A machine learning driven solution to the problem of perceptual video quality metrics

The advent of high-speed internet connections, advanced video coding algorithms, and consumer-grade computers with high computational capabilities has led videostreaming-over-the-internet to make up the majority of network traffic. This effect has led to a continuously expanding video streaming industry that seeks to offer enhanced quality-of-experience (QoE) to its users at the lowest cost possible. Video streaming services are now able to adapt to the hardware and network restrictions that each user faces and thus provide the best experience possible under those restrictions. The most common way to adapt to network bandwidth restrictions is to offer a video stream at the highest possible visual quality, for the maximum achievable bitrate under the network connection in use. This is achieved by storing various pre-encoded versions of the video content with different bitrate and visual quality settings. Visual quality is measured by means of objective quality metrics, such as the Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Visual Information Fidelity (VIF), and others, which can be easily computed analytically. Nevertheless, it is widely accepted that although these metrics provide an accurate estimate of the statistical quality degradation, they do not reflect the viewer’s perception of visual quality accurately. As a result, the acquisition of user ratings in the form of Mean Opinion Scores (MOS) remains the most accurate depiction of human-perceived video quality, albeit very costly and time consuming, and thus cannot be practically employed by video streaming providers that have hundreds or thousands of videos in their catalogues. A recent very promising approach for addressing this limitation is the use of machine learning techniques in order to train models that represent human video quality perception more accurately. To this end, regression techniques are used in order to map objective quality metrics to human video quality ratings, acquired for a large number of diverse video sequences. Results have been very promising, with approaches like the Video Multimethod Assessment Fusion (VMAF) metric achieving higher correlations to useracquired MOS ratings compared to traditional widely used objective quality metrics

Clasificación de fuentes de tráfico HTC y MTC

[ES] El objetivo de este trabajo es realizar una clasificación de las fuentes de tráfico que aparecen involucradas en los sistemas de comunicaciones actuales. Se realizará la clasificación teniendo en cuenta 2 grandes categorías de fuentes de tráfico: HTC (Human Type Communications) y MTC (Machine Type Communications). A partir de estas 2 categorías iniciales se deberán ir agrupando las fuentes en función de sus parámetros de tráfico generando una clasificación de fuentes.Mhanna, MRH. (2015). Clasificación de fuentes de tráfico HTC y MTC. http://hdl.handle.net/10251/56977.TFG

ECG classification using an optimal temporal convolutional network for remote health monitoring

Increased life expectancy in most countries is a result of continuous improvements at all levels, starting from medicine and public health services, environmental and personal hygiene to the use of the most advanced technologies by healthcare providers. Despite these significant improvements, especially at the technological level in the last few decades, the overall access to healthcare services and medical facilities worldwide is not equally distributed. Indeed, the end beneficiary of these most advanced healthcare services and technologies on a daily basis are mostly residents of big cities, whereas the residents of rural areas, even in developed countries, have major difficulties accessing even basic medical services. This may lead to huge deficiencies in timely medical advice and assistance and may even cause death in some cases. Remote healthcare is considered a serious candidate for facilitating access to health services for all; thus, by using the most advanced technologies, providing at the same time high quality diagnosis and ease of implementation and use. ECG analysis and related cardiac diagnosis techniques are the basic healthcare methods providing rapid insights in potential health issues through simple visualization and interpretation by clinicians or by automatic detection of potential cardiac anomalies. In this paper, we propose a novel machine learning (ML) architecture for the ECG classification regarding five heart diseases based on temporal convolution networks (TCN). The proposed design, which implements a dilated causal one-dimensional convolution on the input heartbeat signals, seems to be outperforming all existing ML methods with an accuracy of 96.12% and an F1 score of 84.13%, using a reduced number of parameters (10.2 K). Such results make the proposed TCN architecture a good candidate for low power consumption hardware platforms, and thus its potential use in low cost embedded devices for remote health monitoring

Machine learning-based affect detection within the context of human-horse interaction

This chapter focuses on the use of machine learning techniques within the field of affective computing, and more specifically for the task of emotion recognition within the context of human-horse interaction. Affective computing focuses on the detection and interpretation of human emotion, an application that could significantly benefit quantitative studies in the field of animal assisted therapy. The chapter offers a thorough description, an experimental design, and experimental results on the use of physiological signals, such as electroencephalography (EEG), electrocardiography (ECG), and electromyography (EMG) signals, for the creation and evaluation of machine learning models for the prediction of the emotional state of an individual during interaction with horses

