bluuebunny/crossref_metadata_2025_split huggingface dataset:
A numerical simulation method for ultrasonic transmission in cancellous bone based on a four-parameter random growth method
Authors: Chou Xingxing , Ren Wei , Han Yueqi , Wang Wei , Wang Jin 
Published: October 2024

Abstract
Quantitative ultrasound (QUS) has been widely used in non-destructive evaluation of bone health in research and clinical practice. To make a more accurate bone evaluation, the transmission characteristics of ultrasound in the bone need to be understood in detail. In the two-dimensional finite element model, cancellous bone is usually simulated by a non-porous structure solid or by approximating bone trabeculae as ellipses, which is different from real bone. However, although the error of the model constructed by bone CT images is small, it needs to be based on real bone samples, and the samples are limited. Therefore, a modeling method of cancellous bone based on four-parameter random growth method was proposed in this paper, and on this basis, numerical simulation of ultrasonic transmission was carried out. Firstly, based on the four-parameter random growth method, the aggregation algorithm is used to concentrate discrete pixels and smooth the edge of pores. Meanwhile, the built-in algorithm ensures the same porosity before and after processing to reduce the discrete pore structure. Secondly, based on COMSOL to establish the simulation model of ultrasonic propagation in cancellous bone, we analyzed the change of acoustic field distribution, discussed the correlation between the porosity of cancellous bone and backscattering coefficient (BSC) based on the ultrasonic backscattering method, and compared the experimental results of CT scan images of bone samples. The experimental results show that the cancellous bone modeling method in this paper has the same conclusion as the method based on CT images, which verifies the feasibility of this method. This method can generate a geometric model of the cancellous bone microstructure with specified porosity and different bone trabecular distribution, which is similar to the real bone structure, and can be directly imported into the finite element software to facilitate the study of bone microstructure related problems. It provides a more convenient method to study the mechanism of ultrasonic propagation in cancellous bone and has important significance in solving the inverse problem of recovering effective bone parameters from the received ultrasonic signals.
Electromagnetic compatibility study of acoustoelectric logging detector
Authors: Lu Junqiang , Qin Zhenyu , Men Baiyong , Chen Hongzhi 
Published: October 2024

Abstract
The acoustoelectric effect logging detector can achieve downhole acoustoelectric effect measurement, but the excitation of the acoustic transducer can generate significant electromagnetic interference (EMI) signals, it is difficult to effectively measure weak converted signals of acoustoelectric effect underground. The EMI problem of acoustoelectric effect logging detectors can be solved by studying EMI characteristics. Based on the analysis of the structure, measurement function, and measured interference signals of the receiving electrodes of the detector, the EMI sources, coupling paths, and sensitive components in the detector were studied. The basic process of EMI generated by high-voltage pulse excitation source of acoustic transducer is analysed, and two electromagnetic coupling interference analysis models for detectors, namely conductive coupling and borehole electromagnetic coupling, are established. This study can provide a fundamental method and reference for electromagnetic compatibility analysis of acoustoelectric effect logging detectors.
An application and discussion of wide-band signal processing technology in the primary calibration for hydrophones
Authors: Jia Guanghui , Chen Yi , Wang Shiquan , Zhang Dong 
Published: October 2024

Abstract
Wide-band signals are potentially available in the measurement of transducers, which can obtain wide-band responses of electroacoustic parameters of them directly. The hydrophone of B&K 8103 is calibrated in a Φ 1.2 m×1.8 m small water vessel by wide-band signal processing technology in the frequency range of 3.15 kHz to 100 kHz. A thin pellicle co-vibrates with acoustic particle in the free-field, and its oscillation can be detected by a laser Doppler vibrometer, which can estimate the acoustic pressure distribution. The transfer function model is established in a small water vessel, and the wide-band frequency responses of the transfer impedance of transducer and hydrophone as well as the transfer impedance of transducer and pellicle in the small water vessel are calculated respectively. The wide-band signal processing technology of frequency domain filter process are used, which can isolate the reflecting acoustic wave from the boundaries and the surface of the water vessel. To verify the accuracy of the wide-band calibration measurements, the calibration results are compared with that using tone-burst signals in the water vessel and using free-field reciprocity method in the large water tank. The comparisons show that their calibration results are in a good agreement with each other, and the maximum deviation is 0.7 dB. All these demonstrate that the wide-band signal processing technology described is accurate and stable.
Defect modes in imperfect periodic structures
Authors: Li Yilun , Cottereau Régis , Tie Bing 
Published: October 2024

