Miracle-dz/UniFAR-FTUs huggingface dataset:
Iris Image Normalization Method to Pupil Detection with Intensity Transformation

Iris image taken by infrared camera is often applied to security system, and it is called an iris recognation system. On the iris identification system, iris detection is a crucial factor to determine the iris localization. So, if the pupil detection fallacy occurs it can be said that the iris localization is wrong. Every iris image from the acquisition of infrared camera has a different variation of contrast, illumination, and noise so the image normalization stage is need to be done. This research aims to propose the normalization method to detect pupil by changing the image intensity to the new intensity so that the image contrast can be stretched. Therefore, the pupil area is dark and other area is bright. This normalization also aims to maximize the image illumination so that the contrast between dark and bright on the image after contrast stretching can be seen clearer. The method used to this normalization are contrast stretching and gamma which the value gained from the maximize limit of contrast stretching. A very irritating image noise in the pupil detection process is reflection which comes from either inside or outside the pupil area. This noise can be deleted by the closing morphology operation. Then, the result of normalization image is become as an input image to pupil detection with Circular Hough Transform. The result of this experiment from 150 dataset images taken randomly from Biometric Ideal Test 4.0 version using the proposing method shows that an optimal pupil detection accuracy is 99,33%. Therefore, the pupil detection with the proposed method is suitable to be applied to iris recognition system.
Left DLPFC rTMS Reduces the Development of Long-Term Muscle Pain.

The left dorsolateral prefrontal cortex (DLPFC) is involved in the experience and modulation of pain, and may be an important node linking pain and cognition. Repetitive transcranial magnetic stimulation (rTMS) to the left DLPFC can reduce chronic and experimental pain. However, whether left DLPFC rTMS can influence the development of chronic pain is unknown. Using repeated intramuscular injection of nerve growth factor (NGF) to induce the development of sustained muscle pain (lasting weeks), thirty healthy individuals were randomized to receive 5 consecutive daily treatments of active or sham left DLPFC rTMS, starting before the first NGF injection on day 0. Muscle soreness and pain severity were collected daily for 14 days and disability on every alternate day. Before the first and one day after the last rTMS session, anxiety, depression, affect, pain catastrophizing and cognitive performance on the attention network test were assessed. Left DLPFC rTMS treatment compared to sham was associated with reduced muscle soreness, pain intensity, and painful area (p<0.05), and a similar trend was observed for disability. These effects were most evident during the days rTMS was applied lasting up to three days following intervention. Depression, anxiety, pain catastrophizing, and affect were unchanged. There was a trend toward improved cognitive function with rTMS compared to sham (p=0.057). These data indicate that repeated left DLPFC rTMS reduces the pain severity in a model of prolonged muscle pain. The findings may have implications for the development of sustained pain in clinical populations.
Hypoglycemia and Glucagon Utilization in Insulin-Treated Diabetic Patients

Abstract Background First choice of therapy for severe hypoglycemia outside hospital environment is glucagon injection, an undertaught and underused remedy. Aim of this study was to investigate knowledge about glucagon therapy, possession rate and usage rate in insulin-treated diabetic patients, with special emphasis on history of hypoglycemia and severe hypoglycemia episodes. Methods In this cross-sectional study, 300 insulin-treated diabetic patients (146 males and 154 females, mean age 61.1±16.4 years) were recruited from comprehensive Diabetes Center in Croatia. Specialized self-administered, 13-item questionnaire regarding glucagon therapy and history of hypoglycemia was obtained from each patient, as well as data collected from medical history documentation. Results Experience of hypoglycemic episode was reported by 233 (77.7%), and severe hypoglycemia by 73 (24.3%) patients. Participants with experience of hypoglycemia have significantly longer diabetes duration (17.2±11.2 vs. 11.9±8.5 years, P<0.001) and lower BMI values (26.38±3.97 vs. 31.11±7.17 kg/m2, P<0.001). Knowledge about glucagon therapy had 55.3% patients, 44.7% obtained it from the pharmacy, while glucagon was used in 35.6% cases of severe hypoglycemia. Glucagon knowledge was better in patients that attended at least one diabetes lecture (P=0.038), while educational level showed no statistical significance (P=0.286). Main significant positive predictor of glucagon knowledge was history of severe hypoglycemia (OR 4.71, 95% CI 1.38 – 16.02, P=0.013). Conclusions Glucagon therapy was underused in treating severe hypoglycemia. It is highly important to emphasize value of quality education as one of the fundamentals of good diabetes management.
Effects of N-acetylcysteine supplementation on cellular damage and oxidative stress indicators in volleyball athletes

