Miracle-dz/UniFAR-FTUs huggingface dataset:
Sustained Fixation Induced Changes in Phoria and Convergence Peak Velocity

Purpose This study sought to investigate the influence of phoria adaptation on convergence peak velocity from responses located at different initial vergence positions. Methods Symmetrical 4° convergence step responses and near dissociated phoria (measured at 40 cm from the subject's midline) were recorded from six subjects with normal binocular vision using an infrared limbus tracking system with a haploscope. Two different sustained fixations (1° and 16° convergent rotation along the subject's midline) were used to study whether phoria had an influence on the peak velocity of convergence responses located at two initial vergence positions (1° or ‘far’ steps and 12° or ‘near’ steps). Results Phoria was significantly adapted after a sustained fixation task at near (16°) and far (1°) (p<0.002). A repeated measures ANOVA showed that convergence far steps were significantly faster than the near steps (p<0.03). When comparing convergence steps with the same initial vergence position, steps measured after near phoria adaptation were faster than responses after far adaptation (p<0.02). A regression analysis demonstrated that the change in phoria and the change in convergence peak velocity were significantly correlated for the far convergence steps (r = 0.97, p = 0.001). A weaker correlation was observed for the near convergence steps (r = 0.59, p = 0.20). Conclusion As a result of sustained fixation, phoria was adapted and the peak velocity of the near and far convergence steps was modified. This study has clinical considerations since prisms, which evoke phoria adaptation, can be prescribed to help alleviate visual discomfort. Future investigations should include a systematic study of how prisms may influence convergence and divergence eye movements for those prescribed with prisms within their spectacles.
A scalable algorithm for MAP estimators in Bayesian inverse problems with Besov priors

We present a scalable solver for approximating the maximum a posteriori (MAP) point of Bayesian inverse problems with Besov priors based on wavelet expansions with random coefficients. It is a subspace trust region interior reflective Newton conjugate gradient method for bound constrained optimization problems. The method combines the rapid locally-quadratic convergence rate properties of Newton's method, the effectiveness of trust region globalization for treating ill-conditioned problems, and the Eisenstat--Walker idea of preventing oversolving. We demonstrate the scalability of the proposed method on two inverse problems: a deconvolution problem and a coefficient inverse problem governed by elliptic partial differential equations. The numerical results show that the number of Newton iterations is independent of the number of wavelet coefficients $n$ and the computation time scales linearly in $n$. It will be numerically shown, under our implementations, that the proposed solver is two times faster than the split Bregman approach, and it is an order of magnitude less expensive than the interior path following primal-dual method. Our results also confirm the fact that the Besov $\mathbb{B}_{11}^1$ prior is sparsity promoting, discretization-invariant, and edge-preserving for both imaging and inverse problems governed by partial differential equations.
Power Modeling in Database Management Systems

Data centers consume large amounts of energy. Since databases form one of the main energy sinks in a typical data center, building energy-aware database systems has become an active research topic recently. The quantification of the energy cost of database systems is an important task in designing such systems. In this paper, we report our recent efforts on this topic, with a focus on the power estimation of query plans during query optimization. We start from a series of physical models designed for evaluating power cost of individual relational operators. Such models form the basis for a composite power model for the query plans. Key parameters for the query power model are generated by using linear regression tools upon running experiments with simple workloads in a static environment. Our solution can effectively tune the model parameters at runtime to reach high accuracy of power estimations. The models are implemented in the PostgreSQL kernel and evaluated with a comprehensive set of experimental workloads generated from multiple TPC and scientific database benchmarks.
Knowledge, Perceptions and Attitudes toward Chronic Pain and Its Management: A Cross-Sectional Survey of Frontline Pharmacists in Ontario, Canada

The treatment of chronic pain consumes a significant share of primary care. Community and family health team pharmacists frequently see patients with chronic pain, thus have the opportunity to improve their care. To assess the knowledge, perceptions, and attitudes of Ontario pharmacists, we invited 5,324 Ontario pharmacists, to participate in an online survey we developed using Qualtrics. The 31-question survey gathered demographic information, assessed pharmacists’ knowledge of three chronic pain conditions; chronic lower back pain (CLBP, eight true/false statements); chronic headache disorder (CHD, eight true/false statements) and painful diabetic neuropathy (PDN, seven true/false statements), and their attitudes toward and perceptions of patients with these conditions, and knowledge, attitudes, and perceptions of opioids in pain management. We received 688 responses (12.9%) and 392 pharmacists completed the survey. The mean age of respondents was 48.5 years and 48.5% were male. More than 50% of respondents were in practice for more than 20 years and 58.7% worked 25–40 hours per week. The mean knowledge scores were 4.5/8, 5.5/8, and 5.3/8 for CBLP, CHD, and PDN respectively. While 95% of respondents were aware of the increasing death rates due to opioid use, only half were familiar with the Canadian guideline for safe opioid prescribing for non-cancer use. Responses were compared based on gender, time in practice and location of practice. Pharmacists with more than ten years of experience scored significantly higher than those with less experience. Fewer differences were found in comparisons of gender and location of practice. Safe and effective care of chronic pain patients, particularly with opioids, will require additional pharmacist education.
The Conventional Non-Articulated SACH or a Multiaxial Prosthetic Foot for Hypomobile Transtibial Amputees? A Clinical Comparison on Mobility, Balance, and Quality of Life

The effects of a non-articulated SACH and a multiaxial foot-ankle mechanism on the performance of low-activity users are of great interest for practitioners in amputee rehabilitation. The aim of this study is to compare these two prosthetic feet and assess possible improvements introduced by the increased degrees of freedom provided by the multiaxial foot. For this purpose, a group of 20 hypomobile transtibial amputees (TTAs) had their usual SACH replaced with a multiaxial foot. Participants' functional mobility, involving ambulatory skills in overground level walking, ramps, and stairs, was evaluated by performing Six-Minute Walking Test (6MWT), Locomotor Capability Index-5 (LCI-5), Hill Assessment Index (HAI), and Stair Assessment Index (SAI). Balance performances were assessed using Berg Balance Scale (BBS) and analysing upper body accelerations during gait. Moreover, the Prosthesis Evaluation Questionnaire (PEQ) was performed to indicate the prosthesis-related quality of life. Results showed that participants walked faster using the multiaxial foot (p < 0.05) maintaining the same upright gait stability. Significant improvements with the multiaxial foot were also observed in BBS, LCI-5, and SAI times and 4 of 9 subscales of the PEQ. Our findings demonstrate that a multiaxial foot represents a considerable alternative solution with respect to the conventional SACH in the prosthetic prescription for hypomobile TTAs.
A lane detection method for freeway aerial videos

This paper proposes a method to detect the lanes from the aerial videos, which is composed of two parts: image pre-processing and the lane detection. The first part, image pre-processing, mainly includes down-sampling, image binarizing and lane edge getting, and then a low resolution binary image will be gotten. The second part consists of the line parameter getting based on Hough Transform, false lane parameters removing, lane parameters correcting based on Kalman algorithm and ROI (region of interest) getting. After taking some characteristics of the freeway into consideration, this paper proposes a binaryzation algorithm which can convert color images into binary images directly. Furthermore, the white blocks in the binary image can be removed after lane edge getting. This paper adopts the Progressive Probabilistic Hough Transform to increase the accuracy and efficiency. What's more, in this paper, we put forward two principles to remove false line parameters based on the distribution characteristics of the lanes: the dominance of the lane angles and the similarity of the slope difference and the distance between the adjacent lane markings. Finally, in this paper, the Kalman filter is used to correct and predict the parameters. Above all, this method can detect all the lanes correctly from the aerial video, with good accuracy and robustness, even if many vehicles are on the road and pipes and poles are beside the road, and even if the freeway locates at the corner of the image or has a big dip angle.
A Linear Relationship between Crystal Size and Fragment Binding Time Observed Crystallographically: Implications for Fragment Library Screening Using Acoustic Droplet Ejection

