bluuebunny/crossref_metadata_2025 huggingface dataset:
Distributed acoustic sensing signal event recognition and localization based on improved YOLOv7
Authors: Zhang Hongyu , Wang Chang , Zhang Faxiang , Jiang Shaodong , Sun Zhihui , Wang Xiaodong , Duan Zhenhui , Gao Fengxia , Liu Zhaoying
Published: October 2024

The distributed acoustic sensing (DAS) system based on phase-sensitive optical time domain reflection ( Φ-OTDR) technology is widely used in pipeline safety monitoring, perimeter security, structure monitoring, etc. Accurate localization and recognition of multi-scene events over long distances has always been a challenge. This paper proposes an improved YOLOv7 algorithm for multi-event real-time detection of DAS system. The algorithm employs space-to-depth Conv(SPD-Conv) to replace the strided convolutions and pooling operations in YOLOv7, reducing fine-grained information loss and learning of inefficient feature representations. In addition, the Convolutional Block Attention Module (CBAM) is introduced in YOLOv7 to improve the model performance. We collected spatial–temporal signal data for six types of pipeline safety events, and passed them into the improved YOLOv7 algorithm in the form of data matrixes for training and evaluation. Experiments have shown that the proposed method achieves an mAP@.5 (mean Average Precision) of 99.7% for the identification of six pipeline safety event types. Positioning loss reduced to 0.2%, and detection speed can reach 70 frames per second(FPS). Our scheme achieves significant improvements in localization and classification accuracy compared to Faster R-CNN, etc. The event recognition localization method proposed in this paper has the advantage of fast speed and high accuracy.
Research on Iron Gallium Dipole Logging Transducers
Authors: Zhao Jiaheng , Dai Yuyu , Zhou Yinqiu , Zhu Chenhui
Published: October 2024

Orthogonal dipole acoustic logging is an indispensable means to study the mechanical properties of formation rocks, estimate formation porosity and permeability, and carry out out-of-hole remote detection, and the broadband high-power dipole acoustic logging transducer is one of its core components, which is an urgent and unsolved international problem in actual logging. Therefore, it is of great application background and important academic significance to study the new dipole acoustic logging transducer and overcome the related scientific problems. On the basis of full investigation and study of the characteristics of iron gallium materials, this project first designed the iron gallium bending beam oscillator to verify the feasibility of iron gallium bending vibration, and then designed the iron gallium dipole acoustic logging transducer, optimized the driving magnetic circuit, simulated the driving performance of the transducer, and preliminarily verified the feasibility of the design.
Testing of battery separators: transducers and methods for air-coupled ultrasonic sensing.
Authors: Salso Patricia , Genovés Vicente , Álvarez-Arenas Tomás Gómez
Published: October 2024

Battery separator me3mbranes are thin polymeric microporous films placed between battery electrodes. They are a key component that strongly affects both battery performance and security and controlling its main properties is critical for the industry. In particular, the manufacturing process demands tests that allow checking both the mechanical integrity (porosity, thickness, pore size, etc.) of the materials and the consistency of these properties during the construction of the batteries. The use of an air-coupled ultrasonic system is proposed in this work. It is expected that this will make possible the non-destructive and quick testing of these materials, in order to evaluate thickness, stiffness, pore distribution and pore size of the separator. By means of three pairs of transducers, the modulus and phase of the transmission coefficient was measured from 0.35 to 1.4 MHz in different materials. The measurements show a clear modification of the film response produced by the presence of porosity. This suggests that the transmission of ultrasonic waves in battery separators using air-coupled ultrasound may have two contributions: one corresponds to the propagation though the solid part, the other corresponds to propagation in the pores. The former allows to determine properties like film thickness and elastic constants, while the latter allows to determine porosity and pore size and pore tortuosity. This work set the basis for the development of a quality test for the in-line inspection of these materials during their fabrication. The observed ultrasonic response in microporous separators suggest the possibility to use low frequency air-coupled transducers with limited sensitivity, where the use of MEM transducers at industrial scale can be advantageous.
High frequency venting of MEMS ultrasonic transducers and sensors: materials solutions.
Authors: Álvarez-Arenas T.E.G. , Salso P. , Genovés V.
Published: October 2024

