Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of Important Recent Articles in Pediatric Orthopaedics

Background: Paediatric orthopaedics as a super speciality has evolved in the last 3 decades to become a vast ocean of changing concepts and rethinking of treatment strategies and hence, is abundant in evidence based literature. In the last year over a 100 good articles and research papers have been published on various subjects. In this commentary, we have sifted out a few of the most relevant ones to the day to day clinical practice and some which are relevant to both the general orthopaedic surgeon and paediatric orthopaedic surgeon. The following is a compilation according to categories which we think will interest the reader. The summary has been enlisted here along with a short comment on the utility of the article. The reader is advised to go into the full text of any selected article if any particular article meets their requirements: as providing full text of each article is beyond the purview of this review , making it over lengthy.
Differentiable Canonical Correlation Analysis

Canonical Correlation Analysis (CCA) computes maximally-correlated linear projections of two modalities. We propose Differentiable CCA, a formulation of CCA that can be cast as a layer within a multi-view neural network. Unlike Deep CCA, an earlier extension of CCA to nonlinear projections, our formulation enables gradient flow through the computation of the CCA projection matrices, and free choice of the final optimization target. We show the effectiveness of this approach in cross-modality retrieval experiments on two public image-to-text datasets, surpassing both Deep CCA and a multi-view network with freely-learned projections. We assume that Differentiable CCA could be a useful building block for many multi-modality tasks.
A MEASUREMENT OF THE KINETIC SUNYAEV–ZEL'DOVICH SIGNAL TOWARD MACS J0717.5+3745

We report our analysis of MACS J0717.5+3745 using 140 and 268 GHz Bolocam data collected at the Caltech Submillimeter Observatory. We detect extended Sunyaev–Zel'dovich (SZ) effect signal at high significance in both Bolocam bands, and we employ Herschel-SPIRE observations to subtract the signal from dusty background galaxies in the 268 GHz data. We constrain the two-band SZ surface brightness toward two of the sub-clusters of MACS J0717.5+3745: the main sub-cluster (named C), and a sub-cluster identified in spectroscopic optical data to have a line-of-sight velocity of +3200 km s−1 (named B). We determine the surface brightness in two separate ways: via fits of parametric models and via direct integration of the images. For both sub-clusters, we find consistent surface brightnesses from both analysis methods. We constrain spectral templates consisting of relativistically corrected thermal and kinetic SZ signals, using a jointly-derived electron temperature from Chandra and XMM-Newton under the assumption that each sub-cluster is isothermal. The data show no evidence for a kinetic SZ signal toward sub-cluster C, but they do indicate a significant kinetic SZ signal toward sub-cluster B. The model-derived surface brightnesses for sub-cluster B yield a best-fit, line-of-sight velocity of vz = +3450 ± 900 km s−1, with (1 − Prob[vz ⩾ 0]) = 1.3 × 10−5 (4.2σ away from 0 for a Gaussian distribution). The directly integrated sub-cluster B SZ surface brightnesses provide a best-fit vz = +2550 ± 1050 km s−1, with (1 − Prob[vz ⩾ 0]) = 2.2 × 10−3 (2.9σ).
Stock Price Fluctuations and Productivity Growth 1

This paper studies the relationship between stock prices and fluctuations in TFP. We document a strong predictability of lagged stock price growth on future TFP growth at medium horizons. To explore the sources of this co-movement, we develop a one-sector real business model augmented to allow for (i) endogenous technology through R&D and adoption, and (ii) exogenous shocks to the risk premium. Model simulations produce predictability patterns quantitatively similar to the data. A version of the model with exogenous technology produces no predictability of TFP growth. Decomposing historical TFP, we show that the predictability uncovered in the data is fully driven by the endogenous component of TFP. This finding suggests that fluctuations in risk premia impact TFP growth through their effect on the speed of technology diffusion instead of responding to exogenous fluctuations in future TFP.
Yellow lessens discomfort glare: physiological mechanism(s)

