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Purpose: The aim of this study was to determine the influence of utilization of online past examination papers on academic performance of IT students at Jomo Kenyatta University.Methodology: Descriptive survey research design was used in this study. Respondents were the 105 undergraduate students in Information Technology Department and 2 librarians in Jomo Kenyatta University of Agriculture and Technology-Eldoret Campus. They were sampled using stratified sampling, while Head of library and the library staff in charge of e-resources in JKUAT Eldoret Campus were purposively included in the study. Primary data was collected from students using closed-ended questionnaires, while interview guide was used on librarians. To ensure validity and reliability, pre-testing of research instruments was done on 20 undergraduate students of Mount Kenya university-Eldoret Campus in the department of Information Technology. D Descriptive statistics such as mean, percentage, frequencies and standard deviation, SPSS (version 22) was used in analysing data. Univariate and multiple regression analysis were used to test the hypothesis and overall model respectively. The results were presented using tables and explanations.Results: There is a positive and significant relationship between online past examination papers and academic performance of IT undergraduate students of Jomo Kenyatta University of Agriculture and Technology - Eldoret Campus. The study had a normal mean of 4.7 and standard deviation of 0.58. The online past examination papers had R estimation of 0.715. The P estimation of constant was significant (.000), consequently R square value was used. The R square estimation of 0.711 inferred that online past assessment papers anticipated 71.1% of the fluctuation in the academic performance. It had a beta of 0.504 at p

An interpretable convolutional neural network (CNN) including attribute estimation for image classification is presented in this paper. Although CNNs perform highly accurate image classification, the reason for the classification results obtained by the neural networks is not clear. In order to provide interpretation of CNNs, the proposed method estimates attributes, which explain elements of objects, in an intermediate layer of the network. This enables improvement of the interpretability of CNNs, and it is the main contribution of this paper. Furthermore, the proposed method uses the estimated attributes for image classification in order to enhance its accuracy. Consequently, the proposed method not only provides interpretation of CNNs but also realizes improvement in the performance of image classification.

How best to estimate the accuracy of a predictive rule has been a longstanding question in statistics. Approaches to this task range from simple methods like Mallow’s Cp to algorithmic techniques l...

This dissertation includes three chapters that cover broad topics in economics. The first chapter explores how the US Government's Capital Purchase Program, a large capital injection to local and regional banks through a stock purchase agreement, impacted local establishment dynamics such as entry, exit, employment expansion, and employment contraction following the 2008 Financial Crisis. The Capital Purchase Program dispersed over \$200 billion dollars to banks hoping to prevent failure and ease tightened lending conditions. I estimate the direct effects of a county having a bank receive Capital Purchase Program funds on local business dynamics in the seven years following treatment, as well as spillover effects as entrepreneurs and business in neighboring regions travel to gain access to credit. Estimates show the CPP had no effect on establishment entry and exit, nor employment expansion and contraction. This paper establishes that the business-lending aims of the CPP were not realized in the communities and regions that received funds, and casts further doubt on meaningful pass through of CPP funds to desirable local economic activity.The second chapter develops a joint hypothesis centered Wald test over fixed effects in large N small T panel data models with symmetric serial correlation within cross sectional observations. The enables joint hypothesis tests over inconsistently estimated fixed effects, such as the traditional varying intercept model as well as models with individual specific slope coefficients. I establish two different set of assumptions where feasible tests exist. The first assumption requires that individual errors follow a stationary $\ARp$ process. Under this assumption all second and fourth cross product moments can be consistently estimated while allowing for individual specific hypothesis and covariates to vary across individuals and time with individual specific slopes. The second feasible test requires individuals to have coefficient slopes that are shared among all individuals in a known grouping structure under the null. This set of assumptions enables estimation of a completely unconstrained variance-covariance matrix and higher cross product moments for individuals. Examples of these tests arise in wanting to establish latent panel structure, such as unobserved grouping of individuals, wanting to compare different models of teacher or firm value added against each other, or testing whether or not fixed effects can be approximated by Mundlak-Chamberlain devices.Finally, the third paper estimates how messages displaced on Dynamic Message Boards, large signs either adjacent to or displayed above roads, impact near to sign accidents. In this research, I look at the traffic-related messages such as ``drive sober,'' ``x deaths on roads this year,'' and ``click it or ticket,'' displayed on major highways, on reported near-to-sign traffic accidents. This provides estimates of the impact of different types of nudges on road safety behavior. To estimate the causal effect of these nudges, we build a new high-frequency panel data set using the information on the time and location of messages, crashes, overall traffic levels, and weather conditions using the data of the state of Vermont over a three year time period. I estimate models that control for endogeneity of displayed messages, or allow for spillover effects from neighboring messages.

