Showing papers by "University of Electro-Communications published in 2017"

Highly Luminescent Phase-Stable CsPbI3 Perovskite Quantum Dots Achieving Near 100% Absolute Photoluminescence Quantum Yield.

Abstract: Perovskite quantum dots (QDs) as a new type of colloidal nanocrystals have gained significant attention for both fundamental research and commercial applications owing to their appealing optoelectronic properties and excellent chemical processability. For their wide range of potential applications, synthesizing colloidal QDs with high crystal quality is of crucial importance. However, like most common QD systems such as CdSe and PbS, those reported perovskite QDs still suffer from a certain density of trapping defects, giving rise to detrimental nonradiative recombination centers and thus quenching luminescence. In this paper, we show that a high room-temperature photoluminescence quantum yield of up to 100% can be obtained in CsPbI3 perovskite QDs, signifying the achievement of almost complete elimination of the trapping defects. This is realized with our improved synthetic protocol that involves introducing organolead compound trioctylphosphine–PbI2 (TOP–PbI2) as the reactive precursor, which also leads...

Colloidal Synthesis of Air-Stable Alloyed CsSn1–xPbxI3 Perovskite Nanocrystals for Use in Solar Cells

Abstract: Organic–inorganic hybrid perovskite solar cells have demonstrated unprecedented high power conversion efficiencies in the past few years. Now, the universal instability of the perovskites has become the main barrier for this kind of solar cells to realize commercialization. This situation can be even worse for those tin-based perovskites, especially for CsSnI3, because upon exposure to ambient atmosphere the desired black orthorhombic phase CsSnI3 would promptly lose single crystallinity and degrade to the inactive yellow phase, followed by irreversible oxidation into metallic Cs2SnI6. By alloying CsSnI3 with CsPbI3, we herein report the synthesis of alloyed perovskite quantum dot (QD), CsSn1–xPbxI3, which not only can be phase-stable for months in purified colloidal solution but also remains intact even directly exposed to ambient air, far superior to both of its parent CsSnI3 and CsPbI3 QDs. Ultrafast transient absorption spectroscopy studies reveal that the photoexcited electrons in the alloyed QDs can...

AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling

Abstract: With the emergence of in-vehicle applications, providing the required computational capabilities is becoming a crucial problem. This paper proposes a framework named autonomous vehicular edge (AVE) for edge computing on the road, with the aim of increasing the computational capabilities of vehicles in a decentralized manner. By managing the idle computational resources on vehicles and using them efficiently, the proposed AVE framework can provide computation services in dynamic vehicular environments without requiring particular infrastructures to be deployed. Specifically, this paper introduces a workflow to support the autonomous organization of vehicular edges. Efficient job caching is proposed to better schedule jobs based on the information collected on neighboring vehicles, including GPS information. A scheduling algorithm based on ant colony optimization is designed to solve this job assignment problem. Extensive simulations are conducted, and the simulation results demonstrate the superiority of this approach over competing schemes in typical urban and highway scenarios.

The status of DECIGO

Abstract: DECIGO (DECi-hertz Interferometer Gravitational wave Observatory) is the planned Japanese space gravitational wave antenna, aiming to detect gravitational waves from astrophysically and cosmologically significant sources mainly between 01 Hz and 10 Hz and thus to open a new window for gravitational wave astronomy and for the universe DECIGO will consists of three drag-free spacecraft arranged in an equilateral triangle with 1000 km arm lengths whose relative displacements are measured by a differential Fabry-Perot interferometer, and four units of triangular Fabry-Perot interferometers are arranged on heliocentric orbit around the sun DECIGO is vary ambitious mission, we plan to launch DECIGO in era of 2030s after precursor satellite mission, B-DECIGO B-DECIGO is essentially smaller version of DECIGO: B-DECIGO consists of three spacecraft arranged in an triangle with 100 km arm lengths orbiting 2000 km above the surface of the earth It is hoped that the launch date will be late 2020s for the present

Solving the Bose–Hubbard Model with Machine Learning

Abstract: Motivated by the recent successful application of artificial neural networks to quantum many-body problems [G. Carleo and M. Troyer, Science 355, 602 (2017)], a method to calculate the ground state...

L483: Warm Carbon-chain Chemistry Source Harboring Hot Corino Activity

Abstract: The Class 0 protostar, L483, has been observed in various molecular lines in the 1.2 mm band at a sub-arcsecond resolution with ALMA. An infalling-rotating envelope is traced by the CS line, while a very compact component with a broad velocity width is observed for the CS, SO, HNCO, NH$_2$CHO, and HCOOCH$_3$ lines. Although this source is regarded as the warm carbon-chain chemistry (WCCC) candidate source at a 1000 au scale, complex organic molecules characteristic of hot corinos such as NH$_2$CHO and HCOOCH$_3$ are detected in the vicinity of the protostar. Thus, both hot corino chemistry and WCCC are seen in L483. Although such a mixed chemical character source has been recognized as an intermediate source in previous single-dish observations, we here report the first spatially-resolved detection. A kinematic structure of the infalling-rotating envelope is roughly explained by a simple ballistic model with the protostellar mass of 0.1--0.2 $M_\odot$ and the radius of the centrifugal barrier (a half of the centrifugal radius) of 30--200 au, assuming the inclination angle of 80\degr\ (0\degr\ for a face-on). The broad line emission observed in the above molecules most likely comes from the disk component inside the centrifugal barrier. Thus, a drastic chemical change is seen around the centrifugal barrier.

Ground-based instruments of the PWING project to investigate dynamics of the inner magnetosphere at subauroral latitudes as a part of the ERG-ground coordinated observation network

Abstract: The plasmas (electrons and ions) in the inner magnetosphere have wide energy ranges from electron volts to mega-electron volts (MeV). These plasmas rotate around the Earth longitudinally due to the gradient and curvature of the geomagnetic field and by the co-rotation motion with timescales from several tens of hours to less than 10 min. They interact with plasma waves at frequencies of mHz to kHz mainly in the equatorial plane of the magnetosphere, obtain energies up to MeV, and are lost into the ionosphere. In order to provide the global distribution and quantitative evaluation of the dynamical variation of these plasmas and waves in the inner magnetosphere, the PWING project (study of dynamical variation of particles and waves in the inner magnetosphere using ground-based network observations, http://www.isee.nagoya-u.ac.jp/dimr/PWING/ ) has been carried out since April 2016. This paper describes the stations and instrumentation of the PWING project. We operate all-sky airglow/aurora imagers, 64-Hz sampling induction magnetometers, 40-kHz sampling loop antennas, and 64-Hz sampling riometers at eight stations at subauroral latitudes (~ 60° geomagnetic latitude) in the northern hemisphere, as well as 100-Hz sampling EMCCD cameras at three stations. These stations are distributed longitudinally in Canada, Iceland, Finland, Russia, and Alaska to obtain the longitudinal distribution of plasmas and waves in the inner magnetosphere. This PWING longitudinal network has been developed as a part of the ERG (Arase)-ground coordinated observation network. The ERG (Arase) satellite was launched on December 20, 2016, and has been in full operation since March 2017. We will combine these ground network observations with the ERG (Arase) satellite and global modeling studies. These comprehensive datasets will contribute to the investigation of dynamical variation of particles and waves in the inner magnetosphere, which is one of the most important research topics in recent space physics, and the outcome of our research will improve safe and secure use of geospace around the Earth.

