nils-herrmann/clean_scirepeval huggingface dataset:
Giant cell arteritis: Commentary on recommendations of the French Study Group for Large Vessel Vasculitis (GEFA)
Venue: La Revue de medecine interne

The recently created French Study Group for Large Vessel asculitis (GEFA, "Groupe d'Etude Franc ais des Arterites des gros aisseaux" is a multidisciplinary panel comprised of members ommitted to the care and study of patients with giant cell arteriis (GCA) While our understanding of the vasculitides has grown, uch remains unknown. Treatment is not curative and is associted with significant morbidity  In hoping to inform and guide ractitioners, GEFA members have attempted to achieve at least 0% consensus on recommendations for nomenclature, diagnosis nd treatment. For each of these topics there exists varying degrees f controversy, making a rigorous examination of available data nd provision of sound advice especially welcome. The iterative, onsensus seeking approach taken by GEFA members has been uccessful and is an important contribution for guiding medical ractice. In a field that thankfully continues to evolve, GEFA authors ave been cautious to indicate that their judgments and recomendations are provisional and should be updated over time. In hat vein, this important paper also provides the reader with a comass to conceive of future work that will enrich the state of the art f large vessel vasculitis (LVV) In regard to diagnostic recommendations, the authors' review ncludes 2 studies that address the utility of clinical features ighly suggestive of GCA, and that were also predictive of a ositive temporal artery (TA) biopsy. The presence of masseter uscle claudication, diplopia, new onset uncharacteristic/atypical eadaches and temporal artery abnormalities on physical examinaion significantly increased the probability of a positive TA biopsy. ombinations of features such as polymyalgia rheumatic (PMR)
Effects of Anxiety on Anticipation and Visual Search in Dynamic, Time Constrained Situations

We tested the predictions of Attentional Control Theory (ACT) by examining how anxiety affects visual search strategies, performance efficiency, and performance effectiveness using a dynamic, temporal constrained anticipation task. Higher and lower skilled players viewed soccer situations under 2 task constraints (near vs. far situation) and were tested under high (HA) and low (LA) anxiety conditions. Response accuracy (effectiveness) and response time, perceived mental effort, and eye movements (all efficiency) were recorded. A significant increase in anxiety was evidenced by higher state anxiety ratings on the MRF L scale. Increased anxiety led to decreased performance efficiency because response times and mental effort increased for both skill groups whereas response accuracy did not differ. Anxiety influenced search strategies, with higher skilled players showing a decrease in number of fixation locations for far situations under HA compared with LA condition when compared with lower skilled players. Findings provide support for ACT with anxiety impairing processing efficiency and, potentially, top down attentional control across different task constraints.
The Role of Preceptorship and Group Cohesion on Newly Licensed Registered Nurses' Satisfaction and Intent to Stay.
Venue: Journal of continuing education in nursing

Thirteen percent of newly licensed registered nurses (NLRNs) vacate their first job after 1 year, and 37% report that they feel ready to change jobs. Turnover can lead to consistent and detrimental nursing shortages in nursing units, as well as increased costs for health care systems.  A descriptive, prospective, cross sectional design was used to understand how preceptor role effectiveness and group cohesion affect NLRNs' satisfaction and intent to stay.  NLRNs reported high levels of perceived preceptor role effectiveness, group cohesion, and job satisfaction, with only moderate levels of intent to stay. Statistically significant relationships were found among preceptor role effectiveness, job satisfaction, and intent to stay, as well as among group cohesion, job satisfaction, and intent to stay. Preceptor role effectiveness and group cohesion are predictors of NLRNs' level of job satisfaction. Job satisfaction is a predictor of NLRNs' intent to stay.  Effective preceptors and positive group cohesion are factors that are important to NLRNs' job satisfaction and intent to stay.
FIRE AND WATER, ASPIRATION AND OBLIVION: BAL'MONT'S RE ENVISIONING OF EDGAR

