On the importance of nonlinear modeling in computer performance prediction

Computers are nonlinear dynamical systems that exhibit complex and sometimes even chaotic behavior. The models used in the computer systems community, however, are linear. This paper is an exploration of that disconnect: when linear models are adequate for predicting computer performance and when they are not. Specifically, we build linear and nonlinear models of the processor load of an Intel i7-based computer as it executes a range of different programs. We then use those models to predict the processor loads forward in time and compare those forecasts to the true continuations of the time seriesComment: Appeared in "Proceedings of the 12th International Symposium on Intelligent Data Analysis

Cobalt-substituted porous calcium copper titanate electrodes for paracetamol degradation by an electro-oxidation/peroxymonosulfate system

Developing cobalt-substituted perovskite electroactive membranes with an efficient Co/Cu combination mode is an important environmental challenge for removing drugs via peroxymonosulfate (PMS) activation. In this work, cobalt (Co)-substituted calcium copper titanatewas synthesized with an easy ball milling process and used as an anode in electro-oxidation in the presence of PMS for paracetamol degradation. The Co-CCTO anode with a Co ratio of 0.5 showed the highest removal efficiency (100 % of 10 ppm paracetamol after 180 min) due to the increase of the active sites and the appearance of the Co2+/Co3+ cycle that accelerates the charge transfer with Co incorporation into the lattice. Scavenger experiments showed that sulfate radicals (SO4̇−), oxygen radicals (O2̇-), hydroxyl radicals (̇OH), and singlet oxygen (1O2) were generated in the electro-oxidation-PMS reaction system and that SO4̇−, 1O2, and O2̇- were the dominant active radicals. The toxicity tests with Vibrio fischeri confirmed paracetamol mineralization and decomposition and the elimination of harmful by-products. It is crucial to explore the substitution of CCTO with different metal dopants in order to optimize the membrane performance and overcome the limitations associated with cobalt substitution

Porous calcium copper titanate electrodes for paracetamol degradation by electro-oxidation via CuO-induced peroxymonosulfate activation

Some drugs cannot be efficiently eliminated using routine wastewater treatments and therefore are considered persistent organic pollutants (POPs). POPs can be removed using advanced oxidation processes. Among these processes, the combination of electrocatalysis and a sulfate-based advanced oxidation process via peroxymonosulfate (PMS) activation is an attractive approach due to its high efficiency, low energy consumption and non-selective attack. It is well known that the type of anode strongly affects the electrocatalysis performance for water treatment. Here, we evaluated perovskites as electrode material due to their unique structural properties and high chemical stability. We fabricated porous anodes of calcium copper titanate (CaCu3Ti4O12; CCTO) with different percentages (20%, 30% and 40%) of polymethyl methacrylate (PMMA) by ball-milling. The samples that included PMMA displayed 50% porosity and pores were homogenously distributed. Morphological measurements show the presence of grain structures and grain boundaries containing CCTO and CuO phases, respectively. CCTO with 30 wt% PMMA (CCTO-30) exhibited the highest CuO phase amount, defect percentage and oxidation–reduction peak, and the smallest resistance. We used the obtained CCTO nanocomposites as anodes in a beaker (210 mL) with PMS (0.5 mM) to treat 10 ppm paracetamol in 50 mM sodium sulfate. After 90 minutes, paracetamol was completely decomposed using CCTO-30 due to PMS activation by a copper catalytic cycle (Cu2+/Cu1+ and Cu2+/Cu3+) to generate ˙SO4− radicals and Cu3+ non-radicals that are selective for its removal

Graphene oxide-induced CuO reduction in TiO2/CaTiO3/Cu2O/Cu composites for photocatalytic degradation of drugs via peroxymonosulfate activation

