Highly Quantum-Confined InAs Nanoscale Membranes

Nanoscale size-effects drastically alter the fundamental properties of semiconductors. Here, we investigate the dominant role of quantum confinement in the field-effect device properties of free-standing InAs nanomembranes with varied thicknesses of 5-50 nm. First, optical absorption studies are performed by transferring InAs "quantum membranes" (QMs) onto transparent substrates, from which the quantized sub-bands are directly visualized. These sub-bands determine the contact resistance of the system with the experimental values consistent with the expected number of quantum transport modes available for a given thickness. Finally, the effective electron mobility of InAs QMs is shown to exhibit anomalous field- and thickness-dependences that are in distinct contrast to the conventional MOSFET models, arising from the strong quantum confinement of carriers. The results provide an important advance towards establishing the fundamental device physics of 2-D semiconductors

A Study on Facial Expression Change Detection Using Machine Learning Methods with Feature Selection Technique

Along with the fourth industrial revolution, research in the biomedical engineering field is being actively conducted. Among these research fields, the brain-computer interface (BCI) research, which studies the direct interaction between the brain and external devices, is in the spotlight. However, in the case of electroencephalograph (EEG) data measured through BCI, there are a huge number of features, which can lead to many difficulties in analysis because of complex relationships between features. For this reason, research on BCIs using EEG data is often insufficient. Therefore, in this study, we develop the methodology for selecting features for a specific type of BCI that predicts whether a person correctly detects facial expression changes or not by classifying EEG-based features. We also investigate whether specific EEG features affect expression change detection. Various feature selection methods were used to check the influence of each feature on expression change detection, and the best combination was selected using several machine learning classification techniques. As a best result of the classification accuracy, 71% of accuracy was obtained with XGBoost using 52 features. EEG topography was confirmed using the selected major features, showing that the detection of changes in facial expression largely engages brain activity in the frontal regions

Zooplankton and micronekton respond to climate fluctuations in the Amundsen Sea polynya, Antarctica

The vertical migration of zooplankton and micronekton (hereafter 'zooplankton') has ramifications throughout the food web. Here, we present the first evidence that climate fluctuations affect the vertical migration of zooplankton in the Southern Ocean, based on multi-year acoustic backscatter data from one of the deep troughs in the Amundsen Sea, Antarctica. High net primary productivity (NPP) and the annual variation in seasonal ice cover make the Amundsen Sea coastal polynya an ideal site in which to examine how zooplankton behavior responds to climate fluctuations. Our observations show that the timing of the seasonal vertical migration and abundance of zooplankton in the seasonally varying sea ice is correlated with the Southern Annular Mode (SAM) and El Nino Southern Oscillation (ENSO). Zooplankton in this region migrate seasonally and overwinter at depth, returning to the surface in spring. During +SAM/La Nina periods, the at-depth overwintering period is shorter compared to -SAM/El Nino periods, and return to the surface layers starts earlier in the year. These differences may result from the higher sea ice cover and decreased NPP during +SAM/La Nina periods. This observation points to a new link between global climate fluctuations and the polar marine food web

Ultrathin compound semiconductor on insulator layers for high performance nanoscale transistors

Over the past several years, the inherent scaling limitations of electron devices have fueled the exploration of high carrier mobility semiconductors as a Si replacement to further enhance the device performance. In particular, compound semiconductors heterogeneously integrated on Si substrates have been actively studied, combining the high mobility of III-V semiconductors and the well-established, low cost processing of Si technology. This integration, however, presents significant challenges. Conventionally, heteroepitaxial growth of complex multilayers on Si has been explored. Besides complexity, high defect densities and junction leakage currents present limitations in the approach. Motivated by this challenge, here we utilize an epitaxial transfer method for the integration of ultrathin layers of single-crystalline InAs on Si/SiO2 substrates. As a parallel to silicon-on-insulator (SOI) technology14,we use the abbreviation "XOI" to represent our compound semiconductor-on-insulator platform. Through experiments and simulation, the electrical properties of InAs XOI transistors are explored, elucidating the critical role of quantum confinement in the transport properties of ultrathin XOI layers. Importantly, a high quality InAs/dielectric interface is obtained by the use of a novel thermally grown interfacial InAsOx layer (~1 nm thick). The fabricated FETs exhibit an impressive peak transconductance of ~1.6 mS/{\mu}m at VDS=0.5V with ON/OFF current ratio of greater than 10,000 and a subthreshold swing of 107-150 mV/decade for a channel length of ~0.5 {\mu}m

