128 research outputs found
Fully Realizing Partial Realization
There has been a movement in philosophy, growing over the last twenty years, to treat dispositionality as irreducible and, in turn, offer dispositional accounts of important metaphysical matters such as the laws of nature, free will, causation, and modality. However, unlike the earlier turn towards possible worlds in metaphysics, the turn towards dispositions hasnât had much impact in semantics. But this is, in my view, largely because semanticists have yet to consider what dispositional analyses of (say) tense, aspect, generics, or modals would look like. My aim in this paper is to push the dispositionality movement forward on the semantics front by considering a dispositional analysis of the progressive aspect
Prediction of mental effort derived from an automated vocal biomarker using machine learning in a large-scale remote sample
IntroductionBiomarkers of mental effort may help to identify subtle cognitive impairments in the absence of task performance deficits. Here, we aim to detect mental effort on a verbal task, using automated voice analysis and machine learning.MethodsAudio data from the digit span backwards task were recorded and scored with automated speech recognition using the online platform NeuroVocalixTM, yielding usable data from 2,764 healthy adults (1,022 male, 1,742 female; mean age 31.4 years). Acoustic features were aggregated across each trial and normalized within each subject. Cognitive load was dichotomized for each trial by categorizing trials at >0.6 of each participants' maximum span as âhigh load.â Data were divided into training (60%), test (20%), and validate (20%) datasets, each containing different participants. Training and test data were used in model building and hyper-parameter tuning. Five classification models (Logistic Regression, Naive Bayes, Support Vector Machine, Random Forest, and Gradient Boosting) were trained to predict cognitive load (âhighâ vs. âlowâ) based on acoustic features. Analyses were limited to correct responses. The model was evaluated using the validation dataset, across all span lengths and within the subset of trials with a four-digit span. Classifier discriminant power was examined with Receiver Operating Curve (ROC) analysis.ResultsParticipants reached a mean span of 6.34 out of 8 items (SD = 1.38). The Gradient Boosting classifier provided the best performing model on test data (AUC = 0.98) and showed excellent discriminant power for cognitive load on the validation dataset, across all span lengths (AUC = 0.99), and for four-digit only utterances (AUC = 0.95).DiscussionA sensitive biomarker of mental effort can be derived from vocal acoustic features in remotely administered verbal cognitive tests. The use-case of this biomarker for improving sensitivity of cognitive tests to subtle pathology now needs to be examined
Search for dark matter produced in association with bottom or top quarks in âs = 13 TeV pp collisions with the ATLAS detector
A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fbâ1 of protonâproton collision data recorded by the ATLAS experiment at âs = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements
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Transcriptomic cytoarchitecture reveals principles of human neocortex organization.
Variation in cytoarchitecture is the basis for the histological definition of cortical areas. We used single cell transcriptomics and performed cellular characterization of the human cortex to better understand cortical areal specialization. Single-nucleus RNA-sequencing of 8 areas spanning cortical structural variation showed a highly consistent cellular makeup for 24 cell subclasses. However, proportions of excitatory neuron subclasses varied substantially, likely reflecting differences in connectivity across primary sensorimotor and association cortices. Laminar organization of astrocytes and oligodendrocytes also differed across areas. Primary visual cortex showed characteristic organization with major changes in the excitatory to inhibitory neuron ratio, expansion of layer 4 excitatory neurons, and specialized inhibitory neurons. These results lay the groundwork for a refined cellular and molecular characterization of human cortical cytoarchitecture and areal specialization
Amputation-induced reactive oxygen species are required for successful Xenopus tadpole tail regeneration.
Understanding the molecular mechanisms that promote successful tissue regeneration is critical for continued advancements in regenerative medicine. Vertebrate amphibian tadpoles of the species Xenopus laevis and Xenopus tropicalis have remarkable abilities to regenerate their tails following amputation, through the coordinated activity of numerous growth factor signalling pathways, including the Wnt, Fgf, Bmp, Notch and TGF-ÎČ pathways. Little is known, however, about the events that act upstream of these signalling pathways following injury. Here, we show that Xenopus tadpole tail amputation induces a sustained production of reactive oxygen species (ROS) during tail regeneration. Lowering ROS levels, using pharmacological or genetic approaches, reduces the level of cell proliferation and impairs tail regeneration. Genetic rescue experiments restored both ROS production and the initiation of the regenerative response. Sustained increased ROS levels are required for Wnt/ÎČ-catenin signalling and the activation of one of its main downstream targets, fgf20 (ref. 7), which, in turn, is essential for proper tail regeneration. These findings demonstrate that injury-induced ROS production is an important regulator of tissue regeneration
A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex.
Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis
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