Studies on Dual Helmholtz Resonators and Asymmetric Waveguides for Ventilated Soundproofing.

Achieving the simultaneity of ventilation and soundproofing is a significant challenge in applied acoustics. Ventilated soundproofing relies on the interplay between local resonance and nonlocal coupling of acoustic waves within a sub-wavelength structure. However, previously studied structures possess limited types of fundamental resonators and lack modifications from the basic arrangement. These constraints often force the specified position of each attenuation peak and low absorption performance. Here, we suggest the in-duct-type sound barrier with dual Helmholtz resonators, which are positioned around the symmetry-breaking waveguides. The numerical simulations for curated dimensions and scattered fields show the aperiodic migrations and effective amplifications of the two absorptive domains. Collaborating with the subsequent reflective domains, the designed structure holds two effective attenuation bands under the first Fabry-Pérot resonance frequency. This study would serve as a valuable example for understanding the local and non-local behaviors of sub-wavelength resonating structures. Additionally, it could be applied in selective noise absorption and reflection more flexibly.

Graphene/III-V Quantum Dot Mixed-Dimensional Heterostructure for Enhanced Radiative Recombinations via Hole Carrier Transfer.

Fabrication of high quantum efficiency nanoscale device is challenging due to increased carrier loss at surface. Low dimensional materials such 0D quantum dots and 2D materials have been widely studied to mitigate the loss. Here, we demonstrate a strong photoluminescence enhancement from graphene/III-V quantum dot mixed-dimensional heterostructures. The distance between graphene and quantum dots in the 2D/0D hybrid structure determines the degree of radiative carrier recombination enhancement from 80% to 800% compared to the quantum dot only structure. Time-resolved photoluminescence decay also shows increased carrier lifetimes when the distance decreases from 50 to 10 nm. We propose that the optical enhancement is due to energy band bending and hole carrier transfer, which repair the imbalance of electron and hole carrier densities in quantum dots. This 2D graphene/0D quantum dot heterostructure shows promise for high performance nanoscale optoelectronic devices.

Tunable spin injection and detection across a van der Waals interface.

Van der Waals heterostructures with two-dimensional magnets offer a magnetic junction with an atomically sharp and clean interface. This attribute ensures that the magnetic layers maintain their intrinsic spin-polarized electronic states and spin-flipping scattering processes at a minimum level, a trait that can expand spintronic device functionalities. Here, using a van der Waals assembly of ferromagnetic Fe3GeTe2 with non-magnetic hexagonal boron nitride and WSe2 layers, we demonstrate electrically tunable, highly transparent spin injection and detection across the van der Waals interfaces. By varying an electrical bias, the net spin polarization of the injected carriers can be modulated and reversed in polarity, which leads to sign changes of the tunnelling magnetoresistance. We attribute the spin polarization reversals to sizable contributions from high-energy localized spin states in the metallic ferromagnet, so far inaccessible in conventional magnetic junctions. Such tunability of the spin-valve operations opens a promising route for the electronic control of next-generation low-dimensional spintronic device applications.

Implementation of particle swarm optimization for complete inverse design of multilayered optical filters.

Particle swarm optimization is implemented for the complete inverse design of multilayered optical filters. To achieve this, a model is designed to optimize the thickness and material of each layer, as well as the total number of layers, simultaneously. The performance of the model is evaluated by repeating the optimization process, enabling clarification of the effects of model parameters on the final output. The designed model is also demonstrated for the optimization of various optical filters, including bandstop filters, bandpass filters, and anti-reflection coatings. The results confirm that particle swarm optimization is capable of designing arbitrary optical filters that cannot be designed using conventional design theories.

Fault Diagnosis Method for Human Coexistence Robots Based on Convolutional Neural Networks Using Time-Series Data Generation and Image Encoding.

