The reading the mind in the eyes test (RMET) – which assesses the theory of mind component of social cognition – is often used to compare social cognition between patients with schizophrenia and healthy controls. There is, however, no systematic review integrating the results of these studies. We identified 198 studies published before July 2020 that administered RMET to patients with schizophrenia or healthy controls from three English-language and two Chinese-language databases. These studies included 41 separate samples of patients with schizophrenia (total n = 1836) and 197 separate samples of healthy controls (total n = 23 675). The pooled RMET score was 19.76 (95% CI 18.91–20.60) in patients and 25.53 (95% CI 25.19–25.87) in controls (z = 12.41, p < 0.001). After excluding small-sample outlier studies, this difference in RMET performance was greater in studies using non-English v. English versions of RMET (Chi [Q] = 8.54, p < 0.001). Meta-regression analyses found a negative association of age with RMET score and a positive association of years of schooling with RMET score in both patients and controls. A secondary meta-analysis using a spline construction of 180 healthy control samples identified a non-monotonic relationship between age and RMET score – RMET scores increased with age before 31 and decreased with age after 31. These results indicate that patients with schizophrenia have substantial deficits in theory of mind compared with healthy controls, supporting the construct validity of RMET as a measure of social cognition. The different results for English versus non-English versions of RMET and the non-monotonic relationship between age and RMET score highlight the importance of the language of administration of RMET and the possibility that the relationship of aging with theory of mind is different from the relationship of aging with other types of cognitive functioning.

Reconstructing past climate events relies on the relevant proxies and how they are related. Depending only on such relationships, however, could not be robust because only few proxy observations are usually available at each age. A state-space model employs a prior to make the hidden past climate events correlated with one another so that extreme inferences are precluded. Here, we construct a Gaussian process state-space model for reconstructing past sea surface temperatures from the alkenone paleotemperature proxy and apply the model to nine sediment cores with three different calibration curves and compare the results.

The risk factors of environmental contamination by SARS-CoV-2 are largely unknown. We analyzed 1,320 environmental samples obtained from COVID-19 patients over 1 year. The risk factors for contamination of COVID-19 patients’ surrounding environment were higher viral load in the respiratory tract and shorter duration from symptom onset to sample collection.

Monte Carlo algorithms simulates some prescribed number of samples, taking some random real time to complete the computations necessary. This work considers the converse: to impose a real-time budget on the computation, which results in the number of samples simulated being random. To complicate matters, the real time taken for each simulation may depend on the sample produced, so that the samples themselves are not independent of their number, and a length bias with respect to compute time is apparent. This is especially problematic when a Markov chain Monte Carlo (MCMC) algorithm is used and the final state of the Markov chain—rather than an average over all states—is required, which is the case in parallel tempering implementations of MCMC. The length bias does not diminish with the compute budget in this case. It also occurs in sequential Monte Carlo (SMC) algorithms, which is the focus of this paper. We propose an anytime framework to address the concern, using a continuous-time Markov jump process to study the progress of the computation in real time. We first show that for any MCMC algorithm, the length bias of the final state’s distribution due to the imposed real-time computing budget can be eliminated by using a multiple chain construction. The utility of this construction is then demonstrated on a large-scale SMC$ {}^2 $ implementation, using four billion particles distributed across a cluster of 128 graphics processing units on the Amazon EC2 service. The anytime framework imposes a real-time budget on the MCMC move steps within the SMC$ {}^2 $ algorithm, ensuring that all processors are simultaneously ready for the resampling step, demonstrably reducing idleness to due waiting times and providing substantial control over the total compute budget.

We study the $L^{q}$ -spectrum of measures in the plane generated by certain nonlinear maps. In particular, we consider attractors of iterated function systems consisting of maps whose components are $C^{1+\alpha }$ and for which the Jacobian is a lower triangular matrix at every point subject to a natural domination condition on the entries. We calculate the $L^{q}$ -spectrum of Bernoulli measures supported on such sets by using an appropriately defined analogue of the singular value function and an appropriate pressure function.

