5G-QoE:QoE Modelling for Ultra-HD Video Streaming in 5G Networks

Traffic on future fifth-generation (5G) mobile networks is predicted to be dominated by challenging video applications such as mobile broadcasting, remote surgery and augmented reality, demanding real-time, and ultra-high quality delivery. Two of the main expectations of 5G networks are that they will be able to handle ultra-high-definition (UHD) video streaming and that they will deliver services that meet the requirements of the end user's perceived quality by adopting quality of experience (QoE) aware network management approaches. This paper proposes a 5G-QoE framework to address the QoE modeling for UHD video flows in 5G networks. Particularly, it focuses on providing a QoE prediction model that is both sufficiently accurate and of low enough complexity to be employed as a continuous real-time indicator of the 'health' of video application flows at the scale required in future 5G networks. The model has been developed and implemented as part of the EU 5G PPP SELFNET autonomic management framework, where it provides a primary indicator of the likely perceptual quality of UHD video application flows traversing a realistic multi-tenanted 5G mobile edge network testbed. The proposed 5G-QoE framework has been implemented in the 5G testbed, and the high accuracy of QoE prediction has been validated through comparing the predicted QoE values with not only subjective testing results but also empirical measurements in the testbed. As such, 5G-QoE would enable a holistic video flow self-optimisation system employing the cutting-edge Scalable H.265 video encoding to transmit UHD video applications in a QoE-aware manner

Reversal of SARS-CoV2-Induced Hypoxia by Nebulized Sodium Ibuprofenate in a Compassionate Use Program

Introduction: Sodium ibuprofenate in hypertonic saline (NaIHS) administered directly to the lungs by nebulization and inhalation has antibacterial and anti-inflammatory effects, with the potential to deliver these benefits to hypoxic patients. We describe a compassionate use program that offered this therapy to hospitalized COVID-19 patients. Methods: NaIHS (50 mg ibuprofen, tid) was provided in addition to standard of care (SOC) to hospitalized COVID-19 patients until oxygen saturation levels of > 94% were achieved on ambient air. Patients wore a containment hood to diminish aerosolization. Outcome data from participating patients treated at multiple hospitals in Argentina between April 4 and October 31, 2020, are summarized. Results were compared with a retrospective contemporaneous control (CC) group of hospitalized COVID-19 patients with SOC alone during the same time frame from a subset of participating hospitals from Córdoba and Buenos Aires. Results: The evolution of 383 patients treated with SOC + NaIHS [56 on mechanical ventilation (MV) at baseline] and 195 CC (21 on MV at baseline) are summarized. At baseline, NaIHS-treated patients had basal oxygen saturation of 90.7 ± 0.2% (74.3% were on supplemental oxygen at baseline) and a basal respiratory rate of 22.7 ± 0.3 breath/min. In the CC group, basal oxygen saturation was 92.6 ± 0.4% (52.1% were on oxygen supplementation at baseline) and respiratory rate was 19.3 ± 0.3 breath/min. Despite greater pulmonary compromise at baseline in the NaIHS-treated group, the length of treatment (LOT) was 9.1 ± 0.2 gs with an average length of stay (ALOS) of 11.5 ± 0.3 days, in comparison with an ALOS of 13.3 ± 0.9 days in the CC group. In patients on MV who received NaIHS, the ALOS was lower than in the CC group. In both NaIHS-treated groups, a rapid reversal of deterioration in oxygenation and NEWS2 scores was observed acutely after initiation of NaIHS therapy. No serious adverse events were considered related to ibuprofen therapy. Mortality was lower in both NaIHS groups compared with CC groups. Conclusions: Treatment of COVID-19 pneumonitis with inhalational nebulized NaIHS was associated with rapid improvement in hypoxia and vital signs, with no serious adverse events attributed to therapy. Nebulized NaIHS s worthy of further study in randomized, placebo-controlled trials (ClinicalTrials.gov: NCT04382768).Fil: Salva, Oscar. Clínica Independencia; ArgentinaFil: Doreski, Pablo A.. Fundación Respirar; ArgentinaFil: Giler, Celia S.. Clínica Independencia; ArgentinaFil: Quinodoz, Dario C.. Sanatorio de la Cañada; ArgentinaFil: Guzmán, Lucia G.. Sanatorio de la Cañada; ArgentinaFil: Muñoz, Sonia Edith. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaFil: Carrillo, Mariana Norma del Valle. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaFil: Porta, Daniela Josefina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; ArgentinaFil: Ambasch, Germán. Sanatorio Privado Mayo; ArgentinaFil: Coscia, Esteban. Sanatorio Privado Mayo; ArgentinaFil: Tambini Diaz, Jorge L.. Sanatorio Privado Mayo; ArgentinaFil: Bueno, Germán D.. Sanatorio Privado Mayo; ArgentinaFil: Fandi, Jorge O.. Clínica Independencia; ArgentinaFil: Maldonado, Miriam A.. Sanatorio San Roque; ArgentinaFil: Peña Chiappero, Leandro E.. Sanatori San Roque; ArgentinaFil: Fournier, Fernando. Clínica Francesa; ArgentinaFil: Pérez, Hernán A.. Sanatorio Alive; Argentina. University of Maryland; Estados UnidosFil: Quiroga, Mauro A.. Instituto Modelo de Cardiología; ArgentinaFil: Sala Mercado, Javier Agustin. Instituto Modelo de Cardiología; ArgentinaFil: Martínez Picco, Carlos. Clínica del Sol; ArgentinaFil: Beltrán, Marcelo Alejandro. Hospital Dr. Alberto Duhau; ArgentinaFil: Castillo Argañarás, Luis Fernando. Hospital Dr. Alberto Duhau; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ríos, Nicolás Martínez. Quimica Luar Srl; ArgentinaFil: Kalayan, Galia I.. Provincia de Córdoba. Ministerio de Ciencia y Técnica. Centro de Excelencia en Productos y Procesos de Córdoba; ArgentinaFil: Beltramo, Dante Miguel. Provincia de Córdoba. Ministerio de Ciencia y Técnica. Centro de Excelencia en Productos y Procesos de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Garcia, Nestor Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Ciencias de la Salud. Universidad Nacional de Córdoba. Instituto de Investigaciones en Ciencias de la Salud; Argentina. Provincia de Córdoba. Ministerio de Ciencia y Técnica. Centro de Excelencia en Productos y Procesos de Córdoba; Argentin

Particle-flow reconstruction and global event description with the CMS detector

The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and reconstructed by the algorithm provides a global event description that leads to unprecedented CMS performance for jet and hadronic tau decay reconstruction, missing transverse momentum determination, and electron and muon identification. This approach also allows particles from pileup interactions to be identified and enables efficient pileup mitigation methods. The data collected by CMS at a centre-of-mass energy of 8 TeV show excellent agreement with the simulation and confirm the superior PF performance at least up to an average of 20 pileup interactions

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis