The Tokyo 2020 Olympic and Paralympic Games are promising comprehensive changes to accessibility for all who will be attending, including athletes, coaches, spectators, volunteers and organizers. The promises of accessibility will have impact on disability sport, society and culture, and the economy. This article examines accessible design features for promotional materials, training venues, hotel accommodations and local transportation, followed by a report on the progress made towards the accessibility goals for the Tokyo 2020 Games

This paper reports an expansion of the English as a second language (L2) component of the Multilingual Eye Movement Corpus (MECO L2), an international database of eye movements during text reading. While the previous Wave 1 of the MECO project (Kuperman et al., 2023) contained English as a L2 reading data from readers with 12 different first language (L1) backgrounds, the newly collected dataset adds eye-tracking data on English text reading from 13 distinct L1 backgrounds (N = 660) as well as participants’ scores on component skills of English proficiency and information about their demographics and language background and use. The paper reports reliability estimates, descriptive statistics, and correlational analyses as means to validate the expansion dataset. Consistent with prior literature and the MECO Wave 1, trends in the MECO Wave 2 data include a weak correlation between reading comprehension and oculomotor measures of reading fluency and a greater L1-L2 contrast in reading fluency than reading comprehension. Jointly with Wave 1, the MECO project includes English reading data from more than 1,200 readers representing a diversity of native writing systems (logographic, abjad, abugida, and alphabetic) and 19 distinct L1 backgrounds. We provide multiple pointers to new venues of how L2 reading researchers can mine this rich publicly available dataset.

Low birthweight is a risk factor for type 2 diabetes. We hypothesised that differential associations between birthweight and clinical characteristics in persons with and without type 2 diabetes may provide novel insights into the role of birthweight in type 2 diabetes and its progression. We analysed UK Biobank data from 9,442 persons with and 254,446 without type 2 diabetes. Associations between birthweight, clinical traits, and genetic predisposition were assessed using adjusted linear and logistic regression, comparing the lowest and highest 25% of birthweight to the middle 50%. Each kg increase in birthweight was associated with higher BMI, waist, and hip circumference, with stronger effects in persons with versus without type 2 diabetes (BMI: 0.74 [0.58, 0.90] vs. 0.21 [0.18, 0.24] kg/m2; waist: 2.15 [1.78, 2.52] vs. 1.04 [0.98, 1.09] cm; hip: 1.65 [1.33, 1.97] vs. 1.04 [1.04, 1.09] cm). Family history of diabetes was associated with higher birthweight regardless of diabetes status, albeit with a twofold higher effect estimate in type 2 diabetes. Low birthweight was further associated with prior myocardial infarction regardless of type 2 diabetes status (OR 1.33 [95% CI 1.11, 1.60] for type 2 diabetes; 1.23 [95% CI 1.13, 1.33] without), and hypertension (OR 1.25 [1.23, 1.28] and stroke 1.24 [1.14, 1.34]) only among persons without type 2 diabetes. Differential associations between birthweight and cardiometabolic traits in persons with and without type 2 diabetes illuminate potential causal inferences reflecting the roles of pre- and postnatal environmental versus genetic aetiologies and disease mechanisms.

We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110-ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839 $-$10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less and can detect $10\times$ more FRBs than the current CRAFT incoherent sum system (i.e. 0.5 $-$2 localised FRBs per day), enabling us to better constrain the models for FRBs and use them as cosmological probes.

Two studies were conducted in 2022 and 2023 near Rocky Mount and Clayton, NC, to determine the optimal granular ammonium sulfate (AMS) rate and application timing for pyroxasulfone-coated AMS. In the rate study, AMS rates included 161, 214, 267, 321, 374, 428, and 481 kg ha−1, equivalent to 34, 45, 56, 67, 79, 90, and 101 kg N ha−1, respectively. All rates were coated with pyroxasulfone at 118 g ai ha−1 and topdressed onto 5- to 7-leaf cotton. In the timing study, pyroxasulfone (118 g ai ha−1) was coated on AMS and topdressed at 321 kg ha−1 (67 kg N ha−1) onto 5- to 7-leaf, 9- to 11-leaf, and first bloom cotton. In both studies, weed control and cotton tolerance to pyroxasulfone-coated AMS were compared to pyroxasulfone applied POST and POST-directed. The check in both studies received non-herbicide-treated AMS (321 kg ha−1). Before treatment applications, all plots (including the check) were maintained weed-free with glyphosate and glufosinate. In both studies, pyroxasulfone applied POST was most injurious (8% to 16%), while pyroxasulfone-coated AMS resulted in ≤4% injury. Additionally, no differences in cotton lint yield were observed in either study. With the exception of the lowest rate of AMS (161 kg ha−1; 79%), all AMS rates coated with pyroxasulfone controlled Palmer amaranth ≥83%, comparably to pyroxasulfone applied POST (92%) and POST-directed (89%). In the timing study, the application method did not affect Palmer amaranth control; however, applications made at the mid- and late timings outperformed early applications. These results indicate that pyroxasulfone-coated AMS can control Palmer amaranth comparably to pyroxasulfone applied POST and POST-directed, with minimal risk of cotton injury. However, the application timing could warrant additional treatment to achieve adequate late-season weed control.