This paper introduces the concept of ultrasonic venting. Similar to acoustic vents, ultrasonic vents refer to the aperture in air-coupled MEMS ultrasonic transducers (either PMUT or CMUT) intended to allow the equalization of internal and external pressures, the transfer of heat and the pass of ultrasonic waves, while impeding the penetration of fluids or particles that can affect the transducer membrane. To that end, vents are covered with a porous membrane whose properties are tuned to meet the afore mentioned requirements. The main difficulty in ultrasonic venting, compared with acoustic venting, is that the required “transparency” to ultrasonic waves is much more difficult to achieve. This involves two main problems as both transmission loss and frequency distortion are much larger at ultrasonic frequencies than in the audio range. The objectives of this paper are: to measure the response of acoustic venting materials in the ultrasonic frequency range, to determine the usability of these materials in ultrasonic vents, and to extract useful information for the design of efficient ultrasonic venting materials. Transmission coefficient spectra of different acoustic venting materials is measured in the frequency range 0.2 –2.7 MHz. The origin of the ultrasonic losses and frequency distortion are analysed as well as the role of mode conversion, internal interferences, modes interference, etc. Results reveal that none of the acoustic venting materials analysed can be used in ultrasonic venting applications, but the obtained knowledge about the response of these materials in the ultrasonic frequency range permit to advance in the selection of successful candidate materials for this application.
A numerical study on the relationship between local defect resonance and sub-harmonic resonance for closed cracks
Authors: Maruyama Taizo , Tanihira Tomoki , Nakahata Kazuyuki
Published: October 2024

The sub-harmonic resonance in closed cracks is caused by resonant properties of the system and the contact of crack surfaces. Local defect resonance is considered a potential resonant phenomenon near cracks. This study compares local resonance and sub-harmonic resonance in a surface-breaking crack using numerical simulations. The authors previously simulated nonlinear sub-harmonic resonance using the harmonic balance-boundary element method. The investigation of local defect resonance utilizes both the boundary element method and the Sakurai-Sugiura method. The numerical results indicate a strong relation between the vibration fields of sub-harmonic frequency components and local defect resonance.
Ultrasonic motion scanning method based on flexible microchannel array
Authors: Wang K. , Song Y. , Kang Y.
Published: October 2024

Immersion ultrasound scanning faces limitations in specific detection scenarios, such as those involving moving workpieces or highly intricate surfaces. This issue is particularly pronounced when workpieces exhibit relative motion, resulting in significant signal decay. To address this challenge, an ultrasonic motion scanning method based on a flexible microchannel array is proposed in this paper. This innovative method utilizes a flexible microchannel array as the coupling medium. Initially, the principle of water column formation within the arrays is examined. Subsequently, various shapes and sizes of arrays are meticulously analyzed. Finally, the behavior of the detection signal of the probe in motion is investigated. It is demonstrated that stable detection results can be achieved even while the ultrasound probe is in motion.
Novel Surface Acoustic Wave Strain Sensor with Enhanced High-Temperature Performance and Resistance to Aging
Authors: Zhang Jikai , Mu Danyu , Zhang Zichao , Jin Hao , Chen Jinkai , Xuan Weipeng , Dong Shurong , Luo Jikui
Published: October 2024

Surface acoustic wave (SAW) sensors based on Langasite (La3Ga5SiO14, LGS) have emerged as promising candidates for high-temperature strain measurement in passive wireless systems. However, limitations of strain transfer at temperatures above 800°C have hindered the repeatability of sensors due to temperature-induced effects. For instance, the aging of conventional high-temperature adhesives at elevated temperatures restricts the strain transfer between the measured object and the sensor. Moreover, materials like Inconel-600 exhibit a coefficient of thermal expansion significantly larger than the LGS, leading to thermal strains caused by thermal expansion mismatch beyond the maximum range of existing SAW strain sensors. Such factors increase the likelihood of sensor damage during a test. In this paper, we present a novel SAW sensor utilizing an ultra-thin LGS substrate encapsulated within a ceramic coating, which transfers strain by exerting pressure on both sides of the sensor. The strain sensor is mounted on an equal-strain beam inside a high-temperature furnace. The ceramic coating is not tightly bonded to the sensor, thereby mitigating the thermal expansion mismatch between the sensor and the beam at high temperatures. Furthermore, the ceramic coating can withstand large strain caused by thermal expansion while maintaining pressure on the sensor. This innovative SAW sensor enables repeat strain tests up to 800°C, including both calibration and formal tests. The measured strain exhibits an error of less than 5% compared to a standard strain gauge, demonstrating the sensor’s enhanced performance and reliability.
A distributed parameter model of the cavity-loaded piston transducer
Authors: Liu Wenzhao , Mo Xiping , Chai Yong , Zhang Xiuzhen , Pan Rui
Published: October 2024

