Distribution Of Intervals Research Articles

Elementary integrate-and-fire process underlies pulse amplitudes in Electrodermal activity.

Electrodermal activity (EDA) is a direct read-out of sweat-induced changes in the skin’s electrical conductance. Sympathetically-mediated pulsatile changes in skin sweat measured as EDA resemble an integrate-and-fire process, which yields an inverse Gaussian model as the inter-pulse interval distribution. We have previously showed that the inter-pulse intervals in EDA follow an inverse Gaussian distribution. However, the statistical structure of EDA pulse amplitudes has not yet been characterized based on the physiology. Expanding upon the integrate-and-fire nature of sweat glands, we hypothesized that the amplitude of an EDA pulse is proportional to the excess volume of sweat produced compared to what is required to just reach the surface of the skin. We modeled this as the difference of two inverse Gaussian models for each pulse, one which represents the time required to produce just enough sweat to rise to the surface of the skin and one which represents the time requires to produce the actual volume of sweat. We proposed and tested a series of four simplifications of our hypothesis, ranging from a single difference of inverse Gaussians to a single simple inverse Gaussian. We also tested four additional models for comparison, including the lognormal and gamma distributions. All models were tested on EDA data from two subject cohorts, 11 healthy volunteers during 1 hour of quiet wakefulness and a different set of 11 healthy volunteers during approximately 3 hours of controlled propofol sedation. All four models which represent simplifications of our hypothesis outperformed other models across all 22 subjects, as measured by Akaike’s Information Criterion (AIC), as well as mean and maximum distance from the diagonal on a quantile-quantile plot. Our broader model set of four simplifications offered a useful framework to enhance further statistical descriptions of EDA pulse amplitudes. Some of the simplifications prioritize fit near the mode of the distribution, while others prioritize fit near the tail. With this new insight, we can summarize the physiologically-relevant amplitude information in EDA with at most four parameters. Our findings establish that physiologically based probability models provide parsimonious and accurate description of temporal and amplitude characteristics in EDA.

Seasonal Inventory Management Model for Raw Materials in Steel Industry

We developed a seasonal inventory management model for raw materials, such as iron ore and coal, for multiple suppliers and multiple mills. The Nippon Steel Corporation imports more than 100 million tons of raw material annually by vessels from Australia, Brazil, Canada, and other countries. Once these raw materials arrive in Japan, they are transported to domestic mills and stored in yards before being treated in a blast furnace. A critical problem currently facing the industry is the limited capacity of the yards, which leads to high demurrage costs while ships wait for space to open up in the yards before they can unload. To reduce the demurrage costs, the inventory levels of the raw materials must be kept as low as possible. However, inventory levels that are too low may lead to inventory shortage resulting from seasonal supply disruptions (e.g., a cyclone in Australia) that delay the supply of raw materials. Because both excess and depleted inventory levels lead to increased costs, optimal inventory levels must be determined. To solve this problem, we developed an inventory management model that considers variations on the supply side, differences that should be observable upon looking at the ship operations. The concept is to model the probability distribution of ship arrival intervals by brand groups and mills. We divided ship operations into two stages: arrival at all mills (in Japan) and arrival at individual mills. We modeled the former as a nonhomogeneous Poisson process and the latter as a nonhomogeneous Gamma process. Our proposed model enables inventory levels to be reduced by 14% in summer and 6% in winter.

Method of Identifying Male Lineages Based on Main Haplotype and Analysis of the Distribution of Y-STR Haplotype Mismatch Based on the Bayesian Theory