This paper proposes fault diagnosis methods aimed at proactively preventing potential safety issues in robot systems, particularly human coexistence robots (HCRs) used in industrial environments. The data were collected from durability tests of the driving module for HCRs, gathering time-series vibration data until the module failed. In this study, to apply classification methods in the absence of post-failure data, the initial 50% of the collected data were designated as the normal section, and the data from the 10 h immediately preceding the failure were selected as the fault section. To generate additional data for the limited fault dataset, the Wasserstein generative adversarial networks with gradient penalty (WGAN-GP) model was utilized and residual connections were added to the generator to maintain the basic structure while preventing the loss of key features of the data. Considering that the performance of image encoding techniques varies depending on the dataset type, this study applied and compared five image encoding methods and four CNN models to facilitate the selection of the most suitable algorithm. The time-series data were converted into image data using image encoding techniques including recurrence plot, Gramian angular field, Markov transition field, spectrogram, and scalogram. These images were then applied to CNN models, including VGGNet, GoogleNet, ResNet, and DenseNet, to calculate the accuracy of fault diagnosis and compare the performance of each model. The experimental results demonstrated significant improvements in diagnostic accuracy when employing the WGAN-GP model to generate fault data, and among the image encoding techniques and convolutional neural network models, spectrogram and DenseNet exhibited superior performance, respectively.

CRFalign: A Sequence-Structure Alignment of Proteins Based on a Combination of HMM-HMM Comparison and Conditional Random Fields.

Sequence-structure alignment for protein sequences is an important task for the template-based modeling of 3D structures of proteins. Building a reliable sequence-structure alignment is a challenging problem, especially for remote homologue target proteins. We built a method of sequence-structure alignment called CRFalign, which improves upon a base alignment model based on HMM-HMM comparison by employing pairwise conditional random fields in combination with nonlinear scoring functions of structural and sequence features. Nonlinear scoring part is implemented by a set of gradient boosted regression trees. In addition to sequence profile features, various position-dependent structural features are employed including secondary structures and solvent accessibilities. Training is performed on reference alignments at superfamily levels or twilight zone chosen from the SABmark benchmark set. We found that CRFalign method produces relative improvement in terms of average alignment accuracies for validation sets of SABmark benchmark. We also tested CRFalign on 51 sequence-structure pairs involving 15 FM target domains of CASP14, where we could see that CRFalign leads to an improvement in average modeling accuracies in these hard targets (TM-CRFalign ≃42.94%) compared with that of HHalign (TM-HHalign ≃39.05%) and also that of MRFalign (TM-MRFalign ≃36.93%). CRFalign was incorporated to our template search framework called CRFpred and was tested for a random target set of 300 target proteins consisting of Easy, Medium and Hard sets which showed a reasonable template search performance.

Thermotherapy as an alternative to exercise for metabolic health in obese postmenopausal women: focus on circulating irisin level.

Irisin is a myokine caused by exercise that improves insulin resistance and weight loss. However, under unfavorable conditions such as air pollution, and during the pandemic, outdoor activities are uncomfortable. Therefore, in this study, the effect of heat therapy (half bath 42 ± 0.5°C for 30 min) on irisin circulation levels as an exercise alternative for middle-aged obese women after menopause was investigated. Subjects were 33 women aged 49.54 ± 6.04 years, with parameters of height, 160.12 ± 4.33 cm, weight, 69.71 ± 7.52 kg, body surface area 1.73 ± 0.13 m2, body mass index, 27.19 ± 3.40 kg/m2. The results suggest that circulating irisin levels showed a significant increase after one-time thermotherapy (TH-1). However, the increase in circulating irisin levels after 15 treatments (TH-15, 5 days/week, 3 weeks) was significantly varied. The level of adiponectin, which increases fatty oxidation to reduce fatty deposition, increased significantly at TH-1, but further increased at TH-15, which was significantly different from the level of TH-1. In addition, the basic serum free fatty acid (FFA) level was significantly increased at TH-15 compared to TH-1. Significant differences were also found in the lipid profile (body mass index, waist circumference, and % body fat). Thermotherapy can significantly increase the tympanic temperature and induce changes in circulating irisin and adiponectin levels. Thus, it resulted in positive changes in FFA and lipid profiles. Therefore, repeated thermotherapy is effective in increasing circulating irisin levels in postmenopausal obese women.

Structural insights into CYP107G1 from rapamycin-producing Streptomyces rapamycinicus.

