Miracle-dz/UniFAR-FTUs huggingface dataset:
Factor mRNAs Untranslated Regions of Cytokine and Angiogenic ′ within the 3 Tumors and Binds to Adenine-and Uridine-rich Elements HuR , a RNA Stability Factor , Is Expressed in Malignant Brain

Tumors of the central nervous system (CNS) often have sustained expression of labile genes, including angiogenic growth factors and immunosuppressive cytokines, which promote tumor progression. Stabilization of the RNA transcripts for these genes, such as vascular endothelial growth factor (VEGF), is an important molecular pathway for this upregulation. HuR, a member of the Elav family of RNA-binding proteins, has been implicated in this pathway through its binding to adenine and uridine (AU)-rich stability elements (ARE) located in the 3* untranslated regions (3*-UTRs) of the mRNA. Whereas three of the Elav family members (Hel-N1, HuC, and HuD) are restricted to young and mature neurons, HuR is more broadly expressed, including proliferating cells of the developing CNS. Because RNA stabilization of labile genes may promote tumor growth, we analyzed and compared the expression pattern of HuR in 35 freshly resected and cultured CNS tumors to determine whether there was any correlation with tumor grade or histological type. We found that HuR mRNA was consistently expressed in all of the tumors, regardless of cell origin or degree of malignancy. Using a novel HuR-specific polyclonal antibody, we found that strong HuR protein expression was limited to high-grade malignancies (glioblastoma multiforme and medulloblastoma). Within the glioblastoma multiforme, prominent HuR expression was also detected in perinecrotic areas in which angiogenic growth factors are up-regulated. To further define its role as a potential RNA stabilizer, we analyzed whether HuR could bind to the stability motifs within the 3*-UTRs of cytokines and growth factors linked to brain tumor progression. We used a novel ELISA-based RNA binding assay and focused on the 3*-UTRs of angiogenic factors VEGF, COX-2, and (interleukin) IL-8 as well as the immunomodulating factorsIL-6, transforming growth factor (TGF)-b and tumor necrosis factor (TNF)-a as potential RNA ligands. Our results indicated overall a very high binding affinity to these RNA targets. A comparison of these ligands revealed a hierarchy of binding affinities with the angiogenic factors, and TGF-b showing the highest (Kd of 1.8–3.4 nM), and TNF-a the lowest (Kd of 18.3 nM). The expression pattern of HuR, coupled with the RNA binding data, strongly suggests a role for this protein in the posttranscriptional regulation of these genes in CNS tumors.
TrainAb: a solution based on tangible and distributed user interfaces to improve cognitive disabilities

Nowadays three percent of the world's population has some type of intellectual disability. This disability limits their life and the life of those around them. Technology can provide means to facilitate learning processes and stimulate cognitive capacities. The rapid evolution of technology has changed the way in which we can engage in interactive systems. These days we are witnessing how (MDE) Multi-Device Environments are fast becoming a part of everyday life in today's society. TraInAb (Training Intellectual Abilities) system is a collaborative and interactive game based on MDE scenarios aimed at achieving greater integration in society for intellectually disabled people by encouraging cognitive abilities such as memory, calculation and attention. The system provides a new style of interaction based on tangible and distributed user interfaces.
Dynamic real-time deformations using space & time adaptive sampling

This paper presents a robust, adaptive method for animating dynamic visco-elastic deformable objects that provides a guaranteed frame rate. Our approach uses a novel automatic space and time adaptive level of detail technique, in combination with a large-displacement (Green) strain tensor formulation. The body is partitioned in a non-nested multiresolution hierarchy of tetrahedral meshes. The local resolution is determined by a quality condition that indicates where and when the resolution is too coarse. As the object moves and deforms, the sampling is refined to concentrate the computational load into the regions that deform the most. Our model consists of a continuous differential equation that is solved using a local explicit finite element method. We demonstrate that our adaptive Green strain tensor formulation suppresses unwanted artifacts in the dynamic behavior, compared to adaptive mass-spring and other adaptive approaches. In particular, damped elastic vibration modes are shown to be nearly unchanged for several levels of refinement. Results are presented in the context of a virtual reality system. The user interacts in real-time with the dynamic object through the control of a rigid tool, attached to a haptic device driven with forces derived from the method.
Open clusters in dense fields: the importance of field‐star decontamination for NGC 5715, Lyngå 4, Lyngå 9, Trumpler 23, Trumpler 26 and Czernik 37