The new pandemic disease caused by COVID-19 virus is the crucial event over the world in the beginning of 2020. Studies on corona viruses have been however carried since several decades ago, with recent research papers published on weekly basis. We demonstrate a simple approach to explore CORD-19 dataset to provide a high level overview of important semantic changes that occurred over time. Our method aims to support better understanding of large domain-specific collections of scholarly publications that span long time periods and could be regarded as complementary to frequency-based analysis.

In this study, the role of turbulence-chemistry interaction in diesel spray auto-ignition, flame stabilization and end of injection phenomena is investigated under engine relevant “Spray A” conditions. A recently developed diesel spray combustion modeling approach, Conditional Source-term Estimation (CSE-FGM), is coupled with Reynolds-averaged Navier-Stokes simulation (RANS) framework to study the details of spray combustion. The detailed chemistry mechanism is included through the Flamelet Generated Manifold (FGM) method. Both unsteady and steady flamelet solutions are included in the manifold to account for the auto-ignition process and the subsequent flame propagation in a diesel spray. Conditionally averaged chemical source terms are closed by the conditional scalars obtained in the CSE routine. Both non-reacting and reacting spray jets are computed over a wide range of Engine Combustion Network (ECN) diesel. “Spray A” conditions. The reacting spray results are compared with simulations using a homogeneous reactor combustion model and a flamelet combustion model with the same chemical mechanism. The present study represents the first application of CSE for a diesel spray. The non-reacting liquid/vapour penetration, the mean and RMS mixture fraction, the reactive region, the flame lift-off and the ignition delay show a good agreement with literature data from an optically accessible combustion vessel over a wide range of tested conditions. The CSE-FGM model also shows a better capability in predicting the end-of-injection events in diesel spray combustion. Overall, the CSE-FGM model is shown to capture the experimental trends well, both quantitatively and qualitatively.

I review my scientific career in terms of eight areas and 16 papers. The first two areas are associated with childhood. The other six are associated with residual maximum likelihood (REML), canonical transformation, inbreeding in selected populations, average information residual maximum likelihood (AIREML), the computer program ASReml and sampling-based estimation.

The production efficiency and shadow prices of three environmental outputs (BOD, COD, and SS) of 63 household-level paper-recycling units, from a recycling craft village in Vietnam, are assessed A two-stage procedure, linear programming and stochastic estimation, is used to estimate output distance function. Social capital as a production factor and environmental outputs are included in the output distance function. Results indicate that production efficiencies could potentially be improved by 28%. There is a substantial variation in the shadow prices of environmental outputs among the production units of different types of paper products. Furthermore, the average shadow prices of the three environmental outputs are all positive. This indicates a potential for improving environmental quality though introducing pollution-prevention methods to paper-recycling production processes in Vietnam (e.g., recirculation of wastewater), and suggests that it may be inappropriate to restrict the shadow prices of environmental outputs to be non-positive for the analysis of some production processes.

The data presented here are manually encoded characteristics of research papers in the area of Energy-Economy Nexus (empirical investigation of Granger causality between energy consumption and economic growth) that describe the methods, samples, and other details related to the individual estimations done in the examined empirical papers. Data cover papers indexed by Scopus, published in economic journals, written in English, after year 2000. In addition, papers were manually filtered to only those that deal with Energy-Economy Nexus investigation and have at least 10 citations at (at the time of query – November 2015). This data are to be used to conduct meta-analysis – associated dataset was used in Hajko [1] . Early version of the dataset was used for multinomial logit estimation in Master thesis by Kocianova [2] .

