Is Task-Irrelevant Learning Really Task-Irrelevant?

In the present study we address the question of whether the learning of task-irrelevant stimuli found in the paradigm of task-irrelevant learning (TIPL) [1]–[9] is truly task irrelevant. To test the hypothesis that associations that are beneficial to task-performance may develop between the task-relevant and task-irrelevant stimuli, or the task-responses and the task-irrelevant stimuli, we designed a new procedure in which correlations between the presentation of task-irrelevant motion stimuli and the identity of task-targets or task-responses were manipulated. We found no evidence for associations developing between the learned (task-irrelevant) motion stimuli and the targets or responses to the letter identification task used during training. Furthermore, the conditions that had the greatest correlations between stimulus and response showed the least amount of TIPL. On the other hand, TIPL was found in conditions of greatest response uncertainty and with the greatest processing requirements for the task-relevant stimuli. This is in line with our previously published model that suggests that task-irrelevant stimuli benefit from the spill-over of learning signals that are released due to processing of task-relevant stimuli

Is Task-Irrelevant Learning Really Task-Irrelevant?

In the present study we address the question of whether the learning of task-irrelevant stimuli found in the paradigm of task-irrelevant learning (TIPL) [1]–[9] is truly task irrelevant. To test the hypothesis that associations that are beneficial to task-performance may develop between the task-relevant and task-irrelevant stimuli, or the task-responses and the task-irrelevant stimuli, we designed a new procedure in which correlations between the presentation of task-irrelevant motion stimuli and the identity of task-targets or task-responses were manipulated. We found no evidence for associations developing between the learned (task-irrelevant) motion stimuli and the targets or responses to the letter identification task used during training. Furthermore, the conditions that had the greatest correlations between stimulus and response showed the least amount of TIPL. On the other hand, TIPL was found in conditions of greatest response uncertainty and with the greatest processing requirements for the task-relevant stimuli. This is in line with our previously published model that suggests that task-irrelevant stimuli benefit from the spill-over of learning signals that are released due to processing of task-relevant stimuli

Contrast response function estimation with nonparametric Bayesian active learning

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast sensitivity functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This article describes the development of the machine learning contrast response function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the machine learning contrast sensitivity function (MLCSF) was evaluated to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential

Characterization of SuperCDMS 1-inch Ge Detectors

The newly commissioned SuperCDMS Soudan experiment aims to search for WIMP dark matter with a sensitivity to cross sections of 5×10^(−45)cm^2 and larger (90% CL upper limit). This goal is facilitated by a new set of germanium detectors, 2.5 times more massive than the ones used in the CDMS-II experiment, and with a different athermal phonon sensor layout that eliminates radial degeneracy in position reconstruction of high radius events. We present characterization data on these detectors, as well as improved techniques for correcting position-dependent variations in pulse shape across the detector. These improvements provide surface-event discrimination sufficient for a reach of 5×10^(−45)cm^2

The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease.

BACKGROUND: Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical procedures, therapies, and interventions. METHODS: MAxO incorporates logical structures that link MAxO terms to numerous other ontologies within the OBO Foundry. Term development involves a blend of manual and semi-automated processes. Additionally, we have generated annotations detailing diagnostic modalities for specific phenotypic abnormalities defined by the Human Phenotype Ontology (HPO). We introduce a web application, POET, that facilitates MAxO annotations for specific medical actions for diseases using the Mondo Disease Ontology. FINDINGS: MAxO encompasses 1,757 terms spanning a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. These terms annotate phenotypic features associated with specific disease (using HPO and Mondo). Presently, there are over 16,000 MAxO diagnostic annotations that target HPO terms. Through POET, we have created 413 MAxO annotations specifying treatments for 189 rare diseases. CONCLUSIONS: MAxO offers a computational representation of treatments and other actions taken for the clinical management of patients. Its development is closely coupled to Mondo and HPO, broadening the scope of our computational modeling of diseases and phenotypic features. We invite the community to contribute disease annotations using POET (https://poet.jax.org/). MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO). FUNDING: NHGRI 1U24HG011449-01A1 and NHGRI 5RM1HG010860-04

Diving into the vertical dimension of elasmobranch movement ecology

Knowledge of the three-dimensional movement patterns of elasmobranchs is vital to understand their ecological roles and exposure to anthropogenic pressures. To date, comparative studies among species at global scales have mostly focused on horizontal movements. Our study addresses the knowledge gap of vertical movements by compiling the first global synthesis of vertical habitat use by elasmobranchs from data obtained by deployment of 989 biotelemetry tags on 38 elasmobranch species. Elasmobranchs displayed high intra- and interspecific variability in vertical movement patterns. Substantial vertical overlap was observed for many epipelagic elasmobranchs, indicating an increased likelihood to display spatial overlap, biologically interact, and share similar risk to anthropogenic threats that vary on a vertical gradient. We highlight the critical next steps toward incorporating vertical movement into global management and monitoring strategies for elasmobranchs, emphasizing the need to address geographic and taxonomic biases in deployments and to concurrently consider both horizontal and vertical movements

Search for excited leptons in pp collisions at √s=7 TeV

This is the pre-print version of the final published paper that is available from the link belowResults are presented of a search for compositeness in electrons and muons using a data sample of pp collisions at a center-of-mass energy √s=7 TeV collected with the CMS detector at the LHC and corresponding to an integrated luminosity of 5.0 fb−15.0 fb−1. Excited leptons (ℓ⁎) are assumed to be produced via contact interactions in conjunction with a standard model lepton and to decay via ℓ⁎→ℓγ, yielding a final state with two energetic leptons and a photon. The number of events observed in data is consistent with that expected from the standard model. The 95% confidence upper limits for the cross section for the production and decay of excited electrons (muons), with masses ranging from 0.6 to 2 TeV, are 1.48 to 1.24 fb (1.31 to 1.11 fb). Excited leptons with masses below 1.9 TeV are excluded for the case where the contact interaction scale equals the excited lepton mass. The limits on the cross sections are the most stringent ones published to date

Diving into the vertical dimension of elasmobranch movement ecology

Knowledge of the three-dimensional movement patterns of elasmobranchs is vital to understand their ecological roles and exposure to anthropogenic pressures. To date, comparative studies among species at global scales have mostly focused on horizontal movements. Our study addresses the knowledge gap of vertical movements by compiling the first global synthesis of vertical habitat use by elasmobranchs from data obtained by deployment of 989 biotelemetry tags on 38 elasmobranch species. Elasmobranchs displayed high intra- and interspecific variability in vertical movement patterns. Substantial vertical overlap was observed for many epipelagic elasmobranchs, indicating an increased likelihood to display spatial overlap, biologically interact, and share similar risk to anthropogenic threats that vary on a vertical gradient. We highlight the critical next steps toward incorporating vertical movement into global management and monitoring strategies for elasmobranchs, emphasizing the need to address geographic and taxonomic biases in deployments and to concurrently consider both horizontal and vertical movements

Diving into the vertical dimension of elasmobranch movement ecology

Knowledge of the three-dimensional movement patterns of elasmobranchs is vital to understand their ecological roles and exposure to anthropogenic pressures. To date, comparative studies among species at global scales have mostly focused on horizontal movements. Our study addresses the knowledge gap of vertical movements by compiling the first global synthesis of vertical habitat use by elasmobranchs from data obtained by deployment of 989 biotelemetry tags on 38 elasmobranch species. Elasmobranchs displayed high intra- and interspecific variability in vertical movement patterns. Substantial vertical overlap was observed for many epipelagic elasmobranchs, indicating an increased likelihood to display spatial overlap, biologically interact, and share similar risk to anthropogenic threats that vary on a vertical gradient. We highlight the critical next steps toward incorporating vertical movement into global management and monitoring strategies for elasmobranchs, emphasizing the need to address geographic and taxonomic biases in deployments and to concurrently consider both horizontal and vertical movements

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis