Miracle-dz/UniFAR-FTUs huggingface dataset:
Spinal fMRI of Interoceptive Attention/Awareness in Experts and Novices

Many disciplines/traditions that promote interoceptive (inner sensation of body parts) attention/awareness (IAA) train practitioners to both attend to and be aware of interoceptive sensory experiences in body parts. The effect of such practices has been investigated in previous imaging studies but limited to cerebral neural activity. Here, for the first time, we studied the impact of these practices on the spinal neural activity of experts and novices. We also attempted to clarify the effect of constant and deep breathing, a paradigm utilized in concentration practices to avoid mind wandering, on IAA-related spinal neural activity. Subjects performed IAA tasks with and without a deep and constant breathing pattern in two sessions. Results showed that neural activity in the spinal segment innervating the attended-to body area increased in experts (P = 0.04) when they performed IAA and that this increase was significantly larger for experts versus novices in each of the sessions (P = 0.024). The significant effects of IAA and expertise on spinal neural activity are consistent with and elaborate on previous reports showing similar effects on cerebral neural activity. As the spinal cord directly innervates body parts, the results might indicate that IAA has an instantaneous (possibly beneficial) effect on the physical body after extended training.
Exhaled NO: Determinants and Clinical Application in Children With Allergic Airway Disease

Nitric oxide (NO) is endogenously released in the airways, and the fractional concentration of NO in exhaled breath (FeNO) is now recognized as a surrogate marker of eosinophilic airway inflammation that can be measured using a noninvasive technique suitable for young children. Although FeNO levels are affected by several factors, the most important clinical determinants of increased FeNO levels are atopy, asthma, and allergic rhinitis. In addition, air pollution is an environmental determinant of FeNO that may contribute to the high prevalence of allergic disease. In this review, we discuss the mechanism for airway NO production, methods for measuring FeNO, and determinants of FeNO in children, including host and environmental factors such as air pollution. We also discuss the clinical utility of FeNO in children with asthma and allergic rhinitis and further useful directions using FeNO measurement.
The Effects of Active Stretching Exercise on Passive Stiffness of Rectus Femoris Muscle and Low Back Pain in Patients with Lumbar Extension Rotation Syndrome

Lumbar extension rotation syndrome (L-ext & rot syn) is the most common among 5 classification category of low back pain. One of the characteristic of patients with L-ext & rot syn is that low back pain is increased with excessive lumbopelvic motion in sagittal and transverse plane during active or passive knee flexion. Repeated lumbar extension or rotation in a daily activity induces tissue microtrauma, tissue failure, and resulting the low back pain. Rectus femoris (RF) is a two joint muscle between the tibia and pelvis that is susceptible to increased passive stiffThe Effects of Active Stretching Exercise on Passive Stiffness of Rectus Femoris Muscle and Low Back Pain in Patients with Lumbar Extension Rotation Syndrome
Does the floorplan of a chip affect its yield?

The floorplan of a VLSI chip and its projected yield are usually considered to be completely unrelated issues. This commonly used assumption does not necessarily hold for several recently designed VLSI chips that incorporate some defect tolerance. The purpose of this work is to investigate the relationship between floorplanning and yield for this type of chip.
Motion‐ and Uncertainty‐aware Path Planning for Micro Aerial Vehicles

Localization and state estimation are reaching a certain maturity in mobile robotics, often providing both a precise robot pose estimate at a point in time and the corresponding uncertainty. In the bid to increase the robots' autonomy, the community now turns to more advanced tasks, such as navigation and path planning. For a realistic path to be computed, neither the uncertainty of the robot's perception nor the vehicle's dynamics can be ignored. In this work, we propose to specifically exploit the information on uncertainty, while also accounting for the physical laws governing the motion of the vehicle. Making use of rapidly exploring random belief trees, here we evaluate offline multiple path hypotheses in a known map to select a path exhibiting the motion required to estimate the robot's state accurately and, inherently, to avoid motion in modes, where otherwise observable states are not excited. We demonstrate the proposed approach on a micro aerial vehicle performing visual‐inertial navigation. Such a system is known to require sufficient excitation to reach full observability. As a result, the proposed methodology plans safe avoidance not only of obstacles, but also areas where localization might fail during real flights compensating for the limitations of the localization methodology available. We show that our planner actively improves the precision of the state estimation by selecting paths that minimize the uncertainty in the estimated states. Furthermore, our experiments illustrate by comparison that a naive planner would fail to reach the goal within bounded uncertainty in most cases.
GMM Based Speaker Recognition on Readily Available Databases