The purpose of this paper is to analyse the rate and the impacts of technical change in the Swedish pulp and paper industry. In contrast to earlier research on this industry we replace the standard time trend with time-specific dummy variables enabling the estimation and decomposing of a general index of technical change. The analysis is made within a Translog cost function model, which is estimated using a panel data set with observations across individual paper and board mills over the time period 1974–1994. Our results indicate that the highest rates of technical change have generally occurred during the latter part of this period. Pure technical change is the primary component that has directed technical change over the entire time period. We also find evidence of non-neutral technical change. Energy use has been stimulated by technical improvements while labour use has been discouraged. Also, technical change has had wastepaper and woodpulp using impacts. However, the magnitudes of these latter impacts are relatively small, implying that the increase in wastepaper use during the last decades has mainly been stimulated by relative price changes.

The usage of psychological networks that conceptualize psychological behavior as a complex interplay of psychological and other components has gained increasing popularity in various fields of psychology. While prior publications have tackled the topics of estimating and interpreting such networks, little work has been conducted to check how accurate (i.e., prone to sampling variation) networks are estimated, and how stable (i.e., interpretation remains similar with less observations) inferences from the network structure (such as centrality indices) are. In this tutorial paper, we aim to introduce the reader to this field and tackle the problem of accuracy under sampling variation. We first introduce the current state-of-the-art of network estimation. Second, we provide a rationale why researchers should investigate the accuracy of psychological networks. Third, we describe how bootstrap routines can be used to (A) assess the accuracy of estimated network connections, (B) investigate the stability of centrality indices, and (C) test whether network connections and centrality estimates for different variables differ from each other. We introduce two novel statistical methods: for (B) the correlation stability coefficient, and for (C) the bootstrapped difference test for edge-weights and centrality indices. We conducted and present simulation studies to assess the performance of both methods. Finally, we developed the free R-package bootnet that allows for estimating psychological networks in a generalized framework in addition to the proposed bootstrap methods. We showcase bootnet in a tutorial, accompanied by R syntax, in which we analyze a dataset of 359 women with posttraumatic stress disorder available online., Comment: Accepted for publication in Behavior Research Methods

IntroductionDecreasing participation levels in health surveys pose a threat to the validity of estimates intended to be representative of their target population. If participants and non-participants differ systematically, the results may be biased. The application of traditional non-response adjustment methods, such as weighting, can fail to correct for such biases, as estimates are typically based on the sociodemographic information available. Therefore, a dedicated methodology to infer on non-participants offers advancement by employing survey data linked to administrative health records, with reference to data on the general population. We aim to validate such a methodology in a register-based setting, where individual-level data on participants and non-participants are available, taking alcohol consumption estimation as the exemplar focus.Methods and analysisWe made use of the selected sample of the Health 2000 survey conducted in Finland and a separate register-based sample of the contemporaneous population, with follow-up until 2012. Finland has nationally representative administrative and health registers available for individual-level record linkage to the Health 2000 survey participants and invited non-participants, and the population sample. By comparing the population sample and the participants, synthetic observations representing the non-participants may be generated, as per the developed methodology. We can compare the distribution of the synthetic non-participants with the true distribution from the register data. Multiple imputation was then used to estimate alcohol consumption based on both the actual and synthetic data for non-participants, and the estimates can be compared to evaluate the methodology’s performance.Ethics and disseminationEthical approval and access to the Health 2000 survey data and data from administrative and health registers have been given by the Health 2000 Scientific Advisory Board, Statistics Finland and the National Institute for Health and Welfare. The outputs will include two publications in public health and statistical methodology journals and conference presentations.

In controlling uncertain processes, it is decisive to utilize information provided by measurements in order to estimate parameters and states. Nonlinear Model Predictive Control (NMPC) is a popular method to implement feedback control and deal with uncertainties. Conventional NMPC or nominal control, however, sometimes does not provide enough information for system estimation, leading to unsatisfactory performance. Dual control attempts to strike a balance between the two goals of enhancing system estimation and optimizing the nominal objective function. In this paper, we analyze the performance of these strategies through the interplay between the performance control task and the information gain task in connection with Optimal Experimental Design. Examples illustrate the conflict and agreement between the two tasks and explain why in some cases nominal control performs well. It is also observed that measurement noise provides excitation helping to improve the quality of estimates.

The measurement uncertainty characterizes the dispersion of the quantity values being attributed to the measurand and there are different approaches for uncertainty estimation. This study illustrates the application of the GUM (bottom-up) approach to estimate the measurement results uncertainty for the quantitative determination of Al, Ba, Fe, Mg, Mn, Pb, Sr and Zn from document paper samples using ICP-MS. The measurement uncertainty estimation was done based on identifying, quantifying and combining all the associated sources of uncertainty separately. Certain typical steps were followed: specifying the measurand; identifying the major sources of uncertainty; quantifying the uncertainty components; combining the significant uncertainty components; determining the extended combined standard uncertainty; reviewing the estimates and reporting the measurement uncertainty. For the eight mentioned trace elements the combined standard uncertainties and the expanded uncertainties were determined. The relative measurement uncertainty values lay between 7.7% and 13.6%. In all the five paper samples for each of the eight elements homogenous uncertainty values were obtained. In order to emphasize the uncertainty sources contributions, the percent contribution of the uncertainty components to the combined relative standard uncertainty were graphically represented for the elements determined by ICP-MS in paper samples. The previously validated method proved to be suitable for the intended purpose and when the uncertainty of the measurement results is estimated, it becomes a significant tool for characterizing the elemental composition of the document paper samples. Moreover, the applied approach for the uncertainty estimation enables improving the data quality and decision making.

Purpose - The web application presented in this paper allows for an analysis to reveal centres of excellence in different fields worldwide using publication and citation data. Only specific aspects of institutional performance are taken into account and other aspects such as teaching performance or societal impact of research are not considered. The purpose of this paper is to address these issues. Design/methodology/approach - Based on data gathered from Scopus, field-specific excellence can be identified in institutions where highly-cited papers have been frequently published. Findings - The web application (www.excellencemapping.net) combines both a list of institutions ordered by different indicator values and a map with circles visualising indicator values for geocoded institutions. Originality/value - Compared to the mapping and ranking approaches introduced hitherto, our underlying statistics (multi-level models) are analytically oriented by allowing the estimation of values for the number of excellent papers for an institution which are statistically more appropriate than the observed values; the calculation of confidence intervals as measures of accuracy for the institutional citation impact; the comparison of a single institution with an >average> institution in a subject area: and the direct comparison of at least two institutions.

The purpose of this paper is to suggest a direction for future studies based on the analysis of the articles published in the Korean Journal of Hospice and Palliative Care from 1998 to 2012. A total of 240 articles (51 reviews, 189 original) were examined in three five-year groups. Categories of analysis include authors' background (profession, region) and general characteristics and qualitative aspects of the original paper (participants, topic, study design, data analysis, ethical consideration, multidisciplinary approach, research funds and sample size estimation). While the journal publishes more of articles than before, it is mainly due to the increase in the number of review articles, not original articles. As for study topics, healthcare industry and physical symptoms were most frequently studied. The disparity in authors' regional background is fading, and more articles are published by nurses than before. Moreover, more studies are funded while fewer papers tend to adopt a multidisciplinary approach or focus on care givers. Also, in terms of a study design, the number of experimental and methodological studies has slightly increased. In the qualitative aspect, studies considered ethical issues and collected participation consent, and fewer studies reported an estimated sample size. In data analysis, post-adjustment comparison decreased, and new analytical methods are increasingly used. Our results indicate the need to conduct research with more extensive scientific data in various fields of hospice and palliative care.