We describe a case of novel use of trametinib in treating arrythmia without concomitant cardiomyopathy. Our patient is a two-year-old female born with Costello syndrome due to heterozygous mutations in the HRAS gene c34 G > T p (G12C). Shortly after birth, she was diagnosed with multifocal atrial tachyarrhythmia. Her imaging studies have shown no hypertrophy or CHD. There was poor arrhythmia control despite triple antiarrhythmic therapy. Trametinib, a MEK1 and MEK2 inhibitor, was used in treating her isolated atrial arrythmia, allowing her to wean off other antiarrhythmics. Other case reports have shown trametinib to benefit certain RASopathy patients with lymphatic abnormalities, hypertrophic cardiomyopathy, and concurrent arrhythmias. This case demonstrates effective treatment of isolated arrhythmia without cardiomyopathy, broadening the potential indications for use of trametinib in certain RASopathy patients.

The main purpose of this paper is to investigate the sensitivity analysis of structural equation model when minor perturbation is introduced. Some influence measure that based on the general case weight perturbation is derived for the generalized least squares estimation. An influence measure that related to the Cook's distance is also developed for the special case deletion perturbation scheme. Using the proposed methodology, the influential observation in a data set can be detected. Moreover, the general theory can be applied to detect the influential parameters in a model. Finally, some illustrative artificial and real examples are presented.

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous and/or exogenous variables functional, varying over time, space, or other continua. Computationally, the method reduces to minimizing a penalized least-squares criterion through the adoption of a basis function expansion approach to approximating functions. We develop an alternating regularized least-squares algorithm to minimize this criterion. We apply the proposed method to real datasets to illustrate the empirical feasibility of the proposed method.

Graphical models have received an increasing amount of attention in network psychometrics as a promising probabilistic approach to study the conditional relations among variables using graph theory. Despite recent advances, existing methods on graphical models usually assume a homogeneous population and focus on binary or continuous variables. However, ordinal variables are very popular in many areas of psychological science, and the population often consists of several different groups based on the heterogeneity in ordinal data. Driven by these needs, we introduce the finite mixture of ordinal graphical models to effectively study the heterogeneous conditional dependence relationships of ordinal data. We develop a penalized likelihood approach for model estimation, and design a generalized expectation-maximization (EM) algorithm to solve the significant computational challenges. We examine the performance of the proposed method and algorithm in simulation studies. Moreover, we demonstrate the potential usefulness of the proposed method in psychological science through a real application concerning the interests and attitudes related to fan avidity for students in a large public university in the United States.

The small-world problem revolves around the tracing of a line of acquaintances linking any two persons chosen at random. This paper discusses the statistical analysis of data arising out of two experimental studies of the small-world problem. The estimation of parameters in two previously proposed models is discussed, and the goodness-of-fit of these models is considered.

Several algorithms for covariance structure analysis are considered in addition to the Fletcher-Powell algorithm. These include the Gauss-Newton, Newton-Raphson, Fisher Scoring, and Fletcher-Reeves algorithms. Two methods of estimation are considered, maximum likelihood and weighted least squares. It is shown that the Gauss-Newton algorithm which in standard form produces weighted least squares estimates can, in iteratively reweighted form, produce maximum likelihood estimates as well. Previously unavailable standard error estimates to be used in conjunction with the Fletcher-Reeves algorithm are derived. Finally all the algorithms are applied to a number of maximum likelihood and weighted least squares factor analysis problems to compare the estimates and the standard errors produced. The algorithms appear to give satisfactory estimates but there are serious discrepancies in the standard errors. Because it is robust to poor starting values, converges rapidly and conveniently produces consistent standard errors for both maximum likelihood and weighted least squares problems, the Gauss-Newton algorithm represents an attractive alternative for at least some covariance structure analyses.