— In this paper we give an overview of the most popular databases used in speaker recognition evaluation and clearly outline the means of training and testing an ASR system using them. The complete ASR system including both feature extraction and classiﬁcation is explicitly explained in great detail. The performance of a GMM based system for speaker veriﬁcation and identiﬁcation is reported using various forms of MFCC features on the TIMIT, YOHO and ANDOSL databases.
Automatic extraction of top-k lists from the web

This paper is concerned with information extraction from top-k web pages, which are web pages that describe top k instances of a topic which is of general interest. Examples include “the 10 tallest buildings in the world”, “the 50 hits of 2010 you don't want to miss”, etc. Compared to other structured information on the web (including web tables), information in top-k lists is larger and richer, of higher quality, and generally more interesting. Therefore top-k lists are highly valuable. For example, it can help enrich open-domain knowledge bases (to support applications such as search or fact answering). In this paper, we present an efficient method that extracts top-k lists from web pages with high performance. Specifically, we extract more than 1.7 million top-k lists from a web corpus of 1.6 billion pages with 92.0% precision and 72.3% recall.
Well-being in Healthcare: Psychological Well-Being, Burnout, and Work Engagement in Long-Term Care Employees

The Job Demands-Resources (JD-R) model posits that both job demands and job resources affect employee well-being, including the experience of burnout or work engagement. More recent studies adding to the model suggest that personal resources also contribute to these work-related outcomes. A personal resource that has not been examined in the JD-R model is psychological wellbeing (PWB), which encompasses thriving through the existential challenges of life to actualize human potential, and reflects qualities of self-acceptance, positive relations with others, personal growth, purpose in life, environmental mastery, and autonomy. The purpose of this study is to extend the JD-R model by examining the potential of PWB to inform the model. This work was done within the Canadian LTC context, which has not yet been examined using this model. A convenience sample of 327 LTC employees (110 nurses and 214 nursing assistants; three people chose not to disclose their status), completed a questionnaire assessing burnout, work engagement, job demands, job resources, and PWB. Simultaneous regression was used to examine the relationship between job demands and burnout, and job resources and work engagement, according to the JD-R model. Moderation analysis using PROCESS (Hayes, 2013) was used to ascertain whether PWB contributed to the model as a moderator of either burnout or engagement. Findings were as follows: (i) certain job demands (i.e., workload, emotion load, and role conflict) contribute significantly to burnout in LTC; (ii) certain job resources (i.e., autonomy, relationship with coworkers, relationship with supervisor, and participation) contribute significantly to work engagement in LTC; (iii) PWB moderates the relationship between job demands and burnout; (iv) PWB does not moderate the relationship between job resources and work engagement. These results extend the JD-R model to the Canadian LTC setting. They provide information about the kinds of demands and resources that relate to burnout and work engagement in LTC, and they confirm that PWB is an important personal resource for LTC nurses and nursing assistants, since it moderates (buffers) the relationship between job demands and burnout. These results have implications for promoting work engagement and reducing the likelihood of burnout in LTC.
A Descriptive Analysis of the Most Viewed Youtube Videos Related to Depression

A DESCRIPTIVE ANALYSIS OF THE MOST VIEWED YOUTUBE VIDEOS RELATED TO DEPRESSION Elizabeth Pessin Baquero Depression contributes to a host of health problems resulting in disability, pain, and death. An important aspect of preventing and reducing the harmful effects of depression is educating the public about this pervasive mental disorder, including the importance of early detection and effective treatment. During the past 20 years, many people have turned to the Internet in general and social media in particular to learn about health. Current research has examined YouTube coverage of some mental health topics, but no published research describing YouTube coverage of depression was identified. The purpose of this study was, therefore, to describe the most viewed YouTube videos about depression with respect to source, speaker, format, purpose, number of views, length, upload year, and content. A cross-sectional design was used to examine the 394 most viewed YouTube videos on depression. Collectively, these 394 videos were viewed 155,349,029 times. Three sources— consumers, internet-based video, and nongovernmental agencies—accounted for approximately 85% of the most frequently viewed videos and garnered 93% of the total views (n = 144,506,467). Consumers uploaded almost half of all the most widely viewed videos (n = 193, 48.98%), and these videos had the highest cumulative view count (74,391,500 views). Content mainly focused on signs and symptoms, which were covered in more than 75% of the videos (n = 300, 76.14%), and promotion of healthful behaviors and protective factors, which was covered in 68.52% (n = 270). Slightly more than one-half of the videos explicitly mentioned risk factors (n = 200), and slightly less than one-half provided general information about depression (n = 189). Between 20% and 35% of the videos included content related to suicide (23.10%), stigma (22.08%), psychotherapy (28.93%), medication (31.22%), and alternative therapies (30.96%). Content related to screening was only included in 9 of the most widely videos (2.28%). While good sleep hygiene was only mentioned in 28 videos (7.11%), collectively, these videos received over 16 million views. Another main finding was that governmental agencies have not produced videos that are among those most widely viewed. Given YouTube’s wide reach, they should, however, be using this media channel to help inform the public.
Constraining the bright-end of the UV luminosity function for z 7-9 galaxies: results from CANDELS/GOODS-South

