We introduce a new Bayesian approach to the variable selection problem which we term Bayesian Shrinkage Variable Selection (BSVS ). This approach is inspired by the Relevance Vector Machine (RVM ), which uses a Bayesian hierarchical linear setup to do variable selection and model estimation. RVM is typically applied in the context of kernel regression although it is also suitable in the standar...

The mammalian target of rapamycin (mTOR), a serine-threonine protein kinase, integrates extracellular signals, thereby modulating several physiological and pathological processes, including pain. Previous studies have suggested that rapamycin (an mTOR inhibitor) can attenuate nociceptive behaviors in many pain models, most likely at the spinal cord level. However, the mechanisms of mTOR at the ...

Harmful algal blooms (HABs), events that kill fish, impact human health in multiple ways, and contaminate water supplies, have increased frequency, magnitude, impacts numerous marine freshwaters around the world. Blooms of toxic dinoflagellate Karenia brevis resulted thousands tons dead deaths to many other organisms, respiratory-related hospitalizations, tens hundreds millions dollars economic...

<p style='text-indent:20px;'>The global-in-time existence of classical solutions to the relativistic Vlasov-Maxwell (RVM) system in three space dimensions remains elusive after nearly four decades mathematical research. In this note, a simplified "toy model" is presented and studied. This toy model retains one crucial aspect RVM system: phase-space evolution distribution function governed...

Image processing is playing a vital role in all fields like satellite, medical, telecommunication, and missile. Hyper spectral images show similar statistical properties to natural grayscale or color photographic images. HSI (Hyper Spectral Image) are a more challenging area because of high spectral bands and dimensionality. As well as it is very easy to learn. It will be used to identify the p...

The support vector machine (SVM) is a state-of-the-art technique for regression and classification, combining excellent generalisation properties with a sparse kernel representation. However, it does suffer from a number of disadvantages, notably the absence of probabilistic outputs, the requirement to estimate a trade-off parameter and the need to utilise 'Mercer' kernel functions. In this pap...

Recent studies indicate that persistent pain after tissue or nerve injury is accompanied by an enhanced net descending facilitatory drive that contributes to an amplification and spread of pain. Although 5-HT-containing neurons in the rostral ventromedial medulla (RVM) provide the major descending serotonergic projection to the spinal cord, it is not clear whether the neurotransmitter 5-HT itse...

We introduce a new shrinkage variable selection operator for linear models which we term the adaptive ridge selector (ARiS). This approach is inspired by the relevance vector machine (RVM), which uses a Bayesian hierarchical linear setup to do variable selection and model estimation. Extending the RVM algorithm, we include a proper prior distribution for the precisions of the regression coeffic...

We study the interplay between Dirac eigenmodes and center vortices in SU(2) lattice gauge theory. In particular we focus on vortex-removed configurations and compare them to an ensemble of configurations with random changes of the link variables. We show that removing the vortices destroys all zero modes and the near zero modes are no longer coupled to topological structures. The Dirac spectru...

Although transcutaneous electrical nerve stimulation (TENS) is used extensively in inflammatory joint conditions such as arthritis, the underlying mechanisms are unclear. This study aims to demonstrate an opiate-mediated activation of descending inhibitory pathways from the rostral ventral medulla (RVM) in the antihyperalgesia produced by low- (4 Hz) or high-frequency (100 Hz) TENS. Paw withdra...