On SIR epidemic models with generally distributed infectious periods: number of secondary cases and probability of infection

Recently, Clancy [SIR epidemic models with general infectious period distribution, Statist. Prob. Lett. 85 (2014) 1–5] has shown how SIR epidemics in which individuals’ infection periods are not necessarily exponentially distributed may be modeled in terms of a piecewise-deterministic Markov process (PDMP). In this paper, we present a more detailed description of the underlying PDMP, from which we analyze the population transmission number and the infection probability of a certain susceptible individual

Railway Axle Early Fatigue Crack Detection through Condition Monitoring Techniques

: The detection of cracks in rotating machinery is an unresolved issue today. In this work, a methodology for condition monitoring of railway axles is presented, based on crack detection by means of the automatic selection of patterns from the vibration signal measurement. The time waveforms were processed using the Wavelet Packet Transform, and appropriate alarm values for diagnosis were calculated automatically using non-supervised learning techniques based on Change Point Analysis algorithms. The validation was performed using vibration signals obtained during fatigue tests of two identical railway axle specimens, one of which cracked during the test while the other did not. During the test in which the axle cracked, the results show trend changes in the energy of the vibration signal associated with theoretical defect frequencies, which were particularly evident in the direction of vibration that was parallel to the track. These results are contrasted with those obtained during the test in which the fatigue limit was not exceeded, and the test therefore ended with the axle intact, verifying that the effects that were related to the crack did not appear in this case. With the results obtained, an adjusted alarm value for a condition monitoring process was established

Convolutional Neural Networks Can Be Deceived by Visual Illusions

Visual illusions teach us that what we see is not always what is represented in the physical world. Their special nature make them a fascinating tool to test and validate any new vision model proposed. In general, current vision models are based on the concatenation of linear and non-linear operations. The similarity of this structure with the operations present in Convolutional Neural Networks (CNNs) has motivated us to study if CNNs trained for low-level visual tasks are deceived by visual illusions. In particular, we show that CNNs trained for image denoising, image deblurring, and computational color constancy are able to replicate the human response to visual illusions, and that the extent of this replication varies with respect to variation in architecture and spatial pattern size. These results suggest that in order to obtain CNNs that better replicate human behaviour, we may need to start aiming for them to better replicate visual illusions

Conditions for stability and instability of retrial queueing systems with general retrial times

We study the stability of single server retrial queues under general distribution for retrial times and stationary ergodic service times, for three main retrial policies studied in the literature: classical linear, constant and control policies. The approach used is the renovating events approach to obtain sufficient stability conditions by strong coupling convergence of the process modeling the dynamics of the system to a unique stationary ergodic regime. We also obtain instability conditions by convergence in distribution to improper limiting sequences

Effects of a persistent binge drinking pattern of alcohol consumption in young people: a follow-up study using event-related potentials

Aims: The objective of this study was to examine brain activity related to visual attention processes in youths who had maintained a binge drinking (BD) pattern of alcohol consumption for > 2 years. Methods: The participants were 57 university students (26 binge drinkers: BDs) with no personal or family history of alcoholism or psychopathological disorders in first-degree relatives. Event-related potentials (ERPs) were recorded while participants performed a visual oddball task (twice within a 2-year interval). The latency and amplitude of the P3b component of the ERPs were analysed. Results: The P3b amplitude was larger in young BDs than in aged-matched controls at both evaluation times, and the difference was more pronounced after 2 years of maintenance of a BD pattern of consumption. The larger P3b amplitude was associated with an earlier onset of regular drinking and with a greater quantity and intensity of consumption. Conclusions: These findings suggest that young BDs exhibit anomalies in neural activity involved in attentional/working memory processes, which increase after 2 years of maintenance of BD. This anomalous neural activity may reflect underlying dysfunctions in neurophysiological mechanisms as well as the recruitment of additional attentional/working memory resources to enable the binge drinkers to perform the task adequately.The study was supported by a grant from the Galician Regional R&D Autorithy, Xunta de Galicia, (INCITE08PXIB211015PR) and two grants from the Spanish Ministerio de Ciencia e Innovacion (EDU2008-03400; PSI2011-22575). Eduardo Lopez-Caneda was supported by the FPU program (AP2008-03433) of the Spanish Ministerio de Educacion; S.D. was supported by a postdoctoral contract from the Isidro Parga Pondal program (Xunta de Galicia, Spain), and A.F.G. was supported by the FPI program (CG2008-0461-C02-01) of the Spanish Ministerio de Ciencia e Innovacion