Rapamycin is a clinically important macrolide agent with immunosuppressant and antiproliferative properties, produced by the actinobacterium, Streptomyces rapamycinicus. Two cytochrome P450 enzymes are involved in the biosynthesis of rapamycin. CYP107G1 and CYP122A2 catalyze the oxidation reactions of C27 and C9 of pre-rapamycin, respectively. To understand the structural and biochemical features of P450 enzymes in rapamycin biosynthesis, the CYP107G1 and CYP122A2 genes were cloned, their recombinant proteins were expressed in Escherichia coli, and the purified enzymes were characterized. Both enzymes displayed low spin states in the absolute spectra of ferric forms, and the titrations with rapamycin induced type I spectral changes with Kd values of 4.4 ± 0.4 and 3.0 ± 0.3 µM for CYP107G1 and CYP122A2, respectively. The X-ray crystal structures of CYP107G1 and its co-crystal complex with everolimus, a clinical rapamycin derivative, were determined at resolutions of 2.9 and 3.0 Å, respectively. The overall structure of CYP107G1 adopts the canonical scaffold of cytochrome P450 and possesses large substrate pocket. The distal face of the heme group is exposed to solvents to accommodate macrolide access. When the structure of the everolimus-bound CYP107G1 complex (CYP107G1-Eve) was compared to that of the ligand-free CYP107G1 form, no significant conformational change was observed. Hence, CYP107G1 has a relatively rigid structure with versatile loops to accommodate a bulky substrate. The everolimus molecule is bound to the substrate-binding pocket in the shape of a squeezed donut, and its elongated structure is bound perpendicular to a planar heme plane and I-helix.

Performance Analysis of Millimeter-Wave UAV Swarm Networks under Blockage Effects.

Due to their high mobility, unmanned aerial vehicles (UAVs) can offer better connectivity by complement or replace with the existing terrestrial base stations (BSs) in the mobile cellular networks. In particular, introducing UAV and millimeter wave (mmWave) technologies can better support the future wireless networks with requirements of high data rate, low latency, and seamless connectivity. However, it is widely known that mmWave signals are susceptible to blockages because of their poor diffraction. In this context, we consider macro-diversity achieved by the multiple UAV BSs, which are randomly distributed in a spherical swarm. Using the widely used channel model incorporated with the distance-based random blockage effects, which is proposed based on stochastic geometry and random shape theory, we investigate the outage performance of the mmWave UAV swarm network. Further, based on our analysis, we show how to minimize the outage rate by adjusting various system parameters such as the size of the UAV swarm relative to the distance to the receiver.

Full-coloration based on metallic nanostructures through phase discontinuity in Fabry-Perot resonators.

We demonstrate a flexible full-color plate using Fabry-Perot (FP) resonators with two different types of silver nanostructures, a uniform nanofilm and a layer of nanoislands, for transmissive color elements. Two different nanostructures with deep-subwavelength features are selectively generated according to the layer thickness during vacuum deposition with no patterning process. In the nanofilm case, the primary optical mode accountable for generating the color shifts to blue from the original FP resonance while in the nanoislands case, it shifts to red so that a wide spectrum in the visible range is available through the phase discontinuity in the FP resonators. The peaks in the FP resonance shifted toward the opposite directions are attributed to the opposite signs of the phase retardations by a nanofilm and nanoislands. This approach paves a new way of constructing full-color elements for a variety of display devices and image storage systems.

Selective photonic printing based on anisotropic Fabry-Perot resonators for dual-image holography and anti-counterfeiting.

We present the photonic printing that can display different color images depending on the optical polarization of incident light. The dynamic selection among different images becomes possible by using anisotropic Fabry-Perot resonators that incorporate a layer of liquid crystal molecules aligned by directional molecular registration (DMR) as polarization-dependent color pixels. Using the new device platform, we demonstrate a prototype of an anticounterfeiting label with inherent anti-replicability that results from the molecular-level origin of security images. In addition, this concept is extended to polarization-selective holography. Our molecular-level approach enables to develop a new class of security labels and holographic storage media.

