Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical and Topographical Corneal Changes after Keraring Implantation in Keratoconus Patients

Introduction: Keratoconus is a progressive, non-inflammatory, bilateral, ecstatic disease of the cornea that is characterized by corneal steepening which progresses to irregular conical shape, with subsequent irregular astigmatism and decreased visual acuity. In early stages of disease, spectacles or RGP lenses are the main treatment. At advanced stages, when these treatment options fail to correct visual acuity, surgical procedures such as penetrating keratoplasty or lamellar keratoplasty are required. METHODS: Keraring segments were placed in 30 eyes of 21 keratoconus patients. The mean follow-up time was 6.2 months. All patients underwent a complete ocular examination and corneal topography which was obtained by Pentacam (Oculus Pentacam®, USA). Improvement in uncorrected visual acuity (UCVA), best spectacle corrected visual acuity, refraction and topographic changes including keratometry, maximum anterior and posterior elevation, central corneal thickness and thinnest point thickness and location were evaluated. RESULTS: No intraoperative or postoperative complications occurred in any of the patients. ICRS implantation significantly improved UCVA (P=0.005) and BSCVA (P=0.000). Mean Spherical equivalent significantly reduced from -6.66 ± 3.52 to -4.42 ± 3.20 (p=0.000). A clinically significant reduction in mean keratometry (p=0.000), Max Ant Elevation (P=0.024) and Max Post Elevation (P=0.002) were recorded. No clinically significant changes in central corneal thickness, thinnest point thickness and thinnest point location were observed. Conclusion: With mean follow-up of 6.2 months, Keraring segments implantation caused significant clinical improvement in UCVA, BCVA Refractive Error and Keratometric findings of the most keratoconic patients. Keywords: keratoconus; ICRS; Keraring
Transformations among Pure Multipartite Entangled States via Local Operations are Almost Never Possible

Local operations assisted by classical communication (LOCC) constitute the free operations in entanglement theory. Hence, the determination of LOCC transformations is crucial for the understanding of entanglement. We characterize here almost all LOCC transformations among pure states of n > 3 d –level systems with d > 2. Combined with the analogous results for n -qubit states shown in G. Gour, B. Kraus, N. R. Wallach, J. Math. Phys. 58, 092204 (2017) this gives a characterization of almost all local transformations among multipartite pure states. We show that non-trivial LOCC transformations among generic fully entangled pure states are almost never possible. Thus, almost all multipartite states are isolated. They can neither be deterministically obtained from local unitary (LU)-inequivalent states via local operations, nor can they be deterministically transformed to pure fully entangled LU-inequivalent states. In order to derive this result we prove a more general statement, namely that generically a state possesses no non-trivial local symmetry. We show that these results also hold for certain tripartite systems. We discuss further consequences of this result for multipartite entanglement theory.
The Effect of Perceived Organizational Support on Doctors’ Organizational Commitment in Pakistan

Maintaining employees’ commitment to their workplace is a major challenge faced by many organizations. This study examines the impact of perceived organizational support (POS) on different dimensions of organizational commitment among medical doctors working in healthcare organizations in Pakistan. It also compares the level of POS and organizational commitment between doctors working in the public and private sectors. Based on a 32-item questionnaire administered to a sample of 160 respondents working at two private and two public hospitals, we find a significant, positive relationship between POS and affective as well as normative commitment, and an insignificant relationship between POS and continuance commitment. This suggests that the management should take measures to increase organizational support among employees in order to raise their level of organizational commitment.
Stress, trauma and post-traumatic stress disorder among adolescents in the Gaza strip

Exposure to traumatic events is common in childhood. According to different cultures, prevalence rates and types of traumatic events are vary widely different across studies, estimates from the National Comorbidity Survey Replication [1], based on a representative sample of 5,692 U.S. children younger than age 13, suggest that as many as 39% experience some type of trauma. Studies in the Middle East showed that mean traumatic events ranged from 4-13 traumatic events in children and adolescents in Palestinian children [2-9]. The impact of the Gulf crisis on Kuwaiti children’s psychological functioning is well documented [10,11]. Effects varied across the Kuwaiti population, primarily as a function of exposure severity. Long-term effects on post-traumatic stress (PTS), depressive symptoms, and to some extent anxiety, have been linked to experiences of children’s fathers during the Gulf crisis, with children whose fathers were arrested reporting the highest levels of post-traumatic stress symptoms, when compared to children whose fathers were missing or killed [11]. Traumatic exposures in childhood have mental health consequences including post-traumatic stress disorder (PTSD), depression, anxiety, and other mental health problems. In study of the levels of PTS symptoms in a sample of Kuwait children trauma-exposed to Gulf crisis experience found that rate of PTSD was 4% [12]. Other trauma due to natural disasters was another source of information about prevalence of PTSD. A study conducted in L’Aquila Earthquake in Italy ten months after the earthquake demonstrated a prevalence of PSTD of 38% among students with a mean age of 17.65 years [13]. In Balkan area, rates of clinically significant levels of PTS symptoms were found (19.8%) in war-exposed adults in Balkan countries met criteria for PTSD [14].
A jamming transition from under- to over-parametrization affects loss landscape and generalization