tinct memory of Edgar Allan Poe's original lyric on that theme will realize that something extraordinary has happened to Poe's text. Even before Rachmaninoff reconceived "The Bells" as a majestic choral symphony, Poe's lyric had already been extensively refashioned in Rachmaninoff's libretto, the translation provided by the Russian Symbolist K. D. Bal'mont. It was Bal'mont's conviction that Poe's "immortal poem, which one cannot fail to remember whenever one hears a resounding bell," may be best comprehended as a "requiem mass for the poet himself, who scarcely suspected the prophetic significance of the lines he was creating" when he wrote the lyric not long before his death "bessmertnaja poema, o kotoroj uie nel'zja ne vspomnit' sly'a zvuk kolokola javilas' zaupokojnoju sluiboj po samom po'te vrjad li podozrevavsem predveSdatel'nuju znabitel'nost' strok, kotorye on sozdaval" (SSEP V, 97) And so (as we shall see) Bal'mont adds to Poe's sketched out requiem some new thoughts about the ending of the martyr's torment, about the lasting peace of the grave. But for Bal'mont "The Bells" represented more than a prophecy of Poe's death; it was also a symbolic record of his life Poe's autobiographical self portrait. And it is this self portraiture, above all, that Bal'mont tries to dramatize and clarify in his own rendition of Poe's unwitting requiem. "Kolokol'Eiki i kolokola" is a twofold Bal'montian re envisioning. The Russian poet reconceives the poem as he re envisions the man who wrote it. Bal'mont provides plenty of surrounding context for his reimagining of Poe, and the contextual contributions are wide ranging. Bal'mont translated five volumes of Poe's lyrics, tales, dialogues, essays, and correspondence; his devotion to the American writer's memory and achievement influenced an era in Russian literary culture (Grossman, passim) Moreover, all this intensive work on Poe gave rise to some superb original verse
Tangible Data, explorations in data physicalization
Venue: Tangible and Embedded Interaction

Humans have represented data in many forms for thousands of years, yet the main sensory channel we use to perceive these representations today still remains largely exclusive to sight. Recent developments, such as advances in digital fabrication, microcontrollers, actuated tangibles, and shape changing interfaces offer new opportunities to encode data in physical forms and have stimulated the emergence of 'Data Physicalization' as a research area. The aim of this workshop is (1) to create an awareness of the potential of Data Physicalization by providing an overview of state of the art research, practice, and tools and (2) to build a community around this emerging field and start to discuss a shared research agenda. This workshop therefore addresses both experienced researchers and practitioners as well as those who are new to the field but interested in applying Data Physicalization to their own (research) practice. The workshop will provide opportunities for participants to explore Data Physicalization hands on, by creating their own prototypes. These practical explorations will lead into reflective discussions on the role tangibles and embodiment play in Data Physicalization and the future research challenges for this area.
Quantile Spectral Processes: Asymptotic Analysis and Inference

Quantile and copula related spectral concepts recently have been considered by various authors. Those spectra, in their most general form, provide a full characterization of the copulas associated with the pairs (Xt,Xt k) in a process (Xt )t Z, and account for important dynamic features, such as changes in the conditional shape (skewness, kurtosis) time irreversibility, or dependence in the extremes that their traditional counterparts cannot capture. Despite various proposals for estimation strategies, only quite incomplete asymptotic distributional results are available so far for the proposed estimators, which constitutes an important obstacle for their practical application. In this paper, we provide a detailed asymptotic analysis of a class of smoothed rank based cross periodograms associated with the copula spectral density kernels introduced in Dette et al. [Bernoulli 21 (2015) 781 831].We show that, for a very general class of (possibly nonlinear) processes, properly scaled and centered smoothed versions of those cross periodograms, indexed by couples of quantile levels, converge weakly, as stochastic processes, to Gaussian processes. A first application of those results is the construction of asymptotic confidence intervals for copula spectral density kernels. The same convergence results also provide asymptotic distributions (under serially dependent observations) for a new class of rank based spectral methods involving the Fourier transforms of rank based serial statistics such as the Spearman, Blomqvist or Gini autocovariance coefficients.
Plates Laminates And Shells Asymptotic Analysis And Homogenization

