Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the relationship between work engagement, work alienation and work performance of healthcare professionals

ABSTRACT The purpose of this study was to determine the effect of work engagement and work alienation on performance. Participants included 493 health professionals working in public, university, and private hospitals. Analyses revealed a meaningful and positive relationship of the engagement level of health professionals and its sub-dimensions with their performance, and of work alienation and its sub-dimensions with performance. A regression analysis revealed that the level of participants’ engagement and alienation had a significant influence on performance (P < 0.01). Further, among the vigor dimension of engagement and the powerlessness and meaninglessness dimensions of alienation explained 28% of the total variance. These findings reveal that health professionals’ vigor levels increase their performance, and powerlessness and meaninglessness levels decrease their performance.
Discovery of the Accretion-powered Millisecond X-Ray Pulsar IGR J00291+5934

We report on observations of the sixth accretion-powered millisecond pulsar, IGR J00291+5934, with the Rossi X-Ray Timing Explorer. The source is a faint recurrent X-ray transient initially identified by the International Gamma-Ray Astrophysics Laboratory. The 599 Hz (1.67 ms) pulsation had a fractional rms amplitude of 8% in the 2-20 keV range, and its shape was approximately sinusoidal. The pulses show an energy-dependent phase delay, with the 6-9 keV pulses arriving up to 85 μs earlier than those at lower energies. No X-ray bursts, dips, or eclipses were detected. The neutron star is in a circular 2.46 hr orbit with a very low-mass donor, most likely a brown dwarf. The binary parameters of the system are similar to those of the first known accreting millisecond pulsar, SAX J1808.4-3658. Assuming that the mass transfer is driven by gravitational radiation and that the 2004 outburst fluence is typical, the 3 yr recurrence time implies a distance of at least 4 kpc.
Load disaggregation using harmonic analysis and regularized optimization

In this paper, we present a load disaggregation technique that uses regularized optimization together with harmonic frequency signatures of appliances. The benefits of our technique are twofold: 1) The regularized optimization is faster than integer programming; and 2) The harmonic frequency signatures allow us to disaggregate the loads using as few as 10 cycles (equaling as little as 200 milliseconds) of samples, instead of having to wait for state changes from appliances or weekly usage pattern to emerge. We test our proposed technique in proof-of-concept experiments and show that our technique returns accurate disaggregation results.
A resummed perturbative estimate for the quarkonium spectral function in hot QCD

By making use of the finite-temperature real-time static potential that was introduced and computed to leading non-trivial order in Hard Thermal Loop resummed perturbation theory in recent work, and solving numerically a Schrodinger-type equation, we estimate the quarkonium (in practice, bottomonium) contribution to the spectral function of the electromagnetic current in hot QCD. The spectral function shows a single resonance peak which becomes wider and then disappears as the temperature is increased beyond 450 MeV or so. This behaviour can be compared with recently attempted lattice reconstructions of the same quantity, based on the ``maximum entropy method'', which generically show several peaks. We also specify the dependence of our results on the spatial momentum of the electromagnetic current, as well as on the baryon chemical potential characterising the hot QCD plasma.
A Systematic Investigation of Accuracy and Response Time Based Measures Used to Index ANS Acuity

The approximate number system (ANS) was proposed to be a building block for later mathematical abilities. Several measures have been used interchangeably to assess ANS acuity. Some of these measures were based on accuracy data, whereas others relied on response time (RT) data or combined accuracy and RT data. Previous studies challenged the view that all these measures can be used interchangeably, because low correlations between some of the measures had been observed. These low correlations might be due to poor reliability of some of the measures, since the majority of these measures are mathematically related. Here we systematically investigated the relationship between common ANS measures while avoiding the potential confound of poor reliability. Our first experiment revealed high correlations between all accuracy based measures supporting the assumption that all of them can be used interchangeably. In contrast, not all RT based measures were highly correlated. Additionally, our results revealed a speed-accuracy trade-off. Thus, accuracy and RT based measures provided conflicting conclusions regarding ANS acuity. Therefore, we investigated in two further experiments which type of measure (accuracy or RT) is more informative about the underlying ANS acuity, depending on participants’ preferences for accuracy or speed. To this end, we manipulated participants’ preferences for accuracy or speed both explicitly using different task instructions and implicitly varying presentation duration. Accuracy based measures were more informative about the underlying ANS acuity than RT based measures. Moreover, the influence of the underlying representations on accuracy data was more pronounced when participants preferred accuracy over speed after the accuracy instruction as well as for long or unlimited presentation durations. Implications regarding the diffusion model as a theoretical framework of dot comparison as well as regarding the relationship between ANS acuity and math performance are discussed.
Combining Medical Domain Ontological Knowledge and Low-level Image Features for Multimedia Indexing