Abstract
Lack of periodicity in engineering structures can arise because of imperfections in the production process or a particular purpose to produce desirable physical effects. This contribution presents a series of numerical simulations that quantitatively characterize the influence of defects on the dispersion relation and associated eigenmodes of imperfect periodic structures. Local defects are introduced periodically on a scale larger than the size of the unit cell of the non-disturbed periodic structure. The observations reveal that these defects can give rise to non-propagating modes at frequencies situated within the bandgaps of the periodic structure. The eigenfrequency of such a defect mode varies monotonically with the amplitude of the defects, and its deformations are located in and around the disturbed cell. Additionally, a finite element analysis is conducted to study the existence of the observed defect modes when the imperfect periodic media are bounded.
A New Method for Temperature Dependent COM Parameters Extraction and Its Application to Simulation of SAW Devices
Authors: Li Lingqi , Zhang Qiaozhen , Li Baichuan , Yang Yang , Tian Yahui , Li Honglang 
Published: October 2024

Abstract
Surface Acoustic Wave (SAW) filters are widely used in mobile communication systems due to their superior performance. Yet, application scenarios for these SAW devices can be limited by temperature stability. The coupling of modes (COM) model is proved to be an efficient modeling approach to design SAW devices at present. However, temperature dependent COM parameter extraction is still absent. This work proposed a new method combining COM model with quasi-3D periodic finite element method (FEM) model coupled with thermal field, which can accurately and rapidly simulate and optimize the temperature stability of SAW devices. The COM parameters extraction method used in this study mainly depends on harmonic admittance. For a given temperature (T), the thermal effect can be computed by incorporating the linear thermal expansion coefficients and temperature coefficients of elasticity into the model. For validation, the admittance responses of a finite-length SAW resonator and the S-parameter of a double-mode SAW (DMS) for 42º YX-LiTaO3 piezoelectric substrate are calculated by using P-Matrix with the extracted COM parameters. For validation, the admittance responses of a SAW resonator on 42º YX-LiTaO3 under different temperature conditions is calculated. Furthermore, the temperature behaviors of a DMS filter on 42º YX-LiTaO3 are also analyzed based on the proposed method. Accurate predictions of the temperature behaviors for both resonator and filter were achieved and discussed. This investigation provides guidelines for design of high-performance SAW devices with good temperature stability.
High Order Rayleigh-Type SAW Devices for Advanced 5G Front-ends with Improved Performance
Authors: Liu Luyao , Zhang Qiaozhen , Sun Hao , Yang Yang , Zhao Xiangyong 
Published: October 2024

Abstract
This paper presents a piezoelectric layered structure composed of a rotated LiNbO3 thin film combined with a diamond film for improved comprehensive performance SAW devices. Theoretical analysis of SAW resonator on the proposed structure is performed to calculate its SAW characteristics including electromechanical coupling coefficient (K2
), frequency (f), and quality factor (Q). It is found that a high-order Rayleigh mode is effectively excited and exhibits not only high frequency but also large K2
and high Q. The influences of the Euler angles, layer stack configurations of LiNbO3, and the electrode on the SAW properties are investigated systematically to optimize the device performance of the proposed structure. The results show the resonator can operate at frequency of 6.6 GHz with a large K2
of 13.58% and high Q of 2134, which makes the proposed layered structure a good potential solution for high-performance wideband SAW filters operating over 5 GHz.
Ultrasonic imaging assisted by Phase Coherence and Synthetic Aperture Focusing Technology
Authors: Li Zhengdong , Jiang Xueping , Zhang Meng , Zhu Tiaoyin 
Published: October 2024

