AMiBA Wideband Analog Correlator

A wideband analog correlator has been constructed for the Yuan-Tseh Lee Array for Microwave Background Anisotropy. Lag correlators using analog multipliers provide large bandwidth and moderate frequency resolution. Broadband IF distribution, backend signal processing and control are described. Operating conditions for optimum sensitivity and linearity are discussed. From observations, a large effective bandwidth of around 10 GHz has been shown to provide sufficient sensitivity for detecting cosmic microwave background variations.Comment: 28 pages, 23 figures, ApJ in press

Impaired perceptual learning in a mouse model of Fragile X syndrome is mediated by parvalbumin neuron dysfunction and is reversible.

To uncover the circuit-level alterations that underlie atypical sensory processing associated with autism, we adopted a symptom-to-circuit approach in the Fmr1-knockout (Fmr1-/-) mouse model of Fragile X syndrome. Using a go/no-go task and in vivo two-photon calcium imaging, we find that impaired visual discrimination in Fmr1-/- mice correlates with marked deficits in orientation tuning of principal neurons and with a decrease in the activity of parvalbumin interneurons in primary visual cortex. Restoring visually evoked activity in parvalbumin cells in Fmr1-/- mice with a chemogenetic strategy using designer receptors exclusively activated by designer drugs was sufficient to rescue their behavioral performance. Strikingly, human subjects with Fragile X syndrome exhibit impairments in visual discrimination similar to those in Fmr1-/- mice. These results suggest that manipulating inhibition may help sensory processing in Fragile X syndrome

Metal Oxide Semi-Conductor Gas Sensors in Environmental Monitoring

Metal oxide semiconductor gas sensors are utilised in a variety of different roles and industries. They are relatively inexpensive compared to other sensing technologies, robust, lightweight, long lasting and benefit from high material sensitivity and quick response times. They have been used extensively to measure and monitor trace amounts of environmentally important gases such as carbon monoxide and nitrogen dioxide. In this review the nature of the gas response and how it is fundamentally linked to surface structure is explored. Synthetic routes to metal oxide semiconductor gas sensors are also discussed and related to their affect on surface structure. An overview of important contributions and recent advances are discussed for the use of metal oxide semiconductor sensors for the detection of a variety of gases—CO, NOx, NH3 and the particularly challenging case of CO2. Finally a description of recent advances in work completed at University College London is presented including the use of selective zeolites layers, new perovskite type materials and an innovative chemical vapour deposition approach to film deposition

Two-way communication with neural networks in vivo using focused light

Neuronal networks process information in a distributed, spatially heterogeneous manner that transcends the layout of electrodes. In contrast, directed and steerable light offers the potential to engage specific cells on demand. We present a unified framework for adapting microscopes to use light for simultaneous in vivo stimulation and recording of cells at fine spatiotemporal resolutions. We use straightforward optics to lock onto networks in vivo, to steer light to activate circuit elements and to simultaneously record from other cells. We then actualize this 'free' augmentation on both an 'open' two-photon microscope and a leading commercial one. By following this protocol, setup of the system takes a few days, and the result is a noninvasive interface to brain dynamics based on directed light, at a network resolution that was not previously possible and which will further improve with the rapid advance in development of optical reporters and effectors. This protocol is for physiologists who are competent with computers and wish to extend hardware and software to interface more fluidly with neuronal networks.National Institutes of Health (U.S.) (Postdoctoral Fellowship)Simons Foundation (Postdoctoral Fellowship)National Institutes of Health (U.S.) (Predoctoral Fellowship)National Institutes of Health (U.S.)Simons Foundatio

Gender gaps and reentry into entrepreneurial ecosystems after business failure

Despite the significant role played by serial entrepreneurs in the entrepreneurial process, we know little about group differences in reentry decisions after business failure. Using an ecosystems framework and stigma theory, we investigate the variance in gender gaps related to the reentry decisions of 8,171 entrepreneurs from 35 countries who experienced business failures. We find evidence of persisting gender gaps that vary across ecosystem framework conditions of public stigma of business failure and public fear of business failure. Our findings shed new light on ecosystem inefficiencies that arise from multiple interactions between entrepreneurs and institutions

From Plane to Hierarchy: Deformable Transformer for Remote Sensing Image Captioning

With the growth of remote sensing images, understanding image content automatically has attracted many researchers' interests in deep learning for remote sensing image. Inspired from the natural image captioning, the model with convolutional neural network (CNN)-Recurrent neural network (RNN) as the backbone and supplemented by attention has been widely used in remote sensing image captioning. However, it is inefficient for the current attention layer to simultaneously mine hidden foreground from the background of remote sensing image and perform feature interactive learning. Meanwhile, the new mainstream language model has recently surpassed the traditional long short-term memory (LSTM) in sentence generation. For solving the above problems, in this article, we proposed a novel thought to make the flat remote sensing images stereoscopic by separating the foreground and background. Based on hierarchical image information, we designed a novel Deformable Transformer equipped with deformable scaled dot-product attention to learn multiscale feature from foreground and background through the powerful interactive learning ability. Evaluations are conducted on four classic remote sensing image captioning datasets. Compared with the state-of-the-art methods, our Transformer variant achieves higher captioning accuracy

Dielectric Dispersion at Microwave Frequencies of Some Low Loss Mixed Oxide Perovskites This paper reports the dielectric permittivities of several low loss ceramics of A(B1 1/2 B2 1/2 )O 3 mixed oxide perovskites

/2 )O 3 (SGT), and their modified compositions 0.7Sr(Al 1/2 Nb 1/2 )O 3 -0.3NdGaO 3 (SAN-NG) and 0.7Sr(Al 1/2 Ta 1/2 )O 3 -0.3NdGaO 3 (SAT-NG), measured at microwave frequencies. Measurements of the frequency-dependent dielectric constant and loss tangent are reported. Their loss tangent values are on the order of 10 −4 to 10 −5 , which can not be evaluated by the traditional reflection/transmission spectra or impedance measurement techniques. A parallel-plate dielectric resonance method was adopted for dielectric measurements for such low loss materials. The frequency spectra of dielectric constants and loss tangents of were investigated by the well known classical oscillator model