Miracle-dz/UniFAR-FTUs huggingface dataset:
Visualization Method Based on Contour Map

With the development of data science, the market of data also plays a significant role in the data mining domain gradually. This paper focus on how to use a visualization method based on contour map to seek the relationship between Data Jackets in order to create an innovative chance for data transaction. The analysis of results by questionnaires can illustrate the feasibility of this visualization tool for Data Jacket reasonably.
Inevitable collision states. A step towards safer robots?

An inevitable collision state for a robotic system can be defined as a state for which, no matter what the future trajectory followed by the system is, a collision with an obstacle eventually occurs. An inevitable collision state takes into account both the dynamics of the system and the obstacles, fixed or moving. The main contribution of this paper is to lay down and explore this novel concept (and the companion concept of inevitable collision obstacle). Formal definitions of the inevitable collision states and obstacles are given. Properties fundamental for their characterisation are established. This concept is very general and can be useful both for navigation and motion planning purposes (for its own safety, a robotic system should never find itself in an inevitable collision state). The interest of this concept is illustrated by a safe motion planning example.
The p and hp versions of the finite element method for problems with boundary layers

We study the uniform approximation of boundary layer functions exp(-x/d) for x ∈ (0,1), d ∈ (0,1], by the p and hp versions of the finite element method. For the p version (with fixed mesh), we prove super-exponential convergence in the range p + 1/2 > e/(2d). We also establish, for this version, an overall convergence rate of O(p -1 √ln p) in the energy norm error which is uniform in d, and show that this rate is sharp (up to the √ln p term) when robust estimates uniform in d ∈ (0,1] are considered. For the p version with variable mesh (i.e., the hp version), we show that exponential convergence, uniform in d ∈ (0,1], is achieved by taking the first element at the boundary layer to be of size O(pd). Numerical experiments for a model elliptic singular perturbation problem show good agreement with our convergence estimates, even when few degrees of freedom are used and when d is as small as, e.g., 10 -8 . They also illustrate the superiority of the hp approach over other methods, including a low-order h version with optimal exponential mesh refinement. The estimates established in this paper are also applicable in the context of corresponding spectral element methods.
SLE Peripheral Blood B Cell, T Cell and Myeloid Cell Transcriptomes Display Unique Profiles and Each Subset Contributes to the Interferon Signature

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that is characterized by defective immune tolerance combined with immune cell hyperactivity resulting in the production of pathogenic autoantibodies. Previous gene expression studies employing whole blood or peripheral blood mononuclear cells (PBMC) have demonstrated that a majority of patients with active disease have increased expression of type I interferon (IFN) inducible transcripts known as the IFN signature. The goal of the current study was to assess the gene expression profiles of isolated leukocyte subsets obtained from SLE patients. Subsets including CD19+ B lymphocytes, CD3+CD4+ T lymphocytes and CD33+ myeloid cells were simultaneously sorted from PBMC. The SLE transcriptomes were assessed for differentially expressed genes as compared to healthy controls. SLE CD33+ myeloid cells exhibited the greatest number of differentially expressed genes at 208 transcripts, SLE B cells expressed 174 transcripts and SLE CD3+CD4+ T cells expressed 92 transcripts. Only 4.4% (21) of the 474 total transcripts, many associated with the IFN signature, were shared by all three subsets. Transcriptional profiles translated into increased protein expression for CD38, CD63, CD107a and CD169. Moreover, these studies demonstrated that both SLE lymphoid and myeloid subsets expressed elevated transcripts for cytosolic RNA and DNA sensors and downstream effectors mediating IFN and cytokine production. Prolonged upregulation of nucleic acid sensing pathways could modulate immune effector functions and initiate or contribute to the systemic inflammation observed in SLE.
Trace gas exchange in a high‐Arctic valley: 2. Landscape CH4 fluxes measured and modeled using eddy correlation data

Eddy correlation measurements of methane exchange were conducted during a period of 43 days covering the summer season in high‐arctic, NE Greenland. Measurements were carried out over a fen area and showed fluxes ranging from no exchange in the early part of the campaign to 120 mg m−2 d−1 during midsummer. The emission showed a clear variation related to soil temperatures and water table level in the late part of the summer, whereas the thickness of the active soil layer was a main controlling parameter in the thaw period, in the early part of the season. A model to assess methane emission dependency on physical parameters is found to give a realistic estimate for the seasonal variations in flux. The proportion of C returned to the atmosphere as CH4 relative to the total C cycling was around 2%, which is similar to ratios often reported in literature. On the basis of these findings, an estimate is given for the total summer season emission of CH4, in which a simple model including both physical parameters and net primary production (NPP) is adapted to reproduce CH4 exchange rates for periods when no measurements were undertaken. In this way the total emission of CH4 during the period June 1 to September 1 1997, is found to equal 3.7 ± 0.57 g m−2, which is a relatively high rate given the harsh climate in which the measurements were made.
An Empirical Study of Educational Supply Chain Management for the Universities

