Spoken Discourse Assessment and Analysis in Aphasia: An International Survey of Current Practices.

Purpose Spoken discourse analysis is commonly employed in the assessment and treatment of people living with aphasia, yet there is no standardization in assessment, analysis, or reporting procedures, thereby precluding comparison/meta-analyses of data and hindering replication of findings. An important first step is to identify current practices in collecting and analyzing spoken discourse in aphasia. Thus, this study surveyed current practices, with the goal of working toward standardizing spoken discourse assessment first in research settings with subsequent implementation into clinical settings. Method A mixed-methods (quantitative and qualitative) survey was publicized to researchers and clinicians around the globe who have collected and/or analyzed spoken discourse data in aphasia. The survey data were collected between September and November 2019. Results Of the 201 individuals who consented to participate, 189 completed all mandatory questions in the survey (with fewer completing nonmandatory response questions). The majority of respondents reported barriers to utilizing discourse including transcription, coding, and analysis. The most common barrier was time (e.g., lack of time). Respondents also indicated that there was a lack of, and a need for, psychometric properties and normative data for spoken discourse use in the assessment and treatment of persons with aphasia. Quantitative and qualitative results are described in detail. Conclusions The current survey study evaluated spoken discourse methods in aphasia across research and clinical settings. Findings from this study will be used to guide development of process standardization in spoken discourse and for the creation of a psychometric and normative property database. Supplemental Material https://doi.org/10.23641/asha.166395100

Martensitic transition and magnetoresistance in a Cu-Al-Mn shape memory alloy. Influence of aging

We have studied the effect of ageing within the miscibility gap on the electric, magnetic and thermodynamic properties of a non-stoichiometric Heusler Cu-Al-Mn shape-memory alloy, which undergoes a martensitic transition from a $bcc$-based ($\beta$-phase) towards a close-packed structure ($M$-phase). Negative magnetoresistance which shows an almost linear dependence on the square of magnetization with different slopes in the $M$- and $\beta$-phases, was observed. This magnetoresistive effect has been associated with the existence of Mn-rich clusters with the Cu$_2$AlMn-structure. The effect of an applied magnetic field on the martensitic transition has also been studied. The entropy change between the $\beta$- and $M$-phases shows negligible dependence on the magnetic field but it decreases significantly with annealing time within the miscibility gap. Such a decrease is due to the increasing amount of Cu$_2$MnAl-rich domains that do not transform martensitically.Comment: 9 pages, 9 figures, accepted for publication in PR

Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics.

OBJECTIVE:To evaluate if mid-pregnancy immune and growth-related molecular factors predict preterm birth (PTB) with and without (±) preeclampsia. STUDY DESIGN:Included were 400 women with singleton deliveries in California in 2009-2010 (200 PTB and 200 term) divided into training and testing samples at a 2:1 ratio. Sixty-three markers were tested in 15-20 serum samples using multiplex technology. Linear discriminate analysis was used to create a discriminate function. Model performance was assessed using area under the receiver operating characteristic curve (AUC). RESULTS:Twenty-five serum biomarkers along with maternal age <34 years and poverty status identified >80% of women with PTB ± preeclampsia with best performance in women with preterm preeclampsia (AUC = 0.889, 95% confidence interval (0.822-0.959) training; 0.883 (0.804-0.963) testing). CONCLUSION:Together with maternal age and poverty status, mid-pregnancy immune and growth factors reliably identified most women who went on to have a PTB ± preeclampsia

The role of 44-methylgambierone in ciguatera fish poisoning: Acute toxicity, production by marine microalgae and its potential as a biomarker for Gambierdiscus spp.

Ciguatera fish poisoning (CFP) is prevalent around the tropical and sub-tropical latitudes of the world and impacts many Pacific island communities intrinsically linked to the reef system for sustenance and trade. While the genus Gambierdiscus has been linked with CFP, it is commonly found on tropical reef systems in microalgal assemblages with other genera of toxin-producing, epiphytic and/or benthic dinoflagellates - Amphidinium, Coolia, Fukuyoa, Ostreopsis and Prorocentrum. Identifying a biomarker compound that can be used for the early detection of Gambierdiscus blooms, specifically in a mixed microalgal community, is paramount in enabling the development of management and mitigation strategies. Following on from the recent structural elucidation of 44-methylgambierone, its potential to contribute to CFP intoxication events and applicability as a biomarker compound for Gambierdiscus spp. was investigated. The acute toxicity of this secondary metabolite was determined by intraperitoneal injection using mice, which showed it to be of low toxicity, with an LD50 between 20 and 38 mg kg-1. The production of 44-methylgambierone by 252 marine microalgal isolates consisting of 90 species from 32 genera across seven classes, was assessed by liquid chromatography-tandem mass spectrometry. It was discovered that the production of this secondary metabolite was ubiquitous to the eight Gambierdiscus species tested, however not all isolates of G. carpenteri, and some species/isolates of Coolia and Fukuyoa

Decreasing the minimum length criterion for an episode of hypomania: evaluation using self-reported data from patients with bipolar disorder

Brief hypomania lasting less than 4 days may impair functioning and help to detect bipolarity. This study analyzed brief hypomania that occurred in patients with bipolar disorder who were diagnosed according to the DSM-IV criteria. Daily self-reported mood ratings were obtained from 393 patients (247 bipolar I and 146 bipolar II) for 6 months (75,284 days of data, mean 191.6 days). Episodes of hypomania were calculated using a 4, 3, 2, and single day length criterion. Brief hypomania occurred frequently. With a decrease in the minimum criterion from 4 days to 2 days, there were almost twice as many patients with an episode of hypomania (102 vs. 190), and more than twice as many episodes (305 vs. 863). Single days of hypomania were experienced by 271 (69%) of the sample. With a 2-day episode length, 33% of all hypomania remained outside of an episode. There was no significant difference in the percent of hypomanic days outside of an episode between patients with bipolar I and II disorders. There were no significant differences in the demographic characteristics of patients who met the 4-day minimum as compared with those who only experienced episodes of hypomania using a shortened length criterion. Decreasing the minimum length criterion for an episode of hypomania will cause a large increase in the number of patients who experience an episode and in the aggregate number of episodes, but will not distinguish subgroups within a sample who meet the DSM-IV criteria for bipolar disorder. Frequency may be an important dimensional aspect of brief hypomania. Clinicians should regularly probe for brief hypomania

