Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Deep convolutional neural network with 2D spectral energy maps for fault diagnosis of gearboxes under variable speed.

For industrial safety, correct classification of gearbox fault conditions is necessary. One of the most crucial tasks in data-driven fault diagnosis is determining the best set of features by analyzing the statistical parameters of the signals. However, under variable speed conditions, these statistical parameters are incapable of uncovering the dynamic characteristics of different fault conditions of gearboxes. Later, several deep learning algorithms are used to improve the performance of the feature selection process, but domain knowledge expertise is still necessary. In this paper, a combination domain knowledge analysis and a deep neural network is proposed. By using the input acoustic emission (AE) signal, a two-dimensional spectrum energy map (2D AE-SEM) is created to form an identical fault pattern for various speed conditions of gearboxes. Then, a deep convolutional neural network (DCNN) is proposed to investigate the detailed structure of the 2D input for final fault classification. This 2D AE-SEM offers a graphical depiction of acoustic emission spectral characteristics. Our proposed system offers vigorous and dynamic classification performance through the proposed DCNN with a high diagnostic fault classification accuracy of 96.37% in all considered scenarios

An evoked potential mapping of transcallosal projections in the cat

In ten adult cats anesthetized with ketamine hydrochloride the neocortex was exposed and rectangular pulses (1msec, 0.5 Hz and variable intensity) were applied to discrete points of one side and transcallosal evoked potentials were recorded from the other. The stimulation and recording positions were determined on a cartesian map of most of the exposable neocortical areas and the potentials were analysed as to their components, voltage and latency. Passive spread and electrotonic potentials and the effects of increasing frequency were also analysed. The results showed large transcallosal potentials in some areas and an increase of potentials in the caudorostral direction, attaining the highest values in anteromedial areas of the suprasylvian gyrus. Confirming anatomical studies, a few silent spots were found in the motor and somesthetic cortex and in restricted posterior regions of the visual cortex, where small or zero voltages occurred. While causing weak contralateral potentials, stimulation of some posterior sites provoked high voltage potentials in anterior regions of the side being stimulated and in the corresponding area of the opposite site. These posterior sites are. poorly interconnected by the corpus callosum. The L-shaped indirect connection described in this work may be involved in some types of epilepsy and may explain the effectiveness of partial callosotomy in their treatment

The LSD1-Type Zinc Finger Motifs of Pisum sativa LSD1 Are a Novel Nuclear Localization Signal and Interact with Importin Alpha

Background: Genetic studies of the Arabidopsis mutant lsd1 highlight the important role of LSD1 in the negative regulation of plant programmed cell death (PCD). Arabidopsis thaliana LSD1 (AtLSD1) contains three LSD1-type zinc finger motifs, which are involved in the protein-protein interaction. Methodology/Principal Findings: To further understand the function of LSD1, we have analyzed cellular localization and functional localization domains of Pisum sativa LSD1 (PsLSD1), which is a homolog of AtLSD1. Subcellular localization analysis of green fluorescent protein (GFP)-tagged PsLSD1 indicates that PsLSD1 is localized in the nucleus. Using a series of GFP-tagged PsLSD1 deletion mutants, we found that the three LSD1-type zinc finger motifs of PsLSD1 alone can target GFP to the nucleus, whereas deletion of the three zinc finger motifs or any individual zinc finger motif causes PsLSD1 to lose its nuclear localization, indicating that the three zinc finger motifs are necessary and sufficient for its nuclear localization. Moreover, site-directed mutagenesis analysis of GFP-tagged PsLSD1 indicates that tertiary structure and basic amino acids of each zinc finger motif are necessary for PsLSD1 nuclear localization. In addition, yeast two-hybrid, pull-down, and BiFC assays demonstrate that the three zinc finger motifs of PsLSD1 directly bind to importin alpha in vitro and in vivo. Conclusions/Significance: Our data demonstrate that the LSD1-type zinc finger motifs of PsLSD1 are a novel nuclear localization signal and directly bind to importin alpha, and suggest that the nuclear import of LSD1 may rely on the interaction between its zinc finger motifs and importin alpha. Moreover, the nuclear localization of PsLSD1 suggests that LSD1 may function as a transcription regulator involved in negatively regulating PCD.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000292929500042&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Multidisciplinary SciencesSCI(E)PubMed11ARTICLE7e22131

