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Making Memories: Why Time Matters
In the last decade advances in human neuroscience have identified the critical importance of time in creating long-term memories. Circadian neuroscience has established biological time functions via cellular clocks regulated by photosensitive retinal ganglion cells and the suprachiasmatic nuclei. Individuals have different circadian clocks depending on their chronotypes that vary with genetic, age, and sex. In contrast, social time is determined by time zones, daylight savings time, and education and employment hours. Social time and circadian time differences can lead to circadian desynchronization, sleep deprivation, health problems, and poor cognitive performance. Synchronizing social time to circadian biology leads to better health and learning, as demonstrated in adolescent education. In-day making memories of complex bodies of structured information in education is organized in social time and uses many different learning techniques. Research in the neuroscience of long-term memory (LTM) has demonstrated in-day time spaced learning patterns of three repetitions of information separated by two rest periods are effective in making memories in mammals and humans. This time pattern is based on the intracellular processes required in synaptic plasticity. Circadian desynchronization, sleep deprivation, and memory consolidation in sleep are less well-understood, though there has been considerable progress in neuroscience research in the last decade. The interplay of circadian, in-day and sleep neuroscience research are creating an understanding of making memories in the first 24-h that has already led to interventions that can improve health and learning
Appraisal Using Generalized Additive Models
Many of the results from real estate empirical studies depend upon using a correct functional form for their validity. Unfortunately, common parametric statistical tools cannot easily control for the possibility of misspecification. Recently, semiparametric estimators such as generalized additive models (GAMs) have arisen which can automatically control for additive (in price) or multiplicative (in ln(price)) nonlinear relations among the independent and dependent variables. As the paper shows, GAMs can empirically outperform naive parametric and polynomial models in ex-sample predictive behavior. Moreover, GAMs have well-developed statistical properties and can suggest useful transformations in parametric settings.
Heat-treatment of metal parts facilitated by sand embedment
Embedding metal parts of complex shape in sand contained in a steel box prevents strains and warping during heat treatment. The sand not only provides a simple, inexpensive support for the parts but also ensures more uniform distribution of heat to the parts
A failsafe analysis using NASTRAN's piecewise linear analysis and a nine node linear crack element
A two-dimensional crack element was implemented into NASTRAN as a user dummy element and used to study failsafe characteristics of the C5A fuselage. The element is formulated from Reitsner's functional requiring that it satisfy compatability with the linear boundary displacement elements in NASTRAN. Its accuracy is demonstrated by analyzing for the stress intensity factors of two simple crack configurations for which there are classic solutions
Mechanical stability augmentation system Patent
Mechanical stabilization system for VTOL aircraf
Transpiration Cooling - Its Theory and Application
Transpiration cooling of turbulent boundary layers - theory and applicatio
Arkansas Wheat Cultivar Performance Tests 2013-2014
Wheat cultivar performance tests are conducted each year in Arkansas by the Arkansas Agricultural Experiment Station, Department of Crop, Soil and Environmental Sciences. The tests provide information to companies developing cultivars and/or marketing seed within the state and aid the Arkansas Cooperative Extension Service in formulating cultivar recommendations for small-grain producers
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