Adding a cylindrical liquid cavity at the radiation surface of a piston transducer can introduce the liquid cavity resonance into the vibration system, thereby extending the operating bandwidth of the transducer. However, recent studies have shown that effective coupling of the liquid cavity resonance with the self-resonance of the piston transducer presents difficulties, resulting in significant fluctuations in the transmitting voltage response (TVR) within the operating frequency band. The physical mechanism behind this phenomenon remains unclear to date. In this paper, a distributed parameter model (DPM) for the cavity-loaded piston transducer is proposed. The admittance, amplitude and phase of the vibration velocity and TVR of the transducer are calculated using both DPM and finite element method (FEM). The results from DPM and FEM exhibit good agreement, indicating that the DPM can accurately describe the vibration characteristics of the transducer. Finally, two physical analogies of the transducer are proposed and explanations for the large fluctuations in TVR are given. This study reveals the modal coupling mechanism of the cavity-loaded piston transducer, and provides theoretical support for the analysis and designs of such transducers.
A Miniature PMUT Array for Medical Applications
Authors: Chen Jingqi , Liu Hanzhang , Zhang Xiaoduo , Li Hui , Yin Feng
Published: October 2024

Wearable continuous monitoring technology and internal and cerebrovascular imaging are the frontier hot area of current scientific research, which are of great significance to improving human life and health. Ultrasonic imaging can obtain information such as deep tissue structure by transmitting ultrasonic waves into the tissue and detecting echo signals, and ultrasonic imaging technology has the advantages of high imaging depth, high resolution, high safety, fast and convenient, etc. It is one of the important technologies in the medical field such as wearable continuous monitoring technology and internal cardiovascular and cerebrovascular imaging. But miniaturization and low power consumption are necessary conditions for the success of such medical applications. Therefore, the ultrasonic imaging technology using a miniature ultrasonic probe is one of the most promising imaging technologies for this type of medical application. Aiming at the common technical problems of traditional ultrasonic transducers such as large volume, narrow bandwidth, high power consumption, difficulty in preparing two-dimensional arrays, and difficulty in integrating with ICs. In this paper, the electromechanical-acoustic multi-field coupling mechanism and array structure design technology of MEMS high-performance PMUT ultrasonic transducer elements are first studied, and a CMOS-compatible miniature PMUT high-performance array ultrasonic device suitable for this type of medical application is developed. The simulation results of the transducer are given. The measurement of various physical parameters of the transducer sample and the results of its application in the ultrasonic imaging system show that the miniature PMUT linear array ultrasonic sensor we designed is a kind of high performance ultrasonic array sensors that can be widely used in wearable continuous monitoring technology and internal cardiovascular and cerebrovascular imaging.
Design of an Anti-interference long-range acoustic Communication System Based on optimal length segment coding
Authors: Zhang Luwei , Wang Jiawei , Ke Qihui , Zhou Xuanyi , Wang Xiao , Tao Jianfeng
Published: October 2024

With the increased demand for unmanned vehicles in marine development, the development of underwater acoustic communication technology has received much attention. One of the key technologies in the research of long-range underwater acoustic communication technology is the use of underwater acoustic channels for efficient and stable data transmission. The harsh environment of the underwater acoustic channel has a significant impact on the rate and quality of underwater acoustic communication, making it a challenging research direction to achieve high-speed and reliable telecommunication systems underwater. In this paper, a high-speed remote command-based communication system is investigated, and a long-range acoustic communication system with good adaptability to sudden and continuous interference is designed based on a remote unmanned platform. A method for encoding the communication message in segments of optimal length is proposed in this paper. This coding method can enhance the anti-sudden interference capability of the communication system which has a certain degree of communication confidentiality, and the performance of this anti-interference communication system is verified by laboratory tests and field tests. The verification results show that the proposed telecommunication system based on optimal length segment coding has better performance in anti-sudden interference and continuous interference, which can make the communication system performance more stable and increase the success rate of command-based communication significantly.
Surface acoustic waves in porous soils with two-layered infiltration
Authors: Fomenko Sergey I. , Jana Raghavendra B.
Published: October 2024