High throughput screening technologies such as acoustic droplet ejection (ADE) greatly increase the rate at which X-ray diffraction data can be acquired from crystals. One promising high throughput screening application of ADE is to rapidly combine protein crystals with fragment libraries. In this approach, each fragment soaks into a protein crystal either directly on data collection media or on a moving conveyor belt which then delivers the crystals to the X-ray beam. By simultaneously handling multiple crystals combined with fragment specimens, these techniques relax the automounter duty-cycle bottleneck that currently prevents optimal exploitation of third generation synchrotrons. Two factors limit the speed and scope of projects that are suitable for fragment screening using techniques such as ADE. Firstly, in applications where the high throughput screening apparatus is located inside the X-ray station (such as the conveyor belt system described above), the speed of data acquisition is limited by the time required for each fragment to soak into its protein crystal. Secondly, in applications where crystals are combined with fragments directly on data acquisition media (including both of the ADE methods described above), the maximum time that fragments have to soak into crystals is limited by evaporative dehydration of the protein crystals during the fragment soak. Here we demonstrate that both of these problems can be minimized by using small crystals, because the soak time required for a fragment hit to attain high occupancy depends approximately linearly on crystal size.
Active Contour Model based on Dynamic Extern Force and Gradient Vector Flow

Active contour model, or snakes, are used extensively in digital image processing, particularly to locate object boundary, the model include geometric and parametric active models. Problems associated with initialization and convergence restrict their utility, which have been solved by Xu, who proposed gradient vector flow. However, parametric active models still face the problem that the whole curve may evolve into only a side of the true boundary. This paper presents a new approach based on the parametric active models with generalized gradient vector flow (GGVF) and dynamic extern force, which decreases when iterative number increases and thus makes terminal contour less dependent on the initial curve and it can speed up the iterate process. The image edge and the field that point to round from center decide the initial extern force, which can prevent curve evolution from possible wrong segmentation. The tongue edge can be detected faster and more accurately than ever in the tongue image experiments.
Bioactive and Structural Metabolites of Pseudomonas and Burkholderia Species Causal Agents of Cultivated Mushrooms Diseases

Pseudomonas tolaasii, P. reactans and Burkholderia gladioli pv. agaricicola, are responsible of diseases on some species of cultivated mushrooms. The main bioactive metabolites produced by both Pseudomonas strains are the lipodepsipeptides (LDPs) tolaasin I and II and the so called White Line Inducing Principle (WLIP), respectively, LDPs which have been extensively studied for their role in the disease process and for their biological properties. In particular, their antimicrobial activity and the alteration of biological and model membranes (red blood cell and liposomes) was established. In the case of tolaasin I interaction with membranes was also related to the tridimensional structure in solution as determined by NMR combined with molecular dynamic calculation techniques. Recently, five news minor tolaasins, tolaasins A–E, were isolated from the culture filtrates of P. tolaasii and their chemical structure was determined by extensive use of NMR and MS spectroscopy. Furthermore, their antimicrobial activity was evaluated on target micro-organisms (fungi—including the cultivated mushrooms Agaricus bisporus, Lentinus edodes, and Pleurotus spp.—chromista, yeast and bacteria). The Gram positive bacteria resulted the most sensible and a significant structure-activity relationships was apparent. The isolation and structure determination of bioactive metabolites produced by B. gladioli pv. agaricicola are still in progress but preliminary results indicate their peptide nature. Furthermore, the exopolysaccharide (EPS) from the culture filtrates of B. gladioli pv. agaricicola, as well as the O-chain and lipid A, from the lipopolysaccharide (LPS) of the three bacteria, were isolated and the structures determined.
Inferring the Effects of Vertical Integration from Entry Games: An Analysis of the Generic Pharmaceutical Industry