The exploratory study addresses education supply ch ain and research supply chain as major constituents in the educational supply chain management model for the universities. Model constructs were identified and c onfirmed by 493 respondents, representing university administra tors, faculty and staffs, employers, and graduates. The resulting model was subsequently evaluated for accuracy and validity by multiple linear regression (MLR) analysi s and the structural equation modeling (SEM) technique. The research model furnishes stakeholders of the supply chain with appropriate strategies to review and appraise their performance toward fulfillment of ultimate goals, i.e. producing high-caliber graduates and high-impact research out comes for the betterment of the society.
Insights on the role of accurate state estimation in coupled model parameter estimation by a conceptual climate model study

Abstract. The uncertainties in values of coupled model parameters are an important source of model bias that causes model climate drift. The values can be calibrated by a parameter estimation procedure that projects observational information onto model parameters. The signal-to-noise ratio of error covariance between the model state and the parameter being estimated directly determines whether the parameter estimation succeeds or not. With a conceptual climate model that couples the stochastic atmosphere and slow-varying ocean, this study examines the sensitivity of state–parameter covariance on the accuracy of estimated model states in different model components of a coupled system. Due to the interaction of multiple timescales, the fast-varying atmosphere with a chaotic nature is the major source of the inaccuracy of estimated state–parameter covariance. Thus, enhancing the estimation accuracy of atmospheric states is very important for the success of coupled model parameter estimation, especially for the parameters in the air–sea interaction processes. The impact of chaotic-to-periodic ratio in state variability on parameter estimation is also discussed. This simple model study provides a guideline when real observations are used to optimize model parameters in a coupled general circulation model for improving climate analysis and predictions.
A Novel Anti-Human HB-EGF Monoclonal Antibody with Multiple Antitumor Mechanisms against Ovarian Cancer Cells

Purpose: Heparin-binding epidermal growth factor (EGF)–like growth factor (HB-EGF) is a member of the EGF family and plays a pivotal role in tumor progression in ovarian cancer. We developed an anti-HB-EGF monoclonal antibody (mAb) and investigated its antitumor activities in vitro and in vivo to evaluate its potential as a therapeutic antibody against ovarian cancer. Experimental Design: We prepared mAbs from HB-EGF null mice immunized with recombinant human soluble HB-EGF and evaluated their binding and neutralizing activity against HB-EGF. Next, we generated a mouse–human chimeric antibody and examined its in vitro and in vivo antitumor activities. Results: Two murine anti-HB-EGF mAbs were developed, and one of them, KM3566, was revealed to have a high binding reactivity for membrane-anchored HB-EGF (pro-HB-EGF) expressed on the cell surface, as well as neutralizing activity against growth promoting activity of soluble HB-EGF. The mouse–human chimeric counterpart for KM3566 (cKM3566) induced dose-dependent antibody-dependent cellular cytotoxicity (ADCC) against cancer cells expressing HB-EGF in vitro, and significantly inhibited tumor growth in severe combined immunodeficient mice inoculated with MCAS or ES-2 human ovarian cancer cells. Conclusions: A novel anti-HB-EGF chimeric antibody, cKM3566, with two antitumor mechanisms, neutralization and ADCC, exhibits potent in vivo antitumor activity. These results indicate that cKM3566 is a promising antiovarian cancer therapeutic antibody. Clin Cancer Res; 17(21); 6733–41. ©2011 AACR.
Experience of service provision for adolescents with eating disorders

Eating disorders of all kinds are common and serious in adolescents and young women. Recent government policies have suggested that adolescent mental health strategies should be developed. They have also laid emphasis on early intervention, accessible local provision and have identified eating disorders as a priority. It is acknowledged that services at primary care level for adolescents with eating disorders are sporadic or nonexistent. It was considered that a service user perspective would be beneficial in contributing to assessing the needs of adolescents with eating disorders. The research project was established to identify the service provision used, if any, by adolescent sufferers of eating disorders and what, in their opinion, would have been desirable at that time. The research consisted of a semi-structured interview with a sample of recovered adult participants to establish their experiences of services they had received as adolescents. Additionally the participants were asked what further help they felt would have been beneficial and where that help would have been usefully situated. The main findings suggest that the majority of health professionals are ill informed and not acutely conscious of the needs of eating disordered adolescents. Only counsellors within the voluntary sector agency showed any real understanding and an ability to help constructively. It was concluded that there is a real lack of help at primary care level and that schools should play a wider role in educating adolescents in a positive belief in themselves and in the destructive nature of an eating disorder.
First comparisons between CNR-IMAA multi-wavelength Raman lidar measurements and CALIPSO measurements

