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The purpose of this paper is to prepare a dual-encapsulated halloysite nano-container to release the capsuled inhibitor as an additive for corrosion protection of epoxy coating.

Halloysite nano-containers (HNT) were prepared by simultaneously implanting inhibitor benzotriazole (BTA) into the inside and outside of the halloysite using reduced pressure and layer-by-layer (LBL) assembly, respectively. The microstructure and morphology of treated HNT were investigated using Fourier transform infrared spectroscopy and transmission electron microscopy. In addition, the anti-corrosion behaviors of the composite polyepoxy coating with inhibitor-loaded nano-containers BTA@HNT-2 were investigated using the electrochemical impedance spectroscopy and neutral salt spray test.

Test results showed that the LBL assembly structure of the halloysite nano-container makes the BTA@HNT-2 nano-container be controlled and sustained to release BTA, relying on the pH. Very importantly, the obtained nano-container is also responsive to temperature, owing to the thermosensitivity polyelectrolyte out-shell of the HNT. The result showed R_ct of the composite polyepoxy coating can be sufficient to maintain higher than 8.510E+7 Ω·cm² over 72 h of immersion test. Moreover, the artificial induced defects on the coating surface were sufficiently inhibited in the presence of BTA@HNT-2 nano-container in the polyepoxy coating.

Use of the BTA@HNT-2 as corrosion inhibitor nano-container, with good anti-corrosion property and dual-responsive to pH and temperature, offers a significant rout to prepare smart anti-corrosion coating for protecting metal substrate.

This paper aims to address the challenges in hydroacoustic signal detection, signal distortion and target localization caused by baseline drift. The authors propose a combined algorithm that integrates short-time Fourier transform (STFT) detection, smoothness priors approach (SPA), attitude calibration and direction of arrival (DOA) estimation for micro-electro-mechanical system vector hydrophones.

Initially, STFT method screens target signals with baseline drift in low signal-to-noise ratio environments, facilitating easier subsequent processing. Next, SPA is applied to the screened target signal, effectively removing the baseline drift, and combined with filtering to improve the signal-to-noise ratio. Then, vector channel amplitudes are corrected using attitude correction with 2D compass data. Finally, the absolute target azimuth is estimated using the minimum variance distortion-free response beamformer.

Simulation and experimental results demonstrate that the SPA outperforms high-pass filtering in removing baseline drift and is comparable to the effectiveness of variational mode decomposition, with significantly shorter processing times, making it more suitable for real-time applications. The detection performance of the STFT method is superior to instantaneous correlation detection and sample entropy methods. The final DOA estimation achieves an accuracy within 2°, enabling precise target azimuth estimation.

To the best of the authors’ knowledge, this study is the first to apply SPA to baseline drift removal in hydroacoustic signals, significantly enhancing the efficiency and accuracy of signal processing. It demonstrates the method’s outstanding performance in the field of underwater signal processing. In addition, it confirms the reliability and feasibility of STFT for signal detection in the presence of baseline drift.

In recent years, the incidence of cardiovascular disease has continued to rise, and early screening and prevention are especially critical. Phonocardiography (PCG) and electrocardiography (ECG), as simple, cost-effective and non-invasive tests, are important tools for clinical analysis. However, it is difficult to fully reflect the complexity of the cardiovascular system using PCG or ECG tests alone. Combining the multimodal signals of PCG and ECG can provide complementary information to improve the detection accuracy. Therefore, the purpose of this paper is to propose a multimodal signal classification method based on continuous wavelet transform and improved ResNet18.

The classification method is based on the ResNet18 backbone, and the ResNet18 network is improved by embedding the global grouped coordinate attention mechanism module and the improved bidirectional feature pyramid network. Firstly, a data acquisition system was built using a MEMS-integrated PCG-ECG sensor to construct a private data set. Second is the time-frequency transformation of PCG and ECG synchronized signals on public and private data sets using continuous wavelet transform. Finally, the time-frequency images are categorized.