Alloying Strategy in Cu–In–Ga–Se Quantum Dots for High Efficiency Quantum Dot Sensitized Solar Cells

Abstract: I–III–VI2 group “green” quantum dots (QDs) are attracting increasing attention in photoelectronic conversion applications. Herein, on the basis of the “simultaneous nucleation and growth” approach, Cu–In–Ga–Se (CIGSe) QDs with light harvesting range of about 1000 nm were synthesized and used as sensitizer to construct quantum dot sensitized solar cells (QDSCs). Inductively coupled plasma atomic emission spectrometry (ICP-AES), wild-angle X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) analyses demonstrate that the Ga element was alloyed in the Cu–In–Se (CISe) host. Ultraviolet photoelectron spectroscopy (UPS) and femtosecond (fs) resolution transient absorption (TA) measurement results indicate that the alloying strategy could optimize the electronic structure in the obtained CIGSe QD material, thus matching well with TiO2 substrate and favoring the photogenerated electron extraction. Open circuit voltage decay (OCVD) and impedance spectroscopy (IS) tests indicate that the intrinsic re...

Strong Converse Exponent for Classical-Quantum Channel Coding

Abstract: We determine the exact strong converse exponent of classical-quantum channel coding, for every rate above the Holevo capacity. Our form of the exponent is an exact analogue of Arimoto’s, given as a transform of the Renyi capacities with parameters $${\alpha > 1}$$ . It is important to note that, unlike in the classical case, there are many inequivalent ways to define the Renyi divergence of states, and hence the Renyi capacities of channels. Our exponent is in terms of the Renyi capacities corresponding to a version of the Renyi divergences that has been introduced recently in Muller-Lennert et al. (J Math Phys 54(12):122203, 2013. arXiv:1306.3142 ), and Wilde et al. (Commun Math Phys 331(2):593–622, 2014. arXiv:1306.1586 ). Our result adds to the growing body of evidence that this new version is the natural definition for the purposes of strong converse problems.

Wearable tactile device using mechanical and electrical stimulation for fingertip interaction with virtual world

Abstract: We developed “Finger Glove for Augmented Reality” (FinGAR), which combines electrical and mechanical stimulation to selectively stimulate skin sensory mechanoreceptors and provide tactile feedback of virtual objects. A DC motor provides high-frequency vibration and shear deformation to the whole finger, and an array of electrodes provide pressure and low-frequency vibration with high spatial resolution. FinGAR devices are attached to the thumb, index finger and middle finger. It is lightweight, simple in mechanism, easy to wear, and does not disturb the natural movements of the hand. All of these attributes are necessary for a general-purpose virtual reality system. User study was conducted to evaluate its ability to reproduce sensations of four tactile dimensions: macro roughness, friction, fine roughness and hardness. Result indicated that skin deformation and cathodic stimulation affect macro roughness and hardness, whereas high-frequency vibration and anodic stimulation affect friction and fine roughness.

Space gravitational wave antenna DECIGO and B-DECIGO

Abstract: Since the direct detection of gravitational wave will give us a fruitful insight about the early universe or life of stars, laser interferometric gravitational wave detectors with the strain sensitivity of higher than 10−22 have been developed. In Japan, the space gravitational wave detector project named DECi-hertz Gravitational wave Observatory (DECIGO) has been promoted which consists of three satellites forming equilateral triangle-shaped Fabry–Perot laser interferometer with the arm length of 1000 km. The designed strain sensitivity of DECIGO is 2 × 10−24/√Hz around 0.1 Hz whose targets are gravitational waves originated from the inspiral and the merger of black hole or neutron star binaries and from the inflation at the early universe, and no ground-based gravitational wave detector can access this observation band. Before launching DECIGO in 2030s, a milestone mission named B-DECIGO is planned which is a downsized mission of DECIGO. B-DECIGO also has its own scientific targets in addition to the feasibility test for DECIGO. In the present paper, DECIGO and B-DECIGO projects are reviewed.