Biomedical images are invaluable in establishing diagnosis, acquiring technical skills, and implementing best practices in many areas of medicine. At present, images needed for instructional purposes or in support of clinical decisions appear in specialized databases and in biomedical articles, and are therefore not easily accessible. Our goal is to automatically annotate images extracted from scientific publications with respect to their usefulness for clinical decision support and instructional purposes, and project the annotations onto images stored in databases by linking images through content-based image similarity. This paper presents an overview of our approach to automatic image indexing, content-based image analysis, and the results of a pilot evaluation of an automatic indexing method based on biomedical terms extracted from snippets of text pertaining to images appearing in scientific biomedical articles.
Design and evaluation of ICN-based Internet access scheme on high-speed trains

Today's Internet access approaches on trains focus on establishing and maintaining connections between passengers and terrestrial peers. With network use being dominated by content distribution and retrieval, passengers value the content itself rather than connections over which it travels. This mismatch affects the passenger's experience and deteriorates network performance, especially in high-speed railway scenario which suffers from poor wireless link quality and frequent handover. In this paper we introduce an Internet access scheme on high-speed trains based on Information Centric Network (ICN). Performance can be achieved by leveraging ICN's in-network cache, efficient content distribution and built-in support for mobility. We use simulation to evaluate the proposed scheme in comparison with traditional approach based on TCP/IP, using parameters from field test conducted in Beijing-Shanghai highspeed railway. Results show great improvement in terms of handover performance, throughput, download time and system capacity.
LINEARLY SUPPORTING FEATURE EXTRACTION FOR AUTOMATED ESTIMATION OF STELLAR ATMOSPHERIC PARAMETERS

We describe a scheme to extract linearly supporting (LSU) features from stellar spectra to automatically estimate the atmospheric parameters T 𝚎𝚏𝚏 ? > , log g, and [Fe/H]. “Linearly supporting” means that the atmospheric parameters can be accurately estimated from the extracted features through a linear model. The successive steps of the process are as follow: first, decompose the spectrum using a wavelet packet (WP) and represent it by the derived decomposition coefficients; second, detect representative spectral features from the decomposition coefficients using the proposed method Least Absolute Shrinkage and Selection Operator (LARS)bs; third, estimate the atmospheric parameters T 𝚎𝚏𝚏 ? > , log g, and [Fe/H] from the detected features using a linear regression method. One prominent characteristic of this scheme is its ability to evaluate quantitatively the contribution of each detected feature to the atmospheric parameter estimate and also to trace back the physical significance of that feature. This work also shows that the usefulness of a component depends on both the wavelength and frequency. The proposed scheme has been evaluated on both real spectra from the Sloan Digital Sky Survey (SDSS)/SEGUE and synthetic spectra calculated from Kurucz's NEWODF models. On real spectra, we extracted 23 features to estimate T 𝚎𝚏𝚏 ? > , 62 features for log g, and 68 features for [Fe/H]. Test consistencies between our estimates and those provided by the Spectroscopic Parameter Pipeline of SDSS show that the mean absolute errors (MAEs) are 0.0062 dex for log T 𝚎𝚏𝚏 ? > (83 K for T 𝚎𝚏𝚏 ? > ), 0.2345 dex for log g, and 0.1564 dex for [Fe/H]. For the synthetic spectra, the MAE test accuracies are 0.0022 dex for log T 𝚎𝚏𝚏 ? > (32 K for T 𝚎𝚏𝚏 ? > ), 0.0337 dex for log g, and 0.0268 dex for [Fe/H].
Visualizing Similarity Data with a Mixture of Maps

We show how to visualize a set of pairwise similarities between objects by using several different two-dimensional maps, each of which captures different aspects of the similarity structure. When the objects are ambiguous words, for example, different senses of a word occur in different maps, so “river” and “loan” can both be close to “bank” without being at all close to each other. Aspect maps resemble clustering because they model pair-wise similarities as a mixture of different types of similarity, but they also resemble local multi-dimensional scaling because they model each type of similarity by a twodimensional map. We demonstrate our method on a toy example, a database of human wordassociation data, a large set of images of handwritten digits, and a set of feature vectors that represent words.
CBX3 promotes colon cancer cell proliferation by CDK6 kinase-independent function during cell cycle

Heterochromatin protein 1γ (CBX3) links histone methylation marks to transcriptional silence, DNA repair and RNA splicing, but a role for CBX3 in cancer remains largely unknown. In this study, we show that CBX3 in colon cancer cells promotes the progression of the cell cycle and proliferation in vitro and in vivo. Cell cycle (G1 phase to S phase) related gene CDK6 and p21 were further identified as targets of CBX3. In addition, we found that enhancing CDK6 suppresses cell proliferation by upregulating inhibitor p21 in the absence of CBX3, and this function is independent of the kinase activity of CDK6. Our results demonstrate a key role of CBX3 in colon carcinogenesis via suppressing the expression of CDK6/p21, which may disrupt the role of CDK6 in transcriptionally regulating p21, as part of a negative feedback loop to limit CDK6 excessive activation.
Triangular Memory Polynomial Predistorter

