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Abstract Background Japan implemented strict border control measures and all incoming passengers were subject to entry screening with reverse transcription–polymerase chain reaction or antigen testing. From late 2020, exit screening within 72 h of departure to Japan also became mandatory. In this study, we evaluated the effectiveness of the exit screening policy in Japan by analyzing airport screening data from October 2020 to April 2022. Methods In addition to assessing entry screening data over time of passengers from the United Kingdom, we examined the prevalence of coronavirus disease 2019 (COVID-19) in the United Kingdom based on the Office of National Statistics infection survey. We constructed a statistical model that described entry screening positivity over time using Office of National Statistics prevalence data as the explanatory variable. Ideally, the time-dependent patterns of entry screening and Office of National Statistics prevalence data should resemble each other; however, we found that, sometimes, they were different and regarded the difference to statistically partly reflect the effectiveness of exit screening. Results The average proportion positive in one month before mandatory exit screening was implemented among Japanese passengers was 0.67% (95% confidence interval [CI]: 0.45, 0.98), whereas the proportion positive decreased to 0.49% (95% CI: 0.21, 1.15) in the first month of exit screening. Adjusting for time-dependent prevalence at the origin, we concluded that exit screening contributed to reducing passenger positivity by 59.3% (95% CI: 19.6, 81.3). The overall positivity values among passengers during the Delta and Omicron variant periods were 3.46 times and 1.46 times that during the pre-Delta variant period, respectively. Conclusions We used a simplistic statistical model and empirical data from passengers arriving in Japan from the United Kingdom to support that exit screening helped to reduce the proportion positive by 59%. Although the proportion positive later increased considerably and precluded preventing the introduction of imported cases, submitting a certificate for a negative test result contributed to reducing the positivity among travelers.

Abstract Background The Japanese government has instituted border control measures against COVID-19, including entry and exit screening of people arriving from overseas. We sought to evaluate the effectiveness of the exit screening policy in Japan in reducing the risk of importing COVID-19 cases among travelers from Asian and Pacific countries. Methods The study period was stratified based on the timing of exit screening: (i) the control period (the pre-exit screening period from 25 October 2020 to 16 January 2021), (ii) the time period with the Alpha variant from 17 January to 10 April 2021, and (iii) the time period with the Delta variant from 2 May to 2 October 2021. Incidence data in the countries of origin were used to adjust for the risk of infection among travelers. The positivity rate of entry screening in Japan was compared among the three different study periods, adjusting for the risk of infection in the country of origin. Results The adjusted relative risk of positivity was greatly reduced and substantially below the value of 1 during the Alpha variant period compared with the control period. Although the relative risks increased when comparing the Delta variant period against control, the estimate remained below 1, except for among travelers from India and Myanmar. The relative risk reduction was greatest in high-income countries, with estimates of 100% and 96% risk reduction during the Alpha and Delta variant periods, respectively, followed by upper-middle-income countries with estimates of 90% and 76%, respectively. Conclusions Even in the presence of the Alpha and Delta variants, exit screening clearly reduced the risk of infection among travelers arriving from Asian and Pacific nations. As the testing relies on the country of origin, the effectiveness varied greatly by the socioeconomic income status and epidemiological situation of those countries. Test standardization and quality assurance may be required in low- and middle-income countries.

At the end of 2022, a total of 20,003 diagnoses of human immunodeficiency virus (HIV) infection and 8,983 cases of acquired immunodeficiency syndrome (AIDS) among Japanese nationals, and 3,860 HIV diagnoses and 1,575 AIDS cases among foreign residents, had been notified to the government in Japan. This study updates the estimate of HIV incidence, including during the COVID-19 pandemic. It aimed to reconstruct the incidence of HIV and understand how the disruption caused by COVID-19 affected the epidemiology of HIV. Using a median incubation period of 10.0 years, the number of undiagnosed HIV infections was estimated to be 3,209 (95% confidence interval (CI): 2,642, 3,710) at the end of 2022. This figure has declined steadily over the past 10 years. Assuming that the median incubation period was 10.0 years, the proportion of diagnosed HIV infections, including surviving AIDS cases, was 89.3% (95% CI: 87.8%, 91.0%). When AIDS cases were excluded, the proportion was 86.2% (95% CI: 84.3%, 88.3%). During the COVID-19 pandemic, the estimated annual diagnosis rate was slightly lower than during earlier time intervals, at around 16.5% (95% CI: 14.9%, 18.1%). Japan may already have achieved diagnostic coverage of 90%, given its 9% increment in the diagnosed proportion during the past 5 years. The incidence of HIV infection continued to decrease even during the COVID-19 pandemic from 2020 to 2022, and the annual rate of diagnosis decreased slightly to 16.5%. Monitoring the recovery of diagnosis along with the effective reproduction number is vital in the future.

Abstract Background A major epidemic of COVID-19 caused by the Delta variant (B.1.617.2) occurred in India from March to July 2021, resulting in 19 million documented cases. Given the limited healthcare and testing capacities, the actual number of infections is likely to have been greater than reported, and several modelling studies and excess mortality research indicate that this epidemic involved substantial morbidity and mortality. Methods To estimate the incidence during this epidemic, we used border entry screening data in Japan to estimate the daily incidence and cumulative incidence of COVID-19 infection in India. Analysing the results of mandatory testing among non-Japanese passengers entering Japan from India, we calculated the prevalence and then backcalculated the incidence in India from February 28 to July 3, 2021. Results The estimated number of infections ranged from 448 to 576 million people, indicating that 31.8% (95% confidence interval (CI): 26.1, 37.7) – 40.9% (95% CI: 33.5, 48.4) of the population in India had experienced COVID-19 infection from February 28 to July 3, 2021. In addition to obtaining cumulative incidence that was consistent with published estimates, we showed that the actual incidence of COVID-19 infection during the 2021 epidemic in India was approximately 30 times greater than that based on documented cases, giving a crude infection fatality risk of 0.47%. Adjusting for test-negative certificate before departure, the quality control of which was partly questionable, the cumulative incidence can potentially be up to 2.3–2.6 times greater than abovementioned estimates. Conclusions Our estimate of approximately 32–41% cumulative infection risk from February 28 to July 3, 2021 is roughly consistent with other published estimates, and they can potentially be greater, given an exit screening before departure. The present study results suggest the potential utility of border entry screening data to backcalculate the incidence in countries with limited surveillance capacity owing to a major surge in infections.