Formation of Water Layers on Graphene Surfaces

Abstract: Although graphitic materials were thought to be hydrophobic, recent experimental results based on contact angle measurements show that the hydrophobicity of graphitic surfaces stems from airborne contamination of hydrocarbons This leads us to question whether a pristine graphitic surface is indeed hydrophobic To investigate the water wettability of graphitic surfaces, we use molecular dynamics simulations of water molecules on the surface of a single graphene layer at room temperature The results indicate that a water droplet spreads over the entire surface and that a double-layer structure of water molecules forms on the surface, which means that wetting of graphitic surfaces is possible, but only by two layers of water molecules No further water layers can cohere to the double-layer structure, but the formation of three-dimensional clusters of liquid water is confirmed The surface of the double-layer structure acts as a hydrophobic surface Such peculiar behavior of water molecules can be reasonabl

Chemical labelling for visualizing native AMPA receptors in live neurons

Abstract: The location and number of neurotransmitter receptors are dynamically regulated at postsynaptic sites. However, currently available methods for visualizing receptor trafficking require the introduction of genetically engineered receptors into neurons, which can disrupt the normal functioning and processing of the original receptor. Here we report a powerful method for visualizing native α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-type glutamate receptors (AMPARs) which are essential for cognitive functions without any genetic manipulation. This is based on a covalent chemical labelling strategy driven by selective ligand-protein recognition to tether small fluorophores to AMPARs using chemical AMPAR modification (CAM) reagents. The high penetrability of CAM reagents enables visualization of native AMPARs deep in brain tissues without affecting receptor function. Moreover, CAM reagents are used to characterize the diffusion dynamics of endogenous AMPARs in both cultured neurons and hippocampal slices. This method will help clarify the involvement of AMPAR trafficking in various neuropsychiatric and neurodevelopmental disorders.

Concentration profile of endemic equilibrium of a reaction–diffusion–advection SIS epidemic model

Abstract: Cui and Lou (J Differ Equ 261:3305–3343, 2016) proposed a reaction–diffusion–advection SIS epidemic model in heterogeneous environments, and derived interesting results on the stability of the DFE (disease-free equilibrium) and the existence of EE (endemic equilibrium) under various conditions. In this paper, we are interested in the asymptotic profile of the EE (when it exists) in the three cases: (i) large advection; (ii) small diffusion of the susceptible population; (iii) small diffusion of the infected population. We prove that in case (i), the density of both the susceptible and infected populations concentrates only at the downstream behaving like a delta function; in case (ii), the density of the susceptible concentrates only at the downstream behaving like a delta function and the density of the infected vanishes on the entire habitat, and in case (iii), the density of the susceptible is positive while the density of the infected vanishes on the entire habitat. Our results show that in case (ii) and case (iii), the asymptotic profile is essentially different from that in the situation where no advection is present. As a consequence, we can conclude that the impact of advection on the spatial distribution of population densities is significant.

Kriging-Based Interference Power Constraint: Integrated Design of the Radio Environment Map and Transmission Power

Abstract: This paper proposes a probabilistic interference constraint method with a radio environment map (REM) for spatial spectrum sharing. The REM stores the spatial distribution of the average received signal power. We can optimize the accuracy of the measurement-based REM using the Kriging interpolation. Although several researchers have maintained a continuous interest in improving the accuracy of the REM, sufficient study has not been done to actually explore the interference constraint considering the estimation error. The proposed method uses ordinary Kriging interpolation for the spectrum cartography. According to the predicted distribution of the estimation error, the allowable interference power to the primary user is approximately formulated. Numerical results show that the proposed method can achieve the probabilistic interference constraint asymptotically. Additionally, we compare the performance of the proposed technique with three methods: the perfect estimation, the path loss-based method, and the Kriging-based method without the error prediction. The comparison results show that the proposed method has a higher spectrum sharing opportunity than the path loss-based method, even if only a small amount of measurement data is available. It is also shown that the proposed method dramatically improves the outage probability of the interference power compared to the conventional Kriging-based method.