STEPS-T Program Improves Endovascular Treatment Outcomes of Acute Ischemic Stroke; A 6-Year Study

Background: Early endovascular recanalization of occluded vessels in acute ischemic stroke (AIS) is a major contributor to good clinical outcome. We report the analysis of all AIS patients throughout a 6-year experience following the deployment of a quality initiative aiming at improving care, speed and maintaining quality for AIS treatment. Methods: Using a prospectively collected endovascular database at a comprehensive stroke center between 2012 and 2017, workflow/outcomes were recorded. There were no exclusion criteria. During the first year, a quality program employing “digital-object” technology, staff education, and workflow improvement was implemented to reduce time-to-treatment. Using electronic recording, workflow times were collected for onset (TO), CT (TCT), door (TD), angiography-suite (TA), groin puncture (TG), DSA (TDSA), and recanalization (TR). Recanalization time (TG-TR) and workflow intervals were compared at Year 1 and 6. Results: Analysis of 382 patients (aged 71.3 ± 12.9) undergoing mechanical thrombectomy for AIS (206 male and 176 female) was performed. Recanalization time was significantly reduced from 82min in 2012 to 34min by 2017 (IQR 52–117min and 23–49min), a 59% reduction (P \u3c 0.001). Further, consistent year-over-year reductions in setup time (TA-TG) (44% improvement) and TCT to TA times were observed. During the same period, clinical outcome significantly improved year-over-year as measured with the modified Rankin Scale 0–2 (33, 37, 38, 41, 53, and 58%). Conclusions: Significant improvements were observed following the deployment of a quality initiative enabling iterative evidence-based process improvements, thereby sustaining significant reductions in time-to-treat and improved clinical outcomes for AIS patients

Initial Experience With the Next-Generation Resolute Onyx Zotarolimus-Eluting Stent in Symptomatic Intracranial Atherosclerotic Disease

Background and Purpose: Intracranial atherosclerotic disease (ICAD) is a common cause of stroke worldwide. Although there are different endovascular options for the treatment of symptomatic ICAD (sICAD), it is still controversial. Herein, we aim to study the safety and efficacy of a new generation of drug-eluting balloon-mounted stent (DES); Resolute (R) onyx DES in the treatment of sICAD. Methods:A prospectively maintained neuroendovascular procedures database in a high-volume comprehensive stroke center was reviewed from October 2019 through January 2020. Patients were included if they had sICAD (≥70% stenosis), failed medical management, and underwent intracranial stenting with R-onyx DES. Technical success was defined as the ability to deploy the device at the desired location and achievement of Results: A total of 18 consecutive patients (mean age, 66.6 years; 44.4% were females and 94.4% were Hispanic) were eligible for the analysis. Indication for treatment was recurrent strokes in 13 and recurrent transient ischemic attack (TIA) in 5. A total of 22 symptomatic lesions with a mean baseline stenosis percent (84.9 ± 9.6) were treated using 23 R-onyx DES in 19 procedures. All procedures were done under general anesthesia with 100% technical success, and no reported periprocedural strokes or death. Among 13 patients who had clinical follow-up, 1 (7.7%) patient had TIA. There were no reported ischemic or hemorrhagic strokes. Angiographic follow-up for 9 (50%) patients showed no in-stent restenosis. Conclusion: The use of R-onyx DES in the treatment of sICAD is safe with high technical success rates. Large prospective multicenter trials with long-term follow-up are warranted

There is no difference in safety and efficacy with Tirofiban or Eptifibatide for patients undergoing treatment of large vessel occlusion and underlying intracranial atherosclerosis