Background: The number of people undergoing voluntary HIV testing has abruptly decreased since 2020. The geographical heterogeneity of HIV infection and the impact of COVID-19 on the diagnosis of HIV at regional level are important to understand. This study aimed to estimate the HIV incidence by geographical region and understand how the COVID-19 pandemic influenced diagnosis of HIV. Methods: We used an extended back-calculation method to reconstruct the epidemiological dynamics of HIV/AIDS by geographical region. We used eight regions: Tokyo, the capital of Japan, Hokkaido plus Tohoku, Kanto plus Koshinetsu (excluding Tokyo), Hokuriku, Tokai, Kinki, Chugoku plus Shikoku, and Kyushu plus Okinawa. Four different epidemiological measurements were evaluated: (i) estimated HIV incidence, (ii) estimated rate of diagnosis, (iii) number of undiagnosed HIV infections, and (iv) proportion of HIV infections that had been diagnosed. Results: The incidence of HIV/AIDS during the COVID-19 pandemic from 2020 to 2022 increased in all regions except Kanto/Koshinetsu (51.3 cases/year), Tokyo (183.9 cases/year), Hokuriku (1.0 cases/year), and Tokai (43.1 cases/year). The proportion of HIV infections that had been diagnosed only exceeded 90% in Tokyo (91.7%, 95% confidence interval (CI): 90.6, 93.3), Kanto/Koshinetsu (91.0%, 95% CI: 87.3, 97.8), and Kinki (92.5%, 95% CI: 90.4, 95.9). The proportion of infections that had been diagnosed was estimated at 83.3% (95% CI: 75.1, 98.7) in Chugoku/Shikoku and 80.5% (95% CI: 73.9, 91.0) in Kyusyu/Okinawa. Conclusions: In urban regions with major metropolitan cities, including Tokyo, Kinki, and Kanto/Koshinetsu, the number of undiagnosed HIV infections is substantial. However, the proportion of undiagnosed infections was estimated to be smaller than in other regions. The diagnosed proportion was the lowest in Kyusyu/Okinawa (80.5%), followed by Chugoku/Shikoku and Hokkaido/Tohoku. The level of diagnosis in those regional prefectures may have been more influenced and damaged by the COVID-19 pandemic than in urban settings.

A single-photon avalanche diode (SPAD) is a photon-counting sensor renowned for its exceptional single-photon sensitivity. One significant feature of SPADs is their non-linear response to light, making them ideal for high-dynamic range imaging applications. In SPAD imaging, the photon detection mode, which depends on the quenching method employed, is crucial for optimizing image quality and dynamic range. This paper examines the free-running and gating imaging modes, evaluating their impacts on photon capture and saturation limits. Given that the number of incident photons follows a Poisson distribution, we introduce an innovative imaging-quenching model based on statistical mathematics. We designed and fabricated two SPAD imaging sensors using 180 nm CMOS technology. Image processing and evaluation were conducted using a mapping method. Our results show that in low-light conditions, the gating mode surpasses the free-running mode in the signal-to-noise ratio (SNR). However, the free-running mode exhibits a saturation limit of more than an order of magnitude higher than that of the gating mode, demonstrating its superior capability to handle a broader range of light intensities. This paper provides a thorough analysis of the differences between the two imaging methods, incorporating the theoretical mathematical model, circuit characteristics, and computed imaging quality.

In addition to dynamic methods, purely statistical models, i.e., findings from the statistical analysis of the existing measured database, also play an important role in predicting the different characteristics of climate elements. In our article, we try to estimate the monthly amount of global radiation in each day of the month. In our previous articles, we presented the sliding-average model developed for estimating the average or amount of a climatic element, measured over a time interval, from within the interval. A version of this model for estimating the end-of-interval sums, the sliding-sum model, was used to estimate the amount of monthly global radiation. After generating the characteristics required for the estimation and analyzing their properties, we examined the errors of the performed estimation. Our model can also help solar energy users create the schedule.

The purpose of the present study was to develop a transmission model of COVID-19 cases with and without a contact history to understand the meaning of the proportion of infected individuals with a contact history over time. We extracted epidemiological information regarding the proportion of coronavirus disease 2019 (COVID-19) cases with a contact history and analyzed incidence data stratified by the presence of a contact history in Osaka from January 15 to June 30, 2020. To clarify the relationship between transmission dynamics and cases with a contact history, we used a bivariate renewal process model to describe transmission among cases with and without a contact history. We quantified the next-generation matrix as a function of time; thus, the instantaneous (effective) reproduction number was calculated for different periods of the epidemic wave. We objectively interpreted the estimated next-generation matrix and replicated the proportion of cases with a contact p(t) over time, and we examined the relevance to the reproduction number. We found that p(t) does not take either the maximum or minimum value at a threshold level of transmission with R(t)=1.0. With R(t) < 1 (subcritical level), p(t) was a decreasing function of R(t). Qualitatively, the minimum p(t) was seen in the domain with R(t) > 1. An important future implication for use of the proposed model is to monitor the success of ongoing contact tracing practice. A decreasing signal of p(t) reflects the increasing difficulty of contact tracing. The present study findings indicate that monitoring p(t) would be a useful addition to surveillance.

Abstract Background It has been descriptively argued that the case fatality risk (CFR) of coronavirus disease (COVID-19) is elevated when medical services are overwhelmed. The relationship between CFR and pressure on health-care services should thus be epidemiologically explored to account for potential epidemiological biases. The purpose of the present study was to estimate the age-dependent CFR in Tokyo and Osaka over time, investigating the impact of caseload demand on the risk of death. Methods We estimated the time-dependent CFR, accounting for time delay from diagnosis to death. To this end, we first determined the time distribution from diagnosis to death, allowing variations in the delay over time. We then assessed the age-dependent CFR in Tokyo and Osaka. In Osaka, the risk of intensive care unit (ICU) admission was also estimated. Results The CFR was highest among individuals aged 80 years and older and during the first epidemic wave from February to June 2020, estimated as 25.4% (95% confidence interval [CI] 21.1 to 29.6) and 27.9% (95% CI 20.6 to 36.1) in Tokyo and Osaka, respectively. During the fourth wave of infection (caused by the Alpha variant) in Osaka the CFR among the 70s and ≥ 80s age groups was, respectively, 2.3 and 1.5 times greater than in Tokyo. Conversely, despite the surge in hospitalizations, the risk of ICU admission among those aged 80 and older in Osaka decreased. Such time-dependent variation in the CFR was not seen among younger patients

The article gives information about the attempt made to select configurations, train and test artificial neural networks for predicting yields of grain crops considering of climate changes. Peculiarities of agricultural production require constant improvement of methods for analyzing crop yields, time series, and longterm climatic characteristics. Preliminary statistical evaluation of the considered time series made it possible to identify certain patterns. Time series were divided into four intervals: for building a network, its training, testing and control. During the construction of artificial neural networks, three models were used: MLP - multilayer perceptron, RBF - r adial basis functions and GRNN - g eneralized regression neural network. Based on the results of the construction, the best model was chosen. The sum of active air temperatures and the sum of precipitation for the growing season was used for artificial neural networks at the input, and the crop yield was used at the output. The use of sets of neural systems, generated automatically, contributed to the effective forecasting of crop yields based on the analysis of climate data. As a result, according to the selected model, a yield forecast was made for the coming years considering climatic characteristics.

Applying a statistical test to check statistical assumptions offers a positive or negative response regarding the veracity of the issued hypothesis. In case of variance analysis it’s necessary to apply a post hoc test to determine differences within the group. Statistical estimation using confidence levels provides more information than a statistical test, it shows the high degree of uncertainty resulting from small samples and builds conclusions in terms of "marginally significant" or "almost significant (p being close to 0,05) . The case study shows how the statistical estimation completes the application form the analysis of variance test and Tukey test.

Background: A measles outbreak involving 60 cases occurred in Yamagata, Japan in 2017. Using two different mathematical models for different datasets, we aimed to estimate measles transmissibility over time and explore any heterogeneous transmission patterns. Methods: The first model relied on the temporal distribution for date of illness onset for cases, and a generation-dependent model was applied to the data. Another model focused on the transmission network. Using the illness-onset date along with the serial interval and geographical location of exposure, we reconstructed a transmission network with 19 unknown links. We then compared the number of secondary transmissions with and without clinical symptoms or laboratory findings. Results: Using a generation-dependent model (assuming three generations other than the index case), the reproduction number (R) over generations 0, 1, and 2 were 25.3, 1.3, and

This paper studies the consequences of imperfect information for the precision of stochastic optimization. In particular, it is assumed that the stochastic characteristics of an optimization problem depend on unknown parameters estimated from available data. First, a theoretical result is presented, showing that consistent parameters estimation leads to consistent optimization. Further, a type of the studied models is specified; it is assumed that the random variables present in the optimization problem are influenced by covariates. This influence is expressed via a parametric regression model, whose parameters have to be estimated and used instead of the unknown correct parameters values. The objective is then to explore, with the aid of simulations, the imprecision of the optimization based on these estimates. Several types of regression models are recalled, the variability of estimates and the related precision of sub-optimal solutions is studied in detail on an example dealing with optimal maintenance. The impact of random right-censoring on the deterioration of precision is studied as well.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has rapidly spread across the globe. The variant of concern (VOC) 202012/01 (B.1.1.7, also known as the alpha variant) bearing the N501Y mutation emerged in late 2020. VOC 202012/01 was more transmissible than existing SARS-CoV-2 variants and swiftly became dominant in many regions. More than 150 cases of VOC 202012/01 were reported in Japan by 26 February 2021. During the very early stage of introduction, only a subset arose from domestic transmission. If the reproduction number R (i.e., the average number of secondary transmission events caused by a single primary case) is greater than 1, the corresponding proportion should converge to 1 in a short period of time, and thus it is critical to understand the transmissibility of VOC 202012/01 based on travel history information. The present study aimed to estimate R of VOC 202012/01 using overseas travel history information. A mathematical model was developed to capture the relationship between travel history and R. We obtained travel history data for each confirmed case of VOC 202012/01 infection from 26 December 2020 to 26 February 2021. Maximum likelihood estimation was used to estimate R, accounting for right censoring during real-time estimation. In the baseline scenario, R was estimated at 2.11 (95% confidence interval: 1.63, 2.94). By 26 February 2021, an average of nine generations had elapsed since the first imported case. If the generation time of VOC 202012/01 was assumed to be longer, R was increased, consistent with estimates of R from case data. The estimated R of VOC 202012/01 in Japan exceeded 1 on 26 February 2021, suggesting that domestic transmission events caused a major epidemic. Moreover, because our estimate of R was dependent on generation time and ascertainment biases, continuous monitoring of contact tracing data is crucial to decipher the mechanisms of increased VOC 202012/01 transmissibility.