Copper deficient Zn–Cu–In–Se quantum dot sensitized solar cells for high efficiency

Abstract: Improving the intrinsic optoelectronic properties of quantum dots (QDs) is essential to tap their potential as light-harvesting materials in QD sensitized solar cell (QDSC) applications. High quality composition controllable Zn–Cu–In–Se (ZCISe) QDs were synthesized, and the influence of non-stoichiometry on the optoelectronic properties, as well as on the photovoltaic performance of the resulting QDSCs, was investigated systematically. Experimental results revealed that the Cu content in the ZCISe QDs can remarkably influence the optical properties of QDs as well as the resultant photovoltaic performance of solar cells. The power conversion efficiency (PCE) can be distinctly improved with the use of Cu-deficient ZCISe QDs as a sensitizer regardless of the compromised light harvesting capability. Transient absorption (TA) and open-circuit voltage decay (OCVD) measurements demonstrated that the defect state-related donor–acceptor pair (DAP) in the ZCISe QDs was favorable for the enhancement of the lifetime of photogenerated electrons in the ZCISe QDSCs. The long-lived electrons in the Cu-deficient ZCISe QDs benefit the improvement of the photovoltaic performance of the resultant cell devices by suppressing charge recombination. Electrochemical impedance spectroscopy (EIS) results illustrated that the charge recombination process at the photoanode/electrolyte interfaces can be effectively inhibited in Cu-deficient ZCISe QD based cells. Finally, a highest PCE of 12.57% (Jsc = 25.97 mA cm−2, Voc = 0.752 V and FF = 0.644) was achieved employing ZCISe QDs with a Cu/In molar ratio of 0.7 under AM 1.5 G one full sun illumination. This is one of the highest efficiencies in QDSCs.

Astrochemical Properties of Planck Cold Clumps

Abstract: Ken’ichi Tatematsu, et al, 'Astrochemical Properties of Planck Cold Clumps', The Astrophysical Journal Supplement Series, Vol. 228 (2), 20 pp, February 2017, doi:10.3847/1538-4365/228/2/12. © 2017. The American Astronomical Society. All rights reserved.

Controlled School Choice with Soft Bounds and Overlapping Types

Abstract: School choice programs are implemented to give students/parents an opportunity to choose the public school the students attend. Controlled school choice programs need to provide choices for students/parents while maintaining distributional constraints on the balance on the composition of students, typically in terms of so-cioeconomic status. Previous works show that setting soft-bounds, which flexibly change the priorities of students based on their types, is more appropriate than setting hard-bounds, which strictly limit the number of accepted students for each type. We consider a case where soft-bounds are imposed and one student can belong to multiple types, e.g., \"financially-distressed\" and \"minority\" types. We first show that when we apply a model that is a straightforward extension of an existing model for disjoint types, there is a chance that no stable matching exists. Thus, we propose an alternative model and an alternative stability definition, where a school has reserved seats for each type. We show that a stable matching is guaranteed to exist in this model, and develop a mechanism called Deferred Acceptance for Overlapping Types (DA-OT). The DA-OT mechanism is strategy-proof and obtains the student-optimal matching within all stable matchings. Computer simulation results illustrate that the DA-OT outperforms an artificial cap mechanism, where the number of seats for each type is fixed.

Differential Private Data Collection and Analysis Based on Randomized Multiple Dummies for Untrusted Mobile Crowdsensing

Abstract: Mobile crowdsensing, which collects environmental information from mobile phone users, is growing in popularity. These data can be used by companies for marketing surveys or decision making. However, collecting sensing data from other users may violate their privacy. Moreover, the data aggregator and/or the participants of crowdsensing may be untrusted entities. Recent studies have proposed randomized response schemes for anonymized data collection. This kind of data collection can analyze the sensing data of users statistically without precise information about other users' sensing results. However, traditional randomized response schemes and their extensions require a large number of samples to achieve proper estimation. In this paper, we propose a new anonymized data-collection scheme that can estimate data distributions more accurately. Using simulations with synthetic and real datasets, we prove that our proposed method can reduce the mean squared error and the JS divergence by more than 85% as compared with other existing studies.

