Order Restrictions Research Articles

An analysis of the relationship between self-consciousness and eating attitudes among 8th grade students

This research investigates the relationship between eating attitudes and self-consciousness among 8th-grade students studying in the Kağıthane district of Istanbul during the 2023–2024 academic year. The study included a total of 568 students (300 males and 268 females). Participants were administered the Sociodemographic Form, Eating Attitudes Test (EAT-40), and the Self-Consciousness Scale. Data were analyzed using SPSS 27.0 software. Pearson correlation and multiple regression analysis were conducted to examine the predictive role of self-consciousness on eating attitudes. A positive relationship was found between “self-consciousness” and “eating attitude.” Independent sample t-tests and one-way ANOVA were used to compare groups based on sociodemographic variables. The eating attitudes score was significantly higher among female students compared to male students (t = −6.26; p < 0.001). Students with a family history of dieting had significantly higher eating attitude scores compared to those without (t = 4; p < 0.001). No significant differences were found based on screen usage during meals, meal procurement methods, meal companions, time spent at school, frequency of packaged food consumption, or parental restrictions on packaged foods. Self-consciousness scores were compared based on gender, diet history, household composition, number of siblings, meal companions, birth order, and parental restrictions on packaged foods. Female students had significantly higher scores in private self-consciousness (t = −3.96; p < 0.001), general self-consciousness (t = −9.37; p < 0.001), and social anxiety (t = −7.51; p < 0.001) compared to male students. Students with a diet history had significantly higher general self-consciousness scores (t = 2.39; p < 0.05) compared to those without. No significant differences were found in self-consciousness levels based on household composition, number of siblings, meal companions, birth order, or parental restrictions on packaged foods. For future scientific studies, the findings were discussed, and suggestions were provided.

Extended ARMA graph neural networks for the prognosis of complex systems

With the advancement of intelligent sensing techniques, massive monitoring signals are collected and accumulated from industrial systems. Given that sensors are often correlated and constructed to reflect graph topology, the signals can be conceptualized as graph data. The polynomial filter-based graph neural networks (GNNs) are commonly employed to exploit information from nodes features and graph topology for graph data analysis. However, the polynomial filter-based GNNs encounter difficulty in accurately modeling sharp changes and the coefficients can vary a lot, making them hard to learn. To address this problem, a novel graph neural network named extended auto-regressive moving average graph neural network (eAGNN) is proposed. Compared with auto-regressive moving average (ARMA) neural network, the order restriction are removed, allowing for the inference of a more general neural network, which enables the modeling of filters with more different shapes. Furthermore, both low-frequency and high-frequency information are explicitly and separately extracted so as to alleviate the burden of the learning process and further enhance the learning capability. Finally, several experiments including public node classification and fault diagnosis were conducted. The results demonstrate that the proposed eAGNN exhibits high performance compared to alternative methods.

Order-restricted statistical inference and optimal censoring scheme for Gompertz distribution based on joint type-II progressive censored data

This paper considers the order-restricted statistical inference for two populations based on the joint type-II progressive censoring scheme. The lifetime distributions of the two populations are supposed to follow the Gompertz distribution with the same shape parameter but different scale parameters. The maximum likelihood estimates of the unknown parameters are derived by employing the Newton-Raphson algorithm and the expectation-maximization algorithm, respectively. The Fisher information matrix is then employed to construct asymptotic confidence intervals. For Bayes estimation, we assume an ordered Beta-Gamma prior for the scale parameters and a Gamma prior for the common shape parameter. Bayes estimations and the highest posterior density credible intervals for unknown parameters under two different loss functions are obtained with the importance sampling technique. To evaluate the performance of order-restricted inference, extensive Monte Carlo simulations are performed and two air-conditioning systems datasets are used to illustrate the proposed inference methods. In addition, the results are compared with the case when there is no order restriction on the parameters. Finally, the optimal censoring scheme is obtained by four optimality criteria.

Analysis of dependent complementary competing risks data from a generalized inverted family of lifetime distributions under a maximum ranked set sampling procedure with unequal samples

This paper explores analysis of a dependent complementary competing risks model when the failure causes are distributed by the proposed generalized inverted family of lifetime distributions. Under maximum ranked set sampling with unequal samples (MRSSU), statistical inference of model parameters and reliability indices is discussed under classical frequentist and Bayesian approaches, respectively. Maximum likelihood estimators along with their existence and uniqueness are obtained for model parameters, and associated approximate confidence intervals are constructed in consequence. Bayesian estimation is also performed with respect to general flexible priors, and the Markov Chain Monte Carlo (MCMC) algorithm is proposed for complex posterior computation. The study further examines classical and Bayesian estimations with order restriction of parameters when additional historical information is available in the MRSSU scenario. Finally, the performance of different results is evaluated through numerical simulations and a real data example is presented for demonstrating the application of our methods.

Statistical inference for marshall-olkin bivariate Kumaraswamy distribution under adaptive progressive hybrid censored dependent competing risks data

Abstract The statistical inference under competing risks model is of great significance in reliability analysis and it is more practical to assume that they have dependent competing causes of failure in actual situations. In this article, we make inference for unknown parameters of a Marshall-Olkin bivariate Kumaraswamy distribution under adaptive progressive hybrid censoring mechanism. The maximum likelihood estimations of the unknown parameters are derived, and the Fisher information matrix is then employed to construct asymptotic confidence intervals. Bayes estimates are evaluated against squared error and linex loss functions assuming ordered Gamma-Dirichlet and Gamma-Dirichlet prior distributions for order restriction and without order restriction cases respectively. The Metropolis-Hasting and Lindley techniques are applied to acquire the estimates of all unknown parameters. A thorough simulation analysis is demonstrated to assess the performance of the supplied approaches across various sample sizes. The usefulness of the techniques is illustrated using real engineering data to prove their versatility in practical applications.

The Flexibility of Placing the Subject in Arabic Sentences: A Study of Syntactic Word Order Restrictions and their Application to Arabic Grammar

This research addresses the possibility of placing the subject in a pre-verb position in verbal sentences in Arabic, without necessarily stipulating that if the subject is preposed before the verb, it becomes a topic. In this way, the subject is a non-overt pronoun positioned within or after the verb, because the subject is conventionally acknowledged by grammarians to move freely to various post-verbal positions, but never pre-verbally. The research considers the views and opinions of linguists and grammarians who have dealt with this issue in detail, presenting a discussion of these views to reveal the strict restrictions imposed on the movement of the subject. It is hoped that this will contribute to the facilitation of teaching and learning Arabic grammar. It will also revitalize the discussion of views in Arabic grammatical traditions to try to establish new grammatical principles that contemporary linguists may adopt when reformulating the rules of Arabic grammar. This endeavor may simplify the task of learning rules and contribute to presenting them more flexibly and plausibly.

Alopecia Areata of the Nails: Diagnosis and Management.

Background: Alopecia areata (AA) is a common form of non-scarring alopecia characterized by acute hair loss. Nail involvement, though not always present, can occur in AA patients. Nail changes are more frequent in severe forms of AA and in children. Methods: Literature related to nail changes in AA was comprehensively reviewed after a search on the PubMed database without time restrictions in order to identify common clinical presentations and associated factors to aid clinicians with the correct evaluation and management of these dystrophies. Results: Nail changes in AA include pitting, trachyonychia, leukonychia, red lunula, and miscellaneous alterations such as longitudinal ridging and brittle nails. Nail changes are usually asymptomatic but, nevertheless, sometimes cosmetically disfiguring and can be associated with a reduced quality of life and impaired daily activities. Conclusions: Nail changes in AA may precede or follow hair loss and can occur as an isolated finding. Diagnosis may require a biopsy for definitive identification. Spontaneous improvement is possible, particularly in children, and treatment is not always necessary. Further research is, however, needed to establish a consensus on treatment approaches according to age and severity.

Constrained inference in scaled mixed effects models with applications to London Junior School Project data

Multiple outcomes arise frequently in many different settings. Mixed effect models are a useful tool for the analyses of such data. However, when outcomes are measured on different scales, analyses based on any one scale are misleading. Often parameters of the model are subject to known order restrictions. To incorporate heterogeneity across different outcomes, we propose a scaled linear mixed effect model. To estimate parameters, we propose a maximum likelihood estimation procedure based on a restricted version of the expectation-conditional maximization either algorithm. Constrained hypotheses testing procedures are developed using likelihood ratio tests. The empirical significance levels and powers are studied using simulations. This article shows that incorporating the restrictions improves the mean squared errors of the estimates and the power of the tests. The methodology is applied on the London Junior School Project data incorporating known restrictions of patterns of scores. Journal of Statistical Research 2023, Vol 57, No.1-2, pp.81-94

The format of public events in modern Russia

The subject of the study is the analysis of legal norms in the organization and conduct of public events. When preparing for meetings, rallies, demonstrations, marches and picketing, the legislation provides for restrictions in order to maintain public order, preserve moral values and protect the interests of citizens. In this regard, the organizers coordinate the permissible number of participants, time, place, purpose of the event with the executive authorities of the subjects or local governments, from which reasonable proposals may be received, about any change, in order to ensure public order and protect the rights of participants in the event. At the same time, it is important to take into account the trend of recent years aimed at holding public events in an online format, in this regard, the main purpose of the study is to substantiate the need for regulatory consolidation of events in a digital format. The research methods are based on a wide application of general methods (generalization, observation), general scientific (systemic and logical), private scientific (sociological and historical) and special (comparative legal and formal legal). Special research methods were mainly used in studying the limits of restrictions during public events. The authors conclude that serious complex restrictions, initially caused by the COVID-19 pandemic, and then by the beginning of a special military operation, led to the use of an online format for public events. This entails amendments to the Federal Law "On Assemblies, Rallies, Demonstrations, Marches and Picketing" and the consolidation of a number of conditions: firstly, to provide for an online format for holding public events using digital technologies; secondly, to consolidate the requirements for holding digital events (including the choice of an online platform) and mandatory early coordination of the actions of the organizers with the executive authorities of the subject or local governments; thirdly, to introduce administrative liability for violation of the established procedure for organizing or holding a digital public event.

Sharing effects of split conjuncts in German

Abstract Split conjunction refers to discontinuous coordinate structures in which conjuncts are spread across the clause. In German, split conjuncts show connectivity effects such as plural agreement on the finite verb. This paper argues for an underlying biclausal structure with subsequent deletion of redundant material in the last conjunct – also known as a stripping analysis. We propose that the connectivity effects are caused by multiple dominance of shared constituents, which subsequently move out of the coordinate structure in order to be linearized. Evidence for this proposal comes from word order restrictions with plural agreement and multiply bound pronouns, an incompatibility with collective predicates, lack of sloppy identity readings, and the possibility of cumulative quantifier readings.

Reliability estimation and order-restricted inference based on joint type-II progressive censoring scheme with application to splashing data in atomization process

Censoring commonly occurs in real-world scenarios, either intentionally or unintentionally. In addition, in engineering and applied studies, two or more populations are required to perform the experiment. In this article, we develop the order-restricted ( OR) statistical inference of two inverted exponentiated Rayleigh ( IERayleigh) populations based on the joint type-II progressive censoring scheme ( J-IIProgCS). We also consider the problem of the stress-strength reliability Re = P( X> Y) estimation under J-IIProgCS. The process of estimating the parameters with order restriction ( PaR-OR) and Re are performed using the maximum likelihood (ML) and Bayesian methods. On the presumption that the gamma priors are independent, the Bayesian estimate of reliability model is obtained using the hybrid Gibbs within Metropolis-Hastings ( G-MeHa) algorithm. Moreover, with assumption the ordered Beta-Gamma prior for the shape parameters and the Gamma prior for the common scale parameter, the Bayes estimates of the parameters with order restriction are evaluated. The classical confidence intervals and the Bayesian credible interval are created. A detailed numerical illustration using simulated data sets is carried out. A real engineering example related to splashing phenomenon is considered for illustrative purposes.

A comprehensive examination of temporal-seasonal variations of PM1.0 and PM2.5 in taiwan before and during the COVID-19 lockdown

COVID-19 has been a significant global concern due to its contagious nature. In May 2021, Taiwan experienced a severe outbreak, leading the government to enforce strict Pandemic Alert Level 3 restrictions in order to curtail its spread. Although previous studies in Taiwan have examined the effects of these measures on air quality, further research is required to compare different time periods and assess the health implications of reducing particulate matter during the Level 3 lockdown. Herein, we analyzed the mass concentrations, chemical compositions, seasonal variations, sources, and potential health risks of PM1.0 and PM2.5 in Central Taiwan before and during the Level 3 lockdown. As a result, coal-fired boilers (47%) and traffic emissions (53%) were identified as the predominant sources of polycyclic aromatic hydrocarbons (PAHs) in PM1.0, while in PM2.5, the dominant sources of PAHs were coal-fired boilers (28%), traffic emissions (50%), and iron and steel sinter plants (22.1%). Before the pandemic, a greater value of 20.9 ± 6.92 μg/m3 was observed for PM2.5, which decreased to 15.3 ± 2.51 μg/m3 during the pandemic due to a reduction in industrial and anthropogenic emissions. Additionally, prior to the pandemic, PM1.0 had a contribution rate of 79% to PM2.5, which changed to 89% during the pandemic. Similarly, BaPeq values in PM2.5 exhibited a comparable trend, with PM1.0 contributing 86% and 65% respectively. In both periods, the OC/EC ratios for PM1.0 and PM2.5 were above 2, due to secondary organic compounds. The incremental lifetime cancer risk (ILCR) of PAHs in PM2.5 decreased by 4.03 × 10-5 during the pandemic, with PM1.0 contributing 73% due to reduced anthropogenic activities.

Older individuals and preventative behavioural interventions for COVID-19: a scoping review and perspective on wellbeing

Background In response to the COVID-19 pandemic, nations around the world introduced a range of behavioural interventions and restrictions in order to manage the spread of the virus. These included social distancing, lockdowns, and use of personal protective equipment, amongst others. The aim of the present paper is to examine some of the effects of these interventions on the psychological wellbeing and mental health of older adults, especially those with hearing loss. Methods The present review focused on published peer reviewed studies focusing on older adults. Search engines included Google Scholar, SpringerLink Journals, ProQuest Central, and PubMed employing different combinations of search terms such as “COVID-19”, “older adults”, and “isolation”. Results Older adults were at risk of experiencing increased anxiety and depression and poorer wellbeing during lockdowns across nations, with those self-reporting loneliness reporting more severe symptomatology. Reductions in wellbeing were observed both amongst community-dwelling older adults and those living in residential care facilities. Use of personal protective equipment, especially masks, and social distancing requirements impacted communication amongst older adults with hearing loss, with this subgroup reporting increased depression, anxiety, and stress, with symptoms increasing with the severity of the hearing loss. Conclusions While technology can help to mitigate the impacts of lockdowns and restrictions, limited access to devices and a range of challenges in upskilling older adults has impacted the utility of these technologies for promoting wellbeing. Education and training in the use of technologies and digital devices for both older adults and families might assist in promoting wellbeing, with increased accessibility needed in aged care facilities to further support the wellbeing of residents.

