Sound Absorption by Acoustic Microlattice with Optimized Pore Configuration

Sound absorption or dissipation principally involves joint interactions between sound waves, material morphology and the air medium. How these elements work most efficiently for sound absorption remains elusive to date. In this paper, we suggest a fundamental relation concisely cross-linking the three elements, which reveals that optimal sound absorption efficiency occurs when the pore size of the material is twice the thickness of the viscous boundary layer of the acoustic air medium. The study is validated by microlattice materials comprising of well-controlled regular structures that absorb sound in a tunable manner. Optimized material morphology in terms of pore size and porosity is determined to provide a robust guidance for optimizing sound absorbing materials.Comment: 14 pages, 7 figure

Improvements on "Multi-Party Quantum Summation without a Third Party based on dd-Dimensional Bell States"

In 2021, Wu et al. presented a multi-party quantum summation scheme exploiting the entanglement properties of d-dimensional Bell states (Wu et al. in Quantum Inf Process 20:200, 2021). In particular, the authors proposed a three-party quantum summation protocol and then extended their work to a multi-party case. It is claimed that their protocol is secure against outside and participants' attacks. However, this work points out that Wu's protocol has a loophole, i.e., two or more dishonest participants who meet a specific location relationship can conspire to obtain the private inputs of some honest participants without being detected. Accordingly, improvements are proposed to address these issues

FACILE AND EFFECTIVE PHONONIC STRUCTURES FOR ULTRASOUND FOCUSING APPLICATION

ABSTRACT Ultrasound therapy is a highly popular non-invasive method to treat diseases. It is desired to increase the resolution of ultrasound therapy, providing more efficient therapeutic effect. In this study, a simple but effective phononic structure was designed to achieve higher resolution close to wavelength resolution of ultrasound focusing. The objective of this study is to design a unique phononic structure to focus acoustic wave into human body more deeply and precisely. It is known that overheating by high frequency ultrasound will cause a series of side effects including bone burns, soft tissue burns, swelling and bleeding problems. In addition, due to the limited propagation of recovered evanescent wave, the penetration depth of acoustic energy being focused by the acoustic metamaterials is often hindered. In this study, we will design a multilayer acoustic metamaterial which shows sub-wavelength focusing ability at relatively low frequencies. More importantly, our design will also extend the ability of penetration depth by manipulating the focusing length through optimization of the phononic structure

Finite-Time Chaos Control of a Complex Permanent Magnet Synchronous Motor System

This paper investigates the finite-time chaos control of a permanent magnet synchronous motor system with complex variables. Based on the finite-time stability theory, two control strategies are proposed to realize stabilization of the complex permanent magnet synchronous motor system in a finite time. Two numerical simulations have been conducted to demonstrate the validity and feasibility of the theoretical analysis

Research of the Real-time Database in Embedded Configuration Software

In recent years, the application of embedded technology and configuration technology in industrial control is more and more widely. The embedded configuration software which is combined of embedded and configuration has become the inevitable trend in industrial control field. Real-time database system as the core of embedded configuration software, the organizational structure whether reasonable and effective is directly related to the performance of the whole system, affecting field devices real-time communication and data transmission in graphic display interface. Based on a large number of configuration-related papers, this paper deeply researched the real-time database and using three layer storage structures which consist of shared memory, file system and general database. It improves the access efficiency of real-time database and data reliability in a timely manner. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4778

Hopf Bifurcation Analysis for the van der Pol Equation with Discrete and Distributed Delays

We consider the van der Pol equation with discrete and distributed delays. Linear stability of this equation is investigated by analyzing the transcendental characteristic equation of its linearized equation. It is found that this equation undergoes a sequence of Hopf bifurcations by choosing the discrete time delay as a bifurcation parameter. In addition, the properties of Hopf bifurcation were analyzed in detail by applying the center manifold theorem and the normal form theory. Finally, some numerical simulations are performed to illustrate and verify the theoretical analysis

Design of a drop-in EBI sensor probe for abnormal tissue detection in minimally invasive surgery

It is a common challenge for the surgeon to detect pathological tissues and determine the resection margin during a minimally invasive surgery. In this study, we present a drop-in sensor probe based on the electrical bioimpedance spectroscopic technology, which can be grasped by a laparoscopic forceps and controlled by the surgeon to inspect suspicious tissue area conveniently. The probe is designed with an optimized electrode and a suitable shape specifically for Minimally Invasive Surgery (MIS). Subsequently, a series of ex vivo experiments are carried out with porcine liver tissue for feasibility validation. During the experiments, impedance measured at frequencies from 1 kHz to 2 MHz are collected on both normal tissues and water soaked tissue. In addition, classifiers based on discriminant analysis are developed. The result of the experiment indicate that the sensor probe can be used to measure the impedance of the tissue easily and the developed tissue classifier achieved accuracy of 80% and 100% respectively.

Association between visceral adiposity index, lipid accumulation products, and frailty in older Americans: the 2007–2018 NHANES cross-sectional study

The aim of this study was to investigate the relationship between visceral adiposity index (VAI) and lipid accumulation products (LAP) and frailty index (FI) in older Americans. Based on data from the 2007–2018 National Health and Nutrition Examination Survey (NHANES), the study population consisted of 3,396 older adults aged 60 years and older with a mean age of 69.48 ± 6.76 years. The findings of weighted multivariate regression analysis demonstrated a strong correlation between the prevalence of frailty prevalence and greater VAI and LAP. In the fully adjusted model, the association of VAI with frailty remained significant, with an OR of 1.49 (95% CI: 1.26, 1.77; p < 0.0001.) The association of LAP with frailty was also significant, with an OR of 1.88 (95% CI: 1.55, 2.29; p < 0.0001). Further nonlinear analyses by generalized additive modeling (GAM) revealed significant nonlinear relationships between VAI and LAP and frailty, and the nonlinear effects were more pronounced in the female population. Subgroup analyses showed that the positive correlations between VAI and LAP and frailty were generalized across populations and there was no significant interaction in most subgroups. In addition, sensitivity analyses validated the robustness of these results, further confirming the conclusion of VAI and LAP as independent risk factors for frailty. Finally, ROC analysis showed that LAP outperformed VAI in predicting frailty, suggesting the potential of LAP in early screening for frailty. Overall, VAI and LAP are independent risk factors for frailty in the elderly population and have important clinical applications

DPAL-BERT: A Faster and Lighter Question Answering Model

Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems. However, with the constant evolution of algorithms, data, and computing power, the increasing size and complexity of these models have led to increased training costs and reduced efficiency. This study aims to minimize the inference time of such models while maintaining computational performance. It also proposes a novel Distillation model for PAL-BERT (DPAL-BERT), specifically, employs knowledge distillation, using the PAL-BERT model as the teacher model to train two student models: DPAL-BERT-Bi and DPAL-BERT-C. This research enhances the dataset through techniques such as masking, replacement, and n-gram sampling to optimize knowledge transfer. The experimental results showed that the distilled models greatly outperform models trained from scratch. In addition, although the distilled models exhibit a slight decrease in performance compared to PAL-BERT, they significantly reduce inference time to just 0.25% of the original. This demonstrates the effectiveness of the proposed approach in balancing model performance and efficiency