Introduction The World Health Organization recommends TT surveys to be conducted in adults aged 15+ years (TT 15 survey) and certifies elimination of TT as a public health problem when there is less than 1 unknown case per 1,000 people of all ages. There is no standard survey method to accurately confirm this elimination prevalence threshold of 0.1% because rare conditions require large and expensive prevalence survey samples. The aim of this study was to develop an accurate operational research method to measure the total backlog of TT in people of all ages and detect when the elimination threshold is achieved. Methods Between July to October 2016, an innovative Community-based, Mapping, Mop-up and Follow-up (CMMF) approach to elimination of TT as a public health problem was developed and tested in Esoit, Siana, Megwara and Naikara sub-locations in Narok County in Kenya. The County had ongoing community-based TT surgical camps and case finders. TT case finders were recruited from existing pool of Community health volunteers (CHV) in the Community Health Strategy Initiative Programme of the Ministry of Health. They were trained, validated and supervised by experienced TT surgeons. A case finder was allocated a population unit with 2 to 3 villages to conduct a de jure pre-survey census, examine all people in the unit and register those with TT (TT all survey). Identified cases were confirmed by TT surgeons prior to surgery. Operated patients were reviewed at 1 day, 2 weeks and 3-6 months. The case finders will also be used to identify and refer new and recurrent cases. People with other eye and medical conditions were treated and referred accordingly. Standardised data collection and computer based data capture tools were used. Case finders kept registers with details of all persons with TT, those operated and those who refused to be operated (refusals). These details informed decision and actions on follow-up and counselling. Progress towards achievement of elimination threshold was assessed by dividing the number of TT cases diagnosed by total population in the population unit multiplied by 1,000. Results Narok County Government adopted both the CMMF approach and TT all survey method. All persons in 4,784 households in the four sub-locations were enumerated and examined. The total population projection was 29,548 and pre-survey census 22,912 people. Fifty-three cases of TT were diagnosed. The prevalence was 0.23% and this is equivalent to 2.3 cases per thousand population of all ages. Prior to this study, the project required to operate on at least 30 cases (excess cases) to achieve the elimination threshold of 1 case per 1000 population. Conclusion The total backlog of TT was confirmed and the project is now justified to lay claim of having eliminated TT as a public health problem in the study area. TT all method may not be appropriate in settings with high burden of TT. Nomadic migrations affect estimation of population size. Non-trachomatous TT could not be ruled-out.