A long standing mystery is the improved visibility people report with yellow glasses. Car drivers and pilots claim reduced discomfort of oncoming head lamps at night and the blue sky during the day respectively. While people clearly benefit, scientists have not been able to pin down the causal mechanism(s). Several hypotheses have been proposed regarding the physiological origin of this “blue sensitivity” including scotopic (rod) response, excessive iris contraction, blue (S) cone response, brightness perception, and circadian receptor response. We compared the level of discomfort glare of filter pairs that discriminate between these hypotheses with 16 subjects. The results show that more Scone stimulation corresponds to more discomfort, while more rod stimulation does not. This is consistent but does not prove a causal relation between the S-cones and discomfort glare and it is not consistent with a major role for either the pupillary constriction hypothesis or the circadian photoreceptor. The modified spectral efficiency function Vm(λ) and large field photopic spectral sensitivity V10(λ) do not significantly change these conclusions based on the standard V(λ). The present study has therefore been successful in eliminating several physiological mechanisms of discomfort glare, leaving the S-cones as the primary candidate.
The Eulerian description of dilute collisionless suspension

We analyze the statistical properties of a Eulerian fluid model describing the evolution of a suspension of inertial particles in an incompressible flow. Regularity and compressibility of the velocity field for the inertial phase are investigated in the limit of heavy particles by means of numerical simulations in two- and three-dimensional flows. We show that in the small Stokes number regime the Eulerian fluid model is able to capture fine details of the clustering dynamics, and exhibits good agreement with fully Lagrangian simulations of inertial particle trajectories. The fluid description breaks down due to collisions at Stokes numbers ≳ 0.1, the actual value depending on the carrier flow characteristics.
Factors that Affect the Strategic Choice of Sales Channels

The clothing retail industry has developed globally and is today one of the world’s largest industries. In recent years, Sweden has developed a competitive fashion industry, where the new trend in e-commerce is clear. Since e-commerce is a suitable strategy for rapid growth, it is especially important for managers to understand the impact e-commerce has on their businesses. To be able to have the ability to survive in the long-term industrial competitiveness, firms have to continuously improve their knowledge base about the factors that must be considered when choosing sales channels in the clothing retail industry. In this master thesis we have studied and analysed factors that must be considered when choosing sales channels. A literature review was done, where eleven initial factors that affect the choice of sales channels were identified. Thereafter, to conduct a comprehensive empirical study, we conducted eight case studies with semi-structured interviews with companies in the Swedish clothing retail industry, founded no longer than approximately a decade ago to cover the recent developments in the industry. The empirical study resulted in that six factors from the literature were reinforced and that four new factors were identified. These ten final factors were thereafter analysed from two main perspectives: company focus and consumer focus. Finally, the impact of the final factors on the three different sales channels; online, brick-and-mortar and retailing, was discussed. The ten final factors are: Marketing and Customer Loyalty, High Costs, Customer Behaviour, Outsourcing or Insourcing, Managerial Productivity, Intangibility and Tangibility, Fill a Gap, Customer Experience Control, Spread of Distribution and Type of Assortment. Our contribution to previous research is that this study has a more distinct company focus, and due to the development of e-commerce this study has captured the new characteristics of the industry. Key-words: clothing retail industry; sales channels; factors; online shop; brick-and-mortar; retailers.
1 A Real-time Calibration Method of Kinect 2 Recognition Range Extension for Media Art 3

Kinect is a device that has been widely used in many areas since it was released in 2010. 11 Kinect SDK was announced in 2011 and used in many other areas than its original purpose, which 12 was a controller for gaming. In particular, it has been used by a number of artists in digital media 13 art since it is inexpensive and has a fast recognition rate. However, there is a problem. Kinect create 14 3D coordinates with a single 2D RGB image for x, y value single depth image for z value. And this 15 creates a significant limitation on the installation for interactivity of media art. Because the 16 Cartesian XY coordinate and the spherical Z coordinate system are used in combination, depth 17 error depending on the distance is generated, which makes real-time rotation recognition and 18 coordinate correction difficult above coordinate system. This paper proposes a real-time calibration 19 method of Kinect recognition range expansion for useful application in the digital media art area. 20 The proposed method can recognize the viewer accurately by calibrating a coordinate in any 21 direction in front of the viewer. 3,400 datasets witch acquire from experiment were measured as 22 five stances: the 1m attention stance, 1m hands-up stance, 2m attention stance, 2m hands-up stance, 23 and 2m hands-half-up stance, which were taken and recorded every 0.5 sec. The experimental 24 results showed that the accuracy rate was improved about 11.5% compared with front 25 measurement data according to Kinect reference installation method. 26
A Computational Model of Fraction Arithmetic (in press, Psychological Review)