The global grouped coordinate attention mechanism and bidirectional feature pyramid network modules proposed in this paper significantly enhance the model’s performance. On public data sets, the method achieves precision, sensitivity, specificity, accuracy and F1 score of 97.96%, 98.51%, 97.58%, 98.08% and 98.23%, respectively, which represent improvements of 3.54%, 3.92%, 4.18%, 4.03% and 3.72% compared to ResNet18. Additionally, it demonstrates a clear advantage over existing mainstream algorithms. On private data sets, the method’s five metrics are 98.15%, 98.76%, 98.08%, 98.42% and 98.45%, further validating the model’s generalization ability.

The method proposed in this paper not only improves the accuracy and efficiency of the test but also provides an effective solution for early screening and prevention of cardiovascular diseases.

In acoustic detection technology, optical microcavities offer higher detection bandwidth and sensitivity than traditional acoustic sensors. However, research on acoustic detection technologies involving optical microcavities has not yet been reported. Therefore, this paper aims to design and construct an underwater acoustic detection system based on optical microcavities and study its acoustic detection technology to improve its performance.

Based on the principles of optical microcavity acoustic sensors, a signal-detection circuit was designed to form a detection system in conjunction with a laser, an optical waveguide resonator and an oscilloscope. This circuit consists of two modules: a photodetection module and a filter amplification module.

The photodetection module features a baseline noise of −106.499 dBm and can detect device spectral line depths of up to 2410 mV. The gain stability of the filter amplification module was 58 dB ± 1 dB with a noise gain of −107.626 dBm. This design allows the acoustic detection system to detect signals with high sensitivity within the 10 Hz−1.2 MHz frequency band, achieving a maximum sensitivity of −126 dB re 1 V/µPa at 800 Hz and a minimum detectable pressure (MDP) of 0.37 mPa/Hz^1/2, corresponding to a noise equivalent pressure (NEP) of 51.36 dB re 1 V/µPa.

This study designs and constructs a broadband underwater acoustic detection system specifically for optical waveguide resonators based on the sensing principles of silicon dioxide optical waveguide resonators. Experiments demonstrated that the signal detection module improves the sensitivity of underwater acoustic detection based on optical waveguides.

Sinusoidal signals are often used as the inputs of the six degree of freedom (DOF) motion simulator platforms. The purpose of this paper is to propose a fuzzy incremental controller (FIC) to improve sinusoidal signal tracking performances of an electrohydraulic Gough-Stewart platform (GSP).

An FIC is proposed to control an electrohydraulic GSP without any model parameters. The FIC output can be self-organized by only using the hydraulic actuator position information. The control rules are determined by a systematic deterministic method.

Experimental results show that the proposed FIC is valid and can achieve better tracking performances compared with classical PID controller and a decoupling controller (a model-based controller).

An FIC using a systematic deterministic rule-base determination method is proposed to improve sinusoidal signal tracking performances of electrohydraulic GSP.

The purpose of this paper is to present systematic optimal design procedures for the Gough-Stewart platforms used as engineering motion simulators.

Three systematic optimal design procedures are proposed to solve the engineering design problems for the Gough-Stewart platform used as motion simulators. In these systematic optimal design procedures, two contradicting design optimality criteria with good representations of performances of the Gough-Stewart platforms are chosen as the objective functions. In addition, the two objective function optimization problems are solved by using the multi-objective evolutionary algorithms.

In the systematic optimal design procedures, multiple compromised design solutions are found by using Elitist Non-Dominated Sorting Genetic Algorithm version II in the primary design stage, and many candidates can be used in the secondary design stage for higher decisions. Two higher decision methods have been presented to choose the final solutions.

This paper proposes three systematic optimal design procedures to solve the practical design problems of the Gough-Stewart platforms used as motion simulators, which are very important for the engineering designers.

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a regular pattern in the time series is disrupted. This study shows that the CIR# not only performs better than the considered baseline models but also has a much lower error than other additional models or approaches reported in the literature.

Typically, tourism demand tends to follow regular trends, such as low and high seasons on a quarterly/monthly level and weekends and holidays on a daily level. The data set consists of nights spent in Italy at tourist accommodation establishments as collected on a monthly basis by Eurostat before and during the COVID-19 pandemic breaking regular patterns.