Two stage mathematical and computer models based on the finite element solution of Richards’ equation for water infiltration in two-layered fluid-saturated soil and modal analysis using a semi-analytical approach for vertically stratified soils are presented and briefly described. Dispersion curves of surface waves in the layered poroelastic half-space are computed and studied. The features of porous water infiltration effect on the characteristics of surface elastic waves are discussed.
Sound source localization based on microphone array mounted on unmanned aerial vehicles
Authors: Wang Hongzhao , Guo Xinhua
Published: October 2024

Microphone array installed on unmanned aerial vehicles (UAV) can be used for acoustic detection in scenes, such as detecting noise sources in factories or monitoring corona in power grids. However, using acoustic sensors on UAV has great challenges. The motor rotation of UAV and the non-stationary noise generated by propeller make it difficult for microphone array to obtain useful information for sound source localization. In order to reduce self-noise, an improved least mean square (LMS) adaptive filtering algorithm is proposed. Combining filtering algorithm and multiple signal classification (MUSIC) algorithm to locate the sound source, the noise spectrum characteristics of UAV in outdoor free flight mode are analyzed. The microphone array is used to collect data and realize sound source localization in low Signal-to-Noise Ratio (SNR) environment. The simulation and experimental results show that the algorithm improves the robustness of the sound source localization algorithm in low SNR environment, and realizes the real-time localization of the target sound source during the flight of UAV with microphone array.
Research on ultrasonic phased array total focusing multi-mode fusion method
Authors: Bu Yangguang , Cheng Jingwei , Chen Wei , Li Rui , Wang Zhe , Wang Haibin , Yan Chang , Ji Tian , Li Kang , Chen Zhe
Published: October 2024

Welded seams are one of the important structural forms in the construction of industrial equipment. But during use, hazardous defects may occur within the weld. Ultrasonic phased-array total focusing method (TFM) is a relatively new post-processing imaging method that can locate defects. In this study, a multi-mode ultrasonic phased-array total focusing fusion method was explored for weld defects to achieve effective quantification and localization of different types of defects. This study explores the application of different fusion methods such as maximum fusion, average fusion and effective region fusion in multi-mode phased array total focusing method. The experimental results show that the fusion methods can improve the accuracy of defect detection compared to single imaging methods, but the effective area fusion method has the best results in detecting weld defects. Taken together, the effective region fusion method can effectively improve the resolution and signal-to-noise ratio of multi-mode imaging methods.
Effects of interlayer SiO2 or Au on the performances of LNOS-SAW
Authors: Lin Binghui , Gao Chao , Wang Yaxin , Zou Yang , Liu Yan , Liu Wenjuan , Cai Yao , Sun Chengliang
Published: October 2024

Surface acoustic wave (SAW) resonators and filters based on lithium niobate (LN) or lithium tantalate crystals have been widely used in modern wireless communication systems. However, acoustic energy in these kinds of devices is lost in the substrate due to longitudinal attenuation. The enhancements of quality factor and coupling coefficient are still in demand for further applications. This work proposes a SAW based on LN thin film on a sapphire substrate (LNOS). Besides, we explored the effects of using different bonding materials on the LNOS-SAW performances. The presence of the interlayer not only plays a role in bonding but also has an impact on the performance of the resonator. Considering the compatibility of the process in this method, 2 μm-thick silicon dioxide (SiO2) or 1 μm-thick gold (Au) is designed as the interlayer. As the displacement diagrams show, the acoustic energy of the SAW with interlayer is reflected at the interface, and the energy leakage is suppressed. The simulation results show that the presence of SiO2 or Au causes a decrease in resonant frequencies of the resonators, and the effect is more pronounced with Au. Significantly, the presence of SiO2 enhances the coupling efficiency of the resonator while the Au interlayer brings a more obvious improvement in the quality factor.
High-resolution assessment of wind energy potential in the Hami region of Northwestern China
Authors: Xu Jiayu , Tao Yiheng , Yang Shuai , Zou Junyu , Duan Weili , Chen Yuntian , Ye Fan , Ning Jiangmin , Zeng Zhenzhong
Published: October 2024

Wind energy plays a pivotal role in the global effort to mitigate climate change, with China emerging as a leader in renewable energy adoption. The Hami region in northwestern China stands out as a crucial area for wind power development, given its substantial wind resources and strategic importance in China’s energy landscape. However, existing studies on wind energy potential vary widely and involve large uncertainties due to sparse measurements and coarse resolution, highlighting the need for more precise assessments to guide policy decisions and optimize energy utilization. This study leverages high-resolution ERA5 reanalysis data and advanced wind turbine technology to assess wind energy potential in the Hami region, taking into account factors including wind speed patterns, turbine heights, and geographical constraints. The comparison with in-situ data demonstrated that high-resolution ERA5 reanalyzed wind speeds enable to capture multi-year wind speed variations in this region. We find substantial potential for wind energy in Hami, with energy densities exceeding 200 W m−2 in the high-potential wind zones. Importantly, this study identifies a new high-potential area in eastern Hami, termed the East Wind Zone. Our high-resolution assessment of wind energy potential at different heights over the past two decades reveals long-term trends and seasonal variations. Increasing the hub height from 95 m to 140 m raises the average wind power generation potential across Hami by 31.3 GWh yr−1. Our findings highlight the importance of strategic wind farm placement to maximize renewable energy output and provide insights for policy and industry, supporting China’s renewable energy goals.
Seasonal forecasts have sufficient skill to inform some agricultural decisions
Authors: Kondal Ashish , Hegewisch Katherine , Liu Mingliang , Abatzoglou John T , Adam Jennifer C , Nijssen Bart , Rajagopalan Kirti
Published: October 2024

Seasonal forecasts, which look several months into the future, are currently underutilized in active decision-making, particularly for agricultural and natural resource management. This underutilization can be attributed to the absence of forecasts for decision-relevant variables at the required spatiotemporal resolution and at the time when the decisions are made and a perception of poor skill by decision-makers. Addressing these constraints, we quantified the skill of seasonal forecasts in informing two agricultural decisions with differing decision timeframes and influencer variables: (a) whether to apply fertilizer in fall or wait until spring based on expected winter temperatures, and (b) drought response, such as whether to lease water based on expectations of drought. We also looked into how early the forecast can be provided without significant degradation in skill. Currently, drought response decisions are typically formulated in April, utilizing drought forecasts issued in the same month, while fall fertilization decisions are generally made between August and September. There is growing interest among stakeholders in the availability of earlier forecasts to inform these critical choices. We utilized the North American multi-model ensemble (NMME) hindcasts for the time period 1982–2020 over the Pacific Northwest US (PNW) to obtain meteorological variables. Runoff was estimated via simulations of the coupled crop-hydrology VIC-CropSyst model. The skill assessment with the Heidke Skill Score (HSS) yielded promising outcomes in both decisions for the entire PNW region. Notably, NMME’s positive skill (median HSS of 30%) in predicting warmer winters identifies years when fertilizer application should be avoided to prevent fertilizer loss through mineralization (and associated costs). Similarly, there is skill in forecasting drought conditions in most irrigated watersheds for up to two months in advance of April, the current decision time. In conclusion, our findings affirm that contrary to the perception of low skill and resulting underutilization, current seasonal forecasts hold the potential to inform at least some key agricultural decisions.
The convolutional neural network for Pacific decadal oscillation forecast
Authors: Skanupong Nutta , Xu Yongsheng , Yu Lejiang , Wan Zhang , Wang Shuo
Published: October 2024

The Pacific decadal oscillation (PDO) is often described as a long-lived El Niño-like pattern of Pacific climate variability, and it has widespread climate and ecosystem impacts. PDO forecasts can provide useful information for policymakers on how to handle PDO impacts. Nevertheless, due to the long duration of the PDO cycles and their complex formation mechanisms, it remains a challenge to predict long lead time PDO. In this paper, we propose a transfer-learning-enhanced convolutional neural network (CNN) to tackle complex ocean dynamic forecasting and predict PDO events with up to a one-year lead time. Our method first trains the CNN on historical simulations from Coupled Model Intercomparison Project 6 (CMIP6), covering the period from 1850 to 1972. This prior knowledge is then refined by further training the model with observational data from 1854 to 1972, ensuring robust performance on unseen data. Additionally, k-fold cross-validation is also employed to evaluate the model’s performance across diverse subsets of data, enhancing its reliability. Throughout the testing phase from 1983 to 2022, the CNN model consistently outperforms existing dynamical forecast systems, exhibiting superior correlation skills in predicting annual mean PDO indices and PDO phases, including displaying resilience to seasonal variations. The transferred CNN is thus a powerful method to predict PDO events and is potentially valuable for a wide range of applications. This work directly supports the objectives of the World Climate Research Programme Grand Challenge on Climate Prediction.
Mechanical, tribological and modal characteristics of eco-friendly coir/sugarcane fillers reinforced polymer composites
Authors: Shankar A N , George Manuel , Krishna S M Murali , Kakaravada Ismail , S Singholi Ajay K , Lakshmi V V K , Chacko Mathews , Kumar K Arun , Jindal Prakhar , Selvaraj Rajeshkumar
Published: October 2024