Many children fail to master fraction arithmetic even after years of instruction, a failure that hinders their learning of more advanced mathematics as well as their occupational success. To test hypotheses about why children have so many difficulties in this area, we created a computational model of fraction arithmetic learning and presented it with the problems from a widely used textbook series. The simulation generated many phenomena of children’s fraction arithmetic performance through a small number of common learning mechanisms operating on a biased input set. The biases were not unique to this textbook series – they were present in two other textbook series as well – nor were the phenomena unique to a particular sample of children – they were present in another sample as well. Among other phenomena, the model predicted the high difficulty of fraction division, variable strategy use by individual children and on individual problems, relative frequencies of different types of strategy errors on different types of problems, and variable effects of denominator equality on the four arithmetic operations. The model also generated non-intuitive predictions regarding the relative difficulties of several types of problems and the potential effectiveness of a novel instructional approach. Perhaps the most general lesson of the findings is that the statistical distribution of problems that learners encounter influences mathematics learning in powerful and often non-intuitive ways.
From a Quality Assurance and Control System for Medical Processes, Through Epidemiological Trends of Medical Conditions, to a Nationwide Health Project

Yossy Machluf1,2, Amir Navon1, Avi Yona1, Avinoam Pirogovsky1,3, Elio Palma1,4, Orna Tal5, Nachman Ash6, Avi Cohen1 and Yoram Chaiter1 1Quality Assurance and Control Committee, Medical Corps, IDF, 2Weizmann Institute of Science, Rehovot, 3Head of Standards and Regulation Department in the Division of Community Medicine, Ministry of Health, Tel Aviv, 4Head of Department of Occupational Medicine, Clalit Health Services, Afula, 5Israeli Center for Technology Assessment in Health Care; The Gertner Institute for Epidemiology and Health Policy Research, Head of Emerging Technologies Unit, Tel Aviv, 6Chief Medical Officer, Medical Corps, IDF, Israel
The BIG FIVE Quickstart: An Introduction to the Five-factor Model of Personality for Human Resource

The first section of this monograph shows how, by analyzing the language of personality descriptors, researchers have identified five correlated groups of behaviors. It finds that the most popular formulation of the Five-Factor Model (FFM) is that of Costa and McCrae (1992) and that their nomenclature can be adapted to come up with a version for professional development. These five factors are described: Negative Emotionality, Extraversion, Openness, Agreeableness, and Conscientiousness. Six facets identified for each of these five factors are described. Section 2 presents how the FFM may be used in fostering individual development. It covers guidelines for use of FFM test scores in professional development, including the following: awareness of small interaction effects between all five personality dimensions and aging; the social context of the Big Five; when to use factors and when to use facets; and common themes among the /arious facets and factors. It also addresses using the FFM in individual coaching and counseling, in a classroom setting, and in personnel selection. Section 3 presents ways in which the Big Five model can be used in working with teams. It looks at how various kinds of relationships--from two-person teams to larger work teams--can benefit from taking time to study the effects of similarities and differences in personality traits among the people in relationships. Contains 21 references. (YLB) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ***********************************************************************
ANALYSIS OF IDEOGRAM AND NON-SPEECH AUDIO TECHNIQUES IN ALGORITHM ANIMATIONS

