Miracle-dz/UniFAR-FTUs huggingface dataset:
‘ Not Destructive – Not Effective ? ’ — SLT Effectiveness

Selective laser trabeculoplasty (SLT) is a safe and effective treatment modality for lowering the intraocular pressure in patients with glaucoma. It achieves its results by selective absorption of energy in the trabecular pigmented cells, sparing adjacent cells and tissues from thermal damage, with minimal morphological tissue alteration following treatment. On the basis of the peer-reviewed medical literature, SLT is efficacious in lowering IOP, as initial treatment or when medical therapy is insufficient in all types of open-angle glaucoma in all races. SLT achieves intraocular pressure reduction similar to that of argon laser trabeculoplasty but without the tissue destruction and side effects. Observed side effects following SLT were almost uniformly transient and minor. We review highlights of recently published studies on the mechanisms and clinical outcome of SLT in order to address frequently raised issues pertinent to SLT in the clinical practice.
How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments

Consistently checking the statistical significance of experimental results is one of the mandatory methodological steps to address the so-called "reproducibility crisis" in deep reinforcement learning. In this tutorial paper, we explain how the number of random seeds relates to the probabilities of statistical errors. For both the t-test and the bootstrap confidence interval test, we recall theoretical guidelines to determine the number of random seeds one should use to provide a statistically significant comparison of the performance of two algorithms. Finally, we discuss the influence of deviations from the assumptions usually made by statistical tests. We show that they can lead to inaccurate evaluations of statistical errors and provide guidelines to counter these negative effects. We make our code available to perform the tests 1 .
Art-attack ! On style transfers with textures , label categories and adversarial examples

In this short paper, we describe an experiment that entailed using style transferred images to target misclassification in the context of a specific popular commercial off-the-shelf (OTS) API. The test images were drawn from the Kaggle ’Dogs and Cats’ dataset and the style image was drawn from the Describable Textures Dataset (DTD). The style transferred images achieved adversarial attack success rates of 97.5 % (195 out of 200). The goal of this paper is not to proclaim a new black-box attack recipe or to berate the commercial API we have used, but to merely highlight the following observations. The first is regarding the generation of a pair of ’close-by’ images using styletransfer that are indistinguishable to the human eye but that elicit very different predictions from a classifier.Secondly, on account of the fact that the ’raw image’ that is adversarially perturbed is not necessarily a naturally occurring image and is a style-transferred image itself, we believe this should necessarily instigate a conversation over what constitutes a true image category/class and admit to skepticism if the incorrect response of the classifier would indeed qualify as a mis-classification. Lastly, irrespective of what emerges from the above point raised, we would like to highlight the potency of using interpolated style transfer as a recipe of generating mutually adversarial pairs that can be used for model regularization as well as generating ’challenging’ co-class images as inputs into training pipelines for ’embedding deepnets’ trained on triplet-loss cost functions.
Luteal phase ovarian stimulation for poor ovarian responders

Objective To compare the clinical outcomes of follicular versus luteal phase ovarian stimulation in women with poor ovarian response (Bologna criteria) undergoing IVF. Methods This retrospective study investigated 446 patients submitted to 507 cycles in three groups. First, the two larger cohorts were examined: 154 patients treated with luteal phase ovarian stimulation (Group Lu); and 231 patients administered follicular phase ovarian stimulation (Group Fo). Then the clinical outcomes of 61 patients submitted to double ovarian stimulation were analyzed. Clinical outcomes included number of retrieved oocytes, fertilization rate, cleavage rate, top-quality embryo rate, clinical pregnancy rate (CPR), and live birth rate (LBR). Results Longer stimulation, higher dosages of HMG, and higher MII oocyte rates were achieved in Group Lu (p<0.001). There were no significant differences in CPR and LBR between the two groups offered frozen-thawed embryo transfer (28.4% vs. 33.0%, p=0.484; 22.9% vs. 25.5%, p=0.666). In the double ovarian stimulation group, the number of oocytes retrieved in the luteal phase stimulation protocol was higher (p=0.035), although luteal phase stimulation yielded a lower rate of MII oocytes (p=0.031). CPR and LBR were not statistically different (13.8% vs. 21.4%, p=0.525; 10.3% vs. 14.3%, p=0.706). Conclusion Luteal phase ovarian stimulation may be a promising protocol to treat women with POR, particularly for patients unable to yield enough viable embryos through follicular phase ovarian stimulation or other protocols.
Rolling Motion Along an Incline: Visual Sensitivity to the Relation Between Acceleration and Slope

People easily intercept a ball rolling down an incline, despite its acceleration varies with the slope in a complex manner. Apparently, however, they are poor at detecting anomalies when asked to judge artificial animations of descending motion. Since the perceptual deficiencies have been reported in studies involving a limited visual context, here we tested the hypothesis that judgments of naturalness of rolling motion are consistent with physics when the visual scene incorporates sufficient cues about environmental reference and metric scale, roughly comparable to those present when intercepting a ball. Participants viewed a sphere rolling down an incline located in the median sagittal plane, presented in 3D wide-field virtual reality. In different experiments, either the slope of the plane or the sphere acceleration were changed in arbitrary combinations, resulting in a kinematics that was either consistent or inconsistent with physics. In Experiment 1 (slope adjustment), participants were asked to modify the slope angle until the resulting motion looked natural for a given ball acceleration. In Experiment 2 (acceleration adjustment), instead, they were asked to modify the acceleration until the motion on a given slope looked natural. No feedback about performance was provided. For both experiments, we found that participants were rather accurate at finding the match between slope angle and ball acceleration congruent with physics, but there was a systematic effect of the initial conditions: accuracy was higher when the participants started the exploration from the combination of slope and acceleration corresponding to the congruent conditions than when they started far away from the congruent conditions. In Experiment 3, participants modified the slope angle based on an adaptive staircase, but the target never coincided with the starting condition. Here we found a generally accurate performance, irrespective of the target slope. We suggest that, provided the visual scene includes sufficient cues about environmental reference and metric scale, joint processing of slope and acceleration may facilitate the detection of natural motion. Perception of rolling motion may rely on the kind of approximate, probabilistic simulations of Newtonian mechanics that have previously been called into play to explain complex inferences in rich visual scenes.
The Moderating Role of Peer Norms in the Associations of Social Withdrawal and Aggression With Peer Victimization

This study examined the moderating role of classroom injunctive norms salience regarding social withdrawal and regarding aggression in the longitudinal association between these behaviors and peer victimization. A total of 1,769 fourth through sixth graders (895 girls, M = 10.25 years, SD = 1.03) from 23 schools (67 classrooms) completed a peer nomination inventory in the fall (T1) and spring (T2) of the same academic year. Participants circled the name of each student who fit the description provided for social withdrawal, aggression, and peer victimization at T1 and T2. The salience of injunctive norms was sex-specific and operationalized by the extent to which children displaying the behavior were socially rewarded or sanctioned by their classmates. Generalized estimation equations (GEE) showed that the association between social withdrawal at T1 and peer victimization at T2 was moderated by injunctive norms. Social withdrawal at T1 was positively associated with peer victimization at T2 in classrooms where injunctive norms for this behavior were salient and unfavorable, as well as in classrooms where injunctive norms for aggression were salient and favorable, albeit for girls only. The association between aggression at T1 and peer victimization at T2 was also moderated by the injunctive norms regarding this behavior. Aggressive children were less likely to be victimized in classrooms where this behavior was rewarded. These results support bullying interventions that target factors related to the larger peer context, including social norms.
Identification of Botnet hidden behind smartphone applications

With increase in facilities available over Internet, world is transforming into digital world. Gaining popularity and availability of cheaper smartphones with features like desktop system, humans are preferring smartphones and its lots of features for regular activities on Internet instead of using desktop/laptop. Most smartphone users download number of applications regularly without thinking and even aware about security risks from applications. Applications may try to access information available on smartphone without user consent. In this paper, service “Spycat” for Android based smartphones is proposed. Spycat once installed on smartphone runs in background and warns user about any suspicious activity carried out on device by any application. It categorizes all applications on device, check for permissions available, prevents application from accessing information beyond vicinity of the application. Success of Spycat depends on updating lists of permissions. This is achieved by maintaining permission details and categorizing various applications as trusted and untrusted. For this Baysian classification and Backpropagation algorithm is used.
Understanding Mild Traumatic Brain Injury and Postconcussion Syndrome

D espite having a label of "mild," mild traumatic brain injury (MTBI) is a major public health problem in the United States, according to the Centers for Disease Control and Prevention (CDC). It is estimated that up to 1.2 million people sustain a MTBI each year the United States. MTBI accounts for more than 1 million (or 1% of) yearly emergency department visits. Most MTBIs occur to persons under the age of 24 or older than age 74. Fifty percent of MTBIs result from motor vehicle crashes, 25% from falls, 15% from assaults, and 10% from sports injuries. Most fall injuries occur in those younger than 5 and older than 75. ' In 2001, the CDC reported the cost of MTBI to be $16.7 billion. Most of this economic cost was the result of lost productivity. These figures do not include the indirect cost of family caregiver expense and those who were treated in the emergency department, released, and then received subsequent care in other hospitals for symptoms related to their injury. A study by Boake and colleagues found that MTBI patients had similar duration of work absences as did general trauma patients. In their study, work absences resulting from MTBI ranged from 1 week to 3 months. Other researchers have reported unemployment rates
Chemomimesis and Molecular Darwinism in Action: From Abiotic Generation of Nucleobases to Nucleosides and RNA