El conocimiento sobre lo saludable de los productos orgánicos abre posibilidades para el mejoramiento de la alimentación y posible reducción de enfermedades de tipo mórbidas. Este manuscrito analiza el efecto halo producido en la percepción del café orgánico en relación con cinco aspectos: sabor, nutrición, percepción saludable, natural y residual. Se aplican cinco diseños de experimentos factoriales, considerando entre otros, el factor producto/etiqueta de café cuyos niveles son: A, B, orgánico, regular y C; sin informar que A es café regular y B es café orgánico y C es un café regular. Los productos etiquetados como orgánicos se perciben más saludables, nutritivos y de mejores sabores; además, se encuentra que la etiqueta en el empaque del café orgánico genera un efecto halo al predisponer su percepción con mejor sabor y percepción saludable sobre los demás, aunque uno de ellos se enmascara con otra etiqueta siendo igual. La producción orgánica de café ha generado valor agregado, incrementando el mercado saludable y ambientalista, aprovechando la identidad alcanzada por los productos orgánicos, como se demuestra en la investigación por su alto valor agregado percibido, esto incrementa las posibilidades del marketing, ventas y nuevos desarrollos. The knowledge of the healthiness of organic products opens possibilities for the improvement of the diet and possible reduction of morbid diseases. The purpose of this study is to analyze the effect on the perceived value of coffee labeled organic with respect to aspects such as taste and nutritional perception. Five factorial experiment designs are applied, considering among others, the factor product/coffee label, whose levels are: A, B, organic, regular and C; without informing that A is regular coffee and B is organic coffee and C is regular coffee. The healthiest, most nutritious, and best tasting organic products are perceived; in addition, it is found that the label on the packaging of organic coffee generates a halo effect by predisposing its perception with better flavor and healthy perception over the other types of labeled products, even though one of them is masked with another label being from the same organic. The organic production of coffee has generated added value, increasing the healthy and environmental market, taking advantage of the identity achieved by organic products, as demonstrated in the research by its high perceived added value, contributing in the increase of possibilities of marketing, sales and new developments.

BackgroundPublic health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact; these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility.Materials and MethodsWe investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (Rt) before and after these interventions, and then analyzed the relationship between lower Rt values and each PHSM.ResultsWith implementation of pre-emergency measures (PEM) in 16 prefectures, the Rt was estimated to be < 1 in six prefectures; its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated Rt < 1, and the average relative reduction was 26%–39%. No single intervention was identified that uniquely resulted in an Rt value < 1.ConclusionAn SoE can substantially reduce the Rt and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the Rt value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.

BackgroundOsaka, the third largest prefecture in Japan, experienced a rapid replacement of preexisting strains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by variant alpha during March-April 2021. Assessing the burden of variant alpha on health centers and medical institutions is vital to anticipating the surge of patients. The present study aimed to estimate the age-dependent risks of coronavirus disease (COVID-19) putatively caused by variant alpha in Japan, focusing on epidemiological dynamics in Osaka.MethodsDescriptive analyses were conducted using data on confirmed, severe and fatal cases of COVID-19 from 16 November 2020 to 22 May 2021. All cases were divided into 6–9 age groups to compare the risks of confirmed diagnosis, severe illness and death from COVID-19 with variant alpha to those caused by preexisting strains.ResultsIndividuals with COVID-19 aged under 30 years were more likely to be infected with variant alpha than those in their 40s. The incidence of severe illness and death among all age groups with COVID-19 due to variant alpha was higher than that due to preexisting strains. Patients older than 40 years experienced an increased risk of severe illness and death if infected with variant alpha. However, the proportion of severe cases was lower in the group aged 80 years and older infected with variant alpha than in those infected with preexisting strains.ConclusionOur analysis suggests that the incidence of infection among young people aged below 30 years old increased relative to ordinary strains. Risks of severe illness and death in patients with variant alpha COVID-19 was higher than in those with preexisting strains in Osaka, Japan. However, a decrease in the risk of severe illness was observed in people aged ≥80 years, which is probably because medical facilities in Osaka were overwhelmed in April and May 2021. Continuous monitoring of COVID-19 cases with new variants is vital to secure sufficient medical resources for all patients who require medical care.

The article is devoted to the problems of scenario modeling in relation to solving a number of problems of managing the health care system of the Perm Territory, which in recent years has attracted attention by the development of a number of promising projects to develop this industry, to expand the availability of medical services and to improve the level of medical care for the population. Since any good-quality project must be directly linked not only to the future periods of its implementation, but also be scientifically justified in terms of insuring all kinds of risks and threats that will stand in the way of the successful completion of the project, recently all kinds of projects, programs and plans are often developed are created using the so-called scenario approach. Several options for the development of events with this approach are offered to the appropriate circle of leaders or the power structure for the subsequent adoption of an appropriate management decision.The authors of the article consider the main provisions and principles of the scenario approach using the example of the development of the health care system of a particular subject of the federation, which makes the material proposed for consideration very relevant. The authors also define, as they see it, the main result of improving the industry in the form of a target and a national goal — the expected (upcoming) life expectancy of the population of the study area. This socio-economic indicator, which has all the signs of fatefulness, is considered by the authors to be a priority analytical indicator of the level and quality of an effective life of a Russian. The latter determines the purpose of this study.The authors consider the construction of dynamic multivariate models of industry development options for a period of up to three years to be an efficient tool for analyzing and forecasting this indicator, which is presented in the article in the form of five simultaneous equations of multiple regressions. The results of this construction are continued by discussion, and the article ends with the list of the conclusions. The authors also inform the reader about the further direction of their scientific research.

In continuation of the article, the authors of the study devoted to the problems of scenario modeling and solving specific problems of management and development of the health care system of the Perm Territory, built the author’s dynamic multivariate model, which was based on an authoritative approach and consists of a set of five structural simultaneous equations. As a result, each equation of the system is a linear form of recursive regression, where the independent variable as a factor-factor taken into account in one equation becomes a depend- ent variable as an effective factor-factor. In order to eliminate the phenomenon of autocor- relation of residual values, the method of time lagging was used. To estimate the parameters of the reduced form of structural simultaneous equations, the two-step least squares method was used as a special case of the maximum likelihood method. The obtained parameter esti- mates on the whole turned out to be effective with moderate consistency and satisfactory bias. The constructed model made it possible to carry out a short-term forecast of the most important target socio-economic indicator of the success of healthcare development in the region until 2023. The authors considered the national goal as such a priority indicator — the expected (future) life expectancy of the population of the study area. At the end of the article, conclusions were drawn and the prospects for further scientific research of the authors were outlined.

The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy. In this paper, we identify and discuss four broad challenges in the estimation paradigm relating to infectious disease modelling, namely the Uncertainty Quantification framework, data challenges in estimation, model-based inference and prediction, and expert judgement. We also postulate priorities in estimation methodology to facilitate preparation for future pandemics.

This work is dedicated to the construction and evaluation of random number generators used in cryptography. The critical element on which the security of information is based is the cryptographic key (usually a binary sequence). In order to be resistant to brute force attacks it is necessary that it be made up of random variables with a certain degree of randomness and independence. Formally, this comes back to generate the cryptographic key through the systems which ensures a certain minimum level of entropy. The observer has access to a sample, of a certain size, and based on it he will estimate the minimum value of the entropy, in the situations in which the variables resulting from the measurement process are independent. In the situation where these variables are not independent, complex mathematical procedures also allow estimation of the minimum entropy. This article is a review of how mathematical entropy can be estimated and evaluated, of the construction mode (from technologies based on analogue procedures: thermal noise in a transistor to modern procedures: quantum devices), as well as to evaluate the security of binary sequence generators used for generating cryptographic keys or critical security parameters related to new technologies based on quantum principles. The techniques and methods used to generate binary random values as well as the methods of statistical and informational validation (Shannon entropy) are exemplified in this paper.

This work presents a Bayesian statistical approach to the saliency map estimation problem. More specifically, we formalize the saliency map estimation issue in the fully automatic Markovian framework. The major and original contribution of the proposed Bayesian–Markov model resides in the exploitation of a pixel pairwise modeling and a likelihood model based on a parametric mixture of two different class-conditional likelihood distributions whose parameters are adaptively and previously estimated for each image. This allows us to adapt our saliency estimation model to the specific characteristics of each image of the dataset and to provide a nearly parameter-free—hence dataset-independent—unsupervised saliency map estimation procedure. In our case, the parameters of the likelihood model are all estimated under the principles of the iterative conditional estimation framework. Once the estimation step is completed, the MPM (maximum posterior marginal) solution of the saliency map (which we show as particularly suitable for this type of estimation), is then estimated by a stochastic sampling scheme approximating the posterior distribution (whose parameters were previously estimated). This unsupervised data-driven Markovian framework overcomes the limitations of current ad hoc or supervised energy-based or Markovian models that often involve many parameters to adapt and that are finely tuned for each different benchmark database. Experimental results show that the proposed algorithm performs favorably against state-of-the-art methods and turns out to be particularly stable across a wide variety of benchmark datasets.

A simple and efficient method to remove white Gaussian noises and physiological noises from electrocardiogram (ECG) signals is presented. It is based on simple tools usually used in digital signal processing like moving average filter, median filter, baseline drift removal and peak detection. We show by several simulations that the proposed algorithm outperforms significantly conventional median filter and moving average filter and can be considered as a valid concurrent to the standard wavelet-based method.

Whilst several methods exist to provide sample estimates of the probability distribution function at several points, for the probability density of continuous stochastic variables, only a gross representation through the histogram is typically used. It is shown that the newly introduced concept of knowable moments (K-moments) can provide smooth empirical representations of the distribution function, which in turn can yield point and interval estimates of the density function at a large number of points or even at any arbitrary point within the range of the available observations. The proposed framework is simple to apply and is illustrated with several applications for a variety of distribution functions.

Abstract Data scientists need scalable methods to explore and clean big data before applying advanced data analysis and mining algorithms. In this paper, we propose the RSP-Explore method to enable data scientists to iteratively explore big data on small computing clusters. We address three main tasks: statistical estimation, error detection, and data cleaning. The Random Sample Partition (RSP) distributed data model is used to represent the data as a set of ready-to-use random sample data blocks (called RSP blocks) of the entire data. Block-level samples of RSP blocks are selected to understand the data, identify potential types of value errors, and get samples of clean data. We provide a theoretical analysis on using RSP blocks for statistical estimation and demonstrate empirically the advantages of the RSP-Explore method. The experimental results of three real data sets show that the approximate results from RSP-Explore can rapidly converge toward the true values. Furthermore, cleaning a sample of RSP blocks is sufficient to estimate the statistical properties of the unknown clean data.

The survey of protocols of estimation and performance tests of the biometrical systems, and general metrics of the investigation used in case of research of characteristics in biometry are provided. The primary factors of impact on performance criteria of biometrical systems are investigated.

The article is devoted to the problems of scenario modeling in relation to solving a number of problems of managing the health care system of the Perm Territory, which in recent years has at-tracted attention by the development of a number of promising projects to develop this industry, to expand the availability of medical services and to improve the level of medical care for the population. Since any good-quality project must be directly linked not only to the future periods of its implementation, but also be scientifically justified in terms of insuring all kinds of risks and threats that will stand in the way of the successful completion of the project, recently all kinds of projects, programs and plans are often developed are created using the so-called scenario ap-proach. Several options for the development of events with this approach are offered to the ap-propriate circle of leaders or the power structure for the subsequent adoption of an appropriate management decision. The authors of the article consider the main provisions and principles of the scenario approach using the example of the development of the health care system of a particular subject of the fed-eration, which makes the material proposed for consideration very relevant. The authors also de-fine, as they see it, the main result of improving the industry in the form of a target and a national goal - the expected (upcoming) life expectancy of the population of the study area. This socio-economic indicator, which has all the signs of fatefulness, is considered by the authors to be a priority analytical indicator of the level and quality of an effective life of a Russian. The latter determines the purpose of this study. The authors consider the construction of dynamic multivariate models of industry development options for a period of up to three years to be an efficient tool for analyzing and forecasting this indicator, which is presented in the article in the form of five simultaneous equations of multiple regressions. The results of this construction are continued by discussion, and the article ends with a list of conclusions.