Thank you for reading plates laminates and shells asymptotic analysis and homogenization. As you may know, people have search hundreds times for their favorite novels like this plates laminates and shells asymptotic analysis and homogenization, but end up in malicious downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some malicious bugs inside their desktop computer.
Activation of NMDA receptors and the mechanism of inhibition by ifenprodil
Venue: Nature

The physiology of N Methyl D aspartate (NMDA) receptors in mammals is fundamental to brain development and function. NMDA receptors are ionotropic glutamate receptors that function as heterotetramers composed mainly of GluN1 and GluN2 subunits. Activation of NMDA receptors requires binding of neurotransmitter agonists to a ligand binding domain (LBD) and structural rearrangement of an amino terminal domain (ATD) Recent crystal structures of GluN1/GluN2B NMDA receptors in the presence of agonists and an allosteric inhibitor, ifenprodil, represent the allosterically inhibited state. However, how the ATD and LBD move to activate the NMDA receptor ion channel remains unclear. Here, we combine x ray crystallography, single particle electron cryomicroscopy, and electrophysiology to show that, in the absence of ifenprodil, the bi lobed structure of GluN2 ATD adopts an open conformation accompanied by rearrangement of the GluN1 GluN2 ATD heterodimeric interface, altering subunit orientation in the ATD and LBD and forming an active receptor conformation that gates the ion channel.
State of the art on clustering data streams

Clustering is a key data mining task. This is the problem of partitioning a set of observations into clusters such that the intra cluster observations are similar and the inter cluster observations are dissimilar. The traditional set up where a static dataset is available in its entirety for random access is not applicable as we do not have the entire dataset at the launch of the learning, the data continue to arrive at a rapid rate, we can not access the data randomly, and we can make only one or at most a small number of passes on the data in order to generate the clustering results. These types of data are referred to as data streams. The data stream clustering problem requires a process capable of partitioning observations continuously while taking into account restrictions of memory and time. In the literature of data stream clustering methods, a large number of algorithms use a two phase scheme which consists of an online component that processes data stream points and produces summary statistics, and an offline component that uses the summary data to generate the clusters. An alternative class is capable of generating the final clusters without the need of an offline phase. This paper presents a comprehensive survey of the data stream clustering methods and an overview of the most well known streaming platforms which implement clustering.
A Support System for Clustering Data Streams with a Variable Number of Clusters
Venue: TAAS

Many algorithms for clustering data streams that are based on the widely used k Means have been proposed in the literature. Most of these algorithms assume that the number of clusters, k, is known and fixed a priori by the user. Aimed at relaxing this assumption, which is often unrealistic in practical applications, we propose a support system that allows not only estimating the number of clusters automatically from data but also monitoring the process of the data stream clustering. We illustrate the potential of the proposed system by means of a prototype that implements eight algorithms for clustering data streams, namely, Stream LSearch OMRk, Stream LSearch BkM, Stream LSearch IOMRk, Stream LSearch IBkM, CluStream OMRk, CluStream BkM, StreamKM+ OMRk, and StreamKM+ BkM. These algorithms are combinations of three state of the art algorithms for clustering data streams with fixed k, namely, Stream LSearch, CluStream, and StreamKM+ with two algorithms for estimating the number of clusters, which are Ordered Multiple Runs of k Means (OMRk) and Bisecting k Means (BkM) We experimentally compare the performance of these algorithms using both synthetic and real world data streams. Analyses of statistical significance suggest that the algorithms that are based on OMRk yield the best data partitions, while the algorithms that are based on BkM are more computationally efficient. Additionally, StreamKM+ OMRk and Stream LSearch IBkM provide the best tradeoff relationship between accuracy and efficiency.
Slurry Erosion Behavior of F6NM Stainless Steel and High Velocity Oxygen Fuel Sprayed WC 10Co 4Cr Coating
Venue: Journal of Thermal Spray Technology

WC 10Co 4Cr coating was applied to the surface of F6NM stainless steel by high velocity oxygen fuel spraying. The slurry erosion behavior of the matrix and coating was examined at different rotational speeds using a self made machine. This experiment effectively simulates real slurry erosion in an environment with high silt load. At low velocity <6 m/s) the main failure mechanism was cavitation. Small bubbles acted as an air cushion, obstructing direct contact between sand and the matrix surface. However, at velocity above 9 m/s, abrasive wear was the dominant failure mechanism. The results indicate that WC 10Co 4Cr coating significantly improved the slurry resistance at higher velocity, because it created a thin and dense WC coating on the surface.
Study on erosion wear behavior and mechanism of plasma sprayed alumina based coatings by a novel slurry injection method

In this paper, Al 2 O 3 Cr 2 O 3 composite coating was fabricated by plasma spraying. It has better mechanical performances than Al 2 O 3 coating. Erosion wear resistance of the coatings was evaluated by a new type of solid particle impact test (slurry jet) Slurry was mixed with compressed air in the nozzle and eventually injected on coating surface at high velocity. Injected slurry on coating surface resulted in a wear progression (wear rate) proportionately to the erosion strength of the coating material. Al 2 O 3 Cr 2 O 3 composite coating possesses better erosion wear resistance than pure Al 2 O 3 coating.
Abstractive headline generation for spoken content by attentive recurrent neural networks with ASR error modeling
Venue: 2016 IEEE Spoken Language Technology Workshop (SLT)

Headline generation for spoken content is important since spoken content is difficult to be shown on the screen and browsed by the user. It is a special type of abstractive summarization, for which the summaries are generated word by word from scratch without using any part of the original content. Many deep learning approaches for headline generation from text document have been proposed recently, all requiring huge quantities of training data, which is difficult for spoken document summarization. In this paper, we propose an ASR error modeling approach to learn the underlying structure of ASR error patterns and incorporate this model in an Attentive Recurrent Neural Network (ARNN) architecture. In this way, the model for abstractive headline generation for spoken content can be learned from abundant text data and the ASR data for some recognizers. Experiments showed very encouraging results and verified that the proposed ASR error model works well even when the input spoken content is recognized by a recognizer very different from the one the model learned from.
Oil in oil emulsions stabilised solely by solid particles.
Venue: Soft matter

A brief review of the stabilisation of emulsions of two immiscible oils is given. We then describe the use of fumed silica particles coated with either hydrocarbon or fluorocarbon groups in acting as sole stabilisers of emulsions of various vegetable oils with linear silicone oils (PDMS) of different viscosity. Transitional phase inversion of emulsions, containing equal volumes of the two oils, from silicone in vegetable (S/V) to vegetable in silicone (V/S) occurs upon increasing the hydrophobicity of the particles. Close to inversion, emulsions are stable to coalescence and gravity induced separation for at least one year. Increasing the viscosity of the silicone oil enables stable S/V emulsions to be prepared even with relatively hydrophilic particles. Predictions of emulsion type from calculated contact angles of a silica particle at the oil oil interface are in agreement with experiment provided a small polar contribution to the surface energy of the oils is included. We also show that stable multiple emulsions of V/S/V can be prepared in a two step procedure using two particle types of different hydrophobicity. At fixed particle concentration, catastrophic phase inversion of emulsions from V/S to S/V can be effected by increasing the volume fraction of vegetable oil. Finally, in the case of sunflower oil 20 cS PDMS, the study is extended to particles other than silica which differ in chemical type, particle size and particle shape. Consistent with the above findings, we find that only sufficiently hydrophobic particles (clay, zinc oxide, silicone, calcium carbonate) can act as efficient V/S emulsion stabilisers.
Oil in Oil Emulsions Stabilized by Asymmetric Polymersomes Formed by AC BC Block Polymer Co Assembly.
Venue: Journal of the American Chemical Society

