3,895 research outputs found
Concurrent Deficits in Behavior Inhibition, Non-verbal Working Memory and Psychological Sense of Time in ADHD
According to the Hybrid Model of Executive Function for Attention Deficit Hyperactivity Disorder (ADHD), hyperactive and combined types, a delay in behavior inhibition causes secondary deficits in four executive function; non-verbal working memory, verbal working memory, reconstitution and self-regulation of affect/motivation/arousal. The deficit in non-verbal working memory causes a deficit in psychological sense of time, which in tum impairs self-regulation in those with ADHD. This single case study investigated concurrent deficits in behavior inhibition, non-verbal working memory and psychological sense of time in a 1O-year-old male with ADHD, combined type. Three interrelated components of behavior inhibition were measured by the Continuous Performance Test-II, The Wisconsin Card Sorting Test, and the Stroop Test. Non-verbal working memory was measured by using the Rey-Complex Figure Test and Recognition Trial, and the psychological sense of time was measured by the Time Perception Test, which is a time reproduction task. The results of this case study supports the Hybrid Model of Executive Function as concurrent deficits in behavior inhibition, non-verbal working memory and psychological sense of time were found in a subject with ADHD, combined type. The implications of these findings for treatment and future research are discussed
The effects of multiple aerospace environmental stressors on human performance
An extended Fitt's law paradigm reaction time (RT) task was used to evaluate the effects of acceleration on human performance in the Dynamic Environment Simulator (DES) at Armstrong Laboratory, Wright-Patterson AFB, Ohio. This effort was combined with an evaluation of the standard CSU-13 P anti-gravity suit versus three configurations of a 'retrograde inflation anti-G suit'. Results indicated that RT and error rates increased 17 percent and 14 percent respectively from baseline to the end of the simulated aerial combat maneuver and that the most common error was pressing too few buttons
Enhancing electrochemical intermediate solvation through electrolyte anion selection to increase nonaqueous Li-O battery capacity
Among the 'beyond Li-ion' battery chemistries, nonaqueous Li-O batteries
have the highest theoretical specific energy and as a result have attracted
significant research attention over the past decade. A critical scientific
challenge facing nonaqueous Li-O batteries is the electronically insulating
nature of the primary discharge product, lithium peroxide, which passivates the
battery cathode as it is formed, leading to low ultimate cell capacities.
Recently, strategies to enhance solubility to circumvent this issue have been
reported, but rely upon electrolyte formulations that further decrease the
overall electrochemical stability of the system, thereby deleteriously
affecting battery rechargeability. In this study, we report that a significant
enhancement (greater than four-fold) in Li-O cell capacity is possible by
appropriately selecting the salt anion in the electrolyte solution. Using
Li nuclear magnetic resonance and modeling, we confirm that this
improvement is a result of enhanced Li stability in solution, which in turn
induces solubility of the intermediate to LiO formation. Using this
strategy, the challenging task of identifying an electrolyte solvent that
possesses the anti-correlated properties of high intermediate solubility and
solvent stability is alleviated, potentially providing a pathway to develop an
electrolyte that affords both high capacity and rechargeability. We believe the
model and strategy presented here will be generally useful to enhance Coulombic
efficiency in many electrochemical systems (e.g. Li-S batteries) where
improving intermediate stability in solution could induce desired mechanisms of
product formation.Comment: 22 pages, 5 figures and Supporting Informatio
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Leaf-inspired microcontact printing vascular patterns.
The vascularization of tissue grafts is critical for maintaining viability of the cells within a transplanted graft. A number of strategies are currently being investigated including very promising microfluidics systems. Here, we explored the potential for generating a vasculature-patterned endothelial cells that could be integrated into distinct layers between sheets of primary cells. Bioinspired from the leaf veins, we generated a reverse mold with a fractal vascular-branching pattern that models the unique spatial arrangement over multiple length scales that precisely mimic branching vasculature. By coating the reverse mold with 50 μg ml-1 of fibronectin and stamping enabled selective adhesion of the human umbilical vein endothelial cells (HUVECs) to the patterned adhesive matrix, we show that a vascular-branching pattern can be transferred by microcontact printing. Moreover, this pattern can be maintained and transferred to a 3D hydrogel matrix and remains stable for up to 4 d. After 4 d, HUVECs can be observed migrating and sprouting into Matrigel. These printed vascular branching patterns, especially after transfer to 3D hydrogels, provide a viable alternative strategy to the prevascularization of complex tissues
Beyond behaviorism, positivism, and neo-institutionalism in economics: A conversation with Deirdre Nansen McCloskey
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Important Considerations in Plasmon-Enhanced Electrochemical Conversion at Voltage-Biased Electrodes.
In this perspective we compare plasmon-enhanced electrochemical conversion (PEEC) with photoelectrochemistry (PEC). PEEC is the oxidation or reduction of a reactant at the illuminated surface of a plasmonic metal (or other conductive material) while a potential bias is applied. PEC uses solar light to generate photoexcited electron-hole pairs to drive an electrochemical reaction at a biased or unbiased semiconductor photoelectrode. The mechanism of photoexcitation of charge carriers is different between PEEC and PEC. Here we explore how this difference affects the response of PEEC and PEC systems to changes in light, temperature, and surface morphology of the photoelectrode
Integrating aftershock forecasting into humanitarian decision-making: lessons from the April 2015 Nepal earthquake
Memory Aware Synapses: Learning what (not) to forget
Humans can learn in a continuous manner. Old rarely utilized knowledge can be
overwritten by new incoming information while important, frequently used
knowledge is prevented from being erased. In artificial learning systems,
lifelong learning so far has focused mainly on accumulating knowledge over
tasks and overcoming catastrophic forgetting. In this paper, we argue that,
given the limited model capacity and the unlimited new information to be
learned, knowledge has to be preserved or erased selectively. Inspired by
neuroplasticity, we propose a novel approach for lifelong learning, coined
Memory Aware Synapses (MAS). It computes the importance of the parameters of a
neural network in an unsupervised and online manner. Given a new sample which
is fed to the network, MAS accumulates an importance measure for each parameter
of the network, based on how sensitive the predicted output function is to a
change in this parameter. When learning a new task, changes to important
parameters can then be penalized, effectively preventing important knowledge
related to previous tasks from being overwritten. Further, we show an
interesting connection between a local version of our method and Hebb's
rule,which is a model for the learning process in the brain. We test our method
on a sequence of object recognition tasks and on the challenging problem of
learning an embedding for predicting triplets.
We show state-of-the-art performance and, for the first time, the ability to
adapt the importance of the parameters based on unlabeled data towards what the
network needs (not) to forget, which may vary depending on test conditions.Comment: ECCV 201
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