At CNR-IMAA, an aerosol lidar system is operative since May 2000 in the framework of EARLINET (European Aerosol Research Lidar Network) ), the first lidar network for tropospheric aerosol study on continental scale. Since August 2005, PEARL (Potenza EARlinet Lidar) system provides backscatter coefficient profiles at 1064 nm, and independent measurements of extinction and backscatter coefficient profiles at 355 and 532 nm. In addition, measurements of the vertical profiles of aerosol and cloud depolarization ratio at 532 nm are obtained by means of the detection of components of backscattered light polarized perpendicular and parallel to the direction of the linearly polarized transmitted laser beam. High quality multi-wavelength measurements (3 backscatter + 2 extinction) plus depolarization measurements make PEARL a reference point for the validation of CALIPSO data products. A direct comparison with CALIPSO data can be carried out for depolarization ratio and aerosol backscatter at 532 and 1064 nm measurements. Furthermore PEARL aerosol extinction measurements at 532 nm and 355 nm and backscatter measurements at 355 nm can be used to improve the retrieval of aerosol backscatter coefficient from pure backscatter lidar. Since 14 June 2006, devoted measurements are performed at CNR-IMAA in coincidence of CALIPSO overpasses (maximum 80 km and 2 hours as spatial and temporal distance). First results of comparison between PEARL and CALIPSO observations are shown.
An Interactive Model for Structural Pattern Recognition based on the Bayes Classifier

This paper presents an interactive model for structural pattern recognition based on a naive Bayes classifier. In some applications, the automatically computed correlation between local parts of two images is not good enough. Moreover, humans are very good at locating and mapping local parts of images although any kind of global transformations had been applied to these images. In our model, the user interacts on the automatically obtained correlation (or correspondences between local parts) and helps the system to find the best correspondence while the global transformation parameters are automatically recomputed. The model is based on a Bayes classifier in which the human interaction is properly modelled and embedded in the model. We show that with little human interaction, the quality of the returned correspondences and global transformation parameters drastically increases.
Polyphonic Instrument Recognition Using Spectral Clustering

The identification of the instruments playing in a polyphonic music signal is an important and unsolved problem in Music Information Retrieval. In this paper, we propose a framework for the sound source separation and timbre classification of polyphonic, multi-instrumental music signals. The sound source separation method is inspired by ideas from Computational Auditory Scene Analysis and formulated as a graph partitioning problem. It utilizes a sinusoidal analysis front-end and makes use of the normalized cut, applied as a global criterion for segmenting graphs. Timbre models for six musical instruments are used for the classification of the resulting sound sources. The proposed framework is evaluated on a dataset consisting of mixtures of a variable number of simultaneous pitches and instruments, up to a maximum of four concurrent notes.
Blocking Epidermal Growth Factor Receptor Signaling in HTR-8/SVneo First Trimester Trophoblast Cells Results in Dephosphorylation of PKBα/AKT and Induces Apoptosis

We identified a major peptide signaling target of EGF/EGFR pathway and explored the consequences of blocking or activating this pathway in the first trimester extravillous trophoblast cells, HTR-8/SVneo. A global analysis of protein phosphorylation was undertaken using novel technology (Kinexus Kinetworks) that utilizes SDS-polyacrylamide minigel electrophoresis and multi-lane immunoblotting to permit specific and semiquantitative detection of multiple phosphoproteins. Forty-seven protein phosphorylation sites were queried, and the results reported based on relative phosphorylation at each site. EGF- and Iressa-(gefitinib, ZD1839, an inhibitor of EGFR) treated HTR-8/SVneo cells were subjected to immunoblotting and flow cytometry to confirm the phosphoprotein screen and to assess the effects of EGF versus Iressa on cell cycle and apoptosis. EGFR mediates the phosphorylation of important signaling proteins, including PKBα/AKT. This pathway is likely to be central to EGFR-mediated trophoblast survival. Furthermore, EGF treatment induces proliferation and inhibits apoptosis, while Iressa induces apoptosis.
The role of the pinna in human localization *

The pinna, or ex ternal ear, has been shown experim entally to perform an acoustical tran sfo r­ m ation essential to localization in hum an hearing. The m athem atical form of th e tran sfo rm a­ tion is given, the inverse to the transform ation is shown to exist, and a theory of localization constructed from the evidence. The theory is extended to reverberation and o ther facets of hum an hearing. The basic theorem applied to the study is 6 in order to know, th e inverse to the transform ation of perception m ust be construc ted ’.
The software aging and rejuvenation repository: Http://openscience.us/repo/software-aging/