We demonstrate a facile route to asymmetric polymersomes by blending AC and BC block copolymers in oil in oil emulsions containing polystyrene (PS) and polybutadiene (PB) in chloroform (CHCl3) Polymersomes were prepared by mixing polystyrene b poly(ethylene oxide) (SO) and polybutadiene b poly(ethylene oxide) (BO) in the oil in oil emulsion, where the droplets and continuous phase are PS and PB rich, respectively. The polymersome structure was directly visualized using dye labeled SO and BO with confocal fluorescence microscopy; SO and BO with a high O block fraction co assemble to produce asymmetric polymersomes. As the O block is insoluble in both PS and PB, we infer that the detailed structure of the polymersomes is a bilayer in which the S and B blocks face the PS inner and PB outer phases, respectively, while the common O blocks form the core membrane. This structure is only observed for sufficiently long O blocks. It is remarkable that although all the polymers are soluble in CHCl3, such elaborate structures are created by straightforward co assembly. These asymmetric polymersomes should provide robust bilayer membranes around emulsion droplets, leading to stable nanoscopic dispersions of two fluids.
Data prediction, compression, and recovery in clustered wireless sensor networks for environmental monitoring applications
Venue: Inf. Sci.

Environmental monitoring is one of the most important applications of wireless sensor networks (WSNs) which usually requires a lifetime of several months, or even years. However, the inherent restriction of energy carried within the battery of sensor nodes brings an extreme difficulty to obtain a satisfactory network lifetime, which becomes a bottleneck in scale of such applications in WSNs. In this paper, we propose a novel framework with dedicated combination of data prediction, compression, and recovery to simultaneously achieve accuracy and efficiency of the data processing in clustered WSNs. The main aim of the framework is to reduce the communication cost while guaranteeing the data processing and data prediction accuracy. In this framework, data prediction is achieved by implementing the Least Mean Square (LMS) dual prediction algorithm with optimal step size by minimizing the mean square derivation (MSD) in a way that the cluster heads (CHs) can obtain a good approximation of the real data from the sensor nodes. On this basis, a centralized Principal Component Analysis (PCA) technique is utilized to perform the compression and recovery for the predicted data on the CHs and the sink, separately in order to save the communication cost and to eliminate the spatial redundancy of the sensed data about environment. All errors generated in these processes are finally evaluated theoretically, which come out to be controllable. Based on the theoretical analysis, we design a number of algorithms for implementation. Simulation results by using the real world data demonstrate that our framework provides a cost effective solution to such as environmental monitoring applications in cluster based WSNs.
Sub harmonic broadband humps and tip noise in low speed ring fans.
Venue: The Journal of the Acoustical Society of America

A joint experimental and numerical study has been achieved on a low speed axial ring fan in clean inflow. Experimental evidence shows large periodic broadband humps at lower frequencies than the blade passing frequencies and harmonics even at design conditions. These sub harmonic humps are also found to be sensitive to the fan process and consequently to its tip geometry. Softer fans yield more intense humps more shifted to lower frequencies with respect to the fan harmonics. Unsteady turbulent flow simulations of this ring fan mounted on a test plenum have been achieved by four different methods that have been validated by comparing with overall performances and detailed hot wire velocity measurements in the wake. Noise predictions are either obtained directly or are obtained through Ffowcs Williams and Hawkings' analogy, and compared with narrowband and third octave power spectra. All unsteady simulations correctly capture the low flow rates, the coherent vortex dynamics in the tip clearance and consequently the noise radiation dominated by the tip noise in the low to mid frequency range. Yet, only the scale adaptive simulation and the lattice Boltzmann method simulations which can describe most of the turbulent structures accurately provide the proper spectral shape and levels, and consequently the overall sound power level.