Abstract
B-Scan is widely applied in ultrasonic testing. However, the imaging quality is affected by noise and acoustic diffusion. This paper proposed a method combining synthetic aperture focusing technology (SAFT) and phase-coherent imaging (PCI) technology to improve image quality. In SAFT, a transducer at different positions is utilized to form an array, which represents a large aperture transducer to obtain high resolution. By constructing a weight matrix based on the phase of signals, PCI is used to modify the SAFT imaging, thus the signal-to-noise ratio is significantly improved.
In this paper, finite element models were built and the corresponding simulations were carried out first. Then, the Hilbert transform was implemented to all the simulated echoes with artificial white noise. The amplitudes and phases were extracted, whilst the amplitudes were used to construct SAFT images. The phases were used to construct a coherent weight matrix. Finally, images of SAFT modified by phase-coherent matrix were reconstructed and compared with SAFT images and B-scan. It verifies that the SAFT-PCI method can improve the image effectively.
Enhancing the performance of a resonance-based sensor network for soft robots using binary excitation
Authors: Chubb Kevin , Berry Damon , Burke Ted 
Published: October 2024

Abstract
Embedded, flexible, multi-sensor sensing networks have shown the potential to provide soft robots with reliable feedback while navigating unstructured environments. Time delay associated with extracting information from these sensing networks and the complexity of constructing them are significant obstacles to their development. This paper presents a novel enhancement to an existing class of embedded sensor network with the potential to overcome these challenges. In its original version, this sensor network extracts information from multiple reactive sensors on a two-wire electrical circuit simultaneously. This paper proposes to change the excitation signal applied to this sensor network to a binary signal. This change offers two key advantages: it provides the ability to employ small, inexpensive microcontrollers and results in a faster data extraction process. The potential of this enhanced system is demonstrated here with a proof of concept implementation. The self-inductance of all inductance-based sensors within this proof of concept sensor network can be measured at a rate of over 5000 times per second with an average measurement error of less than 2%.
Gallic acid functionalized silk fibroin/gelatin composite wound dressing for enhanced wound healing
Authors: Li Ping , Tan Ding , Su Aihua , Xiong Xingliang , Gao Shasha , Zhang Haiyang , Yang Jiaqi , Jian Jie , Zheng Jun , Jiang Qifeng 
Published: October 2024

Abstract
As the incidence of chronic wounds increases, the requirements for wound dressings are rising. The specific aim of this study is to propose a novel gallic acid (GA) functionalized silk fibroin (SF) and gelatin (Gel) composite wound dressing in which GA is used as an antibacterial and wound healing substance. Via electrospinning, SF, Gel, and GA mixed solutions could be conveniently fabricated into a composite nanofiber mat (SF-Gel-GA), consisting of uniform fibers with an average diameter around 134.57 ± 84 nm. The internal mesh structure of SF-Gel-GA provides sufficient drug loading capacity, proper moisture permeability, and proper degradation rate. SF-Gel-GA presents excellent biocompatibility. NIH-3T3 fibroblast cells could adhere and spread stably on the SF-Gel-GA surface with slightly promoted proliferation. In the presence of SF-Gel-GA, the growth of both Gram-positive and Gram-negative bacteria, including Staphylococcus aureus and Pseudomonas aeruginosa, is significantly inhibited in both plate and suspension cultures. A cutaneous excisional mouse wound model proves the efficient ability of SF-Gel-GA to promote wound healing. Compared with pure SF dressing and commercial Tegaderm Hydrocolloid3M dressing, the wound closure rate with SF-Gel-GA treatment is significantly improved. The histological assessments further demonstrate SF-Gel-GA could facilitate collagen deposition, neovascularization, and epithelialization at wound sites to promote wound healing. In conclusion, a novel SF-Gel-GA composite wound dressing with efficient wound healing activities have been developed for chronic wound treatment with broad healing potential.
Claiming Madness
Authors: Rembis Michael 
Published: October 2024