Sheet and film forming processes such as paper manufacturing pose a challenging monitoring and control problem, where quality variations are classified into machine direction (MD), cross-machine direction (CD) and residual variation. The measurements are typically collected with a scanning sensor that covers only a small part of the paper web, and therefore provides a very limited view of the paper web, setting performance limitations on the online monitoring and control. The development of cameras, light sources and computation hardware enable the consideration of utilizing in-use web inspection systems in paper machines to measure the paper web variations with a considerably higher resolution, sampling rate and coverage. The light transmittance images captured with this kind of system need, however, to be converted into a controllable quality property, such as basis weight, in order to utilize the new measurement information for control purposes. In this thesis, computational methods are identified and developed that are capable of combining light transmittance and scanning measurements, and can efficiently utilize the combined information for control purposes. The possible benefits gained with these image-based measurements in paper machine online monitoring and profile control are evaluated in a simulation environment. In a real paper machine, the benefits are ultimately dependent on the machine configuration and the nature of paper variations therein. It was found that with a suitable estimation method, light transmittance could increase the awareness of basis weight variations such as fast MD variation, tilted waves and dynamic CD variation patterns, which are practically undetectable using scanner-based measurement. The enhanced basis weight estimation enables a considerable improvement in the dynamic performance of profile controls. CD control was able to handle fast variations earlier classified as uncontrollable residual variation. In MD control, enhanced estimation enabled the development of a control strategy that led to improved reference tracking and disturbance rejection properties. Tiivistelmä Paperinvalmistus on yksi esimerkki levyjen tai kalvojen valmistusprosesseista, jotka ovat tyypillisesti haasteellisia prosessin monitoroinnin ja säädön kannalta. Laatuvaihtelut näissä prosesseissa luokitellaan koneensuuntaisiin (MD), poikkisuuntaisiin (CD) ja jäännösvaihteluihin. Paperikoneella mittaukset kerätään tavallisesti radan yli liikkuvalla skannaavalla sensorilla, joka tarjoaa vain hyvin rajoitetun määrän informaatiota paperiradasta, asettaen siten rajoituksia online monitoroinnin ja säädön suorituskyvylle. Kameroiden ja valonlähteiden kehitys sekä laskentakapasiteetin kasvu mahdollistavat paperiradan vaihteluiden mittaamisen huomattavasti korkeammalla resoluutiolla ja näytteenottovälillä jo käytössä olevilla vianilmaisujärjestelmillä. Vianilmaisujärjestelmän keräämä valon transmittanssitieto pitää kuitenkin muuntaa esimerkiksi neliömassatiedoksi, jotta uutta mittausinformaatiota voitaisiin hyödyntää myös prosessin online säädössä nykyisillä toimilaitteilla. Tässä työssä on identifioitu ja kehitetty laskennallisia menetelmiä, jotka kykenevät yhdistämään kuvantavan ja skannaavan mittauksen sekä käyttämään tätä yhdistettyä tietoa säätötarkoituksissa. Kuvapohjaisen mittauksen mahdollisia hyötyjä online monitoroinnissa ja profiilien säädössä on arvioitu simulointiympäristössä. Saavutettavat hyödyt paperikoneella ovat lopulta riippuvaisia myös koneen konfiguraatiosta ja koneella ilmenevien laatuvaihteluiden luonteesta. Tulokset osoittavat, että transmittanssimittauksen ja tehokkaan estimointimenetelmän avulla kyetään lisäämään tietämystä neliömassamuutoksista, joita ei käytännössä voida havaita pelkän skannaavan mittauksen avulla. Estimoinnin parempi suorituskyky mahdollistaa myös profiilisäätöjen dynaamisen suorituskyvyn kasvattamisen. CD-säätö voitiin laajentaa kattamaan myös nopeita vaihteluita, jotka ovat aiemmin luokiteltu jäännösvaihteluksi. MD-säädölle voitiin kehittää säätöstrategia, jonka avulla sekä asetusarvojen seurantaa että häiriöiden vaimennusta pystyttiin parantamaan.

Interest in the actual estimation of the uncertainty affecting flood hazard assessments is increasing within the scientific community and among decision makers. Several works may be found in the hydrological and hydraulic literature listing the sources of uncertainty affecting the estimation of extreme flood levels. Here, a well-assessed uncertainty treatment procedure is applied to carry out a complete flood hazard assessment study to encompass both the hydrological and hydraulic components. In particular, the focus is on modeling the sources of uncertainty via a direct (for discharge) or inverse (for roughness hydraulic coefficient) approach. The results illustrate the relative importance of the hydraulic and hydrological uncertainty sources on the final uncertainty. The solution of the inverse problem for the calibration of the roughness coefficient proves useful for several reasons, including the quantification of model error.

This report is a critique of the Centre for Health Economics Research Paper No. 81 (CHERP81), which estimates that the marginal cost of a QALY for the NHS in England in 2008/9 was £12,936. There is much to admire in the approach, detailed analysis, and reporting set out in CHERP81 and we recommend detailed reading of it. The focus of this OHE Occasional Paper is, however, on the points where we take issue with or have queries about the CHERP81 work. The magnitude of the marginal cost of a QALY in the NHS is important as it informs the cost effectiveness threshold used in health technology assessments (HTAs) by the National Institute for Health and Care Excellence (NICE). Indeed this was the motivation for the commissioning of the study by the Medical Research Council (MRC) as part of a programme of methodological research relevant to NICE. Understanding the expected QALYs displaced in the NHS by a NICE recommendation is an important part of helping NICE make optimal decisions in relation to the approval of new technologies. The CHERP81 estimate for 2008/9 is lower than NICE’s announced threshold range for approving new products of £20,000 to £30,000 per QALY.