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. In addition, given the importance of accurate forecasts, many studies have proposed novel hybrid models or used various combinations of methods. Thus, although there are clear benefits in adopting more complex approaches, the risk is that of dealing with unwieldy models. To demonstrate how this approach can be fruitfully extended to tourism, the accuracy of the CIR# is tested by using standard metrics such as root mean squared errors, mean absolute errors, mean absolute percentage error or average relative mean squared error.

The CIR# model is notably simpler than other models found in literature and does not rely on black box techniques such as those used in neural network (NN) or data science-based models. The carried analysis suggests that the CIR# model outperforms other reference predictions in terms of statistical significance of the error.

The proposed model stands out for being a viable option to the Holt–Winters (HW) model, particularly when dealing with irregular data.

The proposed model has demonstrated superiority even when compared to other models in the literature, and it can be especially useful for tourism stakeholders when making decisions in the presence of disruptions in data patterns.

The novelty lies in the fact that the proposed model is a valid alternative to the HW, especially when the data are not regular. In addition, compared to many existing models in the literature, the CIR# model is notably simpler and more transparent, avoiding the “black box” nature of NN and data science-based models.

一般来说, 旅游需求往往遵循规律的趋势, 例如季度/月的淡季和旺季, 以及日常的周末和假期。该数据集包括欧盟统计局在打破常规模式的2019冠状病毒病大流行之前和期间每月收集的在意大利旅游住宿设施度过的夜晚。

本研究旨在通过一个名为cir#的非线性单因素随机模型来预测意大利游客住宿设施的过夜住宿情况。这项研究的贡献是双重的:在预测准确性方面和在简洁方面(从数据和建模复杂性的角度来看), 特别是当时间序列中的规则模式被打乱时。我们表明, cir#不仅比考虑的基线模型表现更好, 而且比文献中报告的其他模型或方法具有更低的误差。

当大量搜索强度指标被作为旅游需求指标时, 传统的旅游需求预测模型将面临挑战。此外, 鉴于准确预测的重要性, 许多研究提出了新的混合模型或使用各种方法的组合。因此, 尽管采用更复杂的方法有明显的好处, 但风险在于处理难使用的模型。为了证明这种方法能有效地扩展到旅游业, 使用RMSE、MAE、MAPE或AvgReIMSE等标准指标来测试cir#的准确性。

cir#模型明显比文献中发现的其他模型简单, 并且不依赖于黑盒技术, 例如在神经网络或基于数据科学的模型中使用的技术。所进行的分析表明, cir#模型在误差的统计显著性方面优于其他参考预测。

这个模型作为Holt-Winters模型的一个拟议模型, 特别是在处理不规则数据时。

即使与文献中的其他模型相比, 所提出的模型也显示出优越性, 并且在数据模式中断时对旅游利益相关者做出决策特别有用。

创新之处在于所提出的模型是Holt-Winters模型的有效替代方案, 特别是当数据不规律时。此外, 与文献中的许多现有模型相比, cir#模型明显更简单、更透明, 避免了神经网络和基于数据科学的模型的“黑箱”性质。

Normalmente, la demanda turística tiende a seguir tendencias regulares, como temporadas altas y bajas a nivel trimestral/mensual y fines de semana y festivos a nivel diario. El conjunto de datos consiste en las pernoctaciones en Italia en establecimientos de alojamiento turístico recogidas mensualmente por Eurostat antes y durante la pandemia de COVID-19, rompiendo los patrones regulares.

El presente estudio pretende predecir las pernoctaciones en Italia en establecimientos de alojamiento turístico mediante un modelo estocástico no lineal de un solo factor denominado CIR#. La contribución de este estudio es doble: en términos de precisión de la predicción y en términos de parsimonia (tanto desde la perspectiva de los datos como de la complejidad de la modelización), especialmente cuando un patrón regular en la serie temporal se ve interrumpido. Demostramos que el CIR# no sólo aplica mejor que los modelos de referencia considerados, sino que también tiene un error mucho menor que otros modelos o enfoques adicionales de los que se informa en la literatura.

Los modelos tradicionales de previsión de la demanda turística pueden enfrentarse a desafíos cuando se adoptan cantidades masivas de índices de intensidad de búsqueda como indicadores de la demanda turística. Además, dada la importancia de unas previsiones precisas, muchos estudios han propuesto modelos híbridos novedosos o han utilizado diversas combinaciones de métodos. Así pues, aunque la adopción de enfoques más complejos presenta ventajas evidentes, el riesgo es el de enfrentarse a modelos poco manejables. Para demostrar cómo este enfoque puede extenderse de forma fructífera al turismo, se comprueba la precisión del CIR# utilizando métricas estándar como RMSE, MAE, MAPE o AvgReIMSE.

El modelo CIR# es notablemente más sencillo que otros modelos encontrados en la literatura y no se basa en técnicas de caja negra como las utilizadas en los modelos basados en redes neuronales o en la ciencia de datos. El análisis realizado sugiere que el modelo CIR# supera a otras predicciones de referencia en términos de significación estadística del error.

El modelo propuesto destaca por ser una opción viable al modelo Holt-Winters, sobre todo cuando se trata de datos irregulares.

El modelo propuesto ha demostrado su superioridad incluso cuando se compara con otros modelos de la bibliografía, y puede ser especialmente útil para los agentes del sector turístico a la hora de tomar decisiones cuando se producen alteraciones en los patrones de datos.

La novedad radica en que el modelo propuesto es una alternativa válida al Holt-Winters especialmente cuando los datos no son regulares. Además, en comparación con muchos modelos existentes en la literatura, el modelo CIR# es notablemente más sencillo y transparente, evitando la naturaleza de “caja negra” de los modelos basados en redes neuronales y en ciencia de datos.

This paper aims to present the design of a micro-electro-mechanical system (MEMS)-based three-dimensional combined vector hydrophone tailored for unmanned underwater vehicles (UUVs). The proposed design addresses the left-right ambiguity inherent in conventional MEMS hydrophones and enhances acoustic sensing capabilities to support improved UUV performance in underwater environments.

A novel MEMS-based three-dimensional vector hydrophone (M3DH) is proposed, integrating a highly sensitive MEMS chip with a piezoelectric ceramic-based scalar channel. A theoretical model of the hydrophone’s packaging was developed, and its acoustic performance was analyzed through COMSOL Multiphysics 6.2 simulations. Experimental validation of the hydrophone’s sensitivity and directional characteristics was conducted in a standing wave tank.

The MEMS-based three-dimensional combined hydrophone (M3DH) achieved a triaxial vector channel sensitivity of −175.6 dB at 800 Hz (re 1 V/µPa) and a scalar channel sensitivity of −186.3 dB (0 dB = 1 V/µPa). In addition, at 500 Hz, the vector channel exhibited a distinct “8”-shaped directivity pattern, whereas the scalar channel maintained a circular omnidirectional response. The hydrophone demonstrated excellent acoustic performance in three-dimensional space, effectively providing comprehensive acoustic information for small underwater platforms.

This research addresses the left-right ambiguity issue in MEMS hydrophones by presenting an MEMS-based three-dimensional combined hydrophone designed for integration into UUVs, offering an innovative solution to enhance underwater acoustic sensing capabilities in small platforms.

This study aims to design a small-size conformable flexible micro-electro-mechanical system (MEMS) vector hydrophone to meet the miniaturization requirements of unmanned underwater vehicle.

The cilia receive the acoustic signal to oscillate to cause changes in the stress on the beam, which in turn causes changes in the piezoresistive resistance on the beam, and changes in the resistance cause changes in the output voltage.

The results show that the flexible hydrophone in the paper has a sensitivity of −182 dB@1 kHz (re 1V/µPa) at 1 Pa sound pressure, can detect low-frequency hydroacoustic signals from 20 to 550 Hz and has good spatial directivity, and the flexible substrate permits the hydrophone to realize bending deformation, which can be well attached to the surface of the object.

In this study, a finite element simulation model of the hydrophone microstructure is constructed and its performance is verified by simulation. The success rate of the proposed MEMS transfer process is as high as 94%, and the prepared piezoresistors exhibit excellent resistance characteristics and high consistency. These results provide innovative ideas to enhance the performance and stability and achieve miniaturization of hydrophones.