Algorithm animation (AA) involves the process of cycling through and graphically generating a series of snapshots taken of an algorithm’s critical states over the course of its execution. Professionals in the computing community have a strong intuition that these forms of visualization act as powerful pedagogical tools to foster student comprehension and learning of an algorithm’s abstract notations. However, this popular belief has left researchers wondering about AA effectiveness due to its mixed performance in studies and underutilized in education. Since viewers rely heavily on visual stimuli when viewing an AA, the extra burden could hinder their performance in the comprehension of algorithms. It is the goal of this study to lessen the burden on the visual stimuli by using non-speech audio to reinforce and/or replace some graphical representations. Another technique we examine is the use of ideograms to make AAs more clear and concise. INDEX WORDS: algorithm animations, non-speech audio, ideograms ANALYSIS OF IDEOGRAM AND NON-SPEECH AUDIO TECHNIQUES IN ALGORITHM ANIMATIONS
Upgrading from Gaussian Processes to Student's-T Processes

Gaussian process priors are commonly used in aerospace design for performing Bayesian optimization. Nonetheless, Gaussian processes suffer two significant drawbacks: outliers are a priori assumed unlikely, and the posterior variance conditioned on observed data depends only on the locations of those data, not the associated sample values. Student's-T processes are a generalization of Gaussian processes, founded on the Student's-T distribution instead of the Gaussian distribution. Student's-T processes maintain the primary advantages of Gaussian processes (kernel function, analytic update rule) with additional benefits beyond Gaussian processes. The Student's-T distribution has higher Kurtosis than a Gaussian distribution and so outliers are much more likely, and the posterior variance increases or decreases depending on the variance of observed data sample values. Here, we describe Student's-T processes, and discuss their advantages in the context of aerospace optimization. We show how to construct a Student's-T process using a kernel function and how to update the process given new samples. We provide a clear derivation of optimization-relevant quantities such as expected improvement, and contrast with the related computations for Gaussian processes. Finally, we compare the performance of Student's-T processes against Gaussian process on canonical test problems in Bayesian optimization, and apply the Student's-T process to the optimization of an aerostructural design problem.
AEROBIC FITNESS AMONG CAUCASIAN, AFRICAN-AMERICAN,

Objective: The prevalence of obesity and related comorbidities has dramatically increased in the pediatric population in recent years, and youth from ethnic minorities appear to be disproportionately affected. Although several factors play a role in these ethnic health disparities, evidence suggests fitness may also be an important mediator of disease risk in children. Therefore, the purpose of the present investigation was to compare aerobic fitness (VO2peak) in healthy Caucasian (C), AfricanAmerican (AA), and Latino (L) youth and to evaluate differences after controlling for gender, maturational stage, and body composition.
Short Selling Meets Hedge Fund 13F: An Anatomy of Informed Demand

The existing literature treats the short side (i.e., short selling) and long side of hedge fund trading (i.e., changes in holdings) independently. The two sides, however, complement each other in revealing important economic motivations of trading: opposite changes in short interest and hedge fund holdings are likely to be driven by information, whereas simultaneous increases (decreases) in short interest and hedge fund holdings may be motivated by hedging (unwinding) considerations. We use this intuition to identify informed demand, and document that it exhibits highly significant predictive power on returns: stocks with informed long demand can outperform stocks with informed short demand by approximately 10% per year. We also find that informed demand forecasts future firm fundamentals (e.g., ROA, earnings surprise, analyst revision) but that it is less related to mutual fund flows or liquidity provision. These findings suggest that information discovery about firm fundamentals could be among the most important drivers for informed demand.
Bouncing Oil Droplets, de Broglie’s Quantum Thermostat, and Convergence to Equilibrium