The purpose of this study was to evaluate the effects of N-acetylcysteine (NAC) supplementation on cellular damage and oxidative stress indicators in volleyball athletes. Twenty male volleyball athletes at national level performed a physical training session and were divided into 2 groups, which for 7 days took the placebo substance or NAC. After 7 days the athletes repeated the same training session. In both sessions, blood samples were collected 30 min before and immediately after the training session to measure cellular damage and oxidative stress markers. The main results show that, although higher concentrations of glutathione peroxidase and superoxide dismutase were observed in post-session 1 than those in postsession 2, the other markers showed an increase in antioxidant action after supplementation of NAC, once the effect of experimental conditions (P=0.030) were observed in: time effect (P<0.001) and interaction (P=0.019) for total glutathione; time effect (P<0.001) and interaction (P<0.001) for reduced glutathione; and time effect (P<0.001) for ferric-reducing antioxidant potential. The oxidant action indicated by the protein carbonyl was higher in the placebo group than in the NAC group (P=0.028), but a time effect (P<0.001) for the thiobarbituric acid reactive substances showed lower values in presession 1 than in presession 2. For the cellular damage markers, antagonistic results between markers were found. Based in the results, the supplementation of NAC during a short period was effective in reducing oxidant action and increasing antioxidant action. However, conclusive alterations in the responses of the cellular damage markers were not obtained.
Evaluating Navigation Techniques for 3D Graph Visualizations in Virtual Reality

Research into how virtual reality (VR) can be a beneficial technology for new and emerging large, complex data visualizations for data scientists is ongoing. In this paper, we evaluate three-dimensional VR navigation technique for data visualizations and test their effectiveness with a large graph visualization. We evaluate two prominent navigation techniques employed in VR (Teleportation and One-Handed Flying) against two less common methods (Two-Handed Flying and Worlds In Miniature) and evaluate their performance and effectiveness through a series of tasks. We found Steering Patterns (One-Handed Flying and Two-Handed Flying) to be faster and preferred by participants for completing searching tasks in comparision to Teleportation. Worlds-In-Miniature was the least physically demanding of the navigations, and was preferred by participants for tasks that required an overview of the graph such as triangle counting.
No-Reference Image Quality Assessment Using Orthogonal Color Planes Patterns

This paper proposes a new general-purpose no-reference image quality assessment (NR-IQA) method based on color texture analysis. Specifically, the proposed method uses the statistics of the orthogonal color planes pattern (OCPP) descriptor to characterize image quality. The OCPP descriptor, proposed in this paper, is an extension of the local binary pattern operator that incorporates color information. To make NR-IQA methods more generic, that is, more sensitivity to different types of degradation (e.g., color and contrast degradation), it is important to take into consideration the color information. In the proposed NR-IQA method, we use the statistics of the OCPP descriptor as an input vector to a regression algorithm, which models the nonlinear relationship between the OCPP statistics and the subjective opinion scores. Experimental results show that proposed IQA method is quite efficient when compared to popular state-of-the-art NR-IQA methods.
Cooperativity in proton sensing by PIP aquaporins

One of the most intriguing properties of plasma membrane intrinsic protein (PIP) aquaporins (AQPs) is their ability to modulate water transport by sensing different levels of intracellular pH through the assembly of homo‐ and heterotetrameric molecular species in the plasma membrane. In this work, using a phenomenological modeling approach, we demonstrate that cooperativity in PIP biological response cannot be directly attributed to a cooperative proton binding, as it is usually considered, since it could also be the consequence of a cooperative conformation transition between open and closed states of the channel. Moreover, our results show that, when mixed populations of homo‐ and heterotetrameric PIP channels are coexpressed in the plasma membrane of the same cell, the observed decrease in the degree of positive cooperativity would result from the simultaneous presence of molecular species with different levels of proton sensing. Indeed, the random mixing between different PIP paralogues as subunits in a single tetramer, plus the possibility of mixed populations of homo‐ and heterotetrameric PIP channels widen the spectrum of cooperative responses of a cell membrane. Our approach offers a deep understanding of cooperative transport of AQP channels, as members of a multiprotein family where the relevant proton binding sites of each member have not been clearly elucidated yet.
Extended duration vancomycin in recurrent Clostridium difficile infection: a systematic review