To establish a classification method to identify different male lineages in a large population, to study the distribution patterns of Y-STR loci mismatches among Han Chinese male lineage members and to explore the mismatch probability distribution among the members with different meiosis intervals in the family. Peripheral blood samples of 269 male individuals from 12 lineages in Han Chinese population and 45 unrelated male individuals were collected. Then, Yfiler Plus TM and ZGWZ FSY or Yfiler Platinum amplification kits were used, obtaining 314 Y-STR haplotypes. The Y-STR haplotype with 3 or more repetitions were selected as the main haplotype, in which the largest number was selected as the first data center. According to the standard of Y-STR genotype, those with mismatches within five loci and six steps were clustered and merged. Then, the main haplotype of the largest number in the remaining data was taken as the second data center, and cluster analysis is carried out in turn until there is no main haplotype remained. Pair comparison was conducted between lineage members and unrelated individuals, and the mismatch distribution among lineage members and unrelated individuals was calculated respectively. The average mismatch rate of each locus was subsequently calculated, as well as the mismatch probability distribution among members with different meiosis intervals within the lineage. 269 out of the 314 individuals were divided into 12 groups by cluster analysis method, accomplishing 100% accuracy between the cluster groups thus identified and the 12 known lineages. The remaining 45 unrelated individuals were scattered. The mismatch loci was within 0-7 loci and 0-7 steps among lineage members and the mismatch between unrelated individuals was at least 11 loci and 15 steps. The mismatch loci with the largest number of one-step and two-step mismatch were different in each lineage and had features that were specific to each lineage. The minimum mutation count and average mismatch rate of each locus were significantly correlated with the mutation rate. Two individuals with no mismatch had a 19.7% probability of 1 meiosis interval and a 71.2% probability of less than 6 meiosis interval. Two individuals with 3 loci mismatches had a 65.2% probability of more than 10 meiosis intervals. The cluster analysis method based on main haplotypes provided in this paper can quickly and effectively differentiate large male lineage samples. The clustering method and the mismatch probability distribution of different meiosis intervals obtained thus can provide new ideas for research and screening instruments, and important reference for lineage investigation, data analysis and practical application of Y-STR database in the future.

Temporal Correlates to Monaural Edge Pitch in the Distribution of Interspike Interval Statistics in the Auditory Nerve.

Pitch is a perceptual attribute enabling perception of melody. There is no consensus regarding the fundamental nature of pitch and its underlying neural code. A stimulus which has received much interest in psychophysical and computational studies is noise with a sharp spectral edge. High-pass (HP) or low-pass (LP) noise gives rise to a pitch near the edge frequency (monaural edge pitch; MEP). The simplicity of this stimulus, combined with its spectral and autocorrelation properties, make it an interesting stimulus to examine spectral versus temporal cues that could underly its pitch. We recorded responses of single auditory nerve (AN) fibers in chinchilla to MEP-stimuli varying in edge frequency. Temporal cues were examined with shuffled autocorrelogram (SAC) analysis. Correspondence between the population’s dominant interspike interval and reported pitch estimates was poor. A fuller analysis of the population interspike interval distribution, which incorporates not only the dominant but all intervals, results in good matches with behavioral results, but not for the entire range of edge frequencies that generates pitch. Finally, we also examined temporal structure over a slower time scale, intermediate between average firing rate and interspike intervals, by studying the SAC envelope. We found that, in response to a given MEP stimulus, this feature also systematically varies with edge frequency, across fibers with different characteristic frequency (CF). Because neural mechanisms to extract envelope cues are well established, and because this cue is not limited by coding of stimulus fine-structure, this newly identified slower temporal cue is a more plausible basis for pitch than cues based on fine-structure.

Real World Clinical and Economic Burden of Patients with Hodgkin Lymphoma (HL) Who Fail Frontline (FL) Therapy in the US