DNN-based source enhancement self-optimized by reinforcement learning using sound quality measurements

Abstract: We investigated whether a deep neural network (DNN)-based source enhancement function can be self-optimized by reinforcement learning (RL). The use of a DNN is a powerful approach to describing the relationship between two sets of variables and can be useful for source enhancement function design. By training the DNN using a huge amount of training data, sound quality of output signals are improved. However, collecting a huge amount of training data is often difficult in practice. To use limited training data efficiently, we focus on the “self-optimization” of DNN-based source enhancement function in which RL is commonly utilized in the development of game playing computers. As a reward for RL, quantitative metrics that reflect a human's perceptual score (perceptual score), e.g., perceptual evaluation methods for audio source separation (PEASS), are utilized. To investigate whether the sound quality is improved by RL-based source enhancement, subjective tests were conducted. It was confirmed that the output sound quality of the RL-based source enhancement function improved as the number of iterations was increased and finally outperformed the conventional method.

A Reinforcement Learning-Based Data Storage Scheme for Vehicular Ad Hoc Networks

Abstract: Vehicular ad hoc networks (VANETs) have been attracting interest for their potential roles in intelligent transport systems (ITS). In order to enable distributed ITS, there is a need to maintain some information in the vehicular networks without the support of any infrastructure such as road side units. In this paper, we propose a protocol that can store the data in VANETs by transferring data to a new carrier (vehicle) before the current data carrier is moving out of a specified region. For the next data carrier node selection, the protocol employs fuzzy logic to evaluate instant reward by taking into account multiple metrics, specifically throughput, vehicle velocity, and bandwidth efficiency. In addition, a reinforcement learning-based algorithm is used to consider the future reward of a decision. For the data collection, the protocol uses a cluster-based forwarding approach to improve the efficiency of wireless resource utilization. We use theoretical analysis and computer simulations to evaluate the proposed protocol.

Simultaneous Improvements in Performance and Durability of an Octahedral PtNix/C Electrocatalyst for Next-Generation Fuel Cells by Continuous, Compressive, and Concave Pt Skin Layers

Abstract: Simultaneous improvements in oxygen reduction reaction (ORR) activity and long-term durability of Pt-based cathode catalysts are indispensable for the development of next-generation polymer electrolyte fuel cells but are still a major dilemma. We present a robust octahedral core–shell PtNix/C electrocatalyst with high ORR performance (mass activity and surface specific activity 6.8–16.9 and 20.3–24.0 times larger than those of Pt/C, respectively) and durability (negligible loss after 10000 accelerated durability test (ADT) cycles). The key factors of the robust octahedral nanostructure (core–shell Pt73Ni27/C) responsible for the remarkable activity and durability were found to be three continuous Pt skin layers with 2.0–3.6% compressive strain, concave facet arrangements (concave defects and high coordination), a symmetric Pt/Ni distribution, and a Pt67Ni33 intermetallic core, as found by STEM-EDS, in situ XAFS, XPS, etc. The robust core–shell Pt73Ni27/C was produced by the partial release of the stress, ...

Image-Based Food Calorie Estimation Using Knowledge on Food Categories, Ingredients and Cooking Directions

Abstract: Image-based food calorie estimation is crucial to diverse mobile applications for recording everyday meal. However, some of them need human help for calorie estimation, and even if it is automatic, food categories are often limited or images from multiple viewpoints are required. Then, it is not yet achieved to estimate food calorie with practical accuracy and estimating food calories from a food photo is an unsolved problem. Therefore, in this paper, we propose estimating food calorie from a food photo by simultaneous learning of food calories, categories, ingredients and cooking directions using deep learning. Since there exists a strong correlation between food calories and food categories, ingredients and cooking directions information in general, we expect that simultaneous training of them brings performance boosting compared to independent single training. To this end, we use a multi-task CNN [1]. In addition, in this research, we construct two kinds of datasets that is a dataset of calorie-annotated recipe collected from Japanese recipe sites on the Web and a dataset collected from an American recipe site. In this experiment, we trained multi-task and single-task CNNs. As a result, the multi-task CNN achieved the better performance on both food category estimation and food calorie estimation than single-task CNNs. For the Japanese recipe dataset, by introducing a multi-task CNN, 0.039 were improved on the correlation coefficient, while for the American recipe dataset, 0.090 were raised compared to the result by the single-task CNN.