Molecular Darwinian evolution is an intrinsic property of reacting pools of molecules resulting in the adaptation of the system to changing conditions. It has no a priori aim. From the point of view of the origin of life, Darwinian selection behavior, when spontaneously emerging in the ensembles of molecules composing prebiotic pools, initiates subsequent evolution of increasingly complex and innovative chemical information. On the conservation side, it is a posteriori observed that numerous biological processes are based on prebiotically promptly made compounds, as proposed by the concept of Chemomimesis. Molecular Darwinian evolution and Chemomimesis are principles acting in balanced cooperation in the frame of Systems Chemistry. The one-pot synthesis of nucleosides in radical chemistry conditions is possibly a telling example of the operation of these principles. Other indications of similar cases of molecular evolution can be found among biogenic processes.
Content-aware Efficient Video Uploading for Crowdsourced Multi-view Video Streaming

Integration of video streams captured by many mobile cameras at a crowded event into a multi-view video enables viewers to experience the different perspectives of the event. The streaming of such crowdsourced multi-view videos has been popular in many applications such as entertainment, surveillance, social sharing and is potentially applicable to medical, educational and military areas. However, due to the resourceconstrained nature of wireless network and the huge amount of video traffic, simultaneous uploading of video streams from many mobile cameras limits the quality of the video streams. In this paper, we propose a content-aware video uploading scheme for crowdsourced multi-view video streaming. Our work considers correlation-based differential encoding with multiple reference streams by packet overhearing to keep better quality under the reduced video traffic. The proposed scheme consists of two parts: correlation estimation and transmission order determination. First, we exploit the correlation among the mobile cameras based on the content features of the captured videos. Second, we decide the encoding behavior of each camera based on the correlation degrees among the cameras. Based on the encoding behavior, we schedule the transmission order of the cameras that can realize the differential encoding by packet overhearing. Evaluation results show up to 2.5 dB quality improvement with the traffic reduction of up to 30% in a strongly correlated network of mobile cameras.
Awe in Nature Heals: Evidence From Military Veterans, At-Risk Youth, and College Students

The power of nature to both heal and inspire awe has been noted by many great thinkers. However, no study has examined how the impact of nature on well-being and stress-related symptoms is explained by experiences of awe. In the present investigation, we examine this process in studies of extraordinary and everyday nature experiences. In Study 1, awe experienced by military veterans and youth from underserved communities while whitewater rafting, above and beyond all the other positive emotions measured, predicted changes in well-being and stress-related symptoms one week later. In Study 2, the nature experiences that undergraduate students had during their everyday lives led to more awe, which mediated the effect of nature experience on improvements in well-being. We discuss how accounting for people’s emotional experiences during outdoors activities can increase our understanding of how nature impacts people’s well-being.
Multi object detection techniques in video surveillance application

One of the important task in computer vision is to accurately detect the moving objects from dynamic scene. The most popular and repeatedly used technique for object detection is Background subtraction (BS) method. Background modeling is undoubtedly the first step in BS method. For accurate object detection, exact construction of background model is very important. Further steps of video surveillance system such as object recognition, tracking are greatly dependent on quality of detection. In this paper, we have implemented the object detection techniques such as Approximate Median filter(AMF), Gaussian Mixture Model (GMM) and Optical flow method (OF) and compare their results with the help of quantitative analysis. Experimental results gives the performances of implemented algorithms on various video sequences.
The use of an e-learning module on return to work advice for physiotherapists – A prospective cohort study

ABSTRACT Background: Nonspecific low back pain (LBP) can progress to chronic disability and prolonged absence from work. Despite clinical and professional guidelines, physiotherapists often fail to address return to work outcomes. Aims: The aim of this exploratory study was to determine whether an e-learning resource tailored to physiotherapy practice could affect physiotherapists’ attitudes and beliefs regarding return to work advice for their patients. Design: A prospective interventional cohort study (pilot). Methods: Participants were recruited via the Chartered Society of Physiotherapy website. Responses on a clinical vignette, the Health Care Providers’ Pain and Impairment Scale (HC-Pairs), and the Behavioral Constructs Questionnaire (BCQ) were collected online at baseline (Q1) and 2-months post-intervention (Q2). Results: Fifty-four physiotherapists completed Q1 and the response rate for Q2 was 44/54 (81%). Changes in the degree of agreement with guidelines indicated that the intervention made an impact on respondents (kappa 0.345; p = 0.003). HC-Pairs and BCQ results showed a nonstatistically significant trend toward the target behavior. Conclusions: There is a need for interventions to improve adherence with advice for return to work following nonspecific LBP. An e-learning tool for physiotherapists on advising patients regarding return to work has potential to positively affect self-reported clinical behavior.
A study on channel assignment algorithms for multi-channel multi-radio wireless mesh networks

