scholarly journals A testable prediction

2007 ◽  
Vol 3 (12) ◽  
pp. 827-827
Author(s):  
David Goodstein
Keyword(s):  
Testable Prediction

scholarly journals A testable prediction of the no-signalling condition using a variant of the EPR-Bohm example

2013 ◽  
Vol 377 (7) ◽  
pp. 540-545
Author(s):  
Dipankar Home ◽  
Ashutosh Rai ◽  
A.S. Majumdar
Keyword(s):  
Testable Prediction

Accounting Fundamentals and Systematic Risk: Corporate Failure over the Business Cycle

2019 ◽  
Vol 95 (5) ◽  
pp. 321-350 ◽  
Author(s):  
Maria Ogneva ◽  
Joseph D. Piotroski ◽  
Anastasia A. Zakolyukina
Keyword(s):  
Asset Pricing ◽  
Business Cycle ◽  
Systematic Risk ◽  
Accounting Data ◽  
Corporate Failure ◽  
Testable Prediction ◽  
The Business Cycle ◽  
Lasso Method ◽  
Asset Pricing Tests ◽  
Jel Classifications

ABSTRACT In this paper, we use accounting fundamentals to measure systematic risk of distress. Our main testable prediction—that this risk increases with the probability of recessionary failure, P(R|F)—is based on a stylized model that guides our empirical analyses. We first apply the lasso method to select accounting fundamentals that can be combined into P(R|F) estimates. We then use the obtained estimates in asset-pricing tests. This approach successfully extracts systematic risk information from accounting data—we document a significant positive premium associated with P(R|F) estimates. The premium covaries with the news about the business cycle and aggregate failure rates. Additional tests underscore the importance of the “structure” imposed through recessionary-failure-probability estimation. The “agnostic” return predictor that relies only on past correlations between the same fundamental variables and returns exhibits markedly different properties. JEL Classifications: G12; G32; G33; M41.

Cortical Map Reorganization as a Competitive Process

1994 ◽  
Vol 6 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Granger G. Sutton ◽  
James A. Reggia ◽  
Steven L. Armentrout ◽  
C. Lynne D'Autrechy
Keyword(s):  
Synaptic Plasticity ◽  
Computational Model ◽  
Somatosensory Cortex ◽  
Computational Models ◽  
Cortical Lesion ◽  
Cortical Lesions ◽  
Additional Mechanism ◽  
Two Phase ◽  
Testable Prediction ◽  
Cortical Map

Past models of somatosensory cortex have successfully demonstrated map formation and subsequent map reorganization following localized repetitive stimuli or deafferentation. They provide an impressive demonstration that fairly simple assumptions about cortical connectivity and synaptic plasticity can account for several observations concerning cortical maps. However, past models have not successfully demonstrated spontaneous map reorganization following cortical lesions. Recently, an assumption universally used in these and other cortex models, that peristimulus inhibition is due solely to horizontal intracortical inhibitory connections, has been questioned and an additional mechanism, the competitive distribution of activity, has been proposed. We implemented a computational model of somatosensory cortex based on competitive distribution of activity. This model exhibits spontaneous map reorganization in response to a cortical lesion, going through a two-phase reorganization process. These results make a testable prediction that can be used to experimentally support or refute part of the competitive distribution hypothesis, and may lead to practically useful computational models of recovery following stroke.

scholarly journals Is the sky the limit? On the expansion threshold of a species’ range

2017 ◽  
Author(s):  
Jitka Polechová
Keyword(s):  
Genetic Diversity ◽  
Genetic Drift ◽  
Environmental Heterogeneity ◽  
Species Range ◽  
Two Dimensional ◽  
Range Margin ◽  
Species Ranges ◽  
Testable Prediction ◽  
Two Parameters ◽  
Number Of Individuals