Introduction: Hodgkin lymphoma (HL) is a hematologic malignancy for which frontline treatment options and outcomes have remained unchanged for several decades. HL is considered to have a favorable prognosis although failure rates after FL therapy range from 10% to 30% depending on stage. Patients who fail go on to bear the burden of additional therapy after FL. Little real-world evidence exists on the burden of disease for patients who fail FL (FLF) therapy for healthcare providers to contextualize the value of novel therapies. This study aimed to identify FLF patients and compare healthcare costs between HL patients with and without FLF.Methods: This retrospective analysis used the MarketScan Commercial and Medicare Supplemental administrative claims databases to select adults aged >18 years with ≥ 1 inpatient or 2 outpatient claims with a HL diagnosis (ICD-9 201.xx excluding Hodgkin paragranuloma, Hodgkin sarcoma and lymphocytic-histiocytic predominance) from 1/1/2010 to 9/30/2015. Eligible patients were required to have continuous plan enrollment for > 6 months prior to the diagnosis, no prior cancer, and initiate a multi-agent regimen indicative of curative intent.Patients were in the FLF cohort if they had one of the following failure events: initiate a new chemotherapy after discontinuing FL (gap >60 days with no chemotherapy), switch to a new treatment, or having a stem cell transplant (SCT). Patients were in FLF+XRT cohort if they also received radiation after completing FL chemotherapy. Index dates for the FLF and FLF+XRT cohorts were the earliest date of the failure events, and were randomly assigned for non-FLF patients based on distribution of intervals between FL start date and index date for the FLF cohort. They had to have > 30-day post-index continuous enrollment and followed until date of disenrollment, death, or end of the study period.Annual healthcare costs were measured at 12-month post-index periods among patients with > 12-months post-index continuous enrollment. Costs were measured during FL and the entire follow-up period (reported as per patient per month [PPPM]).Results: 795 patients met the selection criterion (mean age 38.5 years, 47.5% female). 67.8% of patients 18-44 years old, 26.4% 45-64 years old, and 5.8% ≥65 years old. Most resided in urban areas (81.9%), and the mean pre-index Charlson Comorbidity Index score of study patients was 2.9±1.9. The two most frequent coded comorbidities during FL were symptoms involving the respiratory system (41.3%) and cardiovascular (22.9%) in both cohorts. Of the patients in the FL+XRT cohort, 60.1% received XRT after FL discontinuation, 21.8% discontinued and restarted therapy, 10.4% switched to a new therapy, and 7.8% went on to a SCT directly after FL.The PPPM costs for FLF cohort during the follow up was $12,494 (N=77, Table 1) and the annual all-cause cost of failure was $160,839 (N=33, Table 2) higher than patients who did not fail FL. The PPPM costs in FLF+XRT cohort (N=193) was $11,918 (vs $7,772) (Table 1). The annual all-cause cost in was $68,431 (N=94) higher than patients in non-FLF cohort (Table 2). PPPM costs during FL in FLF+XRT was $21,676 (vs $16,396) (Table 1) driven by outpatient services (50.5%) and inpatient admissions (48.6%). The FLF+XRT (vs non-FLF) cohort had a significantly shorter duration of FL therapy (average of 112 vs 131 days, p<0.05).The economic burden of failure varied by type (Table 3). The annual costs of failure due to restarting, switching, SCT, or radiation were $269,189, $46,951, $231,824, and $55,989, respectively. Similar trends in cost were observed among patients with ≥24 months post-index enrollment (n=200).Conclusions: HL patients who fail FL represent a substantially higher economic burden compared to those without FLF, not accounting for stage at diagnosis. We did not assess the indirect costs or societal impact of FLF for the population and therefore this is an underestimate of the overall burden. More research is needed to determine optimal treatment that could reduce the risk of progression, the need for treatment after completion of FL and enhance long-term clinical and economic outcomes. [Display omitted] DisclosuresStraus:Received consulting fee from Seattle Genetics for involvement in the research: Consultancy. Bonafede:Employee of Truven Health Analytics, an IBM Company, that received a research contract to conduct this study with and on behalf of Seattle Genetics, Inc: Employment. Feliciano:Seattle Genetics: Employment, Equity Ownership. Cai:Truven Health Analytics: Employment, Other: I am an employee of Truven Health Analytics, an IBM company which received funding from Seattle Genetics to conduct this study. Noxon:Truven Health Analytics, an IBM company which received project funding from Global Blood Therapeutics: Employment. Princic:Truven Health Analytics, IBM Company: Employment. Josephson:Seattle Genetics: Employment, Equity Ownership. Richhariya:Seattle Genetics: Employment, Equity Ownership.

Maximum cross section method in the filtering problem for continuous systems with Markovian switching

Abstract New solution algorithms of optimal filtering problem are proposed for systems with random structure and continuous time. This problem consists in estimating the current state of system based on the results of measurements. The mathematical model of the system includes nonlinear stochastic differential equations whose right-hand side determines the structure of the dynamic system or mode of operation. The right-hand side may vary at random time moments. The number of structures of the system is assumed to be finite and the process of changing the structure to be Markov or conditionally Markov. The state vector of such system consists of two components, namely, a vector with real coordinates and an integer structure number. The law of change of the structure number is determined by the distribution of the random time interval between switchings with a given intensity dependent on the state of system.

Measurement of Pulsatile Insulin Secretion: Rationale and Methodology.