Star clusters projected on to dense stellar fields in general require field-star (FS) decontam- ination to confirm their nature and derive intrinsic photometric and structural fundamental parameters. This work focuses on the open clusters (OCs) or candidates NGC 5715, Lynga4 , Lynga 9, Trumpler 23, Trumpler 26 and Czernik 37 which are projected within 317 ◦ � 2. ◦ 2 and |b| 2. ◦ 8, against crowded bulge and/or disc fields. To tackle these difficult objects we develop a colour-magnitude diagram FS-decontamination algorithm based on 2MASS J, (J − H) and (J − Ks) data, and respective uncertainties, to detect cluster star excesses over the background. On the other hand, colour-magnitude filters are used to build stellar radial density profiles and mass functions. The results convey compelling evidence that Lynga9 and Czernik 37 are intermediate-age OCs, and their fundamental parameters are measured for the first time. Trumpler 23 is a particularly challenging object, since besides high back- ground level, its field presents variable absorption in near-infrared bands. We confirm it to be an intermediate-age OC. Trumpler 26 is studied in more detail than in previous works, while NGC 5715 and Lynga 4 have fundamental parameters determined for the first time. These OCs are located 0.9-1.6 kpc within the solar circle, with ages similar to that of the Hyades. Structurally, they are well described by King profiles. In all cases, core and limiting radii are significantly smaller than those of nearby OCs outside the solar circle. We test the effect of background levels on cluster radii determinations by means of simulations. They indicate that for central clusters, radii may be underestimated by about 10-20 per cent, which suggests that the small sizes measured for the present sample reflect as well intrinsic properties related to dynamical evolution effects. The objects probably have been suffering important tidal ef- fects that may have accelerated dynamical evolution, especially in Czernik 37, the innermost object.
Analyzing software process models with AVISPA

Software process models are sophisticated and large specifications aimed at organizing and managing software development. Their formal specification demands an enormous effort, but once specified there are few approaches and even fewer tools that aid the process engineer to analyze the quality of the process. For the last five years we have aided software companies in specifying their software processes and we have found a series of error patterns that indicate the potential presence of misconceptions or misspecifications. This paper presents these patterns, characterizes the kinds of errors they potentially reveal, and details how errors could be localized within a software process model. To assist process engineers to analyze the quality of their processes, we provide Avispa, a tool that graphically renders different aspects of a process model and highlights potential errors as intuitive and comprehensible indicators. The approach and the supporting tool are illustrated by applying them for analyzing the software process models of three Chilean software companies.
Multi-Level Hybrid Parallel Optimization of Possion ’ s Equation Solver On Multi-core SMP Clusters

The distributed multi-core systems has become a popular and promising approach for high performance computing, but the corresponding Preconditioned Conjugate Gradient method (PCG) algorithm has not been studied thoroughly. In some research studies, the MPI+OpenMP hybrid algorithm performs poorer than the pure MPI algorithm. This paper develops a pure MPI version and a MPI+OpenMP version of PCG on process-level by mesh partition, then on thread-level by algorithm optimization and OpenMP thread optimizations. The multi-level hybrid algorithm outperforms the pure MPI algorithm in a distributed shared memory HPC system. Key-Words: Possion’s Equation Solver, Preconditioned conjugate gradient method, SpMV, hybrid optimization, multi-core
Historical Introgression of the Downy Mildew Resistance Gene Rpv12 from the Asian Species Vitis amurensis into Grapevine Varieties

The Amur grape (Vitis amurensis Rupr.) thrives naturally in cool climates of Northeast Asia. Resistance against the introduced pathogen Plasmopara viticola is common among wild ecotypes that were propagated from Manchuria into Chinese vineyards or collected by Soviet botanists in Siberia, and used for the introgression of resistance into wine grapes (Vitis vinifera L.). A QTL analysis revealed a dominant gene Rpv12 that explained 79% of the phenotypic variance for downy mildew resistance and was inherited independently of other resistance genes. A Mendelian component of resistance–a hypersensitive response in leaves challenged with P. viticola–was mapped in an interval of 0.2 cM containing an array of coiled-coil NB-LRR genes on chromosome 14. We sequenced 10-kb genic regions in the Rpv12+ haplotype and identified polymorphisms in 12 varieties of V. vinifera using next-generation sequencing. The combination of two SNPs in single-copy genes flanking the NB-LRR cluster distinguished the resistant haplotype from all others found in 200 accessions of V. vinifera, V. amurensis, and V. amurensis x V. vinifera crosses. The Rpv12+ haplotype is shared by 15 varieties, the most ancestral of which are the century-old ‘Zarja severa’ and ‘Michurinets’. Before this knowledge, the chromosome segment around Rpv12+ became introgressed, shortened, and pyramided with another downy mildew resistance gene from North American grapevines (Rpv3) only by phenotypic selection. Rpv12+ has an additive effect with Rpv3+ to protect vines against natural infections, and confers foliar resistance to strains that are virulent on Rpv3+ plants.
Formative Evaluation of a Virtual Reality Telerehabilitation System for the Lower Extremity

Usability studies are an essential and iterative component of technology development and ease its transfer from the laboratory to the clinic. Although such studies are standard methodology in today’s graphical user interface/windows world of applications, new technologies strain the current methods and require experimentation in what can be transferred to the new user interaction situations. In this paper five integrated interfaces with three simultaneous users and a remote monitoring setup are evaluated via a usability study that uses both traditional and new methods to assess the viability of the interface design. This formative evaluation was carried out by an expert domain user on the Rutgers Ankle Rehabilitation System (RARS) and its telerehabilitation sub-system. The tester and developer’s observations, along with the session videotapes and therapist-user questionnaires were triangulated to identify user problems and suggest design changes that will increase the usability of the system. Changes that resulted from the analysis are described and recommendations for future usability studies are proposed. The validity of usability studies in the development and refinement of rehabilitation technology is highlighted.
Online estimation of multijoint human arm viscoelasticity for the case of unknown variance

In this paper, an online estimation method of multijoint human arm viscoelasticity for the case of unknown variance is considered. For the unknown variance process of a human multijoint arm, an estimation method of the human multijoint arm viscoelasticity is proposed. The proposed method includes two estimators, the first estimator is to calculate the variance, and the human multijoint arm viscoelasticity is obtained by the second estimator. The effectiveness of the proposed method is shown by the simulation results.
Does a cycle-based segmentation improve accelerometer-based biometric gait recognition?

When machine learning algorithms are used for accelerometer-based biometric gait recognition, the general approach is to divide the data into segments of a fixed time-length, extract features from the segments and use these feature vectors to train the classifiers and authenticate the subjects. In this research we enhance the segmentation by a cycle extraction method. A gait cycle contains data of two steps, and our technique assures that each segment contains the same amount of steps. These cycle-based segments are input to the feature extraction process. We apply Hidden Markov Models (HMMs) for classification and compare the results to previous ones obtained using segments of a fixed time-length. We show that the fixed-length segmentation is the better approach as it achieves similar error rates while requiring a lower computational effort.
Understanding Macrophage Signaling Pathways through DNA Microarray Data Using Hybrid Self-Organizing Map and Fuzzy Logic Data Mining Approach

