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Ever since the resumption of cricket during COVID-19 pandemic, players and support staff have to stay in an isolated environment during the tournaments to prevent the risk of contracting COVID-19 from the external environment. This can have an adverse effect on the mental health of the players as they have to spend a lot of alone time, which can lead to introspection and rumination consisting of constant negative feelings. The authors evaluated media reports published between 1st July, 2020 and 31st May, 2021, on players withdrawing from a tournament midway or players who pulled out of an entire tournament citing bio-bubble fatigue (mental fatigue due to the bio-bubble environment) and found eight such cases. Mental fatigue builds in a cumulative manner, and therefore, more players are likely to suffer from bio-bubble fatigue during the next couple of months if this issue is not addressed. The authors recommend that every team must have a sports medicine physician/ sports psychologist at all times during the tournaments to make sure that the players remain mentally fit during this phase of COVID-19 pandemic.

Little peer-reviewed information is available regarding the accuracy and precision of the occlusal contact reproduction of digitally mounted stereolithographic casts.The purpose of this in vitro study was to evaluate the accuracy and precision of occlusal contacts among stereolithographic casts mounted by digital occlusal registrations.Four complete anatomic dentoforms were arbitrarily mounted on a semi-adjustable articulator in maximal intercuspal position and served as the 4 different simulated patients (SP). A total of 60 digital impressions and digital interocclusal registrations were made with a digital intraoral scanner to fabricate 15 sets of mounted stereolithographic (SLA) definitive casts for each dentoform. After receiving a total of 60 SLA casts, polyvinyl siloxane (PVS) interocclusal records were made for each set. The occlusal contacts for each set of SLA casts were measured by recording the amount of light transmitted through the interocclusal records. To evaluate the accuracy between the SP and their respective SLA casts, the areas of actual contact (AC) and near contact (NC) were calculated. For precision analysis, the coefficient of variation (CoV) was used. The data was analyzed with t tests for accuracy and the McKay and Vangel test for precision (α=.05).The accuracy analysis showed a statistically significant difference between the SP and the SLA cast of each dentoform (P.05). For the AC in all dentoforms, a significant increase was found in the areas of actual contact of SLA casts compared with the contacts present in the SP (P.05). Conversely, for the NC in all dentoforms, a significant decrease was found in the occlusal contact areas of the SLA casts compared with the contacts in the SP (P.05). The precision analysis demonstrated the different CoV values between AC (5.8 to 8.8%) and NC (21.4 to 44.6%) of digitally mounted SLA casts, indicating that the overall precision of the SLA cast was low.For the accuracy evaluation, statistically significant differences were found between the occlusal contacts of all digitally mounted SLA casts groups, with an increase in AC values and a decrease in NC values. For the precision assessment, the CoV values of the AC and NC showed the digitally articulated cast's inability to reproduce the uniform occlusal contacts.

The accuracy of interproximal distances of the definitive casts made by computer-aided design and computer-aided manufacturing (CAD-CAM) technology is not yet known.The purpose of this in vitro study was to compare the interproximal distances of stereolithographic casts made by CAD-CAM technology with those of stone casts made by the conventional method.Dentoform teeth were prepared for a single ceramic crown on the maxillary left central incisor, a 3-unit fixed dental prosthesis (FDP) on the second premolar for a metal-ceramic crown, and a maxillary right first molar for a metal crown. Twenty digital intraoral impressions were made on the dentoform with an intraoral digital impression scanner. The digital impression files were used to fabricate 20 sets of stereolithographic casts, 10 definitive casts for the single ceramic crown, and 10 definitive casts for the FDP. Furthermore, 20 stone casts were made by the conventional method using polyvinyl siloxane impression material with a custom tray. Each definitive cast for stereolithographic cast and stone cast consisted of removable die-sectioned casts (DC) and nonsectioned solid casts (SC). Measurements of interproximal distance of each cast were made using CAD software to provide mean ±standard deviation (SD) values. Data were first analyzed by repeated measures analysis of variance (ANOVA), using different methods of cast fabrication (stone and stereolithography) as one within subject factor and different cast types (DC and SC) as another within subject factor. Post hoc analyses were performed to investigate the differences between stone and stereolithographic casts depending upon the results from the repeated measures ANOVA (α=.05).Analysis of interproximal distances showed the mean ±SD value of the single ceramic crown group was 31.2 ±24.5 μm for stone casts and 261.0 ±116.1 μm for stereolithographic casts, whereas the mean ±SD value for the FDP group was 46.0 ±35.0 μm for stone casts and 292.8 ±216.6 μm for stereolithographic casts. For both the single ceramic crown and the FDP groups, there were significant differences in interproximal distances between stereolithographic casts and stone casts (P.001). In addition, the comparisons of DC with SC of stone and stereolithographic casts for the single ceramic crown and FDP groups demonstrated there was statistically significant differences among interproximal distances between DC stereolithographic casts and SC stereolithographic casts only for the FDP group (P.001).For both the single ceramic crown and the FDP groups, the stereolithographic cast group showed significantly larger interproximal distances than the stone cast group. In terms of the comparison between DC and SC, DC stereolithographic casts for the FDP group only showed significantly larger interproximal values than those of the SC stereolithographic casts for the FDP group.

A multiple hypothesis problem with directional alternatives is considered in a decision theoretic framework. Skewness in the alternatives is considered, and it is shown that this skewness permits the Bayes rules to possess certain advantages when one direction of the alternatives is more important or more probable than the other direction. Bayes rules subject to constraints on certain directional false discovery rates are obtained, and their performances are compared with a traditional FDR rule through simulation. We also analyzed a gene expression data using our methodology, and compare the results to that of a FDR method.

In this short article the following inequality called the “Pitman inequality” is proved for the exchangeable random vector ( X 1 , X 2 , … , X n ) without the assumption of continuity and symmetry for each component X i : P ( | 1 n ∑ i = 1 n X i | ≤ | ∑ i = 1 n α i X i | ) ≥ 1 2 , where all α i ≥ 0 are special weights with ∑ i = 1 n α i = 1 .

We consider a hypothesis problem with directional alternatives. We approach the problem from a Bayesian decision theoretic point of view and consider a situation when one side of the alternatives is more important or more probable than the other. We develop a general Bayesian framework by specifying a mixture prior structure and a loss function related to the Kullback–Leibler divergence. This Bayesian decision method is applied to Normal and Poisson populations. Simulations are performed to compare the performance of the proposed method with that of a method based on a classical z-test and a Bayesian method based on the “0–1” loss.

This paper discusses a method of modeling temporal pattern and event detection based on Hidden Markov Model (HMM) for a continuous time series data. We also provide methods for checking model adequacy and predicting future events. These methods are applied to a real example of sludge bulking data for detecting sludge bulking for a water plant in Chicago.

Many hypothesis problems in practice require the selection of the left side or the right side alternative when the null is rejected. For parametric models, this problem can be stated as H 0 : θ = θ 0 vs. H − : θ θ 0 or H + : θ > θ 0 . Frequentists use Type-III error (directional error) to develop statistical methodologies. This approach and other approaches considered in the literature do not take into account the situations where the selection of one side may be more important or when one side may be more probable than the other. This problem can be tackled by specifying a loss function and/or by specifying a hierarchical prior structure with allowing the skewness in the alternatives. Based on this, we develop a Bayesian decision theoretic methodology and show that the resulted Bayes rule perform better in the side of the alternatives which is more probable. The methodology can be also used in a frequentist's framework when it is desired to discover an alternative that is more important. We also consider the multiple hypotheses problem and develop new false discovery rates for the selection of the left and the right sides of alternatives. These discovery rates would be useful in the situations when one side of the alternatives are more important or more probable than the other.

The problem of selecting the best treatment is studied under generalized linear models. For certain balanced designs, it is shown that simple rules are Bayes with respect to any non-informative prior on the treatment effects under any monotone invariant loss. When the nuisance parameters such as block effects are assumed to follow a uniform (improper) prior or a normal prior, Bayes rules are obtained for the normal linear model under more suitable balanced designs, keeping the generality of the loss and the generality of the non-informativeness on the prior of the treatment effects. These results are extended to certain types of informative priors on the treatment effects. When the designs are unbalanced, algorithms based on the Gibbs sampler and the Laplace method are provided to compute the Bayes rules.