Contamination of water bodies is a global environmental and human health issue. Conventional water treatment systems cannot efficiently eliminate organic contaminants, particularly drugs. Photocatalysis is a promising, environmentally friendly oxidation process for the removal of such compounds. A key point is the choice of material to be used as photocatalyst. Here, TiO2/CaTiO3/Cu2O/Cu composites were fabricated by adding different amounts (x) of graphene oxide (GO) (x wt% = 1, 3, and 5 %) to CaCu3Ti4O12 powder using the solid-state synthesis method. The produced pellets were sintered under inert nitrogen atmosphere at 1100 °C for 3 h. X-ray diffraction analysis showed that the Cu metal amount was increased upon GO addition, and the UV–Vis diffuse reflectance spectroscopy showed that the spectral response was extended to the visible range. Then, high performance liquid chromatography assessment of paracetamol degradation by a photocatalytic cell using TiO2/CaTiO3/Cu2O/Cu composites with different GO amounts showed that the removal efficiency was increased upon introduction of 0.5 mM peroxymonosulfate (PMS) as active component to generate radical dotSO4‾ radicals. After 3 h under visible light, 96 % of 10 ppm paracetamol was degraded by the composite with 3 % of GO (1 cm2 surface photocatalyst) compared with 50 % by the composite without GO in the same experimental conditions (PMS in 210 mL of aqueous solution). Free radical trapping and the acute toxicity of potential degradation by-products were also investigated. Our results indicate that TiO2/CaTiO3/Cu2O/Cu with 3 % GO displays long-term stability and durability for the photocatalytic removal of pharmaceutical pollutants from wastewater

Cognitive Information Processing

Contains research objectives, summary of research and reports on four research projects.National Institutes of Health (Grant 5 PO1 GM14940-02)National Institutes of Health (Grant 5 P01 GM15006-03)Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DA 28-043-AMC-02536(E)National Institutes of Health (Grant 5 T01 GM01555-03

Characterizing key attributes of the epidemiology of COVID-19 in China: Model-based estimations

AbstractBackgroundA novel coronavirus strain, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China in late 2019. The resulting disease, Coronavirus Disease 2019 (COVID-2019), soon became a pandemic. This study aims to characterize key attributes of the epidemiology of this infection in China.MethodsAn age-stratified mathematical model was constructed to describe the transmission dynamics and estimate the age-specific differences in the biological susceptibility to the infection, age-assortativeness in transmission mixing, case fatality rate (CFR), and transition in rate of infectious contacts (and reproduction number R0) following introduction of mass interventions.ResultsThe model estimated the infectious contact rate in early epidemic at 0.59 contacts per day (95% uncertainty interval (UI)=0.48-0.71). Relative to those 60-69 years of age, susceptibility to the infection was only 0.06 in those ≤19 years, 0.34 in 20-29 years, 0.57 in 30-39 years, 0.69 in 40-49 years, 0.79 in 50-59 years, 0.94 in 70-79 years, and 0.88 in ≥80 years. The assortativeness in transmission mixing by age was very limited at 0.004 (95% UI=0.002-0.008). Final CFR was 5.1% (95% UI=4.8-5.4%). R0 rapidly declined from 2.1 (95% UI=1.8-2.4) to 0.06 (95% UI=0.05-0.07) following onset of interventions.ConclusionAge appears to be a principal factor in explaining the patterns of COVID-19 transmission dynamics in China. The biological susceptibility to the infection seems limited among children, intermediate among young to mid-age adults, but high among those &gt;50 years of age. There was no evidence for differential contact mixing by age, consistent with most transmission occurring in households rather than in schools or workplaces.</jats:sec

Characterizing key attributes of COVID-19 transmission dynamics in China's original outbreak: Model-based estimations.

A novel coronavirus strain, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China. This study aims to characterize key attributes of SARS-CoV-2 epidemiology as the infection emerged in China. An age-stratified mathematical model was constructed to describe transmission dynamics and estimate age-specific differences in biological susceptibility to infection, age-assortativeness in transmission mixing, and transition in rate of infectious contacts (and reproduction number R 0) following introduction of mass interventions. The model estimated the infectious contact rate in early epidemic at 0.59 contacts/day (95% uncertainty interval-UI = 0.48-0.71). Relative to those 60-69 years, susceptibility was 0.06 in those ?19 years, 0.34 in 20-29 years, 0.57 in 30-39 years, 0.69 in 40-49 years, 0.79 in 50-59 years, 0.94 in 70-79 years, and 0.88 in ?80 years. Assortativeness in transmission mixing by age was limited at 0.004 (95% UI = 0.002-0.008). R 0 rapidly declined from 2.1 (95% UI = 1.8-2.4) to 0.06 (95% UI = 0.05-0.07) following interventions' onset. Age appears to be a principal factor in explaining the transmission patterns in China. The biological susceptibility to infection seems limited among children but high among those >50 years. There was no evidence for differential contact mixing by age