Protein structure modeling and refinement by global optimization in CASP12.

For protein structure modeling in the CASP12 experiment, we have developed a new protocol based on our previous CASP11 approach. The global optimization method of conformational space annealing (CSA) was applied to 3 stages of modeling: multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain re-modeling. For better template selection and model selection, we updated our model quality assessment (QA) method with the newly developed SVMQA (support vector machine for quality assessment). For 3D chain building, we updated our energy function by including restraints generated from predicted residue-residue contacts. New energy terms for the predicted secondary structure and predicted solvent accessible surface area were also introduced. For difficult targets, we proposed a new method, LEEab, where the template term played a less significant role than it did in LEE, complemented by increased contributions from other terms such as the predicted contact term. For TBM (template-based modeling) targets, LEE performed better than LEEab, but for FM targets, LEEab was better. For model refinement, we modified our CASP11 molecular dynamics (MD) based protocol by using explicit solvents and tuning down restraint weights. Refinement results from MD simulations that used a new augmented statistical energy term in the force field were quite promising. Finally, when using inaccurate information (such as the predicted contacts), it was important to use the Lorentzian function for which the maximal penalty arising from wrong information is always bounded.

Generation of intensity-tunable structural color from helical photonic crystals for full color reflective-type display.

A new concept of intensity-tunable structural coloration is proposed on the basis of a helical photonic crystal (HPC). The HPCs are constructed from a mixture of chiral reactive mesogens by spin-coating, followed by the photo-polymerization. A liquid crystal (LC) layer, being homogeneously aligned, is prepared on the HPCs to serve as a tunable waveplate. The electrical modulation of the phase retardation through the LC layer directly leads to the intensity-tunable Bragg reflection from the HPCs upon the incidence of the polarized light. The bandwidths of the structural colors are found to be well preserved regardless of the applied voltage. A prototype of a full color reflective-type display, incorporated with three primary color units, is demonstrated. Our concept of decoupling two mutually independent functions, the intensity modulation by the tunable waveplate and the color reflection by the HPCs provides a simple and powerful way of producing a full color reflective-type display which possesses high color purity, high optical efficiency, the cycling durability, and the design flexibility.

Superconducting Open-Framework Allotrope of Silicon at Ambient Pressure.

Diamond Si is a semiconductor with an indirect band gap that is the basis of modern semiconductor technology. Although many metastable forms of Si were observed using diamond anvil cells for compression and chemical precursors for synthesis, no metallic phase at ambient conditions has been reported thus far. Here we report the prediction of pure metallic Si allotropes with open channels at ambient pressure, unlike a cubic diamond structure in covalent bonding networks. The metallic phase termed P6/m-Si_{6} can be obtained by removing Na after pressure release from a novel Na-Si clathrate called P6/m-NaSi_{6}, which is predicted through first-principles study at high pressure. We identify that both P6/m-NaSi_{6} and P6/m-Si_{6} are stable and superconducting with the critical temperatures of about 13 and 12 K at ambient pressure, respectively. The prediction of new Na-Si and Si clathrate structures presents the possibility of exploring new exotic allotropes useful for Si-based devices.

Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics.

As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

Coverage Probability and Area Spectral Efficiency of Clustered Linear Unmanned Vehicle Sensor Networks.

In this paper, we consider clustered unmanned vehicle (UV) sensor networks for swarm sensing applications in a linear structure such as highway, tunnel, underwater pipelines, power lines, and international border. We assume that the linear UV sensor networks follow Thomas cluster process (TCP), in which the cluster locations are modelled by Poisson point process (PPP), while the cluster members (UVs) are normally distributed around their cluster centers. We focus on communications between UVs within a cluster such as local sensing data transfer or swarm coordination, where multiple UV pairs can share the same frequency band simultaneously. Thus, in the presence of co-channel interference both from the same cluster and the other clusters, we study the coverage and area spectral efficiency of the clustered UV sensor networks in a linear topology.

Template based protein structure modeling by global optimization in CASP11.