We argue that in fully-connected networks a phase transition delimits the overand under-parametrized regimes where fitting can or cannot be achieved. Under some general conditions, we show that this transition is sharp for the hinge loss. In the whole over-parametrized regime, poor minima of the loss are not encountered during training since the number of constraints to satisfy is too small to hamper minimization. Our findings support a link between this transition and the generalization properties of the network: as we increase the number of parameters of a given model, starting from an under-parametrized network, we observe that the generalization error displays three phases: (i) initial decay, (ii) increase until the transition point — where it displays a cusp — and (iii) slow decay toward a constant for the rest of the over-parametrized regime. Thereby we identify the region where the classical phenomenon of over-fitting takes place, and the region where the model keeps improving, in line with previous empirical observations for modern neural networks. The theoretical results presented here appeared in [18] for a physics audience. The results on generalization are new.
Energy transfer in resonant and near-resonant internal wave triads for weakly non-uniform stratifications. Part 1. Unbounded domain

Abstract In this paper, using multiple-scale analysis, we derive a generalized mathematical model for amplitude evolution, and for calculating the energy exchange in resonant and near-resonant global triads consisting of weakly nonlinear internal gravity wavepackets in weakly non-uniform density stratifications in an unbounded domain in the presence of viscous and rotational effects. Such triad interactions are one of the mechanisms by which high-wavenumber internal waves lead to ocean turbulence and mixing via parametric subharmonic instability. Non-uniform stratification introduces detuning – mismatch in the vertical wavenumber triad condition, which may strongly affect the energy transfer process. We investigate in detail how factors like wavepacket width, group speeds, nonlinear coupling coefficients, detuning and viscosity affect energy transfer in weakly varying stratification. We also investigate the effect of detuning on energy transfer in varying stratification for different daughter wave combinations of a fixed parent wave. We find limitations of the well-known ‘pump-wave approximation’ and derive a non-dimensional number, which can be evaluated from initial conditions, that can predict the maximum energy transferred from the parent wave during the later stages. Two additional non-dimensional numbers, based on various factors affecting energy transfer between near-resonant wavepackets, have also been defined. Moreover, we identify the optimal background stratification in a medium of varying stratification for the parent wave to form a triad with no detuning so that the energy transfer is maximum.
Research of the Elastic Wave Velocity Dispersion in X-Ray-Irradiated LiF Crystals

The influence of a preliminary deformation (the residual strain ε = 0.65%) and x-ray irradiation to exposure doses of 0–800 R on the frequency dependence of the sound velocity, v ( f ) , in LiF crystals in the frequency interval from 7.5 to 232.5 MHz and at room temperature has been studied using the pulsed technique. By extrapolating the results obtained for v ( f ) to the low-frequency interval and using the well-known theoretical relations, the coefficient of dynamic viscosity B and the dislocation density Λ were found to be independent of the irradiation dose. At the same time, the absolute values of B were found to be lower and the values of Λ higher by an order of magnitude than the corresponding values obtained with the use of the most reliable techniques, such as the methods of high-frequency internal friction and etch pit counting, respectively.
What are SO galaxies

L'etude des galaxies SO montre que la distribution des frequences des luminosites n'est pas intermediaire entre celle des galaxies E et des galaxies Sa. Ces resultats indiquent que la classe SO comprend au moins 2 sous-groupes (qui se recouvrent partiellement en luminosite): les galaxies SO brillantes qui sont reellement intermediaires entre les galaxies de type E et Sa, et les galaxies lenticulaires en forme de disque moins lumineuses. Une troisieme classe de galaxies SO, telles que NGC 5128 et NGC 5195, presentent une morphologie qui vient probablement d'une interaction ou d'une coalescence. Il est conclu que le type SO comprend un nombre de types distincts d'objets qui revelent uniquement des similarites morphologiques superficielles
Dantzig Selector with an Approximately Optimal Denoising Matrix and its Application in Sparse Reinforcement Learning

Dantzig Selector (DS) is widely used in compressed sensing and sparse learning for feature selection and sparse signal recovery. Since the DS formulation is essentially a linear programming optimization, many existing linear programming solvers can be simply applied for scaling up. The DS formulation can be explained as a basis pursuit denoising problem, wherein the data matrix (or measurement matrix) is employed as the denoising matrix to eliminate the observation noise. However, we notice that the data matrix may not be the optimal denoising matrix, as shown by a simple counter-example. This motivates us to pursue a better denoising matrix for defining a general DS formulation. We first define the optimal denoising matrix through a minimax optimization, which turns out to be an NP-hard problem. To make the problem computationally tractable, we propose a novel algorithm, termed as "Optimal" Denoising Dantzig Selector (ODDS), to approximately estimate the optimal denoising matrix. Empirical experiments validate the proposed method. Finally, a novel sparse reinforcement learning algorithm is formulated by extending the proposed ODDS algorithm to temporal difference learning, and empirical experimental results demonstrate to outperform the conventional "vanilla" DS-TD algorithm.
A Shannon-Theoretic Approach to the Storage-Retrieval Tradeoff in PIR Systems

We consider the storage–retrieval rate trade-off in private information retrieval (PIR) systems using a Shannon-theoretic approach. Our focus is mostly on the canonical two-message two-database case, for which a coding scheme based on random codebook generation and the binning technique is proposed. This coding scheme reveals a hidden connection between PIR and the classic multiple description source coding problem. We first show that when the retrieval rate is kept optimal, the proposed non-linear scheme can achieve better performance over any linear scheme. Moreover, a non-trivial storage-retrieval rate trade-off can be achieved beyond space-sharing between this extreme point and the other optimal extreme point, achieved by the retrieve-everything strategy. We further show that with a method akin to the expurgation technique, one can extract a zero-error PIR code from the random code. Outer bounds are also studied and compared to establish the superiority of the non-linear codes over linear codes.
Do graph readers prefer the graph type most suited to a given task? Insights from eye tracking

Research on graph comprehension suggests that point differences are easier to read in bar graphs, while trends are easier to read in line graphs. But are graph readers able to detect and use the most suited graph type for a given task? In this study, we applied a dual repre-sentation paradigm and eye tracking methodology to determine graph readers’ preferential processing of bar and line graphs while solving both point difference and trend tasks. Data were analyzed using linear mixed-effects models. Results show that participants shifted their graph preference depending on the task type and refined their preference over the course of the graph task. Implications for future research are discussed.
This Looks Like That: Deep Learning for Interpretable Image Recognition

When we are faced with challenging image classification tasks, we often explain our reasoning by dissecting the image, and pointing out prototypical aspects of one class or another. The mounting evidence for each of the classes helps us make our final decision. In this work, we introduce a deep network architecture that reasons in a similar way: the network dissects the image by finding prototypical parts, and combines evidence from the prototypes to make a final classification. The model thus reasons in a way that is qualitatively similar to the way ornithologists, physicians, geologists, architects, and others would explain to people on how to solve challenging image classification tasks. The network uses only image-level labels for training, meaning that there are no labels for parts of images. We demonstrate our method on the CUB-200-2011 dataset and the CBIS-DDSM dataset. Our experiments show that our interpretable network can achieve comparable accuracy with its analogous standard non-interpretable counterpart as well as other interpretable deep models.
Incidence of low back pain related occupational diseases in the Netherlands

Until recently, no evidence‐based criteria were available to determine the work‐relatedness of low back pain (LBP) in an individual worker. Incidence figures for LBP that can be qualified as occupational disease (OD) are scarce. We studied the trend in the number of OD notifications due to LBP in the Netherlands and estimated incidence rates of LBP‐related OD notifications.
Face Detection & Feature Tracking Data Interpolation & Unstable Features Removal Temporal Filtering PCA SHIBBS FastICA JADE Suspected Pattern Identification Component Analysis Bad Components Removal Moving Dynamic Time Warping ( MDTW ) on Each Component Peak DetectionOptimal ComponentSelection Pulse

Human heartbeat can be measured using several different ways appropriately based on the patient condition which includes contact base such as measured by using instruments and non-contact base such as computer vision assisted techniques. Non-contact based approached are getting popular due to those techniques are capable of mitigating some of the limitations of contact-based techniques especially in clinical section. However, existing vision guided approaches are not able to prove high accurate result due to various reason such as the property of camera, illumination changes, skin tones in face image, etc. We propose a technique that uses video as an input and returns pulse rate in output. Initially, key point detection is carried out on two facial subregions: forehead and nose-mouth. After removing unstable features, the temporal filtering is applied to isolate frequencies of interest. Then four component analysis methods are employed in order to distinguish the cardiovascular pulse signal from extraneous noise caused by respiration, vestibular activity and other changes in facial expression. Afterwards, proposed peak detection technique is applied for each component which extracted from one of the four different component selection algorithms. This will enable to locate the positions of peaks in each component. Proposed automatic components selection technique is employed in order to select an optimal component which will be used to calculate the heartbeat. Finally, we conclude with comparison of four component analysis methods (PCA, FastICA, JADE, SHIBBS), processing face video datasets of fifteen volunteers with verification by an ECG/EKG Workstation as a ground truth. Keywords—video-based pulse detection, face feature tracking, component analysis, automatic component selection, moving dynamic time warping, singular spectral analysis
Academic engagement: Differences between intention to adopt Social Networking Sites and other online technologies 1. Introduction

