Design of non-circular membranes metasurfaces for broadband sound absorption

Acoustic metasurfaces have been attracting much attention due to their effectiveness in controlling sound wave propagation despite a structure well below the wavelength at operating frequency. We propose a novel decorated membrane resonator structure with multiple circular membranes leading to multiplexing the resonant modes through breaking symmetry of the membrane's vibrational modes. By numerical analysis, the structure is optimized for wideband (500 to 1500 Hz) sound absorption. The designed structure is fabricated by using a 3D printer and its sound absorption property is verified experimentally by an impedance tube measurement. The results demonstrate that the present approach is simple but effective to broadband sound absorption with thin and lightweight artificial acoustic structures

Unsupervised Detection of Cell-Assembly Sequences by Similarity-Based Clustering

Neurons which fire in a fixed temporal pattern (i.e., "cell assemblies") are hypothesized to be a fundamental unit of neural information processing. Several methods are available for the detection of cell assemblies without a time structure. However, the systematic detection of cell assemblies with time structure has been challenging, especially in large datasets, due to the lack of efficient methods for handling the time structure. Here, we show a method to detect a variety of cell-assembly activity patterns, recurring in noisy neural population activities at multiple timescales. The key innovation is the use of a computer science method to comparing strings ("edit similarity"), to group spikes into assemblies. We validated the method using artificial data and experimental data, which were previously recorded from the hippocampus of male Long-Evans rats and the prefrontal cortex of male Brown Norway/Fisher hybrid rats. From the hippocampus, we could simultaneously extract place-cell sequences occurring on different timescales during navigation and awake replay. From the prefrontal cortex, we could discover multiple spike sequences of neurons encoding different segments of a goal-directed task. Unlike conventional event-driven statistical approaches, our method detects cell assemblies without creating event-locked averages. Thus, the method offers a novel analytical tool for deciphering the neural code during arbitrary behavioral and mental processes

Angular-based Edge Bundled Parallel Coordinates Plot for the Visual Analysis of Large Ensemble Simulation Data

With the continuous increase in the computational power and resources of modern high-performance computing (HPC) systems, large-scale ensemble simulations have become widely used in various fields of science and engineering, and especially in meteorological and climate science. It is widely known that the simulation outputs are large time-varying, multivariate, and multivalued datasets which pose a particular challenge to the visualization and analysis tasks. In this work, we focused on the widely used Parallel Coordinates Plot (PCP) to analyze the interrelations between different parameters, such as variables, among the members. However, PCP may suffer from visual cluttering and drawing performance with the increase on the data size to be analyzed, that is, the number of polylines. To overcome this problem, we present an extension to the PCP by adding B\'{e}zier curves connecting the angular distribution plots representing the mean and variance of the inclination of the line segments between parallel axes. The proposed Angular-based Parallel Coordinates Plot (APCP) is capable of presenting a simplified overview of the entire ensemble data set while maintaining the correlation information between the adjacent variables. To verify its effectiveness, we developed a visual analytics prototype system and evaluated by using a meteorological ensemble simulation output from the supercomputer Fugaku

Effectiveness of surgery and hyperbaric oxygen for antiresorptive agent-related osteonecrosis of the jaw: A subgroup analysis by disease stage

Antiresorptive agent-related osteonecrosis of the jaw (ARONJ) is an adverse event induced by antiresorptive agents (ARAs). The purpose of this study was to evaluate variables, mainly surgery and hyperbaric oxygen (HBO) therapy, associated with treatment outcomes in patients with a diagnosis of ARONJ at a single center. We enrolled consecutive patients who presented to our hospital for the management of stage 2 or 3 ARONJ between January 2003 and December 2019. The relationship between potentially predictive factors and outcome variables was examined using statistical analyses, along with a subgroup analysis based on disease stage. Of 252 patients included in this study, 206 had stage 2 ARONJ and 46 had stage 3 ARONJ. There were 119 patients with osteoporosis and 133 with malignant disease. In total, 139 patients were healed, and the healing rate of patients with stage 3 ARONJ was lower than that of patients with stage 2 ARONJ. With regard to the combination of surgery and HBO therapy, most patients underwent HBO before and after surgery. In the univariable analysis, surgery showed a therapeutic effect in both stage 2 and 3 ARONJ, whereas HBO showed a therapeutic effect in stage 2 ARONJ. In the multivariable analysis for stage 2 ARONJ, extensive surgery showed a stronger association with healing than conservative surgery, whereas ≥46 sessions of HBO therapy was less associated with healing than was non-HBO therapy. Our findings suggest that extensive surgery is highly effective against ARONJ regardless of disease stage if there is a sequestrum separation and systemic tolerance, whereas HBO therapy before and after surgical approach can be effective. Further studies are needed to identify treatment strategies for patients with treatment-refractory ARONJ who may be forced to undergo long-term HBO therapy with the expectation of sequestrum separation

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