Primary visual cortex excitability is not atypical in acquired synaesthesia

A wealth of data suggests that psychedelic drugs elicit spontaneous perceptual states that resemble synaesthesia although it is unclear whether these different forms of synaesthesia share overlapping neural mechanisms. Multiple studies have shown that developmental and trained synaesthesia is characterized by selective hyperexcitability in primary visual cortex and it has been proposed that cortical hyperexcitability may contribute to induced and acquired synaesthesia. This study tested the prediction that a case of acquired synaesthesia (LW) would display selectively elevated primary visual cortex excitability, as reflected in lower transcranial magnetic stimulation (TMS) phosphene thresholds, but no difference in motor thresholds, relative to controls. In contrast to this prediction, LW’s phosphene threshold was well within the threshold range of controls. These results suggest that acquired synaesthesia is not characterized by atypical visual cortex excitability

NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps

Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many state-of-the-art (SOA) visual processing tasks. Even though Graphical Processing Units (GPUs) are most often used in training and deploying CNNs, their power efficiency is less than 10 GOp/s/W for single-frame runtime inference. We propose a flexible and efficient CNN accelerator architecture called NullHop that implements SOA CNNs useful for low-power and low-latency application scenarios. NullHop exploits the sparsity of neuron activations in CNNs to accelerate the computation and reduce memory requirements. The flexible architecture allows high utilization of available computing resources across kernel sizes ranging from 1x1 to 7x7. NullHop can process up to 128 input and 128 output feature maps per layer in a single pass. We implemented the proposed architecture on a Xilinx Zynq FPGA platform and present results showing how our implementation reduces external memory transfers and compute time in five different CNNs ranging from small ones up to the widely known large VGG16 and VGG19 CNNs. Post-synthesis simulations using Mentor Modelsim in a 28nm process with a clock frequency of 500 MHz show that the VGG19 network achieves over 450 GOp/s. By exploiting sparsity, NullHop achieves an efficiency of 368%, maintains over 98% utilization of the MAC units, and achieves a power efficiency of over 3TOp/s/W in a core area of 6.3mm$^2$. As further proof of NullHop's usability, we interfaced its FPGA implementation with a neuromorphic event camera for real time interactive demonstrations

Taylor dispersion with absorbing boundaries: A Stochastic Approach

We describe how to solve the problem of Taylor dispersion in the presence of absorbing boundaries using an exact stochastic formulation. In addition to providing a clear stochastic picture of Taylor dispersion, our method leads to closed-form expressions for all the moments of the convective displacement of the dispersing particles in terms of the transverse diffusion eigenmodes. We also find that the cumulants grow asymptotically linearly with time, ensuring a Gaussian distribution in the long-time limit. As a demonstration of the technique, the first two longitudinal cumulants (yielding respectively the effective velocity and the Taylor diffusion constant) as well as the skewness (a measure of the deviation from normality) are calculated for fluid flow in the parallel plate geometry. We find that the effective velocity and the skewness (which is negative in this case) are enhanced while Taylor dispersion is suppressed due to absorption at the boundary.Comment: 4 pages, 1 figur

Nursing and midwifery students\u27 experiences and perception of their clinical learning environment in Malawi: A mixed-method study

© 2020 The Author(s). Background: The clinical learning environment is an important part of the nursing and midwifery training as it helps students to integrate theory into clinical practice. However, not all clinical learning environments foster positive learning. This study aimed to assess the student nurses and midwives\u27 experiences and perception of the clinical learning environment in Malawi. Methods: A concurrent triangulation mixed methods research design was used to collect data from nursing and midwifery students. Quantitative data were collected using a Clinical Learning Environment Inventory, while qualitative data were collected using focus group discussions. The Clinical Learning Environment Inventory has six subscales of satisfaction, involvement, individualisation, innovation, task orientation and personalisation. The focus group interview guide had questions about clinical learning, supervision, assessment, communication and resources. Quantitative data were analysed by independent t-test and multivariate linear regression and qualitative data were thematically analysed. Results: A total of 126 participants completed the questionnaire and 30 students participated in three focus group discussions. Satisfaction subscale had the highest mean score (M = 26.93, SD = 4.82) while individualisation had the lowest mean score (M = 18.01, SD =3.50). Multiple linear regression analysis showed a statistically significant association between satisfaction with clinical learning environment and personalization (β = 0.50, p = \u3c 0.001), and task orientation (β =0.16 p = \u3c 0.05). Teaching and learning resources, hostile environment, poor relationship with a qualified staff, absence of clinical supervisors, and lack of resources were some of the challenges faced by students in their clinical learning environment. Conclusion: Although satisfaction with clinical learning environment subscale had the highest mean score, nursing and midwifery students encountered multifaceted challenges such as lack of resources, poor relationship with staff and a lack of support from clinical teachers that negatively impacted on their clinical learning experiences. Training institutions and hospitals need to work together to find means of addressing the challenges by among others providing resources to students during clinical placement