Clostridium difficile infections have a high recurrence rate following acute treatment. Extended duration vancomycin (EDV) is a mainstay for the treatment of recurrent Clostridium difficile infections (rCDI). Clinical disease guidelines recommend a variety of different vancomycin treatment regimens though based on weak, low-quality evidence. Patients typically receive an initial vancomycin treatment course of 7–14 days for the acute infection, followed by an extended duration vancomycin course. Multiple publications on the utility of EDV regimens have been published but few include reported effectiveness outcomes associated with a prescribed treatment regimen. The purpose of this review is to evaluate the safety and efficacy data on extended duration vancomycin regimens used in recurrent clostridium treatment. Five articles, three case series and two randomized open-label clinical trials, were identified which included both elements. Outcomes were evaluable in 174 patients, 31 from randomized trials, with prior average recurrent episodes ranging from 3 to 4. Vancomycin dose ranged from 3500 to >6800 mg with therapy durations extending from 21 days to over 60 days. Follow-up duration ranged from 10 weeks to 12 months. Case series reported success rates for EDV in rCDI from 61% to 100%, while randomized trials found lower success rates from 26% to 58%. Taper and pulse regimens reported superior outcomes compared to pulse-only regimens, 58–100% versus 26–81%, respectively. Comparative EDV data is limited. Current available data supports an EDV regimen which includes both a daily dosing taper followed by an every 48 or 72 h pulse.
Scaling Optical Soliton Dynamics Over Twelve Orders of Magnitude: from One Watt Picosecond Pulses to Terawatt-Scale Sub-Femtosecond Pulses

Soliton dynamics can be scaled from the 1 W level in conventional fibres, to terrawatt peak powers in simple hollow capillaries. We model sub-femtosecond pulse self-compression, and experimentally demonstrate high-brightness multiple-$\mu J$-scale ultraviolet (115–330 nm) pulse generation.
Prominin‐1 (CD133) modulates the architecture and dynamics of microvilli

Prominin‐1 is a cell surface biomarker that allows the identification of stem and cancer stem cells from different organs. It is also expressed in several differentiated epithelial and non‐epithelial cells. Irrespective of the cell type, prominin‐1 is associated with plasma membrane protrusions. Here, we investigate its impact on the architecture of membrane protrusions using microvilli of Madin‐Darby canine kidney cells as the main model. Our high‐resolution analysis revealed that upon the overexpression of prominin‐1 the number of microvilli and clusters of them increased. Microvilli with branched and/or knob‐like morphologies were observed and stimulated by mutations in the ganglioside‐binding site of prominin‐1. The altered phenotypes were caused by the interaction of prominin‐1 with phosphoinositide 3‐kinase and Arp2/3 complex. Mutation of tyrosine 828 of prominin‐1 impaired its phosphorylation and thereby inhibited the aforementioned interactions abolishing altered microvilli. This suggests that the interplay of prominin‐1‐ganglioside membrane complexes, phosphoinositide 3‐kinase and cytoskeleton components regulates microvillar architecture. Lastly, the expression of prominin‐1 and its mutants modified the structure of filopodia emerging from fibroblast‐like cells and silencing human prominin‐1 in primary hematopoietic stem cells resulted in the loss of uropod‐associated microvilli. Altogether, these findings strengthen the role of prominin‐1 as an organizer of cellular protrusions.
Target Grasping and Obstacle Avoidance Motion Planning of Humanoid Robot

Aiming at the problem of robot motion planning under the environment of obstacles, this paper studies the obstacle avoidance planning method of robot arm under the ROS platform (Robot Operating System). Based on the service robot developed by the team, the robot URDF (Unified Robot Description Format) file is exported from the 3-D SolidWorks model using the SW2URDF plugin, and the configuration and launch files needed for robot arm motion planning are created by MoveIt! Setup Assistant. By using relevant APIs provided by MoveIt! and invoking random sampling based algorithm RRT we completed the obstacle avoidance planning, object grasping and placement tasks in 3-D real-time simulation environment Rviz (ROS visualization), and also derived the position and velocity curves of each joint of the robot arm. Finally, obstacle avoidance planning, grasping and placing experiments were carried out on the robot, the arm successfully grasped the object and placed it on the designated location without collision. The results show that the use of ROS platform for obstacle avoidance planning is convenient and intuitive, and it is instructive to the application research of robot.
A text model - Use your favourite M2M for M2T

Models provide a disciplined representation of information. Model-to-Model (M2M) transformations convert between model structures. When a more readable representation is required, Model-to-Text (M2T) transformations convert a model structure to a concatenation of character sequences. We ignore the obvious conversion di(cid:27)erences and demonstrate that an unmodi(cid:28)ed M2M tool can be used for M2T. We achieve this with a standard Text model that post-processes the M2M model output to yield formatted text.
Control Performance Aware Cooperative Transmission in Multiloop Wireless Control Systems for Industrial IoT Applications