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Domain Decomposition with Local Impedance Conditions for the Helmholtz Equation with Absorption

We consider one-level additive Schwarz preconditioners for a family of Helmholtz problems with absorption and increasing wavenumber $k$. These problems are discretized using the Galerkin method with nodal conforming finite elements of any (fixed) order on meshes with diameter $h = h(k)$, chosen to maintain accuracy as $k$ increases. The action of the preconditioner requires solution of independent (parallel) subproblems (with impedance boundary conditions) on overlapping subdomains of diameter $H$ and overlap $\delta\leq H$. The solutions of these subproblems are linked together using prolongation/restriction operators defined using a partition of unity. In numerical experiments (with $\delta \sim H$) for a model interior impedance problem, we observe robust (i.e. $k-$independent) GMRES convergence as $k$ increases. This provides a highly-parallel, $k-$robust one-level domain decomposition method. We provide supporting theory by studying the preconditioner applied to a range of absorptive problems, $k^2\mapsto k^2+ \mathrm{i} \varepsilon$, with absorption parameter $\varepsilon$. Working in the Helmholtz ``energy'' inner product, and using the underlying theory of Helmholtz boundary-value problems, we prove a $k-$independent upper bound on the norm of the preconditioned matrix, valid for all $\vert \varepsilon\vert \lesssim k^2$. We also prove a strictly-positive lower bound on the distance of the field of values of the preconditioned matrix from the origin which holds when $\varepsilon/k$ is constant or growing arbitrarily slowly with $k$. These results imply robustness of the preconditioner for the corresponding absorptive problem as k increases and give theoretical support for the observed robustness of the preconditioner for the pure Helmholtz problem.
Laser generation on Yb:LuAG ceramics produced by nanocrystalline pressure-less sintering in H2

The spectral and laser properties of 3 at. % Yb3+:Lu3Al5O12 ceramics produced by a new method of nanocrystalline pressure-less sintering in H2 were investigated. The studied sample had a transmittance close to the theoretical value (83.3% at λ = 1070 nm) and a laser level lifetime of 0.93 ms. Laser generation in different regimes with a maximum slope efficiency of 54% and a maximum average power of 206 W was attained, which makes this method highly promising for producing ceramics for lasers with multi-kilowatt average power.
Reynolds Stress Modelling for Turbomachinery Flow Applications

Most industrially relevant flows in turbomachinery components are of a turbulent or at least transitional nature. Hence, the success of the numerical simulation of such flows depends significantly on the correct representation of turbulent effects. In the framework of continuum mechanics, these are described by the Navier-Stokes equations. A direct solution of these equations (Direct Numerical Simulation, DNS) is, however, not feasible at industrially relevant Reynolds numbers due to the enormous computational requirements. For this reason, the Reynolds-averaged Navier-Stokes equations are used to describe the flow and turbulent effects are considered by appropriate statistical models. The present thesis addresses the analysis of differential Reynolds stress models (DRSM). The models are implemented in the DLR solver TRACE and qualified for the application to turbomachinery flows. After a rigorous literature review, with the SSG/LRR-ω and the JH-ω model, two models of different complexity and robustness were chosen. Since the latter is a crucial factor for the successful application of these models, the numerical properties of the DRSMs with special focus on the pressurestrain correlation term are investigated by means of a model problem. In this respect, both a dynamical systems analysis and a numerical phase space analysis are conducted exemplarily. For the robust numerical solution of the model equations, the linearisation of the sophisticated source terms is derived in the context of the implicit solution procedure. Since the transport equations of the turbulence variables are not solved in a coupled manner, a correction to the convective fluxes is developed, which ensures a conservative, second order accurate formulation. Numerous requirements for the application in turbomachinery flows, such as the solution in a rotating frame of reference, rotationally periodic boundary conditions or mixing planes are considered. The implementation of the models is verified and validated by computing a substantial number of building block flows relevant to turbomachinery applications. In the framework of this activity the respective models’ strengths and weaknesses compared to linear eddy viscosity models and explicit algebraic Reynolds stress models as well as each other are highlighted. The applicability of the DRSMs to industrially relevant configurations and their limits are demonstrated and discussed by a detailed evaluation of flows through a compressor cascade, a Ranque-Hilsch vortex tube and a 1.5 stage cold air turbine. The present critical evaluation is supposed to expose the different models’ strengths and weaknesses and to recommend a suitable choice for respective applications.