Inference on order restricted means of inverse Gaussian populations under heteroscedasticity

The hypothesis testing problem of homogeneity of k(≥2) inverse Gaussian means against ordered alternatives is studied when nuisance or scale-like parameters are unknown and unequal. The maximum likelihood estimators (MLEs) of means and scale-like parameters are obtained when means satisfy some simple order restrictions and scale-like parameters are unknown and unequal. An iterative algorithm is proposed for finding these estimators. It has been proved that under a specific condition, the proposed algorithm converges to the true MLEs uniquely. A likelihood ratio test and two simultaneous tests are proposed. Further, an algorithm for finding the MLEs of parameters is given when means are equal but unknown. Using the estimators, the likelihood ratio test is developed for testing against ordered alternative means. Using the asymptotic distribution, the asymptotic likelihood ratio test is proposed. However, for small samples, it does not perform well. Hence, a parametric bootstrap likelihood ratio test (PB LRT) is proposed. Therefore, the asymptotic validity of the bootstrap procedure has been shown. Using the Box-type approximation method, test statistics are developed for the two-sample problem of equality of means when scale-like parameters are heterogeneous. Using these, two PB-based heuristic tests are proposed. Asymptotic null distributions are derived and PB accuracy is also developed. Two asymptotic tests are also proposed using the asymptotic null distributions. To get the critical points and test statistics of the three PB tests and two asymptotic tests, an ‘R’ package is developed and shared on GitHub. Applications of the tests are illustrated using real data.

Evaluation of KIDs List Compliance at a Children’s Hospital Within a Large Academic Medical Center

OBJECTIVES In 2020, a list of Key Potentially Inappropriate Drugs in Pediatrics, known as the “KIDs List,” was published. The objective of this analysis was to evaluate institutional compliance with the ­recommendations in this publication and identify areas for improvement. METHODS Medications in the KIDs List were compared to the institutional formulary at a large academic medical center caring for pediatric and adult patients. Medications listed in the formulary were then ­evaluated for order comments and restrictions related to their use in pediatric patients. Oral liquid products and a group of commonly used intravenous (IV) medications were reviewed for potentially inappropriate excipients through available manufacturer information. The pediatric clinical specialists were then solicited to review and make recommendations for medications that had not been addressed. RESULTS Of the 67 medications or classes listed in the KIDs List, 47 (70.1%) of the medications are listed in our formulary and available for use. Of these 47 medications, 4 (8.5%) included warnings related to their use in pediatric patients. Of the 270 oral liquid medications reviewed, 206 (76.3%) contained at least 1 ­potentially inappropriate excipient. Of the 20 commonly used IV medications, 3 (15%) contained at least 1 potentially inappropriate excipient. CONCLUSIONS This review found that many medications listed in the KIDs List are included in our ­institution’s formulary and that few have warnings for pediatric patients built into the institutional electronic health record. Further review of medications in the formulary will be conducted to determine the next steps to implementing KIDs List recommendations.

Sequences from Fibonacci to Catalan: A combinatorial interpretationviaDyck paths

We use Dyck paths having some restrictions in order to give a combinatorial interpretation for some famous number sequences. Starting from the Fibonacci numbers we show how thek-generalized Fibonacci numbers, the powers of 2, the Pell numbers, thek-generalized Pell numbers and the even-indexed Fibonacci numbers can be obtained by means of constraints on the number of consecutive valleys (at a given height) of the Dyck paths. By acting on the maximum height of the paths we get a succession of number sequences whose limit is the sequence of Catalan numbers. For these numbers we obtain a family of interesting relations including afull historyrecurrence relation. The whole study can be accomplished also by involving particular sets of stringsviaa simple encoding of Dyck paths.

