Crouchnedergaard5209

From about 7 months of age onward, infants start to reliably fixate the goal of an observed action, such as a grasp, before the action is complete. The available research has identified a variety of factors that influence such goal-anticipatory gaze shifts, including the experience with the shown action events and familiarity with the observed agents. However, the underlying cognitive processes are still heavily debated. We propose that our minds (i) tend to structure sensorimotor dynamics into probabilistic, generative event-predictive, and event boundary predictive models, and, meanwhile, (ii) choose actions with the objective to minimize predicted uncertainty. We implement this proposition by means of event-predictive learning and active inference. The implemented learning mechanism induces an inductive, event-predictive bias, thus developing schematic encodings of experienced events and event boundaries. The implemented active inference principle chooses actions by aiming at minimizing expected future uncertainty. We train our system on multiple object-manipulation events. As a result, the generation of goal-anticipatory gaze shifts emerges while learning about object manipulations the model starts fixating the inferred goal already at the start of an observed event after having sampled some experience with possible events and when a familiar agent (i.e., a hand) is involved. Meanwhile, the model keeps reactively tracking an unfamiliar agent (i.e., a mechanical claw) that is performing the same movement. We qualitatively compare these modeling results to behavioral data of infants and conclude that event-predictive learning combined with active inference may be critical for eliciting goal-anticipatory gaze behavior in infants.Identifying the formation time of a document is a problem forensic document examiners often face. It is understood that intersections with different intersecting sequences made by the same laser printer and the same gel pen are distinct from each other under coaxial light, and the appearance of an oil film or bright metallic marks in the regions of interest can be used as the basis to identify that the ink is above the toner. However, the characteristics of intersections may be influenced by a number of factors. Studying the characteristics of the intersections formed by laser-printed graphics and handwriting strokes made with a gel pen in different intersecting sequences can help us determine the formation sequence of each part on a questioned document. In this manuscript, samples were made using three pen types and two laser printers. A Leica stereo microscope M205A was used to capture the apparent morphology of the intersections. Microspectrophotometry spectra of all intersections were collected in reflectance mode using a video spectral comparator 6000 (VSC6000), and the resultant data were measured and analyzed in Statistical Product and Service Solutions 26.0 (SPSS). Tivozanib mw The results showed that 92.5% absolute accuracy was achieved from blind tests, and the intersecting sequence can be determined using the optical data of the intersections with an accuracy of up to 97.5% through discriminant analysis under ideal conditions.The current research investigates how prior preferences affect causal learning. Participants were tasked with repeatedly choosing policies (e.g., increase vs. decrease border security funding) in order to maximize the economic output of an imaginary country and inferred the influence of the policies on the economy. The task was challenging and ambiguous, allowing participants to interpret the relations between the policies and the economy in multiple ways. In three studies, we found evidence of motivated reasoning despite financial incentives for accuracy. For example, participants who believed that border security funding should be increased were more likely to conclude that increasing border security funding actually caused a better economy in the task. In Study 2, we hypothesized that having neutral preferences (e.g., preferring neither increased nor decreased spending on border security) would lead to more accurate assessments overall, compared to having a strong initial preference; however, we did not find evidence for such an effect. In Study 3, we tested whether providing participants with possible functional forms of the policies (e.g., the policy takes some time to work or initially has a negative influence but eventually a positive influence) would lead to a smaller influence of motivated reasoning but found little evidence for this effect. This research advances the field of causal learning by studying the role of prior preferences, and in doing so, integrates the fields of causal learning and motivated reasoning using a novel explore-exploit task.

In low- and middle-income countries, such as Brazil, studies on the causes of death in asbestos-exposed workers are scarce.

A cohort study was performed involving 988 males who had worked in the asbestos-cement industry in the state of São Paulo, with a total of 12,217 person-years of observation between 1995 and 2016. The standardized mortality ratio (SMR) stratified by age was calculated as the ratio between the observed rate and the expected rate in the state of São Paulo.

Increased SMRs were observed for overall mortality (SMR 1.1, 95% confidence interval [CI], 0.98-1.23) and mortality due to pleural malignant neoplasms (MN) (SMR, 69.4; 95% CI, 22.55-162.1), asbestosis (SMR, 975.7; 95% CI, 396.4-2031), peritoneal MN (SMR, 5.0; 95% CI, 0.13-27.78), laryngeal MN (SMR, 1.4; 95% CI, 0.30-4.20), and pulmonary MN (SMR, 1.5; 95% CI, 0.82-2.64).

The present study highlights the damage caused by asbestos exposure and reinforces the existing evidence of a causal association between exposure and increased mortality due to pleural MN, pulmonary MN, and asbestosis.