AbstractMore than a hundred years after Grigg’s influential analysis of species’ borders, the causes of limits to species’ ranges still represent a puzzle that has never been understood with clarity. The topic has become especially important recently as many scientists have become interested in the potential for species’ ranges to shift in response to climate change – and yet, nearly all of those studies fail to recognise or incorporate evolutionary genetics in a way that relates to theoretical developments. I show that range margins can be understood based on just two measurable parameters: i) the fitness cost of dispersal – a measure of environmental heterogeneity – and ii) the strength of genetic drift, which reduces genetic diversity. Together, these two parameters define an expansion threshold: adaptation fails when genetic drift reduces genetic diversity below that required for adaptation to environmental heterogeneity. When the key parameters drop below this expansion threshold locally, a sharp range margin forms. When they drop below this threshold throughout the species’ range, adaptation collapses everywhere, resulting in either extinction, or formation of a fragmented meta-population. Because the effects of dispersal differ fundamentally with dimension, the second parameter – the strength of genetic drift – is qualitatively different compared to a linear habitat. In two-dimensional habitats, genetic drift becomes effectively independent of selection. It decreases with neighbourhood size – the number of individuals accessible by dispersal within one generation. Moreover, in contrast to earlier predictions, which neglected evolution of genetic variance and/or stochasticity in two dimensions, dispersal into small marginal populations aids adaptation. This is because the reduction of both genetic and demographic stochasticity has a stronger effect than the cost of dispersal through increased maladaptation. The expansion threshold thus provides a novel, theoretically justified and testable prediction for formation of the range margin and collapse of the species’ range.Author summaryGene flow across environments has conflicting effects: while it increases the genetic variation necessary for adaptation and counters the loss of genetic diversity due to genetic drift, it may also swamp adaptation to local conditions. This interplay is crucial for the dynamics of a species’ range expansion, which can thus be understood based on two dimensionless parameters: i) the fitness cost of dispersal – a measure of environmental heterogeneity – and ii) the strength of genetic drift – a measure of reduction of genetic diversity. Together, these two parameters define an expansion threshold: adaptation fails when the number of individuals accessible by dispersal within one generation is so small that genetic drift reduces genetic diversity below the level required for adaptation to environmental heterogeneity. This threshold provides a novel, theoretically justified and testable prediction for formation of a range margin and a collapse of a species’ range in two-dimensional habitats.

scholarly journals Reconciling CV phonotactics and high vowel deletion in Japanese

2019 ◽  
Vol 7 ◽  
Author(s):  
James Whang
Keyword(s):  
Phonological Representation ◽  
Consonant Clusters ◽  
Testable Prediction ◽  
Productive Process ◽  
Vowel Deletion ◽  
Vowel Devoicing ◽  
Apparent Conflict

High vowel devoicing is a productive process in Japanese, where /i, u/ become unphonated between voiceless obstruents. Recent studies have shown that the vowels can completely delete as a result of the process, resulting in surface consonant clusters. This seemingly conflicts with the strong CV phonotactic preference that has repeatedly been shown in both phonological and psycholinguistic studies of Japanese. This paper proposes that the apparent conflict can be resolved by having phonotactic repairs and high vowel devoicing apply at different phonological levels, adopting a more sophisticated phonological representation than simple /underlying/ vs. [surface] forms. The proposed framework also makes an empirically testable prediction regarding syllabification of clusters that result from high vowel deletion.

Networks

2020 ◽  
pp. 60-68
Author(s):  
Stephen K. Reed
Keyword(s):  
Brain Injury ◽  
Brain Imaging ◽  
Information Transfer ◽  
Semantic Network ◽  
Spreading Activation ◽  
Activation Model ◽  
Direct Path ◽  
Testable Prediction ◽  
Path Lengths

Networks provide organization through nodes that are connected by links. Characteristics of networks that matter include clusters, path lengths, link weights, and hubs. A semantic network displays connections among concepts in which shorter links represent stronger associations between two concepts. A spreading activation model is a theory of how related concepts become activated. Variations of the theory enable predictions, such as spreading activation, is partitioned among the links at a node. This assumption leads to the testable prediction that the strength of activation along each link diminishes as the number of links increases. Brain imaging has revealed that information transfer depends not only on the direct path between nodes but also on the availability of alternative detour paths. This hyperconnectivity following a lesion lowers efficiency and is reduced with recovery from brain injury.

