Metal-Insulator Phase Transition in Quasi-One-Dimensional VO₂Structures

The metal-insulator transition (MIT) in strongly correlated oxides has attracted considerable attention from both theoretical and experimental researchers. Among the strongly correlated oxides, vanadium dioxide (VO2) has been extensively studied in the last decade because of a sharp, reversible change in its optical, electrical, and magnetic properties at approximately 341 K, which would be possible and promising to develop functional devices with advanced technology by utilizing MITs. However, taking the step towards successful commercialization requires the comprehensive understanding of MIT mechanisms, enabling us to manipulate the nature of transitions. In this regard, recently, quasi-one-dimensional (quasi-1D) VO2structures have been intensively investigated due to their attractive geometry and unique physical properties to observe new aspects of transitions compared with their bulk counterparts. Thus, in this review, we will address recent research progress in the development of various approaches for the modification of MITs in quasi-1D VO2structures. Furthermore, we will review recent studies on realizing novel functional devices based on quasi-1D VO2structures for a wide range of applications, such as a gas sensor, a flexible strain sensor, an electrical switch, a thermal memory, and a nonvolatile electrical memory with multiple resistance.</jats:p

Finding Kinematics-Driven Latent Neural States From Neuronal Population Activity for Motor Decoding

While intracortical brain-machine interfaces (BMIs) demonstrate feasibility to restore mobility to people with paralysis, it is still challenging to maintain high-performance decoding in clinical BMIs. One of the main obstacles for high-performance BMI is the noise-prone nature of traditional decoding methods that connect neural response explicitly with physical quantity, such as velocity. In contrast, the recent development of latent neural state model enables a robust readout of large-scale neuronal population activity contents. However, these latent neural states do not necessarily contain kinematic information useful for decoding. Therefore, this study proposes a new approach to finding kinematics-dependent latent factors by extracting latent factors&apos; kinematics-dependent components using linear regression. We estimated these components from the population activity through nonlinear mapping. The proposed kinematics-dependent latent factors generate neural trajectories that discriminate latent neural states before and after the motion onset. We compared the decoding performance of the proposed analysis model with the results from other popular models. They are factor analysis (FA), Gaussian process factor analysis (GPFA), latent factor analysis via dynamical systems (LFADS), preferential subspace identification (PSID), and neuronal population firing rates. The proposed analysis model results in higher decoding accuracy than do the others (&gt;17% improvement on average). Our approach may pave a new way to extract latent neural states specific to kinematic information from motor cortices, potentially improving decoding performance for online intracortical BMIs

Decoding Kinematic Information From Primary Motor Cortex Ensemble Activities Using a Deep Canonical Correlation Analysis

The control of arm movements through intracortical brain-machine interfaces (BMIs) mainly relies on the activities of the primary motor cortex (M1) neurons and mathematical models that decode their activities. Recent research on decoding process attempts to not only improve the performance but also simultaneously understand neural and behavioral relationships. In this study, we propose an efficient decoding algorithm using a deep canonical correlation analysis (DCCA), which maximizes correlations between canonical variables with the non-linear approximation of mappings from neuronal to canonical variables via deep learning. We investigate the effectiveness of using DCCA for finding a relationship between M1 activities and kinematic information when non-human primates performed a reaching task with one arm. Then, we examine whether using neural activity representations from DCCA improves the decoding performance through linear and non-linear decoders: a linear Kalman filter (LKF) and a long short-term memory in recurrent neural networks (LSTM-RNN). We found that neural representations of M1 activities estimated by DCCA resulted in more accurate decoding of velocity than those estimated by linear canonical correlation analysis, principal component analysis, factor analysis, and linear dynamical system. Decoding with DCCA yielded better performance than decoding the original FRs using LSTM-RNN (6.6 and 16.0% improvement on average for each velocity and position, respectively; Wilcoxon rank sum test, p &lt; 0.05). Thus, DCCA can identify the kinematics-related canonical variables of M1 activities, thus improving the decoding performance. Our results may help advance the design of decoding models for intracortical BMIs

Emerging Applications of Liquid Crystals Based on Nanotechnology.

Diverse functionalities of liquid crystals (LCs) offer enormous opportunities for their potential use in advanced mobile and smart displays, as well as novel non-display applications. Here, we present snapshots of the research carried out on emerging applications of LCs ranging from electronics to holography and self-powered systems. In addition, we will show our recent results focused on the development of new LC applications, such as programmable transistors, a transparent and active-type two-dimensional optical array and self-powered display systems based on LCs, and will briefly discuss their novel concepts and basic operating principles. Our research will give insights not only into comprehensively understanding technical and scientific applications of LCs, but also developing new discoveries of other LC-based devices

Clinical Impact of Tumor Regression Grade after Preoperative Chemoradiation for Locally Advanced Rectal Cancer: Subset Analyses in Lymph Node Negative Patients