Recently, the properties of bouncing oil droplets, also known as “walkers,” have attracted much attention because they are thought to offer a gateway to a better understanding of quantum behavior. They indeed constitute a macroscopic realization of wave-particle duality, in the sense that their trajectories are guided by a self-generated surrounding wave. The aim of this paper is to try to describe walker phenomenology in terms of de Broglie–Bohm dynamics and of a stochastic version thereof. In particular, we first study how a stochastic modification of the de Broglie pilot-wave theory, à la Nelson, affects the process of relaxation to quantum equilibrium, and we prove an H-theorem for the relaxation to quantum equilibrium under Nelson-type dynamics. We then compare the onset of equilibrium in the stochastic and the de Broglie–Bohm approaches and we propose some simple experiments by which one can test the applicability of our theory to the context of bouncing oil droplets. Finally, we compare our theory to actual observations of walker behavior in a 2D harmonic potential well.
Relationships of Subjective Insomnia and Sleep Duration with Depression, Anxiety, and Pain Problems in Childrenand Adolescents with Attention-Deficit/Hyperactivity Disorder

Abstract Objective: This study examined the relationships of subjective insomnia and short and long nocturnal sleep duration with depression, anxiety, and pain problems in children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Methods: A total of 469 children and adolescents (97 girls and 372 boys; age, 6–18 years) who had received a clinical diagnosis of ADHD completed the eight-item Athens Insomnia Scale, Children’s Depression Inventory-Taiwan Version, Multidimensional Anxiety Scale for Children-Taiwanese Version, and a questionnaire about sleep duration, pain-related dysfunction, and the severity of perceived pain. Their parents provided information on the children’s current ADHD and oppositional symptoms, rated on the abridged Chinese version of the Swanson, Nolan, and Pelham Scale, Version IV. Multiple regression was conducted to examine the relationships of subjective insomnia and sleep duration with depression and anxiety. Logistic regression was applied to examine the relationships of subjective insomnia and sleep duration with pain-related dysfunction and the severity of perceived pain. Results: Subjective insomnia was positively associated with depression, anxiety, pain-related dysfunction, and severe perceived pain in the study population. Short nocturnal sleep duration was positively associated with depression, anxiety, and perceived pain. Long nocturnal sleep duration was positively associated with anxiety and perceived pain. Conclusion: Insomnia and short and long nocturnal sleep duration are associated with depression.
A three‐plate kinematic model for Lau Basin opening

We present revised compilations of bathymetry, magnetization, acoustic imagery, and seismicity data for the Lau Basin and surrounds. We interpret these data to more precisely locate the plate boundaries in the region and to derive a three‐plate kinematic model for the opening of the Lau Basin during the Brunhes Chron. Our tectonic model includes the Niuafo'ou microplate, which is separated from the Australian Plate along the Peggy Ridge‐Lau Extensional Transform Zone‐Central Lau Spreading Center and from the Tongan Plate along the newly discovered Fonualei Rift and Spreading Center. Our model shows that Australia‐Tonga plate motion between 15.5°S and 19°S is partitioned across the microplate, and it resolves the former apparent conflict between geodetic versus seafloor spreading velocities. Regionally, this implies that the angular rate of opening of the Lau Basin has been faster than that of the Havre Trough to the south and that the rapid current rates of Pacific subduction at the Tonga Trench (∼240 mm/yr at 16°S) have been sustained for at least 0.78 m.y.
Critical Review: Are There Successful Predictors of Cochlear Implant Outcomes in Children with Auditory europathy Spectrum Disorder (ASD)?

This critical review examines literature that has addressed the question: Are there successful predictors of cochlear implant outcomes in children with auditory neuropathy spectrum disorder (ANSD)? Through a search of the current literature, four studies were included for critical analysis. Study designs included one nonrandomized retrospective cohort study, one nonrandomized longitudinal cohort study, one nonrandomized between groups retrospective study and one case study. Three different potential predictors of cochlear implant success were investigated amongst the studies: Magnetic Resonance Imaging (MRI), Electrocochleography (ECochG) and Genetic mutations (OTOF). Overall, the evidence provided by these studies suggests that MRIs, specifically identification of cochlear nerve deficiency, may be a potential predictor of cochlear implant success. However, no support was found for the use of ECochG and genetic mutations as predictors as a result of small sample sizes, and limited related research available. Future research is warranted in all three predictor areas with a focus on increasing the number of subjects, appropriate methodology and increased reliability.