For achieving motor recovery in individuals with sensorimotor deficits, augmented activation of the appropriate sensorimotor system, and facilitated induction of neural plasticity are essential. An emerging procedure that combines peripheral nerve stimulation and its associative stimulation with central brain stimulation is known to enhance the excitability of the motor cortex. In order to effectively apply this paired stimulation technique, timing between central and peripheral stimuli must be individually adjusted. There is a small range of effective timings between two stimuli, or the inter-stimulus interval window (ISI-W). Properties of ISI-W from neuromodulation in response to mechanical stimulation (Mstim) of muscles have been understudied because of the absence of a versatile and reliable mechanical stimulator. This paper adopted a combination of transcranial magnetic stimulation (TMS) and Mstim by using a high-precision robotic mechanical stimulator. A pneumatically operated robotic tendon tapping device was applied. A low-friction linear cylinder achieved high stimulation precision in time and low electromagnetic artifacts in physiological measurements. This paper describes a procedure to effectively estimate an individual ISI-W from the transiently enhanced motor evoked potential (MEP) with a reduced number of paired Mstim and sub-threshold TMS trials by applying statistical sampling and regression technique. This paper applied a total of four parametric and non-parametric statistical regression methods for ISI-W estimation. The developed procedure helps to reduce time for individually adjusting effective ISI, reducing physical burden on the subject.

Background: Foodborne norovirus outbreak data in Japan from 2005–2006, involving virological surveillance of all symptomatic and asymptomatic individuals, were reanalyzed to estimate the asymptomatic ratio of norovirus infection along with the risk of infection and the probability of virus shedding. Methods: Employing a statistical model that is considered to capture the data-generating process of the outbreak and virus surveillance, maximum likelihood estimation of the asymptomatic ratio was implemented. Results: Assuming that all norovirus outbreaks (n = 55) were the result of random sampling from an identical distribution and ignoring genogroup and genotype specificities, the asymptomatic ratio was estimated at 32.1% (95% confidence interval [CI], 27.7–36.7). Although not significant, separate estimation of the asymptomatic ratio of the GII.4 genotype appeared to be greater than other genotypes and was estimated at 40.7% (95% CI, 32.8–49.0). Conclusion: The present study offered the first explicit empirical estimates of the asymptomatic ratio of norovirus infection in natural infection settings. The estimate of about 30% was consistent with those derived from volunteer challenge studies. Practical difficulty in controlling GII.4 outbreaks was supported by the data, considering that a large estimate of the asymptomatic ratio was obtained for the GII.4 genotype.

To assess the development of renewable energy sources, the structuring of indicators in three groups is performed, namely: economic, environmental, and social ones. The method to calculate the assessment of the development of renewable energy sources in the world based on an integral indicator is substantiated. It is determined that the integral indicator for assessing the development of renewable energy sources reflects the impact of the group indicators. It also determines functional relationships between individual indicators. A method for calculating the corresponding coefficients of influence on the generalizing indicator of the development of renewable energy sources is proposed, and its graphic interpretation is provided. In accordance with the methodology of Harrington, Derringer and Suich, a relationship was established between the quantitative values of the scale of desirability and the perception of the state of development of renewable energy sources. Based on data from the State Statistics Service of Ukraine, IRENA, IEA and REN21 for the period 2006–2016, a comprehensive assessment of the development of renewable energy sources in Ukraine is carried out using the proposed methodology. The results of the calculations indicate a positive trend in the changes of the synthesis indicator and the stable development of renewable energy sources in the country.

The primary purpose of this research is to assess the long-range energy demand assumption made in relevant Roadmaps for the transformation to a low-carbon energy system. A novel interdisciplinary approach is then implemented: a new model is estimated for the aggregated world primary energy demand with long historical time series for world energy, income, and population for the years 1900–2017. The model is used to forecast energy demand in 2050 and assess the uncertainty-derived risk based on the variances of the series and parameters analysed. The results show that large efficiency savings—up to 50% in some cases and never observed before—are assumed in the main Roadmaps. This discrepancy becomes significantly higher when even moderate uncertainty assumptions are taken into account. A discussion on possible future sources of breaks in current patterns of energy supply and demand is also presented, leading to a new conclusion requiring an active political stance to accelerate efficiency savings and lifestyle changes that reduce energy demand, even if energy consumption may be reduced significantly. This will likely include replacing the income-growth paradigm with other criteria based on prosperity or related measures.

Objectives: Despite the verification of measles elimination, Japan experienced multiple generations of measles transmission following importation events in 2016. The purpose of the present study was to analyze the transmission dynamics of measles in Japan, 2016, estimating the transmission potential in the partially vaccinated population. Methods: All diagnosed measles cases were notified to the government, and the present study analyzed two pieces of datasets independently, i.e., the transmission tree of the largest outbreak in Osaka (n = 49) and the final size distribution of all importation events (n = 23 events). Branching process model was employed to estimate the effective reproduction number Rv, and the analysis of transmission tree in Osaka enabled us to account for the timing of introducing contact tracing and case isolation. Results: Employing a negative binomial distribution for the offspring distribution, the model with time-dependent decline in Rv due to interventions appeared to best fit to the transmission tree data with Rv of 9.20 (95% CI (confidence interval): 2.08, 150.68) and the dispersion parameter 0.32 (95% CI: 0.07, 1.17) before interventions were introduced. The relative transmissibility in the presence of interventions from week 34 was estimated at 0.005. Analyzing the final size distribution, models for subcritical and supercritical processes fitted equally well to the observed data, and the estimated reproduction number from both models did not exclude the possibility that Rv > 1. Conclusions: Our results likely reflect the highly contagious nature of measles, indicating that Japan is at risk of observing multiple generations of measles transmission given imported cases. Considering that importation events may continue in the future, supplementary vaccination of adults needs to be considered.

Flux quantification for riverine water-quality constituents has been an active area of research. Statistical approaches are often employed to make estimation for days without observations. One such approach is the Weighted Regressions on Time, Discharge, and Season (WRTDS) method. While WRTDS has been used in many investigations, there is a general lack of effort to identify factors that influence its estimation bias. This work was aimed to (1) synthesize and compare WRTDS estimation bias for constituent concentrations and fluxes for rivers and streams in the Chesapeake Bay watershed (including headwater sites) and (2) identify controlling factors from five broad categories (watershed size, sampling practice, concentration and discharge conditions, land use, and geology). Five major constituents were considered, namely, suspended sediment (SS), total phosphorus (TP), total nitrogen (TN), orthophosphate (PO4), and nitrate-plus-nitrite (NOx). For both concentration and flux, estimation bias follows the general order of SS > TP > PO4 > TN ≈ NOx. Median TN and NOx bias statistics were near zero, with an equal distribution of small positive and negative bias. TP, PO4, and SS each showed a median positive bias across sites of

Background Epidemiological surveillance of HIV infection in Japan involves two technical problems for directly applying a classical backcalculation method, i.e., (i) all AIDS cases are not counted over time and (ii) people diagnosed with HIV have received antiretroviral therapy, extending the incubation period. The present study aimed to address these issues and estimate the HIV incidence and the proportion of diagnosed HIV infections, using a simple statistical model. Methods From among Japanese nationals, yearly incidence data of HIV diagnoses and patients with AIDS who had not previously been diagnosed as HIV positive, from 1985 to 2017, were analyzed. Using the McKendrick partial differential equation, general convolution-like equations were derived, allowing estimation of the HIV incidence and the time-dependent rate of diagnosis. A likelihood-based approach was used to obtain parameter estimates. Results Assuming that the median incubation period was 10.0 years, the cumulative number of HIV infections was estimated to be 29,613 (95% confidence interval (CI): 29,059, 30,167) by the end of 2017, and the proportion of diagnosed HIV infections was estimated at 80.3% (95% CI [78.7%–82.0%]). Allowing the median incubation period to range from 7.5 to 12.3 years, the estimate of the proportion diagnosed can vary from 77% to 84%. Discussion The proportion of diagnosed HIV infections appears to have not yet reached 90% among Japanese nationals. Compared with the peak incidence from 2005–2008, new HIV infections have clearly been in a declining trend; however, there are still more than 1,000 new HIV infections per year in Japan. To increase the diagnosed proportion of HIV infections, it is critical to identify people who have difficulty accessing consultation, testing, and care, and to explore heterogeneous patterns of infection.

Objectives: There has been a growing concern over Zika virus (ZIKV) infection, particularly since a probable link between ZIKV infection during pregnancy and microcephaly in the baby was identified. The present study aimed to estimate a theoretical risk of microcephaly during pregnancy with ZIKV infection in Northeastern Brazil in 2015. Methods: Temporal distributions of microcephaly, reported dengue-like illness and dengue seropositive in Brazil were extracted from secondary data sources. Using an integral equation model and a backcalculation technique, we estimated the risk of microcephaly during pregnancy with Zika virus infection. Results: If the fraction of Zika virus infections among a total of seronegative dengue-like illness cases is 30%, the risk of microcephaly following infection during the first trimester was estimated at 46.7% (95% CI: 9.1, 84.2), comparable to the risk of congenital rubella syndrome. However, the risk of microcephaly was shown to vary widely from 14.0% to 100%. The mean gestational age at delivery with microcephaly was estimated at 37.5 weeks (95% CI: 36.9, 39.3). Conclusions: The time interval between peaks of reported dengue-like illness and microcephaly was consistent with cause–outcome relationship. Our modeling framework predicts that the incidence of microcephaly is expected to steadily decline in early 2016, Brazil.

In this work, we extended a procedure for the spatial decorrelation of fully-developed speckle, originally developed for single-polarization SAR data, to fully-polarimetric SAR data. The spatial correlation of the noise depends on the tapering window in the Fourier domain used by the SAR processor to avoid defocusing of targets caused by Gibbs effects. Since each polarimetric channel is focused independently of the others, the noise-whitening procedure can be performed applying the decorrelation stage to each channel separately. Equivalently, the noise-whitening stage is applied to each element of the scattering matrix before any multilooking operation, either coherent or not, is performed. In order to evaluate the impact of a spatial decorrelation of the noise on the performance of polarimetric despeckling filters, we make use of simulated PolSAR data, having user-defined polarimetric features. We optionally introduce a spatial correlation of the noise in the simulated complex data by means of a 2D separable Hamming window in the Fourier domain. Then, we remove such a correlation by using the whitening procedure and compare the accuracy of both despeckling and polarimetric features estimation for the three following cases: uncorrelated, correlated, and decorrelated images. Simulation results showed a steady improvement of performance scores, most notably the equivalent number of looks (ENL), which increased after decorrelation and closely attained the value of the uncorrelated case. Besides ENL, the benefits of the noise decorrelation hold also for polarimetric features, whose estimation accuracy is diminished by the correlation. Also, the trends of simulations were confirmed by qualitative results of experiments carried out on a true Radarsat-2 image.