scholarly journals New Opacities and the Beta Cephei Stars

1993 ◽  
Vol 139 ◽  
pp. 163-170
Author(s):  
L.A. Balona
Keyword(s):  
Classification Scheme ◽  
Radial Mode ◽  
Pulsation Mode ◽  
Monitoring Campaign ◽  
Testable Prediction ◽  
The Absolute ◽  
Absolute Magnitudes

AbstractThe recent revision of metal opacities has opened up the possibility that the long-sought mechanism for driving pulsations in these stars has at last, been found. This hypothesis makes a testable prediction — that no β Cep variables should exist among metal-poor B-type stars. We report on the results of an intensive CCD monitoring campaign to test this prediction. The question of the pulsation mode of β Cep stars and the consequence of a revision of the absolute magnitudes to accommodate the fundamental radial mode among these stars is also discussed. Pulsational instability due to driving by ionization of metals has many other repercussions for the incidence of pulsation among the B-type stars. A classification scheme for other intrinsically variable B-type stars is suggested. It is shown that if, as generally supposed, pulsation is common among B-type stars then at least two different mechanisms must be in operation.

THE ORIGIN OF SCALE–SCALE CORRELATIONS OF THE DENSITY PERTURBATIONS DURING INFLATION

1999 ◽  
Vol 08 (06) ◽  
pp. 731-738
Author(s):  
LI-ZHI FANG ◽  
WOLUNG LEE ◽  
JESÚS PANDO
Keyword(s):  
Density Perturbation ◽  
Time Dependent ◽  
Long Time Tails ◽  
Long Wavelength ◽  
Testable Prediction ◽  
Slow Roll ◽  
Time Correlations ◽  
Long Time ◽  
Density Perturbations ◽  
Slow Roll Inflation

We show that scale–scale correlations are a generic feature of slow-roll inflation theories. These correlations result from the long-time tails characteristic of the time dependent correlations because the long wavelength density perturbation modes are diffusion-like. A relationship between the scale–scale correlations and time-correlations is established providing a way to reveal the time correlations of the perturbations during inflation. This mechanism provides for a testable prediction that the scale–scale correlations at two different spatial points will vanish.

scholarly journals Dual stochasticity in the cortex as a biologically plausible learning with the most efficient coding

2019 ◽  
Author(s):  
Jun-nosuke Teramae
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Cerebral Cortex ◽  
Learning Algorithm ◽  
Efficient Coding ◽  
Testable Prediction ◽  
Excitability Of Neurons ◽  
Efficient Power ◽  
Stochastic Properties ◽  
The Relationship

AbstractNeurons and synapses in the cerebral cortex behave stochastically. The advantages of such stochastic properties have been proposed in several works, but the relationship and synergy between the stochasticities of neurons and synapses remain largely unexplored. Here, we show that these stochastic features can be inseparably integrated into a simple framework that provides a practical and biologically plausible learning algorithm that consistently accounts for various experimental results, including the most efficient power-law coding of the cortex. The derived algorithm overcomes many of the limitations of conventional learning algorithms of neural networks. As an experimentally testable prediction, we derived the slow retrograde modulation of the excitability of neurons from this algorithm. Because of the simplicity and flexibility of this algorithm, we anticipate that it will be useful in the development of neuromorphic devices and scalable AI chips, and that it will help bridge the gap between neuroscience and machine learning.

scholarly journals The Status of Pulsar Emission Theory

2000 ◽  
Vol 177 ◽  
pp. 721-726 ◽  
Author(s):  
D.B. Melrose
Keyword(s):  
Plasma Frequency ◽  
Emission Mechanism ◽  
Number Density ◽  
Langmuir Turbulence ◽  
Pulsar Emission ◽  
Pulsar Radio ◽  
Testable Prediction ◽  
The Status ◽  
Statistical Sense ◽  
Pulsar Radio Emission

AbstractIt is argued that there is now a preferred pulsar radio emission mechanism, involving beam-driven Langmuir turbulence. A testable prediction is that, at least in a statistical sense, features in the spectra of pulsars should scale with the plasma frequency,υGJ, implied by the Goldreich-Julian number density.

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