To predistort a power amplifier nonlinear with memory effects, a triangular memory polynomial (TMP) predistorter is presented based on the traditional memory polynomial predistorter. The coefficients of the predistorter can be directly extracted from an offline system identification process using an open-loop structure. This reduces the implementation complexity of the system. Experimental results show that the adjacent channel power ratio is improved more than 13dB by utilizing the proposed predistorter. Compared with a traditional memory polynomial predistorter, the proposed TMP predistorter can reduce the number of coefficients efficiently(66% or more).
The intersection of intellectual and developmental disabilities and HIV: A scoping review

ABSTRACT Background: HIV among individuals with intellectual and developmental disabilities (IDD) is rarely studied. This scoping review examined the HIV prevalence, health service use, prevention and risk behaviours among individuals with IDD. Method: Journal articles, book chapters and theses written in English and published from 1991 to 2017 in four academic databases (PubMed, PsycINFO, CINAHL and Web of Science) were eligible for inclusion. Results: From 1636 unique records, 32 documents were included in this review. They contained limited information on HIV prevalence and health service use by individuals with IDD and HIV. Most studies identified a poor understanding of HIV and high-risk behaviours, such as inconsistent condom use, among individuals with IDD. While HIV education programs were effective for this population, no studies identified educational interventions for their service providers. Conclusion: There is a need for educational programs and policies on HIV for both service providers and individuals with IDD.
Dynamic allocation for scratch-pad memory using compile-time decisions

In this research, we propose a highly predictable, low overhead, and, yet, dynamic, memory-allocation strategy for embedded systems with scratch pad memory. A scratch pad is a fast compiler-managed SRAM memory that replaces the hardware-managed cache. It is motivated by its better real-time guarantees versus cache and by its significantly lower overheads in energy consumption, area, and overall runtime, even with a simple allocation scheme. Primarily scratch pad allocation methods are of two types. First, software-caching schemes emulate the workings of a hardware cache in software. Instructions are inserted before each load/store to check the software-maintained cache tags. Such methods incur large overheads in runtime, code size, energy consumption, and SRAM space for tags and deliver poor real-time guarantees just like hardware caches. A second category of algorithms partitions variables at compile-time into the two banks. However, a drawback of such static allocation schemes is that they do not account for dynamic program behavior. It is easy to see why a data allocation that never changes at runtime cannot achieve the full locality benefits of a cache. We propose a dynamic allocation methodology for global and stack data and program code that; (i) accounts for changing program requirements at runtime, (ii) has no software-caching tags, (iii) requires no runtime checks, (iv) has extremely low overheads, and (v) yields 100% predictable memory access times. In this method, data that is about to be accessed frequently is copied into the scratch pad using compiler-inserted code at fixed and infrequent points in the program. Earlier data is evicted if necessary. When compared to a provably optimal static allocation, results show that our scheme reduces runtime by up to 39.8% and energy by up to 31.3%, on average, for our benchmarks, depending on the SRAM size used. The actual gain depends on the SRAM size, but our results show that close to the maximum benefit in runtime and energy is achieved for a substantial range of small SRAM sizes commonly found in embedded systems. Our comparison with a direct mapped cache shows that our method performs roughly as well as a cached architecture.
The double bromodomain protein Brd2 promotes B cell expansion and mitogenesis

Bromodomain‐containing transcriptional regulators represent new epigenetic targets in different hematologic malignancies. However, bromodomain‐mediated mechanisms that couple histone acetylation to transcription in lymphopoiesis and govern mature lymphocyte mitogenesis are poorly understood. Brd2, a transcriptional coregulator that contains dual bromodomains and an extraterminal domain (the BET family), couples chromatin to cell‐cycle progression. We reported previously the first functional characterization of a BET protein as an effector of mammalian mitogenic signal transduction: Eμ‐Brd2 Tg mice develop “activated B cell” diffuse large B cell lymphoma. No other animal models exist for genetic or lentiviral expression of BET proteins, hampering testing of novel anti‐BET anticancer drugs, such as JQ1. We transduced HSCs with Brd2 lentivirus and reconstituted recipient mice to test the hypothesis that Brd2 regulates hematopoiesis in BM and mitogenesis in the periphery. Forced expression of Brd2 provides an expansion advantage to the donor‐derived B cell compartment in BM and increases mature B cell mitogenic responsiveness in vitro. Brd2 binds the cyclin A promoter in B cells, shown by ChIP, and increases cyclin A mRNA and protein levels, and S‐phase progression in vitro in mitogen‐stimulated primary B cells, but not T cells, reinforcing results from Eμ‐Brd2 mice. The small molecule BET inhibitor JQ1 reduces B cell mitogenesis, consistent with the interpretation that BET inhibitors are antiproliferative. Brd2‐specific knockdown experiments show that Brd2 is also required for hematopoiesis. We conclude that Brd2 plays a critical, independent role in regulation of mitogenic response genes, particularly cyclin A, in B cells.
Revisiting Media Choice: A Behavioral Decision-Making Perspective

How do managers select media for communication and collaboration? Previous research has identified a myriad of contextual factors, individual characteristics, social factors, and the fit between medium characteristics and task requirements as influencing media choice. An implication from the cumulative research base is that managers must consider a large number of factors in the process of media selection, but task contingencies may not allow for the assessment of numerous criteria. Based on a behavioral decision-making perspective, this study proposes that task contingencies in the form of complexity, importance, and urgency influence the extent to which individuals evaluate various factors for media selection. The authors utilize data from a survey of managers in a financial organization. Under conditions of high task complexity and/or importance, managers are found to extensively appraise information for media selection. However, if the task is urgent, the extent of information evaluation during medium choice is constrained. Further, to the extent that managers' appraisal is limited, their actual medium choice diverges from the optimal choice. The results indicate that a behavioral decision-making view can provide a fresh perspective and enhance understanding of how managers actually select media for their communication and collaboration activities.
Query expansion using fuzzy abductive inference for creative thinking support system

Proposes a query expansion method using fuzzy abductive inference for a creative thinking support system. This query expansion method for information retrieval is useful, because unexpected related information can probably be obtained by adding new words to the query. The fuzzy abductive inference is the inference method based on Peng and Reggia's (1990) abductive inference. This method infers nonredundant combinations of concept words for the query. This paper also studies how to update the weights of concept-term relationships by the steepest descent method.
Design and Test of a Capsule Type Endoscope Robot with Novel Locomation Principle

Robots become more and more widely used in medical application especially in minimally invasive surgery (MIS) these years, and endoscope robot is a typical example. There is sill not a kind of conventional endoscope which can reach the whole gastrointestinal (GI) tract. And conventional endoscopes generate pain and discomfort to patients due to the stiffness of their body. Such disadvantages do not exist in endoscope robots. However, the soft and elastic characters of GI tract make the locomotion efficiency of endoscope robot very low. To resolve this problem, it is necessary to find a special locomotion principle which fit the GI tract, and many researchers have paid a lot of effort. In this paper, a novel locomotion principle is proposed, which is the first time used in the endoscope robot. The locomotion principle is obtained by analyzing, simulating and simplifying the movement of mucus-cilia system. To evaluate its performance, a prototype of the endoscope robot adopting this locomotion principle is developed, which is driven by shape memory alloy (SMA) actuator. An in-vitro experiment shows that the robot can move successfully with efficiency about 27%. The result of experiment validates that the proposed locomotion principle fit the GI tract. And some suggestions to enhance the locomotion efficiency are proposed
Parallel Subgraph Counting for Multicore Architectures

Computing the frequency of small subgraphs on a large network is a computationally hard task. This is, however, an important graph mining primitive, with several applications, and here we present a novel multicore parallel algorithm for this task. At the core of our methodology lies a state-of-the-art data structure, the g-trie, which represents a collection of subgraphs and allows for a very efficient sequential search. Our implementation was done using Pthreads and can run on any multicore personal computer. We employ a diagonal work sharing strategy to dynamically and effectively divide work among threads during the execution. We assess the performance of our Pthreads implementation on a set of representative networks from various domains and with diverse topological features. For most networks, we obtain a speedup of over 50 for 64 cores and an almost linear speedup up to 32 cores, showcasing the flexibility and scalability of our algorithm. This paves the way for the usage of such counting algorithms on larger subgraph and network sizes without the obligatory access to a cluster.
Performance Evaluation of Inverted Index Traversal Techniques

Large search engines process thousands of queries per second over billions of documents, making query processing a major performance bottleneck. In this paper, we study an important class of index traversal techniques called dynamic pruning, which can efficiently reduce the query computational resources. We give brief overviews of index structure and skipping structure that used to quicken the term-centric and document centric index traversal strategies. Due to the fact that document centric is more efficient than term-centric for large indexes, we review several state-of-the-art dynamic pruning approaches based on document-centric scoring. We then present explicit experimental comparisons of the above index traversal techniques on TREC GOV2 datasets with detailed analytical conclusions. Finally, we provide the prospective future study of dynamic pruning with large scale of indexes.