Pancreatic β-cells are responsible for the synthesis and exocytosis of insulin in response to an increase in circulating glucose. Insulin secretion occurs in a pulsatile manner, with oscillatory pulses superimposed on a basal secretion rate. Insulin pulses are a marker of β-cell health, and secretory parameters, such as pulse amplitude, time interval and frequency distribution, are impaired in obesity, aging and type 2 diabetes. In this review, we detail the mechanisms of insulin production and β-cell synchronization that regulate pulsatile insulin secretion, and we discuss the challenges to consider when measuring fast oscillatory secretion in vivo. These include the anatomical difficulties of measuring portal vein insulin noninvasively in humans before the hormone is extracted by the liver and quickly removed from the circulation. Peripheral concentrations of insulin or C-peptide, a peptide cosecreted with insulin, can be used to estimate their secretion profile, but mathematical deconvolution is required. Parametric and nonparametric approaches to the deconvolution problem are evaluated, alongside the assumptions and trade-offs required for their application in the quantification of unknown insulin secretory rates from known peripheral concentrations. Finally, we discuss the therapeutical implication of targeting impaired pulsatile secretion and its diagnostic value as an early indicator of β-cell stress.

Time-domain based evaluation of detection efficiency in liquid scintillation counting

This work explores the distribution of time intervals between signals from the photomultiplier tubes (PMTs) of a liquid scintillation counting (LSC) system when a scintillation burst caused by an ionizing particle is detected. This distribution is termed the cross-correlation distribution and it is shown that it contains information about the probability to detect a scintillation event. A theoretical model that describes the cross-correlation distribution is derived. The model can be used to estimate the mean number of detected photons in a LSC measurement, which allows the calculation of the detection efficiency. The theoretical findings are validated by Monte Carlo simulations and by experiments with low-energy beta-emitting and electron-capture radionuclides (^3hbox {H}, ^{14}hbox {C}, ^{63}hbox {Ni} and ^{55}hbox {Fe}), with dedicated LSC systems and several commercial LSC cocktails. The results show that some of the parameters of the cross-correlation distribution such as the peak height or the kurtosis can be used as detection efficiency estimators or quenching indicators in LSC. Thus, although the time domain and the cross-correlation distribution have received little to no attention in the practice of LSC, they have the capacity to bring significant improvements in almost all LSC applications related to activity determination of low-energy beta-emitting and electron-capture radionuclides. The results also suggest concepts for the development of innovative LSC systems.

Improved kinematic interpolation for AIS trajectory reconstruction

Ship trajectory information has made a significant contribution to the data-based research in analyzing maritime transportation and has facilitated the improvement of maritime safety. However, the AIS data, which consists of ship trajectory, inevitably contains noises or missing data that can interfere with the conclusion. In this paper, an improved kinematic interpolation is presented for AIS trajectory reconstruction, which integrates data preprocessing and interpolation that considers the ships' kinematic information. The improved kinematic reconstruction method includes four steps: (1) data preprocessing, (2) analysis of time interval distribution, (3) abnormal data detection and removal, (4) kinematic interpolation that takes the kinematic feature of ships (i.e., velocity and acceleration) into account, adding forward and backward track points to help correct the acceleration function of reconstruction points. The proposed method is tested on the AIS dataset of Zhoushan Port and was compared with traditional ship trajectory reconstruction methods. The comparison indicates that the proposed method can effectively reconstruct the ship trajectory with higher performance on a single ship trajectory and a large AIS data set of certain water areas.

Queuing Systems with a Time Lag

The article discusses various queuing systems (QS) formed by four laws of probability distributions: exponential, hyperexponential, Erlang and hyper-Erlang of the second order. These four laws form sixteen different QS. In contrast to the classical theory, this article considers QS with distribution laws shifted to the right from the zero point. Such QS are of type G/G/1 with arbitrary laws of the distribution of intervals between the requirements of the input flow and the service time. As you know, for such systems it is impossible to obtain solutions for the main characteristic of QS the average waiting time in the general case. Therefore, studies of such systems are important for special cases of distribution laws. The article provides an overview of the author's results for the average waiting time in a queue in a closed form for systems with input distributions shifted to the right from the zero point. To solve this problem, the spectral decomposition method for solving the Lindley integral equation was used. In the course of solving the problem, spectral decompositions of the solution of the Lindley integral equation for eight systems were obtained and with their help calculation formulas were derived for the average waiting time in the queue. It is shown that in systems with delay, the average waiting time is shorter than in conventional systems. The obtained calculation formulas for the average waiting time expand and complement the well-known incomplete formula of the queuing theory for the average waiting time for G/G/1 systems. The proposed approach allows us to calculate the average value and moments of higher orders of waiting time for these systems in mathematical packages for a wide range of changes in traffic parameters. Given the fact that the variation in packet delay (jitter) in the telecommunications standard is defined as the spread of waiting time around its average value, the jitter can be determined through the variance of the waiting time.

