Miracle-dz/UniFAR-FTUs huggingface dataset:
Corneal Epithelial Remodeling Induced by Small Incision Lenticule Extraction (SMILE).

PURPOSE To assess the reactive changes of the corneal epithelial thickness (ET) profile induced by small incision lenticule extraction (SMILE) for treatment of myopia. METHODS This prospective observational study included 46 eyes of 23 patients that were scheduled for myopic SMILE. High-resolution spectral-domain optical coherence tomography (SD-OCT) and a custom image segmentation algorithm were applied to measure corneal ET at multiple time points within the central 5-mm zone. Postoperative ET alterations were correlated with treatment parameters and refractive outcomes. RESULTS Mean age was 33 ± 6 years and mean spherical equivalent of surgical refractive correction was -4.78 ± 1.75 diopters. The average ET (averaged over the central 5-mm zone) increased from 52.3 ± 3.6 μm preoperatively to 57.7 ± 5.1 μm 6 months postoperatively (P < 0.01). Average ET was 101.9% of the preoperative thickness at 24 hours postoperatively, 103.2% at 1 week, 106.7% at 6 weeks, 109.3% at 3 months, and 110.4% at 6 months postoperatively. The epithelial thickening response could be modeled by an exponential recovery function and stabilized after 3 months. The extent of epithelial hyperplasia was highly dependent on the magnitude of the induced refractive correction (P = 0.002). CONCLUSIONS In this initial study of corneal ET remodeling after myopic SMILE, significant epithelial thickening was detected as a function of the extent of surgical refractive correction. Moreover, the epithelial remodeling response to the corneal refractive change appeared to decrease with higher age. In our hands, the observed epithelial changes did not appear to affect the refractive outcome of SMILE. (ClinicalTrials.gov number, NCT02614625).
Does Outsourcing to Central and Eastern Europe Really Threaten Manual Workers' Jobs in Germany?

Starting from the observation of significant within-industry skill-upgrading, this paper analyses how international outsourcing has affected the relative demand for manual workers in German manufacturing during the 1990s. We combine trade and input-output data to disentangle international outsourcing and trade in final goods and differentiate between the effects of narrowly and broadly defined outsourcing towards Central and Eastern Europe (CEEC), the European Union (EU15) and the rest of the world. Accounting for the endogeneity of international outsourcing by applying instrumental variable techniques, the empirical analysis showed that international outsourcing is indeed an important explanatory factor for the observed decline in relative demand for manual workers in German manufacturing. Particularly, outsourcing towards CEEC plays a major role, irrespective of whether a narrow or wide measure of outsourcing is applied. Using a narrow outsourcing measure and controlling for the adverse demand effects of skill-biased technological change, time-changing industry characteristics, wages as well as industry unobserved characteristics, international outsourcing towards CEEC is found to have lowered the manual workers' wage bill share by 2.7 per-centage points between 1991 and 2000. In its magnitude this effect is comparable to the skill-biased effect of technological progress, as captured by our controls. Outsourcing towards countries outside CEEC and outside the EU15 is found to have small negative effects on the relative demand for manual workers, but only if one follows the broad definition of international outsourcing. Outsourcing towards the EU15 is, however, always found to be insignificant. Copyright 2006 The Authors Journal compilation 2006 Blackwell Publishing Ltd .
Gap junctions in the vertebrate retina

The vertebrate retina is a highly laminated assemblage of specialized neuronal types, many of which are coupled by gap junctions. With one interesting exception, gap junctions are not directly responsible for the ‘vertical’ transmission of visual information from photoreceptors through bipolar and ganglion cells to the brain. Instead, they mediate ‘lateral’ connections, coupling neurons of a single type or subtype into an extended, regular array or mosaic in the plane of the retina. Such mosaics have been studied by several microscopic techniques, but new evidence for their coupled nature has recently been obtained by intracellular injection of biotinylated tracers, which can pass through gap junctional assemblies that do not pass Lucifer Yellow. This evidence adds momentum to an existing paradigm shift towards a population‐based view of the retina, which can now be envisaged both as an array of semi‐autonomous vertical processing modules, each extending right through the retina, and as a multi‐layered stack of interacting planar mosaics, bearing some resemblance to a set of interleaved neural networks. Junctional conductance across mosaics of horizontal cells is known to be controlled dynamically with a circadian rhythm, and other dynamically‐regulated conductance changes are also likely to make important contributions to signal processing. The retina is an excellent system in which to study such changes because many aspects of its structure and function are already well understood. In this review, we summarize the microscopic appearance, coupling properties and functions of gap junctions for each cell type of the neural retina, the regulatory properties that could be provided by selective expression of different connexin proteins, and the evidence for gap junctional coupling in retinal development. © 1995 Wiley‐Liss, Inc.
Return to Play After the Latarjet Procedure for Anterior Shoulder Instability: A Systematic Review