Understanding the response of human white blood cells (macrophages) to pathogens may provide insights to both the mechanisms of host defenses and the tactics used by pathogens to circumvent these defenses. The DNA microarray method has evolved to become one of the most powerful tools to understand the dynamics of gene response. Currently there is no standard approach to systematically analyze the data and the interpretation of results can vary dramatically. In this paper, we employed a new hybrid Self-Organizing Map (SOM) and Fuzzy Logic data mining approach to explore patterns of time sequence data from eight bacteria with 977 gene responses that showed significant changes on a microarray chip. We annotated the genes by their “biological processes” of Gene Ontology (GO). Our result suggests that the SOM-Fuzzy logic data mining approach is effective in exploring how human macrophages respond to each bacterium with a unique combination of shared biological processes. The shared processes include: signal transduction, transcription, metabolism, and cell cycle and proliferation. Our result also suggests that there are similar responses (identical genes) to several bacteria and the similarities may be related to the shared mechanism of bacterial pathogenesis.
Anytime Best+Depth-First Search for Bounding Marginal MAP

We introduce new anytime search algorithms that combine best-first with depth-first search into hybrid schemes for Marginal MAP inference in graphical models. The main goal is to facilitate the generation of upper bounds (via the best-first part) alongside the lower bounds of solutions (via the depth-first part) in an anytime fashion. We compare against two of the best current state-of-the-art schemes and show that our best+depth search scheme produces higher quality solutions faster while also producing a bound on their accuracy, which can be used to measure solution quality during search. An extensive empirical evaluation demonstrates the effectiveness of our new methods which enjoy the strength of best-first (optimality of search) and of depth-first (memory robustness), leading to solutions for difficult instances where previous solvers were unable to find even a single solution.
Heart Rate Variability Analysis Using Threshold of Wavelet Package Coefficients

In this paper, a new efficient feature extraction method based on the adaptive threshold of wavelet package coefficients is presented. This paper especially deals with the assessment of autonomic nervous system using the background variation of the signal Heart Rate Variability HRV extracted from the wavelet package coefficients. The application of a wavelet package transform allows us to obtain a time-frequency representation of the signal, which provides better insight in the frequency distribution of the signal with time. A 6 level decomposition of HRV was achieved with db4 as mother wavelet, and the above two bands LF and HF were combined in 12 specialized frequencies sub-bands obtained in wavelet package transform. Features extracted from these coefficients can efficiently represent the characteristics of the original signal. ANOVA statistical test is used for the evaluation of proposed algorithm. Keywords-component; Wavelet package; Threshold; Background variability; HRV; ANOVA
Tourism Demand Modelling and Forecasting: How Should Demand Be Measured?

Tourist arrivals and tourist expenditure, in both aggregate and per capita forms, are commonly used measures of tourism demand in empirical research. This study compares these two measures in the context of econometric modelling and the forecasting of tourism demand. The empirical study focuses on demand for Hong Kong tourism by residents of Australia, the UK and the USA. Using the general-to-specific modelling approach, key determinants of tourism demand are identified based on different demand measures. In addition, the forecasting accuracy of these demand measures is examined. It is found that tourist arrivals in Hong Kong are influenced mainly by tourists' income and ‘word-of-mouth’/habit persistence effects, while the tourism price in Hong Kong relative to that of the tourist origin country is the most important determinant of tourist expenditure in Hong Kong. Moreover, the aggregate tourism demand models outperform the per capita models, with aggregate expenditure models being the most accurate. The implications of these findings for tourism decision making are that the choice of demand measure for forecasting models should depend on whether the objective of the decision maker is to maximize tourist arrivals or expenditure (receipts), and also that the models should be specified in aggregate form.
Linking Entities Across Images and Text