Developing a Citizen Social Science approach to understand urban stress and promote wellbeing in urban communities

This paper sets out the future potential and challenges for developing an interdisciplinary, mixed-method Citizen Social Science approach to researching urban emotions. It focuses on urban stress, which is increasingly noted as a global mental health challenge facing both urbanised and rapidly urbanising societies. The paper reviews the existing use of mobile psychophysiological or biosensing within urban environments—as means of ‘capturing’ the urban geographies of emotions. Methodological reflections are included on primary research using biosensing in a study of workplace and commuter stress for university employees in Birmingham (UK) and Salzburg (Austria) for illustrative purposes. In comparing perspectives on the conceptualisation and measurement of urban stress from psychology, neuroscience and urban planning, the difficulties of defining scientific constructs within Citizen Science are discussed to set out the groundwork for fostering interdisciplinary dialogue. The novel methods, geo-located sensor technologies and data-driven approaches to researching urban stress now available to researchers pose a number of ethical, political and conceptual challenges around defining and measuring emotions, stress, human behaviour and urban space. They also raise issues of rigour, participation and social scientific interpretation. Introducing methods informed by more critical Citizen Social Science perspectives can temper overly individualised forms of data collection to establish more effective ways of addressing urban stress and promoting wellbeing in urban communities

Developmental malformation of the corpus callosum: a review of typical callosal development and examples of developmental disorders with callosal involvement

This review provides an overview of the involvement of the corpus callosum (CC) in a variety of developmental disorders that are currently defined exclusively by genetics, developmental insult, and/or behavior. I begin with a general review of CC development, connectivity, and function, followed by discussion of the research methods typically utilized to study the callosum. The bulk of the review concentrates on specific developmental disorders, beginning with agenesis of the corpus callosum (AgCC)—the only condition diagnosed exclusively by callosal anatomy. This is followed by a review of several genetic disorders that commonly result in social impairments and/or psychopathology similar to AgCC (neurofibromatosis-1, Turner syndrome, 22q11.2 deletion syndrome, Williams yndrome, and fragile X) and two forms of prenatal injury (premature birth, fetal alcohol syndrome) known to impact callosal development. Finally, I examine callosal involvement in several common developmental disorders defined exclusively by behavioral patterns (developmental language delay, dyslexia, attention-deficit hyperactive disorder, autism spectrum disorders, and Tourette syndrome)

The Emergence of Emotions

Emotion is conscious experience. It is the affective aspect of consciousness. Emotion arises from sensory stimulation and is typically accompanied by physiological and behavioral changes in the body. Hence an emotion is a complex reaction pattern consisting of three components: a physiological component, a behavioral component, and an experiential (conscious) component. The reactions making up an emotion determine what the emotion will be recognized as. Three processes are involved in generating an emotion: (1) identification of the emotional significance of a sensory stimulus, (2) production of an affective state (emotion), and (3) regulation of the affective state. Two opposing systems in the brain (the reward and punishment systems) establish an affective value or valence (stimulus-reinforcement association) for sensory stimulation. This is process (1), the first step in the generation of an emotion. Development of stimulus-reinforcement associations (affective valence) serves as the basis for emotion expression (process 2), conditioned emotion learning acquisition and expression, memory consolidation, reinforcement-expectations, decision-making, coping responses, and social behavior. The amygdala is critical for the representation of stimulus-reinforcement associations (both reward and punishment-based) for these functions. Three distinct and separate architectural and functional areas of the prefrontal cortex (dorsolateral prefrontal cortex, orbitofrontal cortex, anterior cingulate cortex) are involved in the regulation of emotion (process 3). The regulation of emotion by the prefrontal cortex consists of a positive feedback interaction between the prefrontal cortex and the inferior parietal cortex resulting in the nonlinear emergence of emotion. This positive feedback and nonlinear emergence represents a type of working memory (focal attention) by which perception is reorganized and rerepresented, becoming explicit, functional, and conscious. The explicit emotion states arising may be involved in the production of voluntary new or novel intentional (adaptive) behavior, especially social behavior