The COVID-19 pandemic has had a major impact on clinical practice. Safe standards of practice are essential to protect health care workers while still allowing them to provide good care. The Canadian Society of Clinical Neurophysiologists, the Canadian Association of Electroneurophysiology Technologists, the Association of Electromyography Technologists of Canada, the Board of Registration of Electromyography Technologists of Canada, and the Canadian Board of Registration of Electroencephalograph Technologists have combined to review current published literature about safe practices for neurophysiology laboratories. Herein, we present the results of our review and provide our expert opinion regarding the safe practice of neurophysiology during the COVID-19 pandemic in Canada.

We describe an algorithm that can fit the properties of the dwarf galaxy progenitor of a tidal stream, given the properties of that stream. We show that under ideal conditions (the Milky Way potential, the orbit of the dwarf galaxy progenitor, and the functional form of the dwarf galaxy progenitor are known exactly), the density and angular width of stars along the stream can be used to constrain the mass and radial profile of both the stellar and dark matter components of the progenitor dwarf galaxy that was ripped apart to create the stream. Our provisional fit for the parameters of the dwarf galaxy progenitor of the Orphan Stream indicates that it is less massive and has fewer stars than previous works have indicated.

Objectives: The aim of this study was to evaluate the impact of computer-assisted “drill-and-strategy” cognitive remediation (CR) for community-dwelling individuals with schizophrenia on cognition, everyday self-efficacy, and independent living skills. Methods: Fifty-six people with schizophrenia or schizoaffective disorder were randomized into CR or computer game (CG) playing (control), and offered twenty 1-hr individual sessions in a group setting over 10 weeks. Measures of cognition, psychopathology, self-efficacy, quality of life, and independent living skills were conducted at baseline, end-group and 3 months following intervention completion. Results: Forty-three participants completed at least 10 sessions and the end-group assessment. Linear mixed-effect analyses among completers demonstrated a significant interaction effect for global cognition favoring CR (p=.028). CR-related cognitive improvement was sustained at 3-months follow-up. At end-group, 17 (77%) CR completers showed a reliable improvement in at least one cognitive domain. A significant time effect was evident for self-efficacy (p=.028) with both groups improving over time, but no significant interaction effect was observed. No significant effects were found for other study outcomes, including the functional measure. Conclusions: Computer-assisted drill-and-strategy CR in schizophrenia improved cognitive test performance, while participation in both CR and CG playing promoted enhancements in everyday self-efficacy. Changes in independent living skills did not appear to result from CR, however. Adjunctive psychosocial rehabilitation is likely necessary for improvements in real-world community functioning to be achieved. (JINS, 2018, 24, 549–562)

In field tests, common cocklebur (Xanthium pensylvanicum Wallr.) was controlled at the one- and two-leaf stages with 0.3 kg/ha acifluorfen {5-[2-chloro-4-(trifluoromethyl)phenoxy]-2-nitrobenzoic acid}. Four-leaf common cocklebur required 1.1 kg/ha for comparable control. Acifluorfen at 0.6 and 0.8 kg/ha controlled 96 and 90% of entireleaf morningglory [Ipomoea hederacea (L.) Jacq. var. integriuscula] atone- and two-leaf stages, respectively, but control was reduced as plants aged. Dark applications (2100 h) were more effective than those at sun-up (0600 h) or midday (1200 h) in control of hemp sesbania [Sesbania exaltata (Raf.) Cory], pitted morningglory (Ipomoea lacunosa L.), and smooth pigweed (Amaranthus hybridus L.). Hour of application had no significant influence on control of common cocklebur or prickly sida (Sida spinosa L.). An increase in surfactant (80% alkyl aryl polyoxyethylene glycols) concentration enhanced acifluorfen control of entireleaf morningglory and Texas gourd [Cucurbita texana (A.) Gray] at the 0.3-kg/ha rate applied 2 weeks after emergence. Soybean [Glycine max (L.) Merr.] injury was increased with the 1.1-kg/ha rate when surfactant concentration was increased from 0.5 to 0.75%. Increasing the spray volume increased pitted morningglory control but decreased hemp sesbania control. In the growth chamber, better control of pitted morningglory and common cocklebur was obtained at high (35 C day, 26 C night) than at low temperatures (27 C day, 18 C night) when plants were treated 1 week after emergence.