Background: Traumatic anterior shoulder instability is a common clinical problem among athletic populations. The Latarjet procedure is a widely used treatment option to address shoulder instability in high-demand athletes at high risk of recurrence. However, rates and timing of full return to sports have not been systematically analyzed. Purpose: To systematically review the evidence in the literature to ascertain the rate and timing of return to play and the availability of specific criteria for safe return to play after the Latarjet procedure. Study Design: Systematic review. Methods: A systematic literature search was conducted based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, using the EMBASE, MEDLINE, and Cochrane Library databases. Eligible for inclusion were clinical studies reporting on return to play after the Latarjet procedure. Statistical analysis was performed by use of SPSS. Results: Our review found 36 studies including 2134 cases meeting our inclusion criteria. The majority of patients were male (86.9%), with a mean age of 25.4 years (range, 15-59 years) and a mean follow-up of 83.5 months. The overall rate of return to play was 88.8%, with 72.6% returning to the same level of play. Among collision athletes, the overall rate of return to play was 88.2%, with 69.5% returning to the same level of play. In overhead athletes, the overall rate of return to play was 90.3%, with 80.6% returning to the same level of play. The mean time to return to play was 5.8 months (range, 3.2-8 months). Specific return to play criteria were reported in the majority of the studies (69.4%); time to return to sport was the most commonly reported item (66.7%). Conclusion: The overall rate of return to play was reportedly high after the Latarjet procedure. However, almost a fifth of athletes returning to sports were not able to return at the same level. Further development of validated criteria for safe return to sports could potentially improve clinical outcomes and reduce recurrence rates.
Best-Fit Learning Curve Model for the C4.5 Algorithm

Background: In the area of artificial learners, not much research on the question of an appropriate description of artificial learner's (empirical) performance has been conducted. The optimal solution of describing a learning problem would be a functional dependency between the data, the learning algorithm's internal specifics and its performance. Unfortunately, a general, restrictions-free theory on performance of arbitrary artificial learners has not been developed yet.Objective: The objective of this paper is to investigate which function is most appropriately describing the learning curve produced by C4.5 algorithm.Methods: The J48 implementation of the C4.5 algorithm was applied to datasets (n=121) from publicly available repositories (e.g. UCI) in step wise k-fold cross-validation. First, four different functions (power, linear, logarithmic, exponential) were fit to the measured error rates. Where the fit was statistically significant (n=86), we measured the average mean squared error rate for each function and its rank. The dependent samples T-test was performed to test whether the differences between mean squared error are significantly different, and Wilcoxon's signed rank test was used to test whether the differences between ranks are significant.Results: The decision trees error rate can be successfully modeled by an exponential function. In a total of 86 datasets, exponential function was a better descriptor of error rate function in 64 of 86 cases, power was best in 13, logarithmic in 3, and linear in 6 out of 86 cases. Average mean squared error across all datasets was 0.052954 for exponential function, and was significantly different at P=0.001 from power and at P=0.000 from linear function. The results also show that exponential function's rank is significantly different at any reasonable threshold (P=0.000) from the rank of any other model.Conclusion: Our findings are consistent with tests performed in the area of human cognitive performance, e.g. with works by Heathcote et al. (2000), who were observing that the exponential function is best describing an individual learner. In our case we did observe an individual learner (C4.5 algorithm) at different tasks. The work can be used to forecast and model the future performance of C4.5 when not all data have been used or there is a need to obtain more data for better accuracy.
Improving Passage Retrieval Using Interactive Elicition and Statistical Modeling

Abstract : The University of Maryland and Johns Hopkins University worked together in the 2004 High Accuracy Retrieval from Documents (HARD) track to explore design options for interactive passage retrieval systems. HARD assessors responded to clarification forms by (1) selected additional search terms from an automatically constructed list of potentially discriminating terms, (2) selected relevant passages from an automatically constructed list of possibly relevant passages, and (3) entered additional search terms. Query expansion based on these three types of elicited information yielded statistically significant improvements in R-precision over baselines with and without blind relevance feedback. For topics that requested passages as answers, a preliminary analysis shows that statistical models for passage extent trained on HARD 2003 data yielded a significant improvement over a replication of the University of Maryland's hard-2003 technique for passage extent determination, and the results of the new technique appear to generally be well above the median for HARD 2004 systems.
Energy efficient and quality-driven continuous sensor management for mobile IoT applications

A novel class of mobile Internet of Things applications falls under the category of mobile crowdsensing, whereby large amounts of sensed data are collected and shared by mobile sensing and computing devices for the purposes of observing phenomena of common interest (e.g., traffic monitoring, environmental monitoring). Challenges arise with respect to collecting and managing sensor data in an energy- and bandwidth-efficient manner. In this paper we present a cloud-based system architecture centred around a publish/subscribe middleware interfaced with a quality-driven sensor management function, applicable for building mobile IoT applications. The architecture is designed so as to smartly manage and acquire sensor readings in order to satisfy global sensing coverage requirements, while obviating redundant sensor activity and consequently reducing overall system energy consumption. We evaluate the system using a proposed model for calculating bandwidth and energy savings. Model evaluation based on simulation results provides insight into the energy savings for different application requirements and geographical sensor distribution scenarios. Our results show that in certain identified cases, significant energy consumption reductions can be achieved utilizing the proposed architecture and sensor management scheme (as compared to a standard publish/subscribe approach), while maintaining overall global sensing quality level (in terms of required sensing coverage). Assumptions with regards to user distributions in urban areas are verified using an existing dataset reported in literature.
Evaluation of Proactive, Reactive and Hybrid Ad hoc Routing Protocol for various Battery models in VANET using Qualnet

2 Abstract - In VANET high speed is the real characteristics which leads frequent breakdown, interference etc. In this paper we studied various Ad hoc routing protocols, Reactive, Proactive & Hybrid, taking in to consideration various VANET parameters like speed, altitude etc in real traffic scenario and evaluated them for various battery models for energy conservation. The AODV and DYMO (Reactive), OLSR (Proactive) and ZRP (hybrid) protocols are compared for battery models Duracell AA(MX- 1500),Duracell AAA(MN-2400),Duracell AAA(MX-2400), Duracell C-MN(MN-1400),Panasonic AA standard using Qualnet as a Simulation tool. Since Energy conservation is main focus area now days. Hence performance of the protocols with various battery models counts and helps to make a right selection. Varying parameters of VANET shows that in the real traffic scenarios proactive protocol performs more efficiently for energy conservation.
EHPnet: Taking Inventory of Toxics

Many cellular systems rely on the ability to interpret spatial heterogeneities in chemoattractant concentration to direct cell migration. The accuracy of this process is limited by stochastic fluctuations in the concentration of the external signal and in the internal signaling components. Here we use information theory to determine the optimal scheme to detect the location of an external chemoattractant source in the presence of noise. We compute the minimum amount of mutual information needed between the chemoattractant gradient and the internal signal to achieve a prespecified chemotactic accuracy. We show that more accurate chemotaxis requires greater mutual information. We also demonstrate that a priori information can improve chemotaxis efficiency. We compare the optimal signaling schemes with existing experimental measurements and models of eukaryotic gradient sensing. Remarkably, there is good quantitative agreement between the optimal response when no a priori assumption is made about the location of the existing source, and the observed experimental response of unpolarized Dictyostelium discoideum cells. In contrast, the measured response of polarized D. discoideum cells matches closely the optimal scheme, assuming prior knowledge of the external gradient—for example, through prolonged chemotaxis in a given direction. Our results demonstrate that different observed classes of responses in cells (polarized and unpolarized) are optimal under varying information assumptions.
Recovering Signal Energy From the Cyclic Prefix in OFDM

In orthogonal frequency-division multiplexing (OFDM) systems, a cyclic prefix (CP) is often added at the transmitter and discarded at the receiver. When the length of the CP exceeds the delay spread of the channel, a portion of the CP can be used to recover additional signal energy. In the past, Nyquist windowing techniques have been proposed to recover signal energy, thereby improving performance. In this paper, linear maximum-likelihood (ML) and minimum-mean-square-error (MMSE) approaches are developed, which further improve performance, particularly when the signal-to-noise ratio (SNR) is low. Simpler two-valued windowing (TVW) solutions are also provided, which generally employ one or two non-Nyquist windows.
Plurilingual Ethos: A Peep into the Sociology of Language.