While Software Aging and Rejuvenation (SAR) research has been steadily increasing, the artifacts related to SAR studies (such as software aging measurements and bug datasets) are seldom made available to researchers and practitioners, thus limiting potential improvements of rejuvenation solutions and their practical adoption. We discuss in this paper the role of artifacts in SAR research, and present SARRY (the Software Aging and Rejuvenation RepositorY), an open-access support for the SAR community to share research artifacts (available at http://openscience.us/repo/software-aging/). We invite researchers to contribute to SARRY, in order to aid future SAR research and to improve the visibility and impact of their work.
Localised credit based QoS routing

Localised quality of service (QoS) routing has recently been proposed as a viable alternative approach to traditional QoS routing algorithms that use global state information. In this approach, problems associated with maintaining global state information are avoided by having the source nodes to infer the network QoS state based on flow blocking statistics collected locally, and perform flow routing using this localised view of the network QoS state. A credit based routing algorithm (CBR) which is a simple yet effective localised QoS routing algorithm is introduced. Its performance is compared against the localised proportional sticky routing (PSR) algorithm using different types of network topologies, QoS requirements and traffic patterns and under a wide range of traffic loads. Extensive simulations show that the algorithm outperforms the PSR scheme while maintaining the same level of adaptivity and stability. Its performance is also compared against the global widest-shortest path algorithm (WSP) and it is shown that CBR gives a comparable performance with better time complexity and very low communication overhead.
Making geography mobile: using location aware technology to improve student performance in physical geography

With the increased availability of new technologies, geography educators are revisiting their pedagogical approaches to teaching and calling for opportunities to share local and international practices which will enhance the learning experience and improve students’ performance. This paper reports on the use of handheld mobile devices, fitted with GPS, by secondary (high) school pupils in geography. Two location-aware activities were completed over one academic year (one per semester) and pre-test and post-test scores for both topics revealed a statistically significant increase in pupils’ performance as measured by the standard national assessments. A learner centred educational approach was adopted with the first mobile learning activity being created by the teacher as an exemplar of effective mobile learning design. Pupils built on their experiences of using mobile learning when they were required to created their own location aware learning task for peer use. An analysis of the qualitative data from the pupils’ journals, group diaries and focus group interviews revealed the five pillars of learner centred education are addressed when using location aware technologies and the use of handheld mobile devices offered greater flexibility and autonomy to the pupils thus altering the level of power and control away from the teacher. Due to the relatively small number of participants in the study, the results are more informative than generalisable however in light of the growing interest in geo-spatial technologies in geography education, this paper offers encouragement and insight into the use of location aware technology in a compulsory school context
Towards High-Performance Prediction Serving Systems

Machine Learning models are often composed of sequences of transformations. While this design makes it easy to decompose and efficiently execute single model components at training time, predictions require low latency and high-performance predictability whereby end-to-end and multi-model runtime optimizations are needed to meet such goals. This paper sheds some light on the problem by introducing a new system design for high-performance prediction serving. We report some preliminary results showing how our system design is able to improve performance over several dimensions with respect to current state-of-the-art approaches.
A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

MOTIVATION When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization is a process for reducing this variation. It is common to see non-linear relations between arrays and the standard normalization provided by Affymetrix does not perform well in these situations. RESULTS We present three methods of performing normalization at the probe intensity level. These methods are called complete data methods because they make use of data from all arrays in an experiment to form the normalizing relation. These algorithms are compared to two methods that make use of a baseline array: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure. Two publicly available datasets are used to carry out the comparisons. The simplest and quickest complete data method is found to perform favorably. AVAILABILITY Software implementing all three of the complete data normalization methods is available as part of the R package Affy, which is a part of the Bioconductor project http://www.bioconductor. org. SUPPLEMENTARY INFORMATION Additional figures may be found at http://www.stat.berkeley.edu/~bolstad/normalize/index.html
INTEGRAL observations of the Perseus cluster

We present the results of a 500 ks observation of the Perseus cluster with INTEGRAL, with the aim of investigating the possible diffuse non-thermal component detected in a previous Chandra observation. In the 3−20 keV band with the JEM-X instrument, we detect the source with high significance and resolve it spatially. Above 20 keV with IBIS/ISGRI, we find that the source is point-like, and the cluster could be detected up to 120 keV. From the broad-band ISGRI/JEM-X spectrum, although we detect a non-thermal component, we find that the high-energy flux is variable and is consistent with the extrapolation of the 2−10 keV flux of the central AGN, NGC 1275. The extrapolation of the non-thermal component claimed from Chandra data exceeds the INTEGRAL spectrum by a factor of 3.