As2O3 Induces Oxidative Stress in Gill, Liver, Brain and Blood of Cyprinus carpio

Artículo científicoArsenic (As) is a toxic trace element for diverse aquatic species. It is present naturally in water in diverse oxidation states and chemical species. During its biotransformation, As induces production of reactive oxygen species, eliciting oxidative stress in diverse organisms. This study aimed to evaluate As-induced toxicity in brain, liver, blood and gill of the common carp Cyprinus carpio.Secretaría de Investigación y Estudios Avanzados of the Universidad Autónoma del Estado de México (SIEA-UAEM, project UAEM 3722/2014/CID)

Impaired Mesopic Visual Acuity in Eyes with Early Age-Related Macular Degeneration

Purpose.: To determine photopic and mesopic distance high-contrast visual acuity (HC-VA) and low-contrast visual acuity (LC-VA) in eyes with early age-related macular degeneration (AMD). Methods.: Measurements were made in 22 subjects with early AMD and 28 healthy control subjects. Inclusion criteria included a photopic HC-VA of 20/25 or better. Distance VA was measured using HC (96%) and LC (10%) Bailey-Lovie logMAR letter charts under photopic (85 cd/m2) and mesopic (0.1–0.2 cd/m2) luminance conditions. Results.: Mean mesopic distance HC-VA and LC-VA were significantly worse (0.1 logMAR and 0.28 logMAR, respectively) in the early AMD group than in the control group. Under mesopic conditions, the mean difference between LC-VA and HC-VA was significantly greater in the early AMD (0.45 logMAR) than the control group (0.27 logMAR). Mean differences between mesopic versus photopic HC-VA and mesopic versus photopic LC-VA were significantly greater in the early AMD than the control group (0.13 and 0.32 logMAR of difference between the means, respectively). Sensitivity and specificity were significantly greater for mesopic LC-VA than for mesopic HC-VA (Receiver Operating Characteristics, area under the curve [AUC], 0.94 ± 0.030 and 0.76 ± 0.067, respectively). AUC values for photopic HC-VA and LC-VA were below 0.70. Conclusions.: Visual acuity testing under low luminance conditions emerged as an optimal quantitative measure of retinal function in early AMD

Is Colombia an example of successful containment of the 2020 COVID-19 pandemic? A critical analysis of the epidemiological data, March to July 2020

Background: Colombia detected its first coronavirus disease 2019 (COVID-19) case on March 2, 2020. From March 22 to April 25, it implemented a national lockdown that, apparently, allowed the country to keep a low incidence and mortality rate up to mid-May. Forced by the economic losses, the government then opened many commercial activities, which was followed by an increase in cases and deaths. This paper presents a critical analysis of the Colombian surveillance data in order to identify strengths and pitfalls of the control measures. Methods: A descriptive analysis of PCR-confirmed cases between March and July 25 was performed. Data were described according to the level of measurement. Incidence and mortality rates of COVID-19 were estimated by age, sex, and geographical area. Sampling rates for suspected cases were estimated by geographical area, and the potential for case underestimation was assessed using sampling differences. Results: By July 25, Colombia (population 50 372 424) had reported 240 745 cases and 8269 deaths (case fatality rate of 3.4%). A total of 1 370 271 samples had been analyzed (27405 samples per million people), with a positivity rate of 17%. Sampling rates per million varied by region from 2664 to 158 681 per million, and consequently the incidence and mortality rates also varied. Due to geographical variations in surveillance capacity, Colombia may have overlooked up to 82% of the actual cases. Conclusion: Colombia has a lower case and mortality incidence compared to other South American countries. This may be an effect of the lockdown, but may also be attributed, to some extent, to geographical differences in surveillance capacity. Indigenous populations with little health infrastructure have been hit the hardest