BACKGROUND: We investigated the prognostic significance of tumor regression grade (TRG) after preoperative chemoradiation therapy (preop-CRT) for locally advanced rectal cancer especially in the patients without lymph node metastasis. METHODS: One-hundred seventy-eight patients who had cT3/4 tumors were given 5,040 cGy preoperative radiation with 5-fluorouracil/leucovorin chemotherapy. A total mesorectal excision was performed 4-6 weeks after preop-CRT. TRG was defined as follows: grade 1 as no cancer cells remaining; grade 2 as cancer cells outgrown by fibrosis; grade 3 as a minimal presence or absence of regression. The prognostic significance of TRG in comparison with histopathologic staging was analyzed. RESULTS: Seventeen patients (9.6%) showed TRG1. TRG was found to be significantly associated with cancer-specific survival (CSS; P = 0.001) and local recurrence (P = 0.039) in the univariate study, but not in the multivariate analysis. The ypN stage was the strongest prognostic factor in the multivariate analysis. Subgroup analysis revealed TRG to be an independent prognostic factor for the CSS of ypN0 patients (P = 0.031). TRG had a stronger impact on the CSS of ypN (-) patients (P = 0.002) than on that of ypN (+) patients (P = 0.521). In ypT2N0 and ypT3N0, CSS was better for TRG2 than for TRG3 (P = 0.041, P = 0.048), and in ypN (-) and TRG2 tumors, CSS was better for ypT1-2 than for ypT3-4 (P = 0.034). CONCLUSION: TRG was found to be the strongest prognostic factor in patients without lymph node metastasis (ypN0), and different survival was observed according to TRG among patients with a specific histopathologic stage. Thus, TRG may provide an accurate prediction of prognosis and may be used for f tailoring treatment for patients without lymph node metastasis.ope

Microscopic evidence of strong interactions between chemical vapor deposited 2D MoS2 film and SiO2 growth template

Two-dimensional MoS2 film can grow on oxide substrates including Al2O3 and SiO2. However, it cannot grow usually on non-oxide substrates such as a bare Si wafer using chemical vapor deposition. To address this issue, we prepared as-synthesized and transferred MoS2 (AS-MoS2 and TR-MoS2) films on SiO2/Si substrates and studied the effect of the SiO2 layer on the atomic and electronic structure of the MoS2 films using spherical aberration-corrected scanning transition electron microscopy (STEM) and electron energy loss spectroscopy (EELS). The interlayer distance between MoS2 layers film showed a change at the AS-MoS2/SiO2 interface, which is attributed to the formation of S–O chemical bonding at the interface, whereas the TR-MoS2/SiO2 interface showed only van der Waals interactions. Through STEM and EELS studies, we confirmed that there exists a bonding state in addition to the van der Waals force, which is the dominant interaction between MoS2 and SiO2. The formation of S–O bonding at the AS-MoS2/SiO2 interface layer suggests that the sulfur atoms at the termination layer in the MoS2 films are bonded to the oxygen atoms of the SiO2 layer during chemical vapor deposition. Our results indicate that the S–O bonding feature promotes the growth of MoS2 thin films on oxide growth templates.This work was fnancially supported by National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2018M3D1A1058793, 2019M3E6A1103818, 2020M2D8A206983011, 2021R1A2B5B03001851). The Inter-University Semiconductor Research Center and Institute of Engineering Research at Seoul National University provided research facilities for this work

Surface energy-mediated construction of anisotropic semiconductor wires with selective crystallographic polarity.

ZnO is a wide band-gap semiconductor with piezoelectric properties suitable for opto-electronics, sensors, and as an electrode material. Controlling the shape and crystallography of any semiconducting nanomaterial is a key step towards extending their use in applications. Whilst anisotropic ZnO wires have been routinely fabricated, precise control over the specific surface facets and tailoring of polar and non-polar growth directions still requires significant refinement. Manipulating the surface energy of crystal facets is a generic approach for the rational design and growth of one-dimensional (1D) building blocks. Although the surface energy is one basic factor for governing crystal nucleation and growth of anisotropic 1D structures, structural control based on surface energy minimization has not been yet demonstrated. Here, we report an electronic configuration scheme to rationally modulate surface electrostatic energies for crystallographic-selective growth of ZnO wires. The facets and orientations of ZnO wires are transformed between hexagonal and rectangular/diamond cross-sections with polar and non-polar growth directions, exhibiting different optical and piezoelectrical properties. Our novel synthetic route for ZnO wire fabrication provides new opportunities for future opto-electronics, piezoelectronics, and electronics, with new topological properties

Transmission of Seasonal Outbreak of Childhood Enteroviral Aseptic Meningitis and Hand-foot-mouth Disease

This study was conducted to evaluate the modes of transmission of aseptic meningitis (AM) and hand-foot-mouth disease (HFMD) using a case-control and a case-crossover design. We recruited 205 childhood AM and 116 HFMD cases and 170 non-enteroviral disease controls from three general hospitals in Gyeongju, Pohang, and Seoul between May and August in both 2002 and 2003. For the case-crossover design, we established the hazard and non-hazard periods as week one and week four before admission, respectively. In the case-control design, drinking water that had not been boiled, not using a water purifier, changes in water quality, and contact with AM patients were significantly associated with the risk of AM (odds ratio [OR]=2.8, 2.9, 4.6, and 10.9, respectively), while drinking water that had not been boiled, having a non-water closet toilet, changes in water quality, and contact with HFMD patients were associated with risk of HFMD (OR=3.3, 2.8, 6.9, and 5.0, respectively). In the case-crossover design, many life-style variables such as contact with AM or HFMD patients, visiting a hospital, changes in water quality, presence of a skin wound, eating out, and going shopping were significantly associated with the risk of AM (OR=18.0, 7.0, 8.0, 2.2, 22.3, and 3.0, respectively) and HFMD (OR=9.0, 37.0, 11.0, 12.0, 37.0, and 5.0, respectively). Our findings suggest that person-to-person contact and contaminated water could be the principal modes of transmission of AM and HFMD