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  • Hall effect in gated single-wall carbon nanotube films 

    Yomogida, Yohei; Horiuchi, Kanako; Okada, Ryotaro; Kawai, Hideki; Ichinose, Yota; (2022)
    The presence of hopping carriers and grain boundaries can sometimes lead to anomalous carrier types and density overestimation in Hall-effect measurements. Previous Hall-effect studies on carbon nanotube films reported unreasonably large carrier densities without independent assessments of the carrier types and densities. Here, we have systematically ...
  • Structure and function of axo-axonic inhibition 

    Schneider-Mizell, Casey M; Bodor, Agnes L; Collman, Forrest; Brittain, Derrick; Bleckert, Adam; (2021)
    Inhibitory neurons in mammalian cortex exhibit diverse physiological, morphological, molecular, and connectivity signatures. While considerable work has measured the average connectivity of several interneuron classes, there remains a fundamental lack of understanding of the connectivity distribution of distinct inhibitory cell types with synaptic ...
  • Deep-3D microscope: 3D volumetric microscopy of thick scattering samples using a wide-field microscope and machine learning 

    Li, Bowen; Tan, Shiyu; Dong, Jiuyang; Lian, Xiaocong; Zhang, Yongbing; (2022)
    Confocal microscopy is a standard approach for obtaining volumetric images of a sample with high axial and lateral resolution, especially when dealing with scattering samples. Unfortunately, a confocal microscope is quite expensive compared to traditional microscopes. In addition, the point scanning in confocal microscopy leads to slow imaging speed ...
  • Compact QEPAS humidity sensor in SF6 buffer gas for high-voltage gas power systems 

    Yin, Xukun; Dong, Lei; Wu, Hongpeng; Gao, Miao; Zhang, Le; (2022)
    In SF6 insulated high-voltage gas power systems, H2O is the most problematic impurity which not only decreases insulation performance but also creates an acidic atmosphere that promotes corrosion. Corrosion damages electrical equipment and leads to leaks, which pose serious safety hazards to people and the environment. A QEPAS-based sensor system for ...
  • Using behavioral rhythms and multi-task learning to predict fine-grained symptoms of schizophrenia 

    Tseng, Vincent W.-S.; Sano, Akane; Ben-Zeev, Dror; Brian, Rachel; Campbell, Andrew T.; (2020)
    Schizophrenia is a severe and complex psychiatric disorder with heterogeneous and dynamic multi-dimensional symptoms. Behavioral rhythms, such as sleep rhythm, are usually disrupted in people with schizophrenia. As such, behavioral rhythm sensing with smartphones and machine learning can help better understand and predict their symptoms. Our goal is ...
  • Trace gas sensing based on multi-quartz-enhanced photothermal spectroscopy 

    Ma, Yufei; Hu, Yinqiu; Qiao, Shunda; He, Ying; Tittel, Frank K. (2020)
    A multi-quartz-enhanced photothermal spectroscopy (M-QEPTS) based trace gas detection method is reported for the first time. Different from traditional QEPTS sensor employing a single quartz tuning fork (QTF) as a photothermal detector, two QTFs were used in M-QEPTS to increase the signal amplitude by adding the generated piezoelectric signals. The ...
  • In-plane electrical bias tunable optical properties of 1T-TaS2 

    Li, Weijian; Naik, Gururaj V. (2019)
    Electrically tunable optical properties have been demonstrated in many solid-state materials such as semiconductors, transparent conductive oxides and graphene. However, their tunability is limited in the visible range due to the requirement of extremely large charge build-up or high capacitive fields. Here, we propose strongly correlated materials ...
  • Deep convolutional models improve predictions of macaque V1 responses to natural images 

    Cadena, Santiago A.; Denfield, George H.; Walker, Edgar Y.; Gatys, Leon A.; Tolias, Andreas S.; (2019)
    Despite great efforts over several decades, our best models of primary visual cortex (V1) still predict spiking activity quite poorly when probed with natural stimuli, highlighting our limited understanding of the nonlinear computations in V1. Recently, two approaches based on deep learning have emerged for modeling these nonlinear computations: ...
  • Scalable user selection in FDD massive MIMO 

    Zhang, Xing; Sabharwal, Ashutosh (2021)
    User subset selection requires full downlink channel state information to realize effective multi-user beamforming in frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) systems. However, the channel estimation overhead scales with the number of users in FDD systems. In this paper, we propose a novel propagation domain-based ...
  • Projections and the Potential Societal Impact of the Future of Neurotechnologies 

    Gaudry, Kate S.; Ayaz, Hasan; Bedows, Avery; Celnik, Pablo; Eagleman, David; (2021)
    Traditionally, recording from and stimulating the brain with high spatial and temporal resolution required invasive means. However, recently, the technical capabilities of less invasive and non-invasive neuro-interfacing technology have been dramatically improving, and laboratories and funders aim to further improve these capabilities. These technologies ...
  • GhostiPy: An Efficient Signal Processing and Spectral Analysis Toolbox for Large Data 