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset

The new generation CMB B-mode polarization experiment: POLARBEAR

We describe the Cosmic Microwave Background (CMB) polarization experiment called Polarbear. This experiment will use the dedicated Huan Tran Telescope equipped with a powerful 1,200-bolometer array receiver to map the CMB polarization with unprecedented accuracy. We summarize the experiment, its goals, and current status

Ultra High Energy Cosmology with POLARBEAR

Observations of the temperature anisotropy of the Cosmic Microwave Background (CMB) lend support to an inflationary origin of the universe, yet no direct evidence verifying inflation exists. Many current experiments are focussing on the CMB's polarization anisotropy, specifically its curl component (called "B-mode" polarization), which remains undetected. The inflationary paradigm predicts the existence of a primordial gravitational wave background that imprints a unique B-mode signature on the CMB's polarization at large angular scales. The CMB B-mode signal also encodes gravitational lensing information at smaller angular scales, bearing the imprint of cosmological large scale structures (LSS) which in turn may elucidate the properties of cosmological neutrinos. The quest for detection of these signals; each of which is orders of magnitude smaller than the CMB temperature anisotropy signal, has motivated the development of background-limited detectors with precise control of systematic effects. The POLARBEAR experiment is designed to perform a deep search for the signature of gravitational waves from inflation and to characterize lensing of the CMB by LSS. POLARBEAR is a 3.5 meter ground-based telescope with 3.8 arcminute angular resolution at 150 GHz. At the heart of the POLARBEAR receiver is an array featuring 1274 antenna-coupled superconducting transition edge sensor (TES) bolometers cooled to 0.25 Kelvin. POLARBEAR is designed to reach a tensor-to-scalar ratio of 0.025 after two years of observation -- more than an order of magnitude improvement over the current best results, which would test physics at energies near the GUT scale. POLARBEAR had an engineering run in the Inyo Mountains of Eastern California in 2010 and will begin observations in the Atacama Desert in Chile in 2011.Comment: 8 pages, 6 figures, DPF 2011 conference proceeding

Socioecological Factors Related to Hazardous Alcohol use among Female Sex Workers in Lilongwe, Malawi: A Mixed Methods Study

Background: Alcohol use is pervasive among female sex workers (FSW) placing them at increased risk of violence and sexual risk behaviors. FSW often live and work where alcohol is highly normative. Objective: To understand the socioecological influences on hazardous alcohol use among FSW in Malawi. Methods: In 2014, 200 FSW identified through venue-based sampling in Lilongwe, Malawi, completed a quantitative behavioral survey, with a sub-sample participating in qualitative interviews. Multivariable log-binomial regression was used to identify associations between hazardous alcohol use (AUDIT score ≥ 7) and time in sex work, clients per week, unprotected sex, alcohol use with clients, and living environment. Qualitative interviews enhanced findings from quantitative data and identify emergent themes around socioecological influences on alcohol use. Results: Over 50% reported hazardous alcohol use and lived in an alcohol-serving venue. Hazardous alcohol use was associated with sex work duration of ≥2 years (aPR: 1.30; 95%CI: 1.02,1.65) and alcohol use at last sex with a client (aPR: 1.29; 95%CI: 1.06,1.57). FSW perceived alcohol as a facilitator for sex work by reducing inhibitions and attracting clients, but acknowledged alcohol leads to violence and/or unprotected sex. Despite these risks and a motivation to reduce use, FSW feared that refusing to drink would be tantamount to turning away clients. Conclusions: Although FSW recognized alcohol-related risks, the norms and power dynamics of sex work perpetuated hazardous alcohol use. Multilevel interventions are needed to collectively change norms around drinking and sex work that will enable FSW to reduce alcohol consumption when engaging in their work

Raman microscopy to characterize plasma-wall interaction materials: from carbon era to metallic walls

Plasma-wall interaction in magnetic fusion devices is responsible for wall changes and plasma pollution with major safety issues. It is investigated both in situ and ex situ, especially by realizing large scale dedicated post-mortem campaigns. Selected parts of the walls are extracted and characterized by several techniques. It is important to extract hydrogen isotopes, oxygen or other element content. This is classically done by ion beam analysis and thermal desorption spectroscopy. Raman microscopy is an alternative and complementary technique. The aim of this work is to demonstrate that Raman microscopy is a very sensitive tool. Moreover, if coupled to other techniques and tested on well-controlled reference samples, Raman microscopy can be used efficiently for characterization of wall samples. Present work reviews long experience gained on carbon-based materials demonstrating how Raman microscopy can be related to structural disorder and hydrogen retention, as it is a direct probe of chemical bonds and atomic structure. In particular, we highlight the fact that Raman microscopy can be used to estimate the hydrogen content and bonds to other elements as well as how it evolves under heating. We also present state-of-the-art Raman analyses of beryllium- and tungsten-based materials, and finally, we draw some perspectives regarding boron-based deposits.</p