Crop detection is a critical and evaluative first step towards almost agricultural monitoring systems. The ability to identify crop type makes it possible to estimate the agricultural area allocated under crop and hence compute relevant statistics providing essential information for crop control of area-based subsidies The capabilities of SAR for discriminating crop type have been previously explored. The main aim is to brief the mechanism of crop acreage estimation and area monitoring using SAR data, Envisat-ASAR, or polarimetric SAR with multi-temporal and multi polarized datasets and review the research progress on crop estimation and area monitoring using microwave remote sensing.

In this article I review the modeling of capture, recapture, and removal statistics for the purpose of estimating demographic parameters of fish and wildlife populations. Topics considered include capture-recapture models, band or tag return models, removal and catch per unit effort models, selective removal or change-in-ratio models, radio-tagging survival models, and nest survival models. The purpose is to present important concepts in a general manner for the benefit of a wide audience of statisticians. I will not attempt to be comprehensive, and I indulge in speculation about future directions. I indicate the importance of different statistical tools to this subject, such as Bayesian inference, “boot strapping,” robustness studies, goodness-of-fit tests. I also emphasize connections to other application areas of statistics. Capture-recapture methods, for example, are being considered for estimation of a variety of elusive human populations, such as the homeless and people missed in the census...

The general goal of this discussion paper is to contribute toward the further harmonization of human health risk assessment. It first discusses the development of a formal, harmonized set of assessment factors. The status quo with regard to assessment factors is reviewed, that is, the type of factors to be identified, the range of values assigned, as well as the presence or absence of a scientific basis for these values. Options are presented for a set of default values and probabilistic distributions for assessment factors based on the state of the art. Methods of combining default values or probabilistic distributions of assessment factors are also described. Second, the effect parameter, the no-observed-adverse-effect level (NOAEL), is discussed. This NOAEL as selected from the toxicological database may be a poor substitute for the unknown, true no-adverse-effect level (NAEL). New developments are presented with respect to the estimation of the NAEL. The already widely discussed Benchmark Dose concept can be extended to obtain an uncertainty distribution of the Critical Effect Dose (CED). This CED distribution can be combined with estimated uncertainty distributions for assessment factors. In this way the full distribution of the Human Limit Value will be derived and not only a point estimate, whereas information on dose-response relations is taken into account. Finally, a strategy is proposed for implementation of the new developments into human health risk assessments.

The dynamic general nesting spatial econometric model for spatial panels with common factors is the most advanced model currently available. It accounts for local spatial dependence by means of an endogenous spatial lag, exogenous spatial lags, and a spatial lag in the error term. It accounts for dynamic effects by means of the dependent variable lagged in time, and the dependent variable lagged in both space and time. Finally, it accounts for global cross-sectional dependence by means of cross-sectional averages or principal components with heterogeneous coefficients, which generalizes the traditional controls for time-invariant and spatial-invariant variables by unit-specific and time-specific effects. This paper provides an overview of the main arguments in favor of each of these model components, as well as some potential pitfalls.

Huge data sets from the teletraffic industry exhibit many nonstandard characteristics such as heavy tails and long range dependence. Various estimation methods for heavy tailed time series with positive innovations are reviewed. These include parameter estimation and model identification methods for autoregressions and moving averages. Parameter estimation methods include those of Yule-Walker and the linear programming estimators of Feigin and Resnick as well estimators for tail heaviness such as the Hill estimator and the qq-estimator. Examples are given using call holding data and interarrivals between packet transmissions on a computer network. The limit theory makes heavy use of point process techniques and random set theory.