Slow hot carrier cooling in cesium lead iodide perovskites

Abstract: Lead halide perovskites are attracting a great deal of interest for optoelectronic applications such as solar cells, LEDs, and lasers because of their unique properties. In solar cells, heat dissipation by hot carriers results in a major energy loss channel responsible for the Shockley–Queisser efficiency limit. Hot carrier solar cells offer the possibility to overcome this limit and achieve energy conversion efficiency as high as 66% by extracting hot carriers. Therefore, fundamental studies on hot carrier relaxation dynamics in lead halide perovskites are important. Here, we elucidated the hot carrier cooling dynamics in all-inorganic cesium lead iodide (CsPbI3) perovskite using transient absorption spectroscopy. We observe that the hot carrier cooling rate in CsPbI3 decreases as the fluence of the pump light increases and the cooling is as slow as a few 10 ps when the photoexcited carrier density is 7 × 1018 cm−3, which is attributed to phonon bottleneck for high photoexcited carrier densities. Our findings suggest that CsPbI3 has a potential for hot carrier solar cell applications.

A hybrid BMI-based exoskeleton for paresis: EMG control for assisting arm movements.

Abstract: Objective. Brain–machine interface (BMI) technologies have succeeded in controlling robotic exoskeletons, enabling some paralyzed people to control their own arms and hands. We have developed an exoskeleton asynchronously controlled by EEG signals. In this study, to enable real-time control of the exoskeleton for paresis, we developed a hybrid system with EEG and EMG signals, and the EMG signals were used to estimate its joint angles. Approach. Eleven able-bodied subjects and two patients with upper cervical spinal cord injuries (SCIs) performed hand and arm movements, and the angles of the metacarpophalangeal (MP) joint of the index finger, wrist, and elbow were estimated from EMG signals using a formula that we derived to calculate joint angles from EMG signals, based on a musculoskeletal model. The formula was exploited to control the elbow of the exoskeleton after automatic adjustments. Four able-bodied subjects and a patient with upper cervical SCI wore an exoskeleton controlled using EMG signals and were required to perform hand and arm movements to carry and release a ball. Main results. Estimated angles of the MP joints of index fingers, wrists, and elbows were correlated well with the measured angles in 11 able-bodied subjects (correlation coefficients were 0.81 ± 0.09, 0.85 ± 0.09, and 0.76 ± 0.13, respectively) and the patients (e.g. 0.91 ± 0.01 in the elbow of a patient). Four able-bodied subjects successfully positioned their arms to adequate angles by extending their elbows and a joint of the exoskeleton, with root-mean-square errors <6°. An upper cervical SCI patient, empowered by the exoskeleton, successfully carried a ball to a goal in all 10 trials. Significance. A BMI-based exoskeleton for paralyzed arms and hands using real-time control was realized by designing a new method to estimate joint angles based on EMG signals, and these may be useful for practical rehabilitation and the support of daily actions.

L483: Warm Carbon-Chain Chemistry Source Harboring Hot Corino Activity

Abstract: The Class 0 protostar, L483, has been observed in various molecular lines in the 1.2 mm band at a sub-arcsecond resolution with ALMA. An infalling-rotating envelope is traced by the CS line, while a very compact component with a broad velocity width is observed for the CS, SO, HNCO, NH$_2$CHO, and HCOOCH$_3$ lines. Although this source is regarded as the warm carbon-chain chemistry (WCCC) candidate source at a 1000 au scale, complex organic molecules characteristic of hot corinos such as NH$_2$CHO and HCOOCH$_3$ are detected in the vicinity of the protostar. Thus, both hot corino chemistry and WCCC are seen in L483. Although such a mixed chemical character source has been recognized as an intermediate source in previous single-dish observations, we here report the first spatially-resolved detection. A kinematic structure of the infalling-rotating envelope is roughly explained by a simple ballistic model with the protostellar mass of 0.1--0.2 $M_\odot$ and the radius of the centrifugal barrier (a half of the centrifugal radius) of 30--200 au, assuming the inclination angle of 80\degr\ (0\degr\ for a face-on). The broad line emission observed in the above molecules most likely comes from the disk component inside the centrifugal barrier. Thus, a drastic chemical change is seen around the centrifugal barrier.