    Chu, Joshua P.; Kemere, Caleb T. (2021)
    Recent technological advances have enabled neural recordings consisting of hundreds to thousands of channels. As the pace of these developments continues to grow rapidly, it is imperative to have fast, flexible tools supporting the analysis of neural data gathered by such large-scale modalities. Here we introduce GhostiPy (general hub of spectral ...
  • Revealing nonlinear neural decoding by analyzing choices 

    Yang, Qianli; Walker, Edgar; Cotton, R. James; Tolias, Andreas S.; Pitkow, Xaq (2021)
    Sensory data about most natural task-relevant variables are entangled with task-irrelevant nuisance variables. The neurons that encode these relevant signals typically constitute a nonlinear population code. Here we present a theoretical framework for quantifying how the brain uses or decodes its nonlinear information. Our theory obeys fundamental ...
  • Plasmon-induced trap filling at grain boundaries in perovskite solar cells 

    Yao, Kai; Li, Siqi; Liu, Zhiliang; Ying, Yiran; Dvořák, Petr; (2021)
    The deep-level traps induced by charged defects at the grain boundaries (GBs) of polycrystalline organic–inorganic halide perovskite (OIHP) films serve as major recombination centres, which limit the device performance. Herein, we incorporate specially designed poly(3-aminothiophenol)-coated gold (Au@PAT) nanoparticles into the perovskite absorber, ...
  • EDoF-ToF: extended depth of field time-of-flight imaging 

    Tan, Jasper; Boominathan, Vivek; Baraniuk, Richard; Veeraraghavan, Ashok (2021)
    Conventional continuous-wave amplitude-modulated time-of-flight (CWAM ToF) cameras suffer from a fundamental trade-off between light throughput and depth of field (DoF): a larger lens aperture allows more light collection but suffers from significantly lower DoF. However, both high light throughput, which increases signal-to-noise ratio, and a wide ...
  • Reorganization of CDW stacking in 1T-TaS2 by an in-plane electrical bias 

    Li, Weijian; Naik, Gururaj V. (2021)
    1T-TaS2 is a 2D quantum material supporting charge density waves (CDWs) at room temperature. The strong correlations in this material make its electrical properties extremely sensitive to external stimuli such as an electrical bias and illumination. Recently, we demonstrated that the optical properties of this material also considerably change with ...
  • Computed Tomography Radiomics Kinetics as Early Imaging Correlates of Osteoradionecrosis in Oropharyngeal Cancer Patients 

    Barua, Souptik; Elhalawani, Hesham; Volpe, Stefania; Al Feghali, Karine A.; Yang, Pei; (2021)
    Osteoradionecrosis (ORN) is a major side-effect of radiation therapy in oropharyngeal cancer (OPC) patients. In this study, we demonstrate that early prediction of ORN is possible by analyzing the temporal evolution of mandibular subvolumes receiving radiation. For our analysis, we use computed tomography (CT) scans from 21 OPC patients treated with ...
  • Ancestral circuits for vertebrate color vision emerge at the first retinal synapse 

    Yoshimatsu, Takeshi; Bartel, Philipp; Schröder, Cornelius; Janiak, Filip K.; St-Pierre, François; (2021)
    For color vision, retinal circuits separate information about intensity and wavelength. In vertebrates that use the full complement of four “ancestral” cone types, the nature and implementation of this computation remain poorly understood. Here, we establish the complete circuit architecture of outer retinal circuits underlying color processing in ...
  • CGAT: Cell Graph ATtention Network for Grading of Pancreatic Disease Histology Images 

    Baranwal, Mayank; Krishnan, Santhoshi; Oneka, Morgan; Frankel, Timothy; Rao, Arvind (2021)
    Early detection of Pancreatic Ductal Adenocarcinoma (PDAC), one of the most aggressive malignancies of the pancreas, is crucial to avoid metastatic spread to other body regions. Detection of pancreatic cancer is typically carried out by assessing the distribution and arrangement of tumor and immune cells in histology images. This is further complicated ...
  • Near-infrared laser photoacoustic gas sensor for simultaneous detection of CO and H2S 

    Yin, Xukun; Yin, Xukun; Gao, Miao; Miao, Ruiqi; Zhang, Le; (2021)
    A ppb-level H2S and CO photoacoustic spectroscopy (PAS) gas sensor was developed by using a two-stage commercial optical fiber amplifier with a full output power of 10 W. Two near-infrared diode lasers with the central wavenumbers of 6320.6 cm−1 and 6377.4 cm−1 were employed as the excitation laser source. A time-division multiplexing method was used ...
  • Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data 

    Wang, Minjie; Allen, Genevera I. (2021)
    In mixed multi-view data, multiple sets of diverse features are measured on the same set of samples. By integrating all available data sources, we seek to discover common group structure among the samples that may be hidden in individualistic cluster analyses of a single data view. While several techniques for such integrative clustering have been ...

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