A Comparison of Machine Learning and Classical Demand Forecasting Methods: A Case Study of Ecuadorian Textile Industry

[EN] This document presents a comparison of demand forecasting methods, with the aim of improving demand forecasting and with it, the production planning system of Ecuadorian textile industry. These industries present problems in providing a reliable estimate of future demand due to recent changes in the Ecuadorian context. The impact on demand for textile products has been observed in variables such as sales prices and manufacturing costs, manufacturing gross domestic product and the unemployment rate. Being indicators that determine to a great extent, the quality and accuracy of the forecast, generating also, uncertainty scenarios. For this reason, the aim of this work is focused on the demand forecasting for textile products by comparing a set of classic methods such as ARIMA, STL Decomposition, Holt-Winters and machine learning, Artificial Neural Networks, Bayesian Networks, Random Forest, Support Vector Machine, taking into consideration all the above mentioned, as an essential input for the production planning and sales of the textile industries. And as a support, when developing strategies for demand management and medium-term decision making of this sector under study. Finally, the effectiveness of the methods is demonstrated by comparing them with different indicators that evaluate the forecast error, with the Multi-layer Neural Networks having the best results with the least error and the best performance.The authors are greatly grateful by the support given by the SDAS Research Group (https://sdas-group.com/).Lorente-Leyva, LL.; Alemany Díaz, MDM.; Peluffo-Ordóñez, DH.; Herrera-Granda, ID. (2021). 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A Rare Periosteal Diaphyseal Lesion of the Ulna

Periosteal lesions of the ulna diaphysis are rare, include a wide spectrum of tumors, and may cause considerable diagnostic problems. Surgical treatment may vary widely, based on an accurate diagnosis. We present the case of a periosteal, extraskeletal low grade myxoid chondrosarcoma of the ulna diaphysis. The surgical therapy included an en-bloc resection with allograft reconstruction. The patient showed a favorable outcome. Careful preoperative evaluation and planning are imperative to obtain a satisfactory oncological and functional outcome, especially with uncommon tumor presentations at rare locations

Can we rely on the best trial? A comparison of individual trials and systematic reviews

BACKGROUND: The ideal evidence to answer a question about the effectiveness of treatment is a systematic review. However, for many clinical questions a systematic review will not be available, or may not be up to date. One option could be to use the evidence from an individual trial to answer the question? METHODS: We assessed how often (a) the estimated effect and (b) the p-value in the most precise single trial in a meta-analysis agreed with the whole meta-analysis. For a random sample of 200 completed Cochrane Reviews (January, 2005) we identified a primary outcome and extracted: the number of trials, the statistical weight of the most precise trial, the estimate and confidence interval for both the highest weighted trial and the meta-analysis overall. We calculated the p-value for the most precise trial and meta-analysis. RESULTS: Of 200 reviews, only 132 provided a meta-analysis of 2 or more trials, with a further 35 effect estimates based on single trials. The average number of trials was 7.3, with the most precise trial contributing, on average, 51% of the statistical weight to the summary estimate from the whole meta-analysis. The estimates of effect from the most precise trial and the overall meta-analyses were highly correlated (rank correlation of 0.90).There was an 81% agreement in statistical conclusions. Results from the most precise trial were statistically significant in 60 of the 167 evaluable reviews, with 55 of the corresponding systematic reviews also being statistically significant. The five discrepant results were not strikingly different with respect to their estimates of effect, but showed considerable statistical heterogeneity between trials in these meta-analyses. However, among the 101 cases in which the most precise trial was not statistically significant, the corresponding meta-analyses yielded 31 statistically significant results. CONCLUSIONS: Single most precise trials provided similar estimates of effects to those of the meta-analyses to which they contributed, and statistically significant results are generally in agreement. However, "negative" results were less reliable, as may be expected from single underpowered trials. For systematic reviewers we suggest that: (1) key trial(s) in a review deserve greater attention (2) systematic reviewers should check agreement of the most precise trial and the meta analysis. For clinicians using trials we suggest that when a meta-analysis is not available, a focus on the most precise trial is reasonable provided it is adequately powered

Understanding fear of opportunism in global prize-based science contests: Evidence for gender and age differences

Global prize-based science contests have great potential for tapping into diverse knowledge on a global scale and overcoming important scientific challenges. A necessary step for knowledge to be utilized in these contests is for that knowledge to be disclosed. Knowledge disclosure, however, is paradoxical in nature: in order for the value of knowledge to be assessed, inventors must disclose their knowledge, but then the person who receives that knowledge does so at no cost and may use it opportunistically. This risk of potential opportunistic behavior in turn makes the inventor fearful of disclosing knowledge, and this is a major psychological barrier to knowledge disclosure. In this project, we investigated this fear of opportunism in global prize-based science contests by surveying 630 contest participants in the InnoCentive online platform for science contests. We found that participants in these science contests experience fear of opportunism to varying degrees, and that women and older participants have significantly less fear of disclosing their scientific knowledge. Our findings highlight the importance of taking differences in such fears into account when designing global prize-based contests so that the potential of the contests for reaching solutions to important and challenging problems can be used more effectively