the experimental results show that the encoding complexity can drop to a pre-defined target complexity as low as 20% with bias less than 7%. Meanwhile, our method is verified to preserve the quality of ROI better than another state-of-the-art approach.
Undiagnosed HIV infection among adolescents seeking primary health care in Zimbabwe.

BACKGROUND Mother-to-child transmission of human immunodeficiency virus (HIV) infection was extremely common in southern Africa during the 1990s, and a substantial minority of infected infants have survived to reach adolescence undiagnosed. Studies have shown a high prevalence of HIV infection in hospitalized adolescents who have features associated with long-standing HIV infection, including stunting and frequent minor illnesses. We therefore investigated the epidemiology of HIV infection at the primary care level. METHODS Adolescents (aged 10-18 years) attending two primary care clinics underwent HIV and Herpes simplex virus-2 (HSV-2) serological testing, clinical examination, and anthropometry. All were offered routine HIV counseling and testing. Patients attending for acute primary care (APC) who were HIV infected were asked about their risk factors. RESULTS Five hundred ninety-four participants were systematically recruited (97% participation), of whom 88 (15%) were attending for antenatal care. HIV infection prevalence was higher among APC attendees than among antenatal care attendees (17% vs 6%; P < .007), but for the prevalence of HSV-2 infection, a marker of sexually acquired HIV, the converse was true (4% vs 14%; P < .002). Seventy (81%) of 86 HIV-positive APC attendees were previously undiagnosed. They had a broad range of presenting complaints, with a median CD4 cell count of 329 cells/microL (interquartile range, 176-485 cells/microL) and a high prevalence of stunting, compared with the corresponding prevalence among HIV-negative attendees (40% vs 12%; P < .001). Maternal transmission was considered to be likely by 69 (80%) of the 86 HIV-positive APC attendees, only one of whom was HSV-2 positive. CONCLUSIONS Unrecognized HIV infection was a common cause of primary care attendance. Routine HIV counseling and testing implemented at the primary care level may provide a simple and effective way of identifying older long-term survivors of mother-to-child transmission before the onset of severe immunosuppression and irreversible complications.