The recent Hubble Space Telescope near-infrared imaging with the Wide-Field Camera #3 (WFC 3) of the Great Observatories Origins Deep Survey South (GOODS-S) field in the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) programme covering nearly 100 arcmin2, along with already existing Advanced Camera for Surveys optical data, makes possible the search for bright galaxy candidates at redshift z ≈ 7–9 using the Lyman break technique. We present the first analysis of z′-drop z ≈ 7 candidate galaxies in this area, finding 19 objects. We also analyse Y-drops at z ≈ 8, trebling the number of bright (HAB < 27 mag) Y-drops from our previous work, and compare our results with those of other groups based on the same data. The bright high-redshift galaxy candidates we find serve to better constrain the bright end of the luminosity function at those redshift, and may also be more amenable to spectroscopic confirmation than the fainter ones presented in various previous work on the smaller fields (the Hubble Ultra Deep Field and the WFC 3 Early Release Science observations). We also look at the agreement with previous luminosity functions derived from WFC 3 drop-out counts, finding a generally good agreement, except for the luminosity function of Yan et al. at z ≈ 8, which is strongly ruled out.
RELATIONSHIP BETWEEN JOB SATISFACTION AND TURNOVER INTENTION: An Empirical Study on the IT Firms in Palestine

Studies investigating the relationship between job satisfaction and turnover intention are abundant. Yet, this relationship has not been fully addressed in the IT field particularly in the developing countries. Moving from this point, this study aims at further probe this area by evaluating the levels of job satisfaction and turnover intention among a sample of IT employees in the Palestinian IT firms. Then, it attempts to examine the sources of job satisfaction and the causes of turnover intention among those employees. The findings show job security, work conditions, pay and benefits, work nature, coworkers, career advancement, supervision and management were all significantly correlated with overall job satisfaction. Only job security, pay, and coworkers were able to significantly influence turnover intention. Implications of the findings and future research directions are discussed
Iron Oxide Nanoparticles Stimulates Extra-Cellular Matrix Production in Cellular Spheroids

Nanotechnologies have been integrated into drug delivery, and non-invasive imaging applications, into nanostructured scaffolds for the manipulation of cells. The objective of this work was to determine how the physico-chemical properties of magnetic nanoparticles (MNPs) and their spatial distribution into cellular spheroids stimulated cells to produce an extracellular matrix (ECM). The MNP concentration (0.03 mg/mL, 0.1 mg/mL and 0.3 mg/mL), type (magnetoferritin), shape (nanorod—85 nm × 425 nm) and incorporation method were studied to determine each of their effects on the specific stimulation of four ECM proteins (collagen I, collagen IV, elastin and fibronectin) in primary rat aortic smooth muscle cell. Results demonstrated that as MNP concentration increased there was up to a 6.32-fold increase in collagen production over no MNP samples. Semi-quantitative Immunohistochemistry (IHC) results demonstrated that MNP type had the greatest influence on elastin production with a 56.28% positive area stain compared to controls and MNP shape favored elastin stimulation with a 50.19% positive area stain. Finally, there are no adverse effects of MNPs on cellular contractile ability. This study provides insight on the stimulation of ECM production in cells and tissues, which is important because it plays a critical role in regulating cellular functions.
ASCA Observations of the Crab-Like Supernova Remnant 3C 58