This paper describes a set of methods to link entities across images and text. As a corpus, we used a data set of images, where each image is commented by a short caption and where the regions in the images are manually segmented and labeled with a category. We extracted the entity mentions from the captions and we computed a semantic similarity between the mentions and the region labels. We also measured the statistical associations between these mentions and the labels and we combined them with the semantic similarity to produce mappings in the form of pairs consisting of a region label and a caption entity. In a second step, we used the syntactic relationships between the mentions and the spatial relationships between the regions to rerank the lists of candidate mappings. To evaluate our methods, we annotated a test set of 200 images, where we manually linked the im- age regions to their corresponding mentions in the captions. Eventually, we could match objects in pictures to their correct mentions for nearly 89 percent of the segments, when such a matching exists. (Less)
Somatotype and body composition analysis of Korean youth soccer players according to playing position for sports physiotherapy research

[Purpose] The purpose of this study was to investigate the somatotype and physical characteristic differences among elite youth soccer players. [Subjects and Methods] In the present study, we evaluated twenty-two Korean youth soccer players in different playing positions. The playing positions were divided into forward (FW), midfielder (MF), defender (DF), and goalkeeper (GK). The participants’ lean body mass (LBM), fat free mass (FFM), fat mass (FM), and basal metabolic rate (BMR) were measured and their somatotype determined according to the Heath-Carter method. [Results] The youth soccer players had twelve ectomorphic, eight mesomorphic, and two central predominant types. The DFs were taller than, but otherwise similar in physical characteristics to the FWs and MFs. The GKs were taller and heavier than the other players; however, their somatotype components were not significantly different. LBM, FFM, and BMR were significantly higher in GKs than in FWs and MFs. Although LBM, FFM, and BMR values between GKs and DFs showed large differences, they were not statistically significant. [Conclusion] The present study may contribute to our understanding of the differences in somatotype and body composition of Korean youth soccer players involved in sports physiotherapy research.
A New Technique for Simultaneous Estimation of the Output Gap and Phillips Curve

A new technique to estimate simultaneously the potential output and Phillips curve is demonstrated. Here we define the potential output as the non-accelerating-inflation level of output (NLO). The NLO is not a mere trend of the actual output, but rather is a critical level of output with the following property: If the actual output is at this level, the inflation rate is neither accelerated nor decelerated. Applying our method to the data on the G7 countries, we estimate the NLO and Phillips curves and investigate their properties. It is shown that during the 1980s and 1990s, the output gap measured from the NLO was negative on average, reflecting the worldwide trend of disinflation. We also point out that the output gap has moved in accordance with corporate sentiments, and thus serves as an indicator of business conditions. In Japan, however, after the potential rate of growth dropped between 1 and 2 percent in the mid-1990s, the output gap was too volatile to allow for accurate evaluation. As for Phillips curves, a cross-country comparison shows that Japan's responsiveness of inflation to the output gap is relatively weak.
Seeking Clarity and Confidence in the Divorce Decision-Making Process

ABSTRACT There is a well-established literature dedicated to why couples divorce, transitions associated with divorce, and the impact of divorce on families. However, little is known about the divorce decision-making process. We conducted in-depth interviews with individuals who have recently considered divorce (n = 30) and asked specifically about the roles of 2 concepts in their decision-making process: clarity and confidence. Three major themes emerged from the data: (a) Clarity about a decision to divorce or stay married is desired, it fluctuates, and takes time to find; (b) pivotal moments can bring clarity; and (c) confidence (in the final decision) is desired. Clinical implications and directions for future research are discussed.
Inventive thinking skills in science: A comparative study between students in Malaysia and Brunei

In order to succeed in a digital economy, students will need digital age proficiencies. It is important for the educational system to make parallel changes in order to fulfil its mission in society, namely the preparation of students for the world beyond the classroom. Therefore, the educational system must understand and embrace the 21st century skills within the context rigorous academic standards. The main purposes of this study are to determine the inventive thinking skills in Science among students in Malaysia and Brunei and also to compare the inventive thinking skills of students in Science between Malaysia and Brunei. The dimension of inventive thinking skills is comprised of adaptability and managing complexity, self direction, curiosity, creativity, risk taking and higher order thinking and sound reasoning. This study which employed cross sectional surveys method involved 410 Primary school students from both countries.