Generalized Skein Modules of Surfaces

Frobenius extensions play a central role in the link homology theories based upon the sl(n) link variants, and each of these Frobenius extensions may be recast geometrically via a category of marked cobordisms in the manner of Bar-Natan. Here we explore a large family of such marked cobordism categories that are relevant to generalized sl(n) link homology theories. We also investigate the skein modules that result from embedding these marked cobordisms within 3-manifolds, and arrive at an explicit presentation for several of these generalized skein modules.Comment: 23 pages, multiple figure

A systematic review of loneliness in bereavement:Current research and future directions

Bereaved people suffer from loneliness and loneliness is associated with poor mental health. In this study, this topic is reviewed. An agenda is suggested for future research. Research that is theory-driven, addresses measurement consistency, correlates of loneliness in bereaved and non-bereaved, and treatment is necessary for prevention and intervention

Evidence of Non-Thermal Particles in Coronal Loops Heated Impulsively by Nanoflares

The physical processes causing energy exchange between the Sun's hot corona and its cool lower atmosphere remain poorly understood. The chromosphere and transition region (TR) form an interface region between the surface and the corona that is highly sensitive to the coronal heating mechanism. High resolution observations with the Interface Region Imaging Spectrograph (IRIS) reveal rapid variability (about 20 to 60 seconds) of intensity and velocity on small spatial scales at the footpoints of hot dynamic coronal loops. The observations are consistent with numerical simulations of heating by beams of non-thermal electrons, which are generated in small impulsive heating events called "coronal nanoflares". The accelerated electrons deposit a sizable fraction of their energy in the chromosphere and TR. Our analysis provides tight constraints on the properties of such electron beams and new diagnostics for their presence in the nonflaring corona.Comment: Published in Science on October 17: http://www.sciencemag.org/content/346/6207/1255724 . 26 pages, 10 figures. Movies are available at: http://www.lmsal.com/~ptesta/iris_science_mov

Glutamatergic dysfunction leads to a hyper-dopaminergic phenotype through deficits in short-term habituation: a mechanism for aberrant salience

Psychosis in disorders like schizophrenia is commonly associated with aberrant salience and elevated striatal dopamine. However, the underlying cause(s) of this hyper-dopaminergic state remain elusive. Various lines of evidence point to glutamatergic dysfunction and impairments in synaptic plasticity in the etiology of schizophrenia, including deficits associated with the GluA1 AMPAR subunit. GluA1 knockout (Gria1−/−) mice provide a model of impaired synaptic plasticity in schizophrenia and exhibit a selective deficit in a form of short-term memory which underlies short-term habituation. As such, these mice are unable to reduce attention to recently presented stimuli. In this study we used fast-scan cyclic voltammetry to measure phasic dopamine responses in the nucleus accumbens of Gria1−/− mice to determine whether this behavioral phenotype might be a key driver of a hyper-dopaminergic state. There was no effect of GluA1 deletion on electrically-evoked dopamine responses in anaesthetized mice, demonstrating normal endogenous release properties of dopamine neurons in Gria1−/− mice. Furthermore, dopamine signals were initially similar in Gria1−/− mice compared to controls in response to both sucrose rewards and neutral light stimuli. They were also equally sensitive to changes in the magnitude of delivered rewards. In contrast, however, these stimulus-evoked dopamine signals failed to habituate with repeated presentations in Gria1−/− mice, resulting in a task-relevant, hyper-dopaminergic phenotype. Thus, here we show that GluA1 dysfunction, resulting in impaired short-term habituation, is a key driver of enhanced striatal dopamine responses, which may be an important contributor to aberrant salience and psychosis in psychiatric disorders like schizophrenia

Multi-Channel Auto-Calibration for the Atmospheric Imaging Assembly using Machine Learning

Solar activity plays a quintessential role in influencing the interplanetary medium and space-weather around the Earth. Remote sensing instruments onboard heliophysics space missions provide a pool of information about the Sun's activity via the measurement of its magnetic field and the emission of light from the multi-layered, multi-thermal, and dynamic solar atmosphere. Extreme UV (EUV) wavelength observations from space help in understanding the subtleties of the outer layers of the Sun, namely the chromosphere and the corona. Unfortunately, such instruments, like the Atmospheric Imaging Assembly (AIA) onboard NASA's Solar Dynamics Observatory (SDO), suffer from time-dependent degradation, reducing their sensitivity. Current state-of-the-art calibration techniques rely on periodic sounding rockets, which can be infrequent and rather unfeasible for deep-space missions. We present an alternative calibration approach based on convolutional neural networks (CNNs). We use SDO-AIA data for our analysis. Our results show that CNN-based models could comprehensively reproduce the sounding rocket experiments' outcomes within a reasonable degree of accuracy, indicating that it performs equally well compared with the current techniques. Furthermore, a comparison with a standard "astronomer's technique" baseline model reveals that the CNN approach significantly outperforms this baseline. Our approach establishes the framework for a novel technique to calibrate EUV instruments and advance our understanding of the cross-channel relation between different EUV channels.Comment: 12 pages, 7 figures, 8 tables. This is a pre-print of an article submitted and accepted by A&A Journa