Studies on multilingualism have a rather shady past. Till recently many studies in the field viewed the phenomena of individual or societal multilingualism as a matter of human adjustment, and confined their enquiries to the problems such as accounting for interference in second language acquisition, and for the distortionism, resulting from language contact such as hybridization, pidginization, and so on. This paper examines these phenomena in detail from the point view of societal bilingualism and plurilingualism in India and Pakistan.
Verification and synthesis using real quantifier elimination

We present the application of real quantifier elimination to formal verification and synthesis of continuous and switched dynamical systems. Through a series of case studies, we show how first-order formulas over the reals arise when formally analyzing models of complex control systems. Existing off-the-shelf quantifier elimination procedures are not successful in eliminating quantifiers from many of our benchmarks. We therefore automatically combine three established software components: virtual subtitution based quantifier elimination in Reduce/Redlog, cylindrical algebraic decomposition implemented in Qepcad, and the simplifier Slfq implemented on top of Qepcad. We use this combination to successfully analyze various models of systems including adaptive cruise control in automobiles, adaptive flight control system, and the classical inverted pendulum problem studied in control theory.
Hyperspectral images mapping with group sparse representations

In this paper, we propose a new framework for remote sensing images classification based on group sparse representations. It is well known that it is very difficult to find a suitable sparse representation for remote sensing images because of complicated ground features. Here a remote sensing image is deemed a combination of sub-images of smooth, edges and point like components. Since each domain transformation method is only capable of representing a particular kind of ground objects or textures, a group of domain transformations are combined to sparsely represent the whole image. By applying the group sparse representations as a prior in Maximum a Posterior (MAP) for ill-conditioned problems, each channel of an input hyperspectral data cube can be separated into sub-images of the same size as the input image by using the iterative soft-thresholding algorithm (ISTA). For a particular channel, smooth areas will most likely show in the sub-image with similar amplitude. These smooth areas in a sub-image will work as implicit spatial constraint for that channel. Therefore, those reconstructed sub-images can be added to the original hyperspectral data cube as an augmented data cube with spatial constraint embedded for solving classification problem. This new framework brings hopes for all the classification methods without spatial constraints for the purpose of improving classification accuracy. The improved classification results can be achieved without any changes to those classification methods but using the augmented data cube.
Exploring the self-presentations of Indian IT professionals on social media

Self-presentations are goal-directed acts designed by individuals to convey particular images of their selves and thereby influence how they are perceived and treated by various audiences (Goffman, 1959). Recent literature suggests that individuals are increasingly interacting with their workplace colleagues on personal networking sites like Facebook and Twitter. In such overlapping interactions, individuals often move swiftly and in an asymmetric fashion between physical-virtual settings and personal-professional life. Presumably, diverse self-presentations across physical-virtual settings and personal-professional life may create conflicts or tensions. Drawing on 31 semi-structured interviews, this thesis explores the self-presentations of Indian IT professionals on social media. Overall, the analysis suggests that in most cases, respondents enacted diverse self-presentations across physical-virtual settings and personal-professional life. In such cases, they expressed concerns that overlapping audiences may view their self-presentations on social media out-of-context and inevitably misconstrue their professional image. From a theoretical perspective, the thesis illustrates that individuals who exercise region behavior experience cognitive discomfort when they enact self-presentations on social media as overlapping self-presentations are inevitable. From a practical perspective, empirical evidence suggests that employees take their interactions on social media seriously and thus dispute managers arguments that interacting on social media is merely a time-pass .
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1199 Adaptive Solvers for High-Dimensional PDE Problems on Clusters of Multicore Processors

Grandin, M. 2014. Adaptive Solvers for High-Dimensional PDE Problems on Clusters of Multicore Processors. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1199. 34 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-554-9095-9. Accurate numerical solution of time-dependent, high-dimensional partial differential equations (PDEs) usually requires efficient numerical techniques and massive-scale parallel computing. In this thesis, we implement and evaluate discretization schemes suited for PDEs of higher dimensionality, focusing on high order of accuracy and low computational cost. Spatial discretization is particularly challenging in higher dimensions. The memory requirements for uniform grids quickly grow out of reach even on large-scale parallel computers. We utilize high-order discretization schemes and implement adaptive mesh refinement on structured hyperrectangular domains in order to reduce the required number of grid points and computational work. We allow for anisotropic (non-uniform) refinement by recursive bisection and show how to construct, manage and load balance such grids efficiently. In our numerical examples, we use finite difference schemes to discretize the PDEs. In the adaptive case we show how a stable discretization can be constructed using SBP-SAT operators. However, our adaptive mesh framework is general and other methods of discretization are viable. For integration in time, we implement exponential integrators based on the Lanczos/Arnoldi iterative schemes for eigenvalue approximations. Using adaptive time stepping and a truncated Magnus expansion, we attain high levels of accuracy in the solution at low computational cost. We further investigate alternative implementations of the Lanczos algorithm with reduced communication costs. As an example application problem, we have considered the time-dependent Schrödinger equation (TDSE). We present solvers and results for the solution of the TDSE on equidistant as well as adaptively refined Cartesian grids.