MOCVD of Hierarchical C‐MoS2 Nanobranches for ppt‐Level NO2 Detection

In the past decades, toxic gas emissions have increased significantly owing to the rapid growth of industry and road transportation. Therefore, monitoring major pollutants, such as NO2, is crucial to protecting human health. The 2D materials that contain numerous adsorption sites and exhibit ultrahigh chemical reactivity can be used as sensor materials to detect these toxic gases. Herein, highly uniform, large‐area carbon‐incorporating hierarchical MoS2 nanobranches are synthesized by metal–organic chemical vapor deposition (MOCVD). An in situ carbon‐incorporation method that uses the carbon impurity present in the precursor as the seed during the MOCVD process is employed to form a hierarchical structure containing abundant adsorption sites. A gas sensor based on the resulting C‐MoS2 nanobranches contains many edge sites exhibits high adsorption energy, and consequently, has high NO2 gas sensitivity. Hence, this hierarchical C‐MoS2 gas sensor shows excellent sensing properties, exhibiting a device response of 1.67 at an extremely low NO2 concentration (≈5 ppb). The limit of detection of the gas sensor for NO2 is calculated to be low (≈1.58 ppt), further confirming its exceptional performance. Thus, the hierarchical C‐MoS2 nanobranches deposited herein provide novel insights regarding the properties of 2D materials and are highly suited for fabricating high‐performance NO2 sensors

NGL-2 Deletion Leads to Autistic-like Behaviors Responsive to NMDAR Modulation

NGL-2 is a postsynaptic adhesion molecule known to regulate synaptic transmission, but whether NGL-2 regulates synaptic plasticity and specific behaviors remains unknown. Um et al. find that mice lacking NGL-2 display suppressed NMDA receptor-dependent synaptic plasticity and autistic-like social deficits and repetitive behaviors that are responsive to NMDA receptor activation.Netrin-G ligand 2 (NGL-2)/LRRC4, implicated in autism spectrum disorders and schizophrenia, is a leucine-rich repeat-containing postsynaptic adhesion molecule that interacts intracellularly with the excitatory postsynaptic scaffolding protein PSD-95 and trans-synaptically with the presynaptic adhesion molecule netrin-G2. Functionally, NGL-2 regulates excitatory synapse development and synaptic transmission. However, whether it regulates synaptic plasticity and disease-related specific behaviors is not known. Here, we report that mice lacking NGL-2 (Lrrc4−/− mice) show suppressed N-Methyl-D-aspartate receptor (NMDAR)-dependent synaptic plasticity in the hippocampus. NGL-2 associates with NMDARs through both PSD-95-dependent and -independent mechanisms. Moreover, Lrrc4−/− mice display mild social interaction deficits and repetitive behaviors that are rapidly improved by pharmacological NMDAR activation. These results suggest that NGL-2 promotes synaptic stabilization of NMDARs, regulates NMDAR-dependent synaptic plasticity, and prevents autistic-like behaviors from developing in mice, supporting the hypothesis that NMDAR dysfunction contributes to autism spectrum disorders. © 2018 The Author(s

Cerebellar Shank2 regulates excitatory synapse density, motor coordination, and specific repetitive and anxiety-like behaviors.

Shank2 is a multidomain scaffolding protein implicated in the structural and functional coordination of multiprotein complexes at excitatory postsynaptic sites as well as in psychiatric disorders, including autism spectrum disorders. While Shank2 is strongly expressed in the cerebellum, whether Shank2 regulates cerebellar excitatory synapses, or contributes to the behavioral abnormalities observed in Shank2/ mice, remains unexplored. Here we show that Shank2/ mice show reduced excitatory synapse density in cerebellar Purkinje cells in association with reduced levels of excitatory postsynaptic proteins, including GluD2 and PSD-93, and impaired motor coordination in the Erasmus test. Shank2 deletion restricted to Purkinje cells (Pcp2-Cre;Shank2fl/fl mice) leads to similar reductions in excitatory synapse density, synaptic protein levels, and motor coordination. Pcp2-Cre;Shank2fl/fl mice do not recapitulate autistic-like behaviors observed in Shank2/ mice, such as social interaction deficits, altered ultrasonic vocalizations, repetitive behaviors, and hyperactivity. However, Pcp2-Cre;Shank2fl/fl mice display enhanced repetitive behavior in the hole-board test and anxiety-like behavior in the light-dark test, which are not observed in Shank2/ mice. These results implicate Shank2 in the regulation of cerebellar excitatory synapse density, motor coordination, and specific repetitive and anxiety-like behaviors. © 2016 the authors11091sciescopu