Abstract
Many former asylum inmates who entered public conversations in the decades between 1830 and 1890—years of significant growth of the asylum system—worked to establish themselves as trustworthy informants on the ill-defined but widely discussed topic of madness. The popular belief that madness eluded easy definition opened a critical cultural space from which mad writers could offer their own thoughts about the nature and causes of it. Whether or not they spoke directly to physicians and legislators, former inmates who shared their stories influenced popular, legal, and medical conceptualizations of madness at a time when most Americans seemed to be groping toward a more modern understanding of the many different forms of what they generally referred to as “insanity.”
Reforming the System
Authors: Rembis Michael 
Published: October 2024

Abstract
From the 1830s through the 1890s, dozens, if not hundreds, of former inmates became asylum reformers. They learned through experience and from friends and allies how to organize and how to enact legislative change. Former inmates did not always succeed; they were not always believed by legislators, and they continued to face fierce opposition from some physicians. Yet they persisted in their efforts to share their stories and rewrite what they considered deficient and problematic public policy. Levels of engagement and success varied among former inmates, but the collective force for change generated by their actions cannot be denied. Former inmates turned reformers played a crucial role in bringing about changes in the asylum system that persisted well after their individual reform work ended.
Multi-view learning framework for predicting unknown types of cancer markers via directed graph neural networks fitting regulatory networks
Authors: Wang Xin-Fei , Huang Lan , Wang Yan , Guan Ren-Chu , You Zhu-Hong , Sheng Nan , Xie Xu-Ping , Hou Wen-Ju 
Published: October 2024

Abstract
The discovery of diagnostic and therapeutic biomarkers for complex diseases, especially cancer, has always been a central and long-term challenge in molecular association prediction research, offering promising avenues for advancing the understanding of complex diseases. To this end, researchers have developed various network-based prediction techniques targeting specific molecular associations. However, limitations imposed by reductionism and network representation learning have led existing studies to narrowly focus on high prediction efficiency within single association type, thereby glossing over the discovery of unknown types of associations. Additionally, effectively utilizing network structure to fit the interaction properties of regulatory networks and combining specific case biomarker validations remains an unresolved issue in cancer biomarker prediction methods. To overcome these limitations, we propose a multi-view learning framework, CeRVE, based on directed graph neural networks (DGNN) for predicting unknown type cancer biomarkers. CeRVE effectively extracts and integrates subgraph information through multi-view feature learning. Subsequently, CeRVE utilizes DGNN to simulate the entire regulatory network, propagating node attribute features and extracting various interaction relationships between molecules. Furthermore, CeRVE constructed a comparative analysis matrix of three cancers and adjacent normal tissues through The Cancer Genome Atlas and identified multiple types of potential cancer biomarkers through differential expression analysis of mRNA, microRNA, and long noncoding RNA. Computational testing of multiple types of biomarkers for 72 cancers demonstrates that CeRVE exhibits superior performance in cancer biomarker prediction, providing a powerful tool and insightful approach for AI-assisted disease biomarker discovery.
2D Echocardiographic aortic root dimensions and longitudinal analysis with artificial intelligence using an open dataset from a UK-wide collaborative
Authors: Ng T , Hannan S H , Julea M , Singh A , Zetani M , Vimalesvaran K , Tawil M , Rana B , Demetrescu C , Ghosh A , Sehmi J , Bhattacharyya S , Stowell C , Shun-Shin M J , Francis D P 
Published: October 2024

Abstract

Background
Surveillance of aortic dimensions requires reproducible measurements, and knowledge of the rate of progression in those with dilatation.

Purpose
To develop an open machine-learning method for measuring the aortic root and proximal ascending aorta on echocardiograms, validate it through a multi-expert panel from the Unity UK Echocardiography AI Collaborative, and applying the AI to derive the rate of progression in historical databases.