Background Glycoprotein IIb/IIIa inhibitor use in acute ischemic stroke (AIS) during mechanical thrombectomy (MT) and acute stenting and angioplasty is a topic consistently debated due to concerns over safety and efficacy. Tirofiban is a glycoprotein IIb/IIIa used throughout the world now more commonly used during MT. We report the analysis of all AIS patients treated with Eptifibatide + MT vs. Tirofiban + MT. Methods Using a prospectively collected endovascular database at a CSC between 2013 and 2019, workflow, and outcomes were recorded. Patients are given Tirofiban, and patients given Eptifibatide were analyzed to obtain baseline demographics, modified Ranking Scale (mRS) at discharge, and 90 days follow up, pre and post thrombolysis in cerebral infarction (TICI), mortality rate, and hemorrhage rates. Results A total of 571 MT patients were treated: of those, 89 patients (average age 69.25 ± 14.21, 25.84% female) with underlying intracranial atherosclerosis were treated with a GpIIb/IIIa inhibitor. Analysis of 40.45% (36/89) patients treated with Tirofiban + MT and 59.55% (53/89) patients with Eptifibatide + MT was performed. There was no statistically significant difference in NIHSS upon admission (p = .441). Four patients (11.11%) in the Tirofiban + MT cohort had symptomatic hemorrhage versus four patients (7.55%) in the Eptifibatide + MT cohort (p = .564). There was no significant difference in mortality (p = .573) or final recanalization (p = .678) between the two cohorts. Conclusion Tirofiban use in MT does not increase the risk of symptomatic hemorrhages or mortality compared to Eptifibatide use in MT with acute stenting. Large prospective studies are warranted to confirm the safety/efficacy of Tirofiban in acute ischemic stroke patients treated with mechanical thrombectomy and acute stenting

Repurposing Ivermectin for COVID-19: Molecular Aspects and Therapeutic Possibilities

As of January 2021, SARS-CoV-2 has killed over 2 million individuals across the world. As such, there is an urgent need for vaccines and therapeutics to reduce the burden of COVID-19. Several vaccines, including mRNA, vector-based vaccines, and inactivated vaccines, have been approved for emergency use in various countries. However, the slow roll-out of vaccines and insufficient global supply remains a challenge to turn the tide of the pandemic. Moreover, vaccines are important tools for preventing the disease but therapeutic tools to treat patients are also needed. As such, since the beginning of the pandemic, repurposed FDA-approved drugs have been sought as potential therapeutic options for COVID-19 due to their known safety profiles and potential anti-viral effects. One of these drugs is ivermectin (IVM), an antiparasitic drug created in the 1970s. IVM later exerted antiviral activity against various viruses including SARS-CoV-2. In this review, we delineate the story of how this antiparasitic drug was eventually identified as a potential treatment option for COVID-19. We review SARS-CoV-2 lifecycle, the role of the nucleocapsid protein, the turning points in past research that provided initial 'hints' for IVM's antiviral activity and its molecular mechanism of action- and finally, we culminate with the current clinical findings

Molecular Screening of <i>VAX1</i> Gene Polymorphisms Uncovered the Genetic Heterogeneity of Non-Syndromic Orofacial Cleft in Saudi Arabian Patients

Objective: Nonsyndromic orofacial cleft (NSOFC) including cleft lip with or without cleft palate (CL±P) and cleft palate (CP) are multifactorial developmental disorders with both genetic and environmental etiological factors. In this study we investigated the association between CL±P and CP, and two polymorphisms previously determined using genome-wide association studies, as well as the association between consanguinity and CL±P and CP. Methods: DNA was extracted from saliva specimens from 171 triads consisting of affected individuals and their parents, as well as 189 control triads (matched for age, gender, and location) that were recruited from 11 referral hospitals in Saudi Arabia. Two polymorphisms, rs4752028 and rs7078160, located in the VAX1 gene were genotyped using real-time polymerase chain reaction. A transmission disequilibrium test was carried out using the Family-Based Association Test and PLINK (genetic tool-set) to measure the parent-of-origin effect. Results: Significant differences were found between affected individuals and the control group. In the case of the rs4752028 risk allele in cleft, the phenotypes were: CL±P (fathers: odds ratio [OR] 2.16 [95% CI 1.38–3.4]; mothers: OR 2.39 [95% CI 1.53–3.71]; and infants: OR 2.77 [95% CI 1.77–4.34]) and CP (fathers: OR 2.24 [95% CI 1.15–4.36] and infants: OR 2.43 [95% CI 1.25–4.7]). For CL±P and the rs7078160 risk allele, the phenotypes were: (fathers: OR 1.7 [95% CI 1.05–2.86]; mothers: OR 2.43 [95% CI 1.49–3.97]; and infants: OR 2.34 [95% CI 1.44–3.81]). In terms of consanguinity, we found significant association between consanguinity and the rs4752028 polymorphism minor allele among CL±P compared with controls (p = 0.001). Conclusion: This is the first study to find a relationship between these two loci on 10q25 (rs4752028 and rs7078160) and NSOFC in a population with high levels of consanguinity