Dynamical robustness and firing modes in multilayer memristive neural networks of nonidentical neurons

On the basis of Hindmarsh-Rose neuron model, dynamical robustness and the transition of firing modes of multilayer memristive neural network consisting of nonidentical neurons have been investigated in detail. The dynamic effects of memristive synapses coupling which are either cubic order flux or quadratic flux are detected. Our results suggest that for the cubic order flux-controlled memristors increasing electromagnetic induction parameter and parameter of memristor show the tendency to spoil the dynamical robustness of the multilayer memristive neural network. For quadratic flux-controlled memristors, weak electromagnetic induction can spoil the dynamical robustness while strong electromagnetic induction and parameter of memristor have little influence on dynamical robustness. We found that the ratio of inactive neurons switches the firing patterns of the active neuron among periodic bursting, chaotic bursting and spiking-like. In the case of memristive synapse coupling by cubic order flux-controlled memristors, chaotic bursting alternates with period bursting as the ratio of inactive neurons is increased, and the chaotic bursting occupy a large range of the ratio of inactive neurons. In the case of memristive synapse coupling by quadratic flux-controlled memristors, the main firing pattern of the active neuron is chaotic bursting. The distribution of interspike interval can be broadly classified into two groups: those that are long interspike intervals and those that are short interspike intervals. The dynamics of multilayer memristive neural network is also verified in the circuits built on Multisim. These results could give new mechanism explanation for aging transition by applying electromagnetic field to neural network.

A Portfolio Selection Model Based on the Interval Number

Traditional portfolio theory uses probability theory to analyze the uncertainty of financial market. The assets’ return in a portfolio is regarded as a random variable which follows a certain probability distribution. However, it is difficult to estimate the assets return in the real financial market, so the interval distribution of asset return can be estimated according to the relevant suggestions of experts and decision makers, that is, the interval number is used to describe the distribution of asset return. Therefore, this paper establishes a portfolio selection model based on the interval number. In this model, the semiabsolute deviation risk function is used to measure the portfolio’s risk, and the solution of the model is obtained by using the order relation of the interval number. At the same time, a satisfactory solution of the model is obtained by using the concept of acceptability of the interval number. Finally, an example is given to illustrate the practicability of the model.

Estimates of regional infectivity of COVID-19 in the United Kingdom following imposition of social distancing measures.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reproduction number has become an essential parameter for monitoring disease transmission across settings and guiding interventions. The UK published weekly estimates of the reproduction number in the UK starting in May 2020 which are formed from multiple independent estimates. In this paper, we describe methods used to estimate the time-varying SARS-CoV-2 reproduction number for the UK. We used multiple data sources and estimated a serial interval distribution from published studies. We describe regional variability and how estimates evolved during the early phases of the outbreak, until the relaxing of social distancing measures began to be introduced in early July. Our analysis is able to guide localized control and provides a longitudinal example of applying these methods over long timescales.This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK'.

Blood group O convalescent plasma donations have significantly lower levels of SARS-CoV-2 IgG antibodies compared to blood group A donations.

BackgroundCOVID‐19 convalescent plasma (CCP) is plasma collected from individuals who have recovered from SARS‐CoV‐2 infection. The FDA Emergency Use Authorization restricts use of CCP to high‐titer units only. The purpose of this study was to determine if donor ABO blood group was associated with SARS‐CoV‐2 antibody response, and subsequent qualification as high‐titer CCP.MethodsAll CCP donations collected from April 21, 2020 to September 1, 2020 were included. The Abbott ARCHITECT semi‐quantitative chemiluminescent microparticle immunoassay was used to assess IgG antibodies to the nucleocapsid protein of SARS‐CoV‐2. Units with a S/C value ≥4.5 were considered high titer.ResultsA total of 232 CCP donations were evaluated. There were no significant differences in the distribution of sex, age, and interval from symptom resolution to donation by ABO blood group. The mean SARS‐CoV‐2 IgG antibody S/C value was significantly lower in blood group O donations (3.6), compared to blood group A (5.0) donations (p < .001). There was no difference in antibody response between the other blood group pairings. Blood group O donations resulted in a lower percentage of high‐titer units (35%), compared to blood group A (60%), B (58%), and AB (65%) donations.ConclusionBlood group O donations were found to have significantly lower levels of SARS‐CoV‐2 IgG nucleocapsid antibodies compared to blood group A donations and were less likely to produce CCP units that qualified as high titer. These findings may aid donor recruitment to promote availability of high‐titer CCP to meet patient needs.