Foreign tax administration includes the collection of local tax only. The article represents international experience of local tax administration based on this principal.

Objectives: Zika virus has spread internationally through countries in the South Pacific and Americas. The present study aimed to estimate the basic reproduction number, R0, of Zika virus infection as a measurement of the transmission potential, reanalyzing past epidemic data from the South Pacific. Methods: Incidence data from two epidemics, one on Yap Island, Federal State of Micronesia in 2007 and the other in French Polynesia in 2013–2014, were reanalyzed. R0 of Zika virus infection was estimated from the early exponential growth rate of these two epidemics. Results: The maximum likelihood estimate (MLE) of R0 for the Yap Island epidemic was in the order of 4.3–5.8 with broad uncertainty bounds due to the small sample size of confirmed and probable cases. The MLE of R0 for French Polynesia based on syndromic data ranged from 1.8 to 2.0 with narrow uncertainty bounds. Conclusions: The transmissibility of Zika virus infection appears to be comparable to those of dengue and chikungunya viruses. Considering that Aedes species are a shared vector, this finding indicates that Zika virus replication within the vector is perhaps comparable to dengue and chikungunya.

Objectives: A large cluster of the Middle East respiratory syndrome (MERS) linked to healthcare setting occurred from May to July 2015 in the Republic of Korea. The present study aimed to estimate the case fatality ratio (CFR) by appropriately taking into account the time delay from illness onset to death. We then compare our estimate against previously published values of the CFR for MERS, i.e., 20% and 40%. Methods: Dates of illness onset and death of the MERS outbreak in the Republic of Korea were extracted from secondary data sources. Using the known distribution of time from illness onset to death and an integral equation model, we estimated the delay-adjusted risk of MERS death for the South Korean cluster. Results: Our most up-to-date estimate of CFR for the MERS outbreak in South Korea was estimated at 20.0% (95% confidence intervals (CI): 14.6, 26.2). During the course of the outbreak, estimate of the CFR in real time appeared to have decreased and become significantly lower than 40%. Conclusions: The risk of MERS death in Korea was consistent with published CFR. The estimate decreased with time perhaps due to time-dependent increase in case ascertainment. Crude ratio of cumulative deaths to cases underestimates the actual risk of MERS death because of time delay from illness onset to death.

We characterize the statistical bootstrap for the estimation of informationtheoretic quantities from data, with particular reference to its use in the study of large-scale social phenomena. Our methods allow one to preserve, approximately, the underlying axiomatic relationships of information theory—in particular, consistency under arbitrary coarse-graining—that motivate use of these quantities in the first place, while providing reliability comparable to the state of the art for Bayesian estimators. We show how information-theoretic quantities allow for rigorous empirical study of the decision-making capacities of rational agents, and the time-asymmetric flows of information in distributed systems. We provide illustrative examples by reference to ongoing collaborative work on the semantic structure of the British Criminal Court system and the conflict dynamics of the contemporary Afghanistan insurgency.

Background. An international spread of Zika virus (ZIKV) infection has attracted global attention. ZIKV is conveyed by a mosquito vector, Aedes species, which also acts as the vector species of dengue and chikungunya viruses. Methods. Arrival time of ZIKV importation (i.e., the time at which the first imported case was diagnosed) in each imported country was collected from publicly available data sources. Employing a survival analysis model in which the hazard is an inverse function of the effective distance as informed by the airline transportation network data, and using dengue and chikungunya virus transmission data, risks of importation and local transmission were estimated. Results. A total of 78 countries with imported case(s) have been identified, with the arrival time ranging from 1 to 44 weeks since the first ZIKV was identified in Brazil, 2015. Whereas the risk of importation was well explained by the airline transportation network data, the risk of local transmission appeared to be best captured by additionally accounting for the presence of dengue and chikungunya viruses. Discussion. The risk of importation may be high given continued global travel of mildly infected travelers but, considering that the public health concerns over ZIKV infection stems from microcephaly, it is more important to focus on the risk of local and widespread transmission that could involve pregnant women. The predicted risk of local transmission was frequently seen in tropical and subtropical countries with dengue or chikungunya epidemic experience.

Verification of statistical cloudiness estimations for Europe. The climate forcing induced by cloud cover consists one of the main doubtful aspect of climate change predictions. In the case of cloudiness even the sign of the trends are not cohesive in a given region. In this sense further investigation regarding the behavior of cloudiness are indicated. In this study a statistical estimation of total cloudiness is elaborated using the method of instrumental variables. For this analyze surface-observed monthly mean cloudiness data was applied for the period of 1973-1996. In the second part of the study the verification of results is established using an independent satellite retrieved data series for the period of 2005-2011. Based on verification can be conclude that the applied statistical estimation is able to reproduce the measured values with an RMSE 7, 3%, the difference between the measured and predicted changes of cloudiness is 1.44%, found a stronger decrease of cloudiness in real data as the estimation had indicate. The main differences between the observed and predicted value is evident in the distribution of the frequencies showing a shifting towards the lower values in observed data but not recognized in the estimated values. In the geographical distribution of estimations errors sign a difference is detected between the water surfaces and continental regions.

In recent years, the state-of-the-art research has been dealing with putting into traffic, withdrawing and freeing the environment from electrical and electronic equipment waste-WEEE. In our country there has been no serious research so far concerning this problem, although current and future members of the European Union (EU) are obligated to conduct WEEE directive based on individual responsibility of each "waste manufacturer". The Ministry of Science and Environmental Protection of Serbia has accepted the financing of scientific research project called "The development of electrical and electronic equipment recycling system". In this paper, statistical estimation method of quantity and diffusion of computer waste (which according to the EU classification, belongs to the third category WEEE-devices for computer and communication technique) in the territory of Serbia is described. The implications of the problem on our country are also presented.