The wide application of Internet of Things (IoT) in industrial automation encourages the emergence of a new paradigm of industrial IoT systems, wireless control system (WCS), where the system and/or control information is delivered over wireless channels. In practical systems, WCSs would consist of multiple control-loops in general, the resource competition among which would seriously increase mutual interferences and transmission collisions, making it is difficult to provide the required transmission reliability for the control strategy. To address this issue, we design the control strategy together with the hybrid cooperative transmission scheme for multiloop WCSs in a proactive way. We first define the overall system cost function to explore the impacts of standard linear quadratic regulator control cost and wireless transmission reliability on the control performance. In order to further minimize the overall system cost while guaranteeing the control stability, we then propose a control performance aware cooperative transmission scheme, which is formulated as a constrained optimization problem. Decomposition method and heuristic algorithms are designed based on the feature of network structure to solve the formulated mixed integer nonlinear programming problem efficiently. Finally, simulation results demonstrate that by using the proposed strategy, the overall system cost is significantly reduced, decreasing by 78% and 82% compared to the cases without considerations of system dynamics and without cooperative transmission, respectively.
Propensity Score Matching Using Support Vector Machine in Case of Type 2 Diabetes Mellitus (DM)

Randomization in the treatment and control group was not appropriate for non-experimental studies because it will produced bias estimation of treatment effects. In addition to randomization, the presence of confounding variables will also produce bias estimation of treatment effect. This bias estimation of treatment effect can be handled using Propensity Score (PS) method. One of the methods that have been developed from the propensity score is Propensity Score Matching (PSM). In this study, the propensity score is estimated using Support Vector Machine (SVM). Confounding variables that used in this study is exercise activities. The purpose of this study is to apply the PSM using SVM method and calculate the accuracy and Percent Bias Reduction (PBR) on type 2 Diabetes mellitus (DM) disease complications case. The data used in this study is type 2 Diabetes Mellitus (DM) patients data treated at Pasuruan regional public hospital on March 2017. The results of PSM-SVM analysis shows that there are 40 of 96 patients with type 2 DM who have enough exercise activities paired with patients who have less exercise activities. Average Treatment of Treated (ATT) estimation result shows that exercise activity variables (Z) has significant effect on disease complication variables (Y). The accuracy of the PSM-SVM method is 70.00% and 16.65% of the bias can be reduced.
Research on Passive Stride Assist Based on the Metabolism of Hip Muscles

With the increasing prevalence of lower limb dyskinesia, it is urgent to study exoskeleton devices that can help patients walk normally. Combined with the passive exoskeleton which is rarely studied at present, aiming at the difficulty of walking in the patients with lower limb dyskinesia, this paper makes a simulation study on the metabolism of human muscles at this stage. Firstly, we analyzed the biomechanical characteristics and metabolism of human body during normal walking with a human motion simulation software, OpenSim, and determined the position and stage of the assist, and added the passive exoskeleton equivalent model to the human body model. Then we compared the metabolism of human body with different passive assist stiffness and determined a stiffness which can reduce the body stride metabolism by 18%. Finally, we analyzed the changes of the force of related muscles with and without assist, and optimized the assist stage. After simulation analysis, the loading of passive exoskeleton can reduce the metabolism of human body by 19.47%.
SocialOcean: Visual Analysis and Characterization of Social Media Bubbles

Social media allows citizens, corporations, and authorities to create, post, and exchange information. The study of its dynamics will enable analysts to understand user activities and social group characteristics such as connectedness, geospatial distribution, and temporal behavior. In this context, social media bubbles can be defined as social groups that exhibit certain biases in social media. These biases strongly depend on the dimensions selected in the analysis, for example, topic affinity, credibility, sentiment, and geographic distribution. In this paper, we present SocialOcean, a visual analytics system that allows for the investigation of social media bubbles. There exists a large body of research in social sciences which identifies important dimensions of social media bubbles (SMBs). While such dimensions have been studied separately, and also some of them in combination, it is still an open question which dimensions play the most important role in defining SMBs. Since the concept of SMBs is fairly recent, there are many unknowns regarding their characterization. We investigate the thematic and spatiotemporal characteristics of SMBs and present a visual analytics system to address questions such as: What are the most important dimensions that characterize SMBs? and How SMBs embody in the presence of specific events that resonate with them? We illustrate our approach using three different real scenarios related to the single event of Boston Marathon Bombing, and political news about Global Warming. We perform an expert evaluation, analyze the experts' feedback, and present the lessons learned.
Uniform Classifier for Biometric Ear and Retina Authentication Using Smartphone Application

As biometric systems provide more reliable, efficient and secure means of identity verification, it gains its place as a most important system. Implementing ear biometrics using smartphone application development will justify the best suitable measure for authentication. The retina images are robust non-intrusive functional biometric. This paper proposes an authentication system which uses uniform feature extraction, Histogram of Gradient (HoG) and uniform classifier, Support Vector Machine (SVM) for two physiological biometrics. The best fitting kernel for SVM classification is achieved for radial basis function. The accuracy with uniform classier is 94% for ear biometrics and 93% considering retina images.