Deep Cross-Modal Correlation Learning for Audio and Lyrics in Music Retrieval

Abstract: Little research focuses on cross-modal correlation learning where temporal structures of different data modalities such as audio and lyrics are taken into account. Stemming from the characteristic of temporal structures of music in nature, we are motivated to learn the deep sequential correlation between audio and lyrics. In this work, we propose a deep cross-modal correlation learning architecture involving two-branch deep neural networks for audio modality and text modality (lyrics). Different modality data are converted to the same canonical space where inter modal canonical correlation analysis is utilized as an objective function to calculate the similarity of temporal structures. This is the first study on understanding the correlation between language and music audio through deep architectures for learning the paired temporal correlation of audio and lyrics. Pre-trained Doc2vec model followed by fully-connected layers (fully-connected deep neural network) is used to represent lyrics. Two significant contributions are made in the audio branch, as follows: i) pre-trained CNN followed by fully-connected layers is investigated for representing music audio. ii) We further suggest an end-to-end architecture that simultaneously trains convolutional layers and fully-connected layers to better learn temporal structures of music audio. Particularly, our end-to-end deep architecture contains two properties: simultaneously implementing feature learning and cross-modal correlation learning, and learning joint representation by considering temporal structures. Experimental results, using audio to retrieve lyrics or using lyrics to retrieve audio, verify the effectiveness of the proposed deep correlation learning architectures in cross-modal music retrieval.

Investigation of Interfacial Charge Transfer in Solution Processed Cs2SnI6 Thin Films

Abstract: Cesium tin halide based perovskite Cs2SnI6 has been subjected to in-depth investigations owing to its potentiality toward the realization of environment benign Pb free and stable solar cells In spite of the fact that Cs2SnI6 has been successfully utilized as an efficient hole transport material owing to its p-type semiconducting nature, however, the nature of the majority carrier is still under debate Therefore, intrinsic properties of Cs2SnI6 have been investigated in detail to explore its potentiality as light absorber along with facile electron and hole transport A high absorption coefficient (5 × 104 cm–1) at 700 nm indicates the penetration depth of 700 nm light to be 02 μm, which is comparable to conventional Pb based solar cells Preparation of pure and CsI impurity free dense thin films with controllable thicknesses of Cs2SnI6 by the solution processable method has been reported to be difficult owing to its poor solubility An amicable solution to circumvent such problems of Cs2SnI6 has been p

Development of ultrafast time-resolved dual-comb spectroscopy

Abstract: Ultrafast time-resolved dual-comb spectroscopy (TR-DCS) has been demonstrated, which enables direct observations of transient responses of complex optical spectra by combining dual-comb spectroscopy with the pump–probe method. TR-DCS achieves two-dimensional spectroscopy with a wide dynamic range for both the temporal and frequency axes. As a demonstration, we investigated the femtosecond relaxation dynamics of a photo-excited InGaAs saturable absorber in the near-infrared frequency region. The transient response of the interferogram was successfully obtained, and both the amplitude and phase spectra of the dynamic complex transmittance were independently deduced without using the Kramers-Kronig relations. A high phase resolution in the order of milliradian was achieved by suppressing the effect from the slow phase drift caused in the experimental system. Our proof-of-principle experiment promotes a pathway to coherent, highly accurate, and multi-dimensional pump–probe spectroscopy using the optical frequ...