Potential-productive intervals determination of the Tutleim formation in the central part of the Krasnoleninsky arch

The article presents the results of the Tutleim formation complex studies of core from 16 wells drilled on an area of 900 km2 near the Kamennaya crest of the Krasnoleninsky arch. The area is characterized by the variability of the structural plan, preserved from the time of deposits sedimentation, that might affect the structure of formation. Regionally traceable lithological units were used to describe different types of sections, which were firmly recorded on the core and on the logs. The article presents the results of the sections correlation, that shows the variability of the Tutleim formation through the area, identifies typical sections for the submerged, slope and crestal parts of the investigated field. The section may contain two reservoir intervals of different types: radiolarite and siliceous-phosphate layers with average porosity values of 7% and 15%, respectively. The radiolarite layers form the main potential-productive intervals, that are found in all types of sections on one or two stratigraphic levels: in the crestal sections only in the third unit, in the slope and submerged sections – in the first, second and third units. The phosphorite layer in the fifth unit is a characteristic singularity only of the crestal sections. The obtained results allow predicting the distribution of the potential-productive intervals of the Tutleim formation and its stratigraphic analogues in different areas with higher accuracy.

Serial Intervals and Case Isolation Delays for Coronavirus Disease 2019: A Systematic Review and Meta-Analysis.

BackgroundEstimates of the serial interval distribution contribute to our understanding of the transmission dynamics of coronavirus disease 2019 (COVID-19). Here, we aimed to summarize the existing evidence on serial interval distributions and delays in case isolation for COVID-19.MethodsWe conducted a systematic review of the published literature and preprints in PubMed on two epidemiological parameters namely serial intervals and delay intervals relating to isolation of cases for COVID-19 until 22 October, 2020 following predefined eligibility criteria. We assessed the variation in these parameter estimates by correlation and regression analysis.ResultsOf 103 unique studies identified on serial intervals of COVID-19, 56 were included providing 129 estimates and of 451 unique studies on isolation delays, 18 studies were included providing 74 estimates. Serial interval estimates varied from 1.0 to 9.9 days, while case isolation delays varied from 1.0 to 12.5 days which were associated with spatial, methodological and temporal factors. In mainland China, the pooled mean serial interval was 6.2 (range, 5.1-7.8) days before the epidemic peak and reduced to 4.9 (range, 1.9-6.5) days after the epidemic peak. Similarly, the pooled mean isolation delay related intervals were 6.0 (range, 2.9-12.5) days and 2.4 (range, 2.0-2.7) days before and after the epidemic peak, respectively. There was a positive association between serial interval and case isolation delay.ConclusionsTemporal factors, such as different control measures and case isolation in particular led to shorter serial interval estimates over time. Correcting transmissibility estimates for these time-varying distributions could aid mitigation efforts.

The Effect of Low-Dose Atropine on Alpha Ganglion Cell Signaling in the Mouse Retina.

Low-dose atropine helps to control myopia progression with few side effects. However, the impact of atropine, a non-selective muscarinic Acetylcholine (ACh) receptor antagonist, on retinal ganglion cells (RGCs) remains unclear. After immersing the cornea and adjacent conjunctiva of enucleated eyes in 0.05% (approximately 800 μM) atropine solution for 30 min, the atropine concentration reached in the retina was below 2 μM. After direct superfusion of the retina with 1 μM atropine (considering that the clinical application of 0.05% atropine eye drops will be diluted over time due to tear flow for 30 min), no noticeable changes in the morphology of ON and OFF alpha RGCs (αRGCs) were observed. Atropine affected the light-evoked responses of ON and OFF αRGCs in a dose- and time-dependent fashion. Direct application of less than 100 μM atropine on the retina did not affect light-evoked responses. The time latency of light-induced responses of ON or OFF αRGCs did not change after the application of 0.05–100 μM atropine for 5 min. However, 50 μM atropine extended the threshold of joint inter-spike interval (ISI) distribution of the RGCs. These results indicated that low-dose atropine (<0.5 μM; equal to 1% atropine topical application) did not interfere with spike frequency, the pattern of synchronized firing between OFF αRGCs, or the threshold of joint ISI distribution of αRGCs. The application of atropine unmasked inhibition to induce ON responses from certain OFF RGCs, possibly via the GABAergic pathway, potentially affecting visual information processing.