Since the first patient was detected in India in late February 2020, the SARS-CoV-II virus is playing havoc on India. After the first wave, India is now riding the second wave. As was in the case of European countries like Italy and the UK, the second wave is more contagious and at the time of writing this paper, the per day infection is as high as 400,000. The alarming thing is it is not uncommon that people are getting infected multiple times. On the other hand, mass vaccination has started step by step. There is also a growing danger of potential third wave is unavoidable, which can even infect kids and minors. In this situation, an estimation of the dynamics of SARS-CoV-II is necessary to combat the pandemic. We have used a modified SEIRD model that includes vaccination and repeat infection as well. We have studied India and 8 Indian states with varying SARS-CoV-II infections. We have shown that the COVID-19 wave will be repeated from time to time, but the intensity will slow down with time. In the most possible situation, our calculation shows COVID-19 will remain endemic for the foreseeable future unless we can increase our vaccination rate manifold.

Research on heat waves (periods of excessively hot weather, which may be accompanied by high humidity) is a newly emerging research topic within the field of climate change research with high relevance for the whole of society. In this study, we analyzed the rapidly growing scientific literature dealing with heat waves. No summarizing overview has been published on this literature hitherto. We developed a suitable search query to retrieve the relevant literature covered by the Web of Science (WoS) as complete as possible and to exclude irrelevant literature (n = 8,011 papers). The time-evolution of the publications shows that research dealing with heat waves is a highly dynamic research topic, doubling within about 5 years. An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 and 2003), the cities and countries/regions affected (United States, Europe, and Australia), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality). Risk estimation and future strategies for adaptation to hot weather are major political issues. We identified 104 citation classics which include fundamental early works of research on heat waves and more recent works (which are characterized by a relatively strong connection to climate change)., 40 pages, 2 tables, and 9 figures

The currently ongoing COVID-19 pandemic confronts governments and their health systems with great challenges for disease management. Epidemiological models play a crucial role, thereby assisting policymakers to predict the future course of infections and hospitalizations. One difficulty with current models is the existence of exogenous and unmeasurable variables and their significant effect on the infection dynamics. In this paper, we show how a method from nonlinear control theory can complement common compartmental epidemiological models. As a result, one can estimate and predict these exogenous variables requiring the reported infection cases as the only data source. The method allows to investigate how the estimates of exogenous variables are influenced by non-pharmaceutical interventions and how imminent epidemic waves could already be predicted at an early stage. In this way, the concept can serve as an “epidemometer” and guide the optimal timing of interventions. Analyses of the COVID-19 epidemic in various countries demonstrate the feasibility and potential of the proposed approach. The generic character of the method allows for straightforward extension to different epidemiological models.

To ensure that the process of giftedness development runs smoothly, it is necessary to build adequate socio-emotional competencies related to the ability to use various social and emotional stimulation from the environment to achieve results that enable satisfactory and competent participation in groups, communities, and society to which individual belongs. The goal of this research was to examine whether and to what extent are socio-emotional competencies of parents and Kindergarten teachers are significant predictors of the perception of talents of preschool children. The sample consisted out of 100 participants from Zeničko-Dobojski kanton, 75 parents, and 25 educators. As instruments, we used: Questionnaire of general sociodemographic data (SD questionnaire), Giftedness Questionnaire (Von Krafft and Semke, 2008), and questionnaire of socioemotional competencies of educators (Jusufovic, unpublished paper). The results indicate that among all socio-emotional competencies of parents the only that is significant predictor is awareness of others for assessing the expression of one’s characteristics, for assessing the expression of talent and out of socio-demographic variables, the variable of age parents is significant, but only for assessing the expression of talents (older parents perceive less giftedness). Furthermore, in the case of educators, pure non-violent communication is important for socio-emotional competencies for the expression of one’s characteristics, then for the expression of talents significant factors are non-violent communication, awareness of others, emotion regulation, self-esteem, and the total score of socio-emotional competencies. Among socio-demographic characteristics, the important predictor is working experience for perceiving talents. In addition to this, there are statistically significant differences between parents and educators, in an expression of talent, and the results show that educators are better in the estimation of expression of talents.