Using hybrid automata to model mitigation of global disease spread via travel restriction

<abstract><p>Inspired by the COVID-19 pandemic, we build a large-scale epidemiological model that accounts for coordination between regions, each using travel restrictions in order to attempt to mitigate the spread of disease. There is currently a need for simulations of countries cooperating since travel restriction policies are typically taken without global considerations. It is possible, for instance, that a strategy which appears unfavorable to a region at some point during a pandemic might be best for containing the global spread, or that only by coordinating policies among several regions can a restriction strategy be truly effective. We use the formalism of hybrid automata to model the global disease spread among the coordinating regions. We model a connected network of coupled Susceptible-Exposed-Infected-Recovered (SEIR) models by considering a weighted directed graph with each node corresponding to a single region's disease model. The SEIR dynamics for each region admit terms for inter-regional travel determined by the graph's Laplacian that additionally accounts for travel restrictions between regions. The existence of an edge may change according to so-called guard conditions, which are triggered when the proportion of symptomatic infected individuals in a region reaches a critical value. Lastly, we run simulations in MATLAB of a global disease spreading among regions using automated travel restrictions and analyze the results.</p></abstract>

Conceptual and analytical features of the attribution of multi-project activities of enterprises in the environment of construction development

The development of the state's economy depends on the efficiency of construction enterprises, as one of the indicators reflecting the state and trends of the internal and external economic environment. In the conditions of the functioning of construction enterprises, the importance of relations between the development of the construction and investment project and its stakeholders (project participants, interested persons) is increasing, which affect the resulting indicators as a complex set of organizational, factual and legal actions in the process of professional entrepreneurial activity aimed at creating and (or ) conversion of real estate objects for the purpose of obtaining profit from such transformations. In this context, it should be noted the decrease in the effectiveness of the interaction of construction developers, namely with customers of construction products, contractors, design organizations, competitors, public organizations. In such conditions, there is a need for the formation of theoretical and methodological foundations for the development and implementation of a stakeholder-oriented management strategy of construction enterprises as a method of organizing the investment process, which aims to organize financing and the implementation of a real estate development project within the given time and within the relevant restrictions in order to obtain a commercial benefits The article proposes a definition of the morphological classification of the essence of the concept of "development" in the construction industry on the basis of strategic contours and social directions and is determined by functional, resulting, structural, process, strategic, complex features, the relationships of which have a certain level of risk and threats. Risk and profitability are considered when forming an investment portfolio as two interdependent categories. The formalization of the amount of risk, which is evaluated according to the following parameters: the mathematical (average) expectation of the value of profitability, as well as the degree of variability of profitability, has been carried out.

Estimating the scale parameters of several exponential distributions under order restriction

. In the present work, we have investigated the problem of estimating the parameters of several exponential distributions with ordered scale parameters under linex loss function. The study includes the cases of known as well as unknown location parameters. For both cases, we have considered class of equivariant estimators. Then, sufficient conditions have been obtained under which the equivariant class of estimators improves upon the usual estimators. Using the established results, it has been shown that the restricted maximum likelihood estimator is inadmissible. Finally, for both cases, simulation study has been conducted to compare the risk performance of the proposed estimators.

Inference for dependent complementary competing risks model from an inverted Kumaraswamy distribution under ranked set sampling

AbstractRanked set sampling (RSS) has been proved to be an efficient sampling design for parametric and nonparametric inference. This paper explores inference for a maximum RSS procedure with unequal samples (MRSSU) with multiple dependent failure causes. When the lifetimes of units are characterized by a proposed complementary competing risks model, classical likelihood and Bayesian approaches are discussed for parameters and reliability estimation. Maximum likelihood estimators of model parameters and associated existence and uniqueness are established, and approximate confidence intervals are constructed using asymptotic theory and delta methods. With respect to general flexible priors, Bayesian estimates of interested quantities are also performed and a Monte Carlo sampling algorithm is proposed for complex posterior computation. Additionally, when extra historical information between the competing risks parameters is available, likelihood and Bayesian estimation are also studied under an order restriction case. Different methods are compared based on extensive simulation studies, and another real data example is demonstrated for application propose.