This paper introduces a novel method for examining the effects of vertical integration. The basic idea is to estimate the parameters of a vertical entry game. By carefully specifying firms'payoff equations and constructing appropriate tests, it is possible to use estimates on rival profiteffects to make inferences about the existence of vertical foreclosure. I estimate the vertical entry model using data from the US generic pharmaceutical industry. The estimates indicatethat vertical integration is unlikely to generate anticompetitive foreclosure effects. On the other hand, significant efficiency effects are found to arise from vertical integration. I use the parameter estimates to simulate a policy that bans vertically integrated entry. The simulation results suggest that such a ban is counterproductive; it is likely to reduce entry into smaller markets.
Total variation-based image inpainting and denoising using a primal-dual active set method

while a median filter was introduced by Noori and Saryazdi (2010). A popular variation model in reconstructing blocky images corrupted with Gaussian noise is the Rudin-Osher-Fatemi (ROF) model (Rudin et al. 1992) where Ω is a simply connected bounded domain in ℝ 2 with Lipschitz continuous boundary ∂Ω, and α > 0 is the regulariza-tion parameter. The observed image is u 0 and BV(Ω) denotes the space of functions of bounded variation. A function u ∊ L 1 (Ω) is said to be of bounded variation if the BV seminorm defined by is finite (see Casas et al. 1999, Giusti et al. 1984 for details). The first integral term in (1) is the fidelity term that recovers essential features of the image. The second term is the total variation (TV) term that penalizes high oscillations associated with noise in the image but allows discontinuities associated with edges. Chan and Shen (2001) proposed a restricted version of the ROF model for inpainting non-texture type images: In (2), E is any fixed closed domain outside the inpainting domain D, and | · | denotes the Euclidean norm. The image domain E ∪ D is usually taken to be a square. Since the TV model (2) is nondifferentiable, Chan and Shen introduced a global smoothing KEYWORDS image inpainting, denoising, total variation, active set method T his paper presents a formulation of an 2-based variational model implementable in simultaneous image inpainting and Gaussian denoising. To solve the optimization problem, an active set method that utilizes generalized derivatives on the regularized L 2 TV-type problem and its dual problem is applied. A numerical study ends the paper.
Fast image restoration using the multi-layer best neighborhood matching approach

This paper presents an accurate and fast image restoration for lost block images via wireless image transmission. In the network transmission of block-coded images, fading in wireless channels and congestion in packet switched networks could cause entire blocks to be lost. Instead of using retransmission query protocols, we reconstruct the lost block on the wavelet domain that considers the relation between the lost block and its neighbor coefficients. Thus, this method could use the transmitted image immediately and increase the transmission rate of the network bandwidth. The algorithm considers both the best neighborhood matching (BNM) and the different frequency contents of the multi-layer on wavelet domain, which is referred as the Multi-Layer Best Neighborhood Matching (MLBNM). The MLBNM is proposed to improve the efficiency of search processing and to reconstruct the different frequency composition separately. This method considers the different veins of the directional composition and the independent directional estimation, so that the veins will not influence each other. The experimental results demonstrate the high restoration quality of the proposed system.
Dynamic Innate Immune Responses of Human Bronchial Epithelial Cells to Severe Acute Respiratory Syndrome-Associated Coronavirus Infection

Human lung epithelial cells are likely among the first targets to encounter invading severe acute respiratory syndrome-associated coronavirus (SARS-CoV). Not only can these cells support the growth of SARS-CoV infection, but they are also capable of secreting inflammatory cytokines to initiate and, eventually, aggravate host innate inflammatory responses, causing detrimental immune-mediated pathology within the lungs. Thus, a comprehensive evaluation of the complex epithelial signaling to SARS-CoV is crucial for paving the way to better understand SARS pathogenesis. Based on microarray-based functional genomics, we report here the global gene response of 2B4 cells, a cloned bronchial epithelial cell line derived from Calu-3 cells. Specifically, we found a temporal and spatial activation of nuclear factor (NF)κB, activator protein (AP)-1, and interferon regulatory factor (IRF)-3/7 in infected 2B4 cells at 12-, 24-, and 48-hrs post infection (p.i.), resulting in the activation of many antiviral genes, including interferon (IFN)-β, -λs, inflammatory mediators, and many IFN-stimulated genes (ISGs). We also showed, for the first time, that IFN-β and IFN-λs were capable of exerting previously unrecognized, non-redundant, and complementary abilities to limit SARS-CoV replication, even though their expression could not be detected in infected 2B4 bronchial epithelial cells until 48 hrs p.i. Collectively, our results highlight the mechanics of the sequential events of antiviral signaling pathway/s triggered by SARS-CoV in bronchial epithelial cells and identify novel cellular targets for future studies, aiming at advancing strategies against SARS.
Extracting salient features for network intrusion detection using machine learning methods

This work presents a data preprocessing and feature selection framework to support data mining and network security experts in minimal feature set selection of intrusion detection data. This process is supported by detailed visualisation and examination of class distributions. Distribution histograms, scatter plots and information gain are presented as supportive feature reduction tools. The feature reduction process applied is based on decision tree pruning and backward elimination. This paper starts with an analysis of the KDD Cup ’99 datasets and their potential for feature reduction. The dataset consists of connection records with 41 features whose relevance for intrusion detection are not clear. All trac is either classied ‘normal’ or into the four attack types denial-of-service, network probe, remote-to-local or user-to-root. Using our custom feature selection process, we show how we can signicantly reduce the number features in the dataset to a few salient features. We conclude by presenting minimal sets with 4{8 salient features for two-class and multi-class categorisation for detecting intrusions, as well as for the detection of individual attack classes; the performance using a static classier compares favourably to the performance using all features available. The suggested process is of general nature and can be applied to any similar dataset.
Sensorless collision detection for safe human-robot collaboration

As there have been many attempts for human-robot collaborations, various solutions to collision detection have been proposed in order to deal with safety issues. However, existing methods for collision detection include the usage of skin sensors or joint torque sensors, and cannot be applied to robots without these sensors such as industrial manipulators. In this study we propose a sensorless collision detection method. The proposed method detects the collision between robots and humans by identifying the external torques applied to the robot. Without using extra sensors, we observed the joint friction model and motor current. We have formulated the friction model for the robot by using the dynamics of the robot and the observer based on the generalized momentum. In addition, formulation of the friction model and the identification scheme did not include any use of extra sensors. The performance of the proposed collision detection method was evaluated using a 7 DOF manipulator. The experimental results show that collision can be reliably detected without any extra sensors for any type of robot arm.
Toward atomic force microscopy and mass spectrometry to visualize and identify lipid rafts in plasmodesmata

Plant cell-to-cell communication is mediated by nanopores called plasmodesmata (PDs) which are complex structures comprising plasma membrane (PM), highly packed endoplasmic reticulum and numerous membrane proteins. Although recent advances on proteomics have led to insights into mechanisms of transport, there is still an inadequate characterization of the lipidic composition of the PM where membrane proteins are inserted. It has been postulated that PDs could be formed by lipid rafts, however no structural evidence has shown to visualize and analyse their lipid components. In this perspective article, we discuss proposed experiments to characterize lipid rafts and proteins in the PDs. By using atomic force microscopy (AFM) and mass spectrometry (MS) of purified PD vesicles it is possible to determine the presence of lipid rafts, specific bound proteins and the lipidomic profile of the PD under physiological conditions and after changing transport permeability. In addition, MS can determine the stoichiometry of intact membrane proteins inserted in lipid rafts. This will give novel insights into the role of membrane proteins and lipid rafts on the PD structure.