Measuring and Assessing Typing Skills in Writing Research

In keyboard writing, typing skills are considered an important prerequisite of proficient text production. We describe the design, implementation, and application of a standardized copy-typing task in order to measure and assess individual typing fluency. A test-retest analysis indicates the instrument’s reliability. While the task has been developed across eleven different languages and the related keyboard layouts, we here refer to a corpus of Dutch copy tasks (n = 1682). Analyses show that copying speed non-linearly varies with age. Bayesian analyses reveal differences in the typing performance and the underlying distributions of inter-key intervals between the different task components (e.g., lexical vs. non-lexical materials; high-frequent vs. lowfrequent bigrams). Based on these findings it is strongly recommended to include copy-task measures in the analysis of keystroke logging data in writing studies. This supports a better comparability and interpretability of keystroke data from more complex or communicatively-embedded writing tasks across individuals. Further potential applications of the copy task for writing research are explained and discussed.

Comparison of Different Approaches in Estimating Initial Reproduction Number of SARS-CoV-2 in the Islamic Republic of Iran

Background: The basic reproduction number (R0) is an epidemic threshold parameter that indicates the magnitude of disease transmission and thus allows suggestions for the planning of control measures. Objectives: Our aim in this study was to compare different approaches for estimating R0 in the early stage of the SARS-CoV-2 outbreak and discern the best-fitting model. Methods: The dataset was derived from cumulative laboratory-confirmed COVID-19 cases from 26th February to 30th May 2020 in Iran. The methods of exponential growth (EG) rate, maximum likelihood (ML), time-dependent (TD) reproduction number, attack rate (AR), and sequential Bayesian (SB) model were used. The gamma distribution (mean 4.41 ± 3.17 days) was used for serial interval (SI) distribution. The best-fitting method was selected according to the lowest root mean square error (RMSE). Results: We obtained the following estimated R0 [95% confidence interval]: 1.55 [1.54; 1.55], 1.46 [1.45; 1.46], 1.31 [1.30; 1.32], and 1.40 [1.39; 1.41] using EG, ML, TD, and SB methods, respectively. Additionally, the EG and ML methods showed an overestimation of R0, and the SB method showed to be under-fitting in the estimation of R0. The AR method estimated R0 equal to one. The TD method had the lowest RMSE. Conclusions: The simulated and actual R0 of TD showed that this method had a good fit for actual data and the lowest RMSE. Therefore, the TD method is the most appropriate method with the best performance in estimating actual R0 values.

Multiple attribute decision making using Beta distribution of intervals, expected values of intervals, and new score function of interval-valued intuitionistic fuzzy values

In this paper, we propose a new multiple attribute decision making (MADM) method using the Beta distribution of intervals, the expected values of intervals, and the proposed new score function of interval-valued intuitionistic fuzzy values (IVIFVs). Firstly, it transformed each IVIFV in the decision matrix (DM) into three intervals to get the transformed matrix (TM). Then, it calculates the expected values of the obtained three intervals for each triplet in the TM, respectively, and then uses the proposed new score function to calculate the score value of each IVIFV in the DM to obtain the score matrix. Then, it transforms the interval-valued intuitionistic fuzzy (IVIF) weight of each attribute into three intervals and calculates the expected values of the obtained three intervals, respectively. Then, it uses the proposed new score function to calculate the score value of the IVIF weight of each attribute to obtain the normalized optimal weight of each attribute. Finally, based on the obtained score matrix and the obtained optimal weight of each attribute, it computes the weighted score of each alternative to get the preference order of alternatives. The proposed MADM method can overcome the drawbacks of the existing MADM methods in IVIF environments.