The present study highlights the damage caused by asbestos exposure and reinforces the existing evidence of a causal association between exposure and increased mortality due to pleural MN, pulmonary MN, and asbestosis.Similarity is one of the most important relations humans perceive, arguably subserving category learning and categorization, generalization and discrimination, judgment and decision making, and other cognitive functions. Researchers have proposed a wide range of representations and metrics that could be at play in similarity judgment, yet have not comprehensively compared the power of these representations and metrics for predicting similarity within and across different semantic categories. We performed such a comparison by pairing nine prominent vector semantic representations with seven established similarity metrics that could operate on these representations, as well as supervised methods for dimensional weighting in the similarity function. This approach yields a factorial model structure with 126 distinct representation-metric pairs, which we tested on a novel dataset of similarity judgments between pairs of cohyponymic words in eight categories. We found that cosine similarity and Pearson correlation were the overall best performing unweighted similarity functions, and that word vectors derived from free association norms often outperformed word vectors derived from text (including those specialized for similarity). Importantly, models that used human similarity judgments to learn category-specific weights on dimensions yielded substantially better predictions than all unweighted approaches across all types of similarity functions and representations, although dimension weights did not generalize well across semantic categories, suggesting strong category context effects in similarity judgment. We discuss implications of these results for cognitive modeling and natural language processing, as well as for theories of the representations and metrics involved in similarity.

Neoadjuvant chemotherapy (NAC) is standard management for localized gastric cancer (GC). Attrition during NAC due to treatment-related toxicity or functional decline is considered a surrogate for worse biologic outcomes; however, data supporting this paradigm are lacking. We investigated factors predicting attrition and its association with overall survival (OS) in GC.

Patients with nonmetastatic GC initiating NAC were identified from the US Safety-Net Collaborative (2012-2014). Patient/treatment-related characteristics were compared between attrition/nonattrition cohorts. Cox models determined factors associated with OS.

Of 116 patients initiating NAC, attrition during prescribed NAC occurred in 24%. No differences were observed in performance status, comorbidities, treatment at safety-net hospital, or clinicopathologic factors between cohorts. Despite absence of distinguishing factors, attrition was associated with worse OS (median 11 vs. 37 months; p = 0.01) and was an independent predictor of mortality (hazard ratio [HR] 4.7, 95% confidence interval [CI] 1.5-15.2; p = 0.02). Fewer patients with attrition underwent curative-intent surgery (39% vs. 89%; p < 0.001). Even in patients undergoing surgical exploration (n = 89), NAC attrition remained an independent predictor of worse OS (HR 50.8, 95% CI 3.6-717.8; p = 0.004) despite similar receipt of adjuvant chemotherapy.

Attrition during NAC for nonmetastatic GC is independently associated with worse OS, even in patients undergoing surgery. Attrition during NAC may reflect unfavorable tumor biology not captured by conventional staging metrics.

Attrition during NAC for nonmetastatic GC is independently associated with worse OS, even in patients undergoing surgery. Attrition during NAC may reflect unfavorable tumor biology not captured by conventional staging metrics.

Model 3 of Medicare's Bundled Payments for Care Improvement (BPCI) was a voluntary alternative payment model that held participating skilled nursing facilities (SNFs) accountable for 90-day costs of care. Its overall impact on Medicare spending and clinical outcomes is unknown.

Retrospective cohort study using Medicare claims from 2012 to 2017. We used an interrupted time-series design to compare participating vs matched control SNFs on total 90-day Medicare payments and payment components (initial SNF stay, readmissions, and outpatient/clinician), case mix (volume, proportion Medicaid, proportion black, number of comorbidities), and clinical outcomes (90-day readmission, mortality and healthy days at home, and length of initial SNF stay), overall and among key subgroups with frailty or dementia, for 47 of the 48 conditions in the program (excluding major lower extremity joint replacement).

Our sample included 1001 participating and 3873 matched control SNFs. At baseline, total Medicare institutional pats in patients with frailty that may warrant further study.

SNF participation in BPCI was associated with no overall differential change in total Medicare payments per episode, case selection, or clinical outcomes. Exploratory analyses revealed a decrease in Medicare payments in patients with frailty that may warrant further study.Agricultural communities of New Mexico regularly redistribute manure nutrients from dairies to nearby croplands to fulfill agronomic nutrient needs and protect water quality. Yet competition for water resources can result in land use change that impacts these cooperative manure transfers. Focusing on three clusters of New Mexico dairy farms and their surrounding lands - three manuresheds - we calculated the magnitude of land use changes in 2008-2019 and the balance between manure nutrient supply and crop demand in 2019, to assess how past change may predict future prospects for sustainable management. The overall magnitude of change was small, with each manureshed experiencing a different complement an exchange of cropland and rangeland in the Roosevelt manureshed (7975 ha rangeland to cropland; 7624 ha cropland to rangeland), a 464-ha gain in cropland yet 1187-ha loss of "spreadable" land (cropland, rangeland, fallow) to developed land in the Doña Ana manureshed, and relatively minor changes in the Chaves manureshed.