The problem of selecting the largest treatment parameter, provided it is better than a control, and simultaneously estimating the selected treatment parameter in a general linear model is considered in the decision theoretic Bayes approach. Both cases, where the error variance is known or unknown, are included. Bayes decision rules are derived for noninformative and for normal priors. Bayes rules for noninformative priors are derived under a general loss function for designs that satisfy the BTIB condition of Bechhofer and Tamhane (Technometrics 23 (1981) 45). For unbalanced designs, a linear loss function is adopted and it is demonstrated, via simulations, that the simultaneous estimation of the selected treatment effect plays an important role in correcting an undesirable effect for the selection problem.

In this study, the clinical profile of Hindi-speaking stroke patients with aphasia from northern India has been investigated. We examined the interactional effect between age and gender with aphasia type in 97 Hindi-speaking right-handed individuals, the majority of them with a confirmed diagnosis of a cerebrovascular accident. The subjects included in the study ranged from 3 weeks to two years post-onset with a diagnosis of a common classical aphasia (Broca's, Wernicke's, anomic, global, conduction, and transcortical) types involving both males and females. Also examined was the interaction between literacy and aphasia type since the subjects had varied exposures to education (total illiteracy to professional/university education). While the data reported here about Hindi-speaking aphasics are relatively in agreement with the age-aphasia type patterns discussed in western countries, nonetheless some differences were also observed. The mean age of Indian patients with aphasia was significantly lower. Also, in addition to some gender and literacy related differences, an outstanding difference was that many clinical symptoms that are known to co-occur with aphasia were not readily reported by subjects with stroke.

The problem of selecting the largest treatment parameter, and simultaneously estimating the selected treatment parameter, in a general linear model is considered in the decision theoretic Bayes approach. Both cases, where the error variance is known or unknown, are included. Bayes decision rules are derived for noninformative priors and for normal priors. The problem of finding Bayes designs, i.e. designs that have minimum Bayes risk, within a given class of designs is also discussed.

We study properties of random fields that form conditional bases and their applications in spatial statistics.

We consider a non-linear regression model when the index variable is multidimensional. Sucient conditions on the non-linear function are given under which the least-squares estimators are strongly consistent and asymptotically normally distributed. These sucient conditions are satised by harmonic type functions, which are also of interest in the one dimensional index case where Wu’s (Asymptotic theory of non-linear least-squares estimation, Ann. Statist. 9 (1981) 501{513) and Jennrich’s (Asymptotic properties of non-linear least-squares estimators, Ann. Math. Statist. 40 (1969) 633{643) sucient conditions are not applicable. c 1999 Elsevier Science B.V. All rights reserved

Various characterizations of the univariate normal distribution are presented. c 1999 Elsevier Science B.V. All rights reserved

We consider a general ranking problem in general linear model for ranking the components of treatment effect vector when the error vector follows a spherically symmetric distribution. A conditions on the design matrix is given under which the natural decision rule is minimax. We also discuss Bayes rules under monotone permulation invariant loss function. It is shown that under some condition on the design matrix, the Bayes rule with respect to permutation invariant prior behaves in the same way as the natural decision rule. We also show that the Bayes rule takes a simple form when the posterior distribution has decreasing in transposition (DT) property. We give a condition on the design matrix under which the posterior has DT property.

For the risk measured by the probability of an incorrect decision and under mild assumptions on underlying distributions, the minimax value for a general ranking problem is obtained. A necessary condition for the minimaxity is also derived. Consequently, the minimaxity of natural decision rules, for location and scale probability models, is proved. Minimaxity of natural decision rules for elliptically symmetric distributions is also studied.

We consider a problem of selecting a best of k one parameter exponential families with quadratic variance functions which is associated with the largest mean. It is shown that the minimax value under the “0–1” loss function is 1 − 1/k. Also the Bayes rules are discussed under the “0–1” loss and the other loss functions.