Methods
The neural network was trained on 1478 parasternal long-axis images. Each image was labelled with key points for the aortic annulus, sinus and sinotubular junction, and proximal ascending aorta dimensions. Labels accommodated inner-to-inner and leading-to-leading conventions.
For validation, the end-diastolic and mid-systolic images were identified (accommodating different guidelines recommendations) from 100 studies, and 10 expert echocardiographers made the aortic measurements. The consensus of experts defined the reference standard, and the variation between individual experts defined the acceptable variation for the AI.
The AI was then applied to 724 echocardiograms of 102 patients under surveillance spanning 12 years (ranging from 4 to 17 scans per patient) without intervention. Training data labels and networks are made freely available on our project website.

Results
The median absolute deviations between the AI and the expert consensus ranged from 0.06cm to 0.17cm across the 16 measurements. For the individual expert opinions this was from 0.08cm to 0.19cm. For 7/16 measurements, there was no statistically significant difference between the AI deviation and the individual-expert deviation. The AI’s confidence level was a useful indicator of the reliability of the AI measure. For the top 9 deciles of AI confidence level, the AI measurements had significantly smaller deviations than the individual experts.
The rates of progression averaged across the three aortic measurements was 2.0 mm/decade (95% CI 1.0 to 3.0; p =0.007).

Conclusion
Expert consensus can be used to both define the reference standard and also the range of acceptable deviation from consensus. Overall, the AI performs similarly to experts and more importantly, provides an automated estimate of confidence. The validated AI is consistent over time, and when applied retrospectively to patients with dilated aortic roots, found the rate of progression was more rapid than in previously reported healthy patients. This approach could be applied generally in developing medical AI to not only make reproducible measurements but to automate large scale longitudinal studies with little input, and ultimately serves as a useful research and clinical tool.Figure: AI(red) vs Expert (blue)Table: AIDeviations from Consensus
Aortic integral distensibility based on the auto-segmented dynamic motion of the aortic wall
Authors: Choi J H , Lee C A , Paeng D G 
Published: October 2024

Abstract

Background
Aortic stiffness is important in cardiovascular diseases and predicting outcomes. Echocardiography is a widely used noninvasive imaging modality for assessing aortic stiffness, but its accuracy can be limited by the low spatial resolution of ultrasound-based images and the subjectivity of manual measurements of aortic dimensions. Automated segmentation analysis can provide a more accurate and objective measure.

Objective
An automated algorithm and software have been developed for segmenting the aortic wall. A new measurement technique called "Aortic Integral Distensibility (AID)" has been formulated using this framework. This method overcomes limitations of traditional method focusing solely on the two positions of Aortic Distensibility (AD).

Method
In this particular investigation, 112 participants were subjected to echocardiography in order to quantify the dynamics of the aortic wall. An automated algorithm was devised to delineate the aortic wall by utilizing an M-mode echocardiography scan. The statistical analysis encompassed the measurement of AD and AID before and after the age of 65 group. This analysis was conducted considering various risk factors, including age, gender, weight, BMI, smoking, and blood pressure. Additionally, clinical parameters, specifically AIx @75 (Augmentation Index) and Framingham Risk Score (FRS), were evaluated as well. Inter-rater reliability was conducted between the traditional AD and the newly implemented AID.

Results
The results indicate that the group under 65 had more distensibility than the group over 65, and AID measurements were slightly higher than AD measurements. SBP showed a strong correlation with AID, rather than AD. AIx @75 and FRS had a negative relationship with distensibility. In the 65 years or older group, there was a significant negative correlation observed between AIx @75 and AID (r = -0.4, p = 0.012). Furthermore, a strong correlation was also observed between FRS and AID (r = -0.53, p = 0.002). Bland-Altman analysis demonstrated that the automated methodology had better reproducibility and less variability in distensibility measurements than the manual methodology.

Conclusion
The study suggests that AID could be valuable for assessing aortic stiffness. AID could help clinicians diagnose and manage cardiovascular diseases more accurately. The automatic approach provides reliable measurements for aortic distensibility and strain, which has clinical implications.Schematic Chart of the Study Process