We present here X-ray observation of a Crab-like supernova remnant (SNR) 3C 58 with ASCA. We find that the integrated energy spectrum over the nebula is consistent with previous results, showing a power-law spectrum with the photon index of 7 = 2.2-2.4, modified by interstellar absorption of about (3-4) x 10 21 cm -2 . The inclusion of a blackbody component, which is attributable to the central compact source, significantly improves the spectral fit. Stringent upper limits for any line emitting thin hot plasma are established. We find for the first time that the nebular spectrum is harder in the central part of the SNR, becoming softer toward the periphery, while the absorption column is uniform across the nebula. Correspondingly, the nebular size decreases with increasing photon energy, which is a steeper function of the radius than that of the Crab nebula. The results are compared with synchrotron energy-loss models> and the nature of the putative pulsar is discussed. A timing analysis was performed to search for pulsed X-ray emission from the central compact source. No significant pulsations were observed; and we present the upper limit for the pulsed fraction.
The Cure: Design and Evaluation of a Crowdsourcing Game for Gene Selection for Breast Cancer Survival Prediction

Background Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. Objective The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player’s prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. Methods We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Results Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive accuracy of models trained using this information, these gene sets provided comparable performance to gene sets generated using other methods, including those used in commercial tests. The Cure is available on the Internet. Conclusions The principal contribution of this work is to show that crowdsourcing games can be developed as a means to address problems involving domain knowledge. While most prior work on scientific discovery games and crowdsourcing in general takes as a premise that contributors have little or no expertise, here we demonstrated a crowdsourcing system that succeeded in capturing expert knowledge.
Price Rigidity and the Volatility of Vacancies and Unemployment

The successful matching model developed by Mortensen and Pissarides seems to find its hardest task in explaining the cyclical movements of some key labor market variables such as the vacancy rate and the vacancy-unemployment ratio. Several authors have discussed mechanisms compatible with the matching technology that are able to deliver the kind of correlations observed in the data. In this paper we explore four such additional mechanisms embedded in a full blown SDGE model. We find that price rigidity greatly improves the model's empirical performance making it capable of reproducing second moments of the data. Other components such as intertemporal substitution, endogenous match destruction, capital accumulation and distortionary taxes also play a relevant role.
Demixing multivariate-operator self-similar processes

Operator self-similarity naturally extends the concepts of univariate self-similarity and scale invariance to multivariate data. Beyond a vector of Hurst parameters, operator self-similarity models also involve a mixing matrix. The present contribution aims at estimating the collection of Hurst parameters in the case where the mixing matrix is not diagonal. To the best of our knowledge, this has never been achieved. In addition, the mixing matrix is also identified. The devised procedure relies on a source separation methodology, since the underlying components of the operator self-similar process are assumed to have a diagonal pre-mixing covariance structure. The principle behind the demixing procedure is illustrated based on synthetic 4-variate operator self-similar processes, with a priori prescribed and controlled Hurst parameters and mixing matrix. Identification and estimation performance for both Hurst parameters and mixing matrices are shown to be very satisfactory, using large size Monte Carlo simulations.
Pornography’s associations with open sexual communication and relationship closeness vary as a function of dyadic patterns of pornography use within heterosexual relationships

Couples who use pornography together (shared pornography use) and couples in which both members use pornography alone (concordant solitary pornography use) may have more sexual interests, preferences, and values in common than couples in which one couple member uses pornography and the other does not (discordant pornography use). From this perspective, the associations between pornography use, comfort in sexual communication, and relationship closeness should vary depending on patterns of pornography use within relationships. Several related pre-registered hypotheses were tested using an online cross-sectional survey of heterosexual dyads (N = 200) that were quota sampled to reflect the distribution of age and political affiliation of married American couples. Dyadic analysis indicated that participants who shared pornography use with their partner reported more open sexual communication and greater closeness than those that did not. Further, participants who were in relationships that were discordant in solitary pornography use reported more inhibited sexual communication and lower closeness than participants who were in relationships that were concordant in solitary pornography use. In fact, couples who were concordant in high-frequency solitary pornography use reported similar openness in sexual communication and closeness as couples in which neither partner used pornography alone. These findings have important implications for the field, because they reinforce the view that the links between pornography use and relationship health are largely a function of different patterns of pornography use within couples.
Revisiting the gender academic achievement gap: evidence from a unique environment

ABSTRACT This paper reports evidence on the decomposition of a gender academic achievement gap (GAAP) at the university level by type of college from a unique environment, where the majority of an undergraduate student population shares similar socio-economic and demographic backgrounds and attends the largest and only public university in the country. Results show that between 37% and 45% of the GAAP is due to gender differentials in observable characteristics, and between 55% and 63% is due to the differential in the rates at which productivity-related characteristics are converted into academic achievement. In humanities, the GAAP is a strong reflection of students’ performance at the high school level, whereas at scientific colleges it is also explained by the differentials in the returns to their respective abilities, and by the returns to their behavioral attitudes towards university education.