Nowadays, multi-channel multi-radio wireless mesh networks are gaining more popularity as they have enormous applications like last mile broadband Internet connectivity, home networking, commercial and civilian applications. The performance of wireless mesh networks can be improved by the proper assignment of channels to multiple radios of a mesh node. Thus, channel assignment problem has significant importance. This paper presents the literature survey of various algorithms of channel assignment along with the advantages and limitations of each algorithm. Also, the paper gives the directions for future research work of channel assignment algorithms of wireless mesh networks.
An Enhanced Adaptive P&O MPPT for Fast and Efficient Tracking Under Varying Environmental Conditions

This paper proposes an enhanced adaptive perturb and observe (EA-P&O) maximum power point tracking (MPPT) algorithm for the photovoltaic system. The objective is to mitigate the limitations of the conventional P&O namely, the steady-state oscillation, diverged tracking direction, and inability to detect the global peak during partial shading. A smart oscillation detection scheme and a dynamic boundary condition resolve the first two problems, respectively. Meanwhile, an intelligent prediction method is designed to ensure that the global peak is always correctly tracked. Another feature is the open-circuit voltage is determined without using sensors. The proposed idea is verified using MATLAB simulations by imposing stringent dynamic irradiance and partial shading tests. Moreover, an experimental validation is carried out using a buck–boost converter in conjunction with dSpace DS1104 DSP board. The performance of the algorithm is compared with four prominent MPPT techniques: first, the artificial bee colony; second, modified incremental conduction; third, cuckoo search; and fourth, the hybrid ant colony optimization-P&O. The results show that the proposed method tracks the global peak successfully under distinctive patterns of partial shading, when other algorithms fail occasionally. On top of that, it improves the tracking speed by two to three times, while efficiency is maintained over 99%.
ICTV Virus Taxonomy Profile: Papillomaviridae

The Papillomaviridae is a family of small, non-enveloped viruses with double-stranded DNA genomes of 5 748 to 8 607 bp. Their classification is based on pairwise nucleotide sequence identity across the L1 open reading frame. Members of the Papillomaviridae primarily infect mucosal and keratinised epithelia, and have been isolated from fish, reptiles, birds and mammals. Despite a long co-evolutionary history with their hosts, some papillomaviruses are pathogens of their natural host species. This is a summary of the International Committee on Taxonomy of Viruses (ICTV) Report on the taxonomy of the Papillomaviridae, which is available at http://www.ictv. global/report/papillomaviridae.
Assessment of methane emissions from the U.S. oil and gas supply chain

A leaky endeavor Considerable amounts of the greenhouse gas methane leak from the U.S. oil and natural gas supply chain. Alvarez et al. reassessed the magnitude of this leakage and found that in 2015, supply chain emissions were ∼60% higher than the U.S. Environmental Protection Agency inventory estimate. They suggest that this discrepancy exists because current inventory methods miss emissions that occur during abnormal operating conditions. These data, and the methodology used to obtain them, could improve and verify international inventories of greenhouse gases and provide a better understanding of mitigation efforts outlined by the Paris Agreement. Science, this issue p. 186 Methane leakage from the U.S. oil and natural gas supply chain is much greater than previously estimated. Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO2 from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.
Eigenvalue Sensitivity and Eigenvalue Tracing of Power Systems With Inclusion of Time Delays

As time delays of some remote signals cannot be ignored, the power system model must be represented as time-delay differential and algebraic equations. For this case, we can analyze the local dynamical characteristic of the system by calculating the eigenvalues of the related linearized system. In this paper, we present some practical tools to evaluate the impact of the delays on system modes. First, we derive an analytical method for computing the eigenvalue sensitivity. A Newton method for computing the exact eigenvalues of the time-delay system is then proposed, followed by an eigenvalue tracing method to obtain the eigenvalue trajectory when the delay varies. To realize the methods, a general linearized model and the generalized eigenvalue problem formulation are adopted. The proposed methods are applied to analyze the oscillation modes of two power systems with wide-area controllers.