For the template-based modeling (TBM) of CASP11 targets, we have developed three new protein modeling protocols (nns for server prediction and LEE and LEER for human prediction) by improving upon our previous CASP protocols (CASP7 through CASP10). We applied the powerful global optimization method of conformational space annealing to three stages of optimization, including multiple sequence-structure alignment, three-dimensional (3D) chain building, and side-chain remodeling. For more successful fold recognition, a new alignment method called CRFalign was developed. It can incorporate sensitive positional and environmental dependence in alignment scores as well as strong nonlinear correlations among various features. Modifications and adjustments were made to the form of the energy function and weight parameters pertaining to the chain building procedure. For the side-chain remodeling step, residue-type dependence was introduced to the cutoff value that determines the entry of a rotamer to the side-chain modeling library. The improved performance of the nns server method is attributed to successful fold recognition achieved by combining several methods including CRFalign and to the current modeling formulation that can incorporate native-like structural aspects present in multiple templates. The LEE protocol is identical to the nns one except that CASP11-released server models are used as templates. The success of LEE in utilizing CASP11 server models indicates that proper template screening and template clustering assisted by appropriate cluster ranking promises a new direction to enhance protein 3D modeling. Proteins 2016; 84(Suppl 1):221-232. © 2015 Wiley Periodicals, Inc.

Management of Endometrial Hyperplasia With a Levonorgestrel-Releasing Intrauterine System: A Korean Gynecologic-Oncology Group Study.

OBJECTIVE: The aim of the study was to evaluate the efficacy of the levonorgestrel intrauterine system (LNG-IUS) for treatment of endometrial hyperplasia (EH). METHODS: A prospective multicenter study was conducted from November 2010 to March 2014. Patients with histologically confirmed EH were treated with LNG-IUS. At 3, 6, and 9 months after LNG-IUS insertion, follow-up endometrial aspiration biopsies with the LNG-IUS in the uterus were undertaken. At the 12th month of follow-up, endometrial tissues were obtained via 2 methods: endometrial aspiration biopsy with the LNG-IUS in the uterus, followed by dilatation and curettage (D&C) after LNG-IUS removal. The primary outcome was the regression rate at 12 months after LNG-IUS insertion, and the secondary outcome was the consistency of the results between the endometrial aspiration biopsy and the D&C. RESULTS: The study population comprised 75 patients, including 37 with simple hyperplasia without atypia; 3 with atypical simple hyperplasia; 23 with complex hyperplasia without atypia, and 12 with atypical complex hyperplasia. Of these patients treated with the LNG-IUS, 38 (50.7%) were followed up at 12 months after LNG-IUS insertion. The complete regression rate at 12 months was 94.7% (36/38): 100% (6/6) of patients with atypical EH and 93.7% (30/32) with EH without atypia. In all of the cases (100%, 36/36), patients achieved complete regression within 3 months of LNG-IUS insertion. A comparison of the pathologic results from endometrial aspiration biopsy and D&C was carried out for 15 patients. In the histologic results by endometrial aspiration biopsy, 14 patients were diagnosed as "normal endometrium" and 1 as "insufficient tissue for pathologic evaluation." Among the 14 cases of normal endometrium by endometrial aspiration biopsy, 1 was diagnosed as "residual EH" by D&C, and the 1 case with insufficient tissue was diagnosed as normal endometrium by D&C. CONCLUSIONS: Levonorgestrel intrauterine system is an effective and favorable method for treatment of EH.

Submicro-pillars and holes from the depth-wise Talbot images of a conical phase mask.

We construct two-dimensional arrays of submicro-pillars and holes from the depth-wise Talbot images of a conical phase mask in a photoactive layer prepared on a quartz substrate. In contrast to the conventional Talbot lithography employing only one image in the photoactive layer, two images of the phase mask are produced in a depth-wise manner such that the pillar patterns are in the primary image plane while the hole patterns in the secondary image plane according to the penetration depth of the exposure energy. The conical symmetry plays a critical role in producing the covariant patterns of the phase mask in the photoactive layer through the suppression of higher orders of diffraction. Our two image-type approach is simple and versatile for producing different kinds of periodic structures for photonic applications and surface engineering on a micrometer-to-nanometer scale.