This study examines the impact of COVID-19-induced policy environments on civil servants’ public service motivation (PSM), a topic not yet adequately researched. Using a vignette survey experiment, we investigate how four types of COVID-19 policy environment information – 1) total deduction of annual leave compensation, 2) a significant increase in working hours, 3) positive assessments of government responses from domestic audiences, and 4) positive assessments of government responses from other advanced democracies – shape civil servants’ PSM during the pandemic. We analyze original data from over 4,000 South Korean civil servants in central and local governments, gathered as part of a representative survey. Results show that reducing compensation to prepare the disaster relief fund has a negative impact, whereas recognition by advanced democracies has a positive impact on PSM. Our analysis suggests the importance of policy environments in both motivating and demotivating civil servants during a pandemic crisis.

Galaxy Zoo is an online project to classify morphological features in extra-galactic imaging surveys with public voting. In this paper, we compare the classifications made for two different surveys, the Dark Energy Spectroscopic Instrument (DESI) imaging survey and a part of the Kilo-Degree Survey (KiDS), in the equatorial fields of the Galaxy And Mass Assembly (GAMA) survey. Our aim is to cross-validate and compare the classifications based on different imaging quality and depth. We find that generally the voting agrees globally but with substantial scatter, that is, substantial differences for individual galaxies. There is a notable higher voting fraction in favour of ‘smooth’ galaxies in the DESI+zoobot classifications, most likely due to the difference between imaging depth. DESI imaging is shallower and slightly lower resolution than KiDS and the Galaxy Zoo images do not reveal details such as disc features and thus are missed in the zoobot training sample. We check against expert visual classifications and find good agreement with KiDS-based Galaxy Zoo voting. We reproduce the results from Porter-Temple+ (2022), on the dependence of stellar mass, star formation, and specific star formation on the number of spiral arms. This shows that once corrected for redshift, the DESI Galaxy Zoo and KiDS Galaxy Zoo classifications agree well on population properties. The zoobot cross-validation increases confidence in its ability to compliment Galaxy Zoo classifications and its ability for transfer learning across surveys.

Multi-site and multi-organizational teams are increasingly common in epidemiologic research; however, there is a lack of standards or best practices for achieving success in collaborative research networks in epidemiology. We summarize our experiences and lessons learned from the Diabetes Location, Environmental Attributes, and Disparities (LEAD) Network, a collaborative agreement between the Centers for Disease Control and Prevention and research teams at Drexel University, New York University, Johns Hopkins University and Geisinger, and the University of Alabama at Birmingham. We present a roadmap for success in collaborative epidemiologic research, with recommendations focused on the following areas to maximize efficiency and success in collaborative research agreements: 1) operational and administrative considerations; 2) data access and sharing of sensitive data; 3) aligning network research aims; 4) harmonization of methods and measures; and 5) dissemination of findings. Future collaborations can be informed by our experiences and ultimately dedicate more resources to achieving scientific aims and efficiently disseminating scientific work products.

Neglect remains understudied compared to other forms of maltreatment. While studies have shown that neglect has negative effects on mental health in adolescence, yet unresolved is whether these impacts result from critical period or cumulative effects. In the present article, we use a novel approach to compare these two hypotheses from the impact of two types of neglect, failure to provide (FTP) and lack of supervision (LOS), on adolescent depression and internalizing symptoms. Data derive from the LONGSCAN consortium, a diverse, multi-site, prospective study of children from approximately age 2–16. Despite our hypothesis that the critical period of early childhood would have the greatest impact on adolescent internalizing mental health, exposure to neglect during the critical period of adolescence (ages 12–16) was the best-fitting model for the effects of FTP neglect on depression, and the effects of LOS neglect on both depression and internalizing symptoms. The cumulative model (exposure across all time periods) best explained the effects of FTP neglect on internalizing symptoms. Results were robust to the addition of control variables, including other forms of maltreatment. These findings demonstrate that responding to neglect into adolescence must be considered as urgent for child welfare systems.