Polymer-based composites have been drawing the attention of the research community for many decades, not only in academia but also in industry. However, continuously increasing environmental concerns have led the researchers to focus on natural composite materials. This is a challenge for researchers to develop a natural composite without compromising the composites’ excellent mechanical properties and tribological performance. In this research, coir and sugarcane are selected as the natural fillers, and epoxy resin has been chosen for matrix material. To look into the crystallinity of composites, XRD analysis was done. In addition, a mechanical study was done to look at the manufactured composites’ tensile and flexural characteristics. The tribological performance (i.e., wear rate and friction coefficient) of the composite samples is investigated by using a pin-on-disc setup. The parameters such as filler loading and normal load affecting the tribological performance of epoxy-based natural composites are studied. The results show that the wear and friction characteristics of the composite reinforced with sugarcane and coir were 10.78% and 57.80% lower than those of the neat composite, respectively.
Effects of weed management on soil metagenomic composition in cultivated chickpea fields
Authors: Imran Hammami , Nouha Ferchichi , Wael Toukebri , M’sehli Wissal , Thouraya Ben Hammouda , Arwa Ajengui , Cyrine Guiga , Darine Trabelsi
Published: October 2024

Non-chemical methods, including mechanical and manual weed management are important for improving crop yields and preserving soil microbial diversity. In Tunisia, chickpea cultivation uses a combination of these methods to suppress weeds. This study aimed to evaluate the impact of weeding practices on chickpea (Cicer arietinum L. cultivar REBHA) yield and soil microbial diversity. Field experiments were conducted at the Technical Center for Biological Agriculture in Essaida, Tunisia, using six plots with manual and no weeding treatments. Chickpea yield was measured, and soil samples were collected for metagenomic analysis. Floristic surveys identified 13 weed species, with Chenopodium album L., Rumex acetosa L., and Urtica dioica L. being the most dominant. Seed yield ranged from 23.2 to 26.2 qls/ha in non-weeded plots and from 25.1 to 30.1 qls/ha in weeded plots, showing an increase in yield (11.75%) with manual weeding. Soil metagenomics revealed changes in bacterial community composition between the two treatments. The dominant phylum was Pseudomonadota, whose relative abundance increased from 24.88% in non-weeded plots to 34.76% in weeded plots. Alpha diversity indices showed lower species richness and diversity in weeded soils, with 62000 OTUs in weeded plots compared to 43202 OTUs in non-weeded plots. Betaproteobacteria and Alphaproteobacteria exhibited higher OTU counts in weeded soils. The Simpson diversity index was lower in non-weeded soils (0.025) than in weeded soils (0.075), indicating a more irregular microbial distribution in non-weeded plots. Thus, manual weeding improved chickpea yield and altered the soil bacterial community, increasing diversity in key microbial taxa. This study highlights the complex interaction between weed management practices and soil microbial ecosystems, which may influence crop productivity.
Evaluating the efficacy of lead-free piezoelectric materials in microcantilever based vibration energy harvesters
Authors: Manvi Mahammadrafeeq , K B Mruthyunjaya Swamy
Published: October 2024

The piezoelectric materials have been extensively utilized in various applications, such as sensors, actuators, and energy harvesters. This study evaluates the performance of six lead-free piezoelectric materials- aluminium nitride (AlN), barium titanate (BaTiO3), lithium niobate (LiNbO3), lithium tantalate (LiTaO3), polyvinylidene fluoride (PVDF), and zinc oxide (ZnO) in MEMS-based piezoelectric vibration energy harvesters (PVEHs) using cantilever configurations. Finite element analysis via COMSOL Multiphysics was employed to assess the deflection, voltage, and power outputs of these materials at their resonance frequencies, both with and without proof masses. The results indicate that BaTiO3 and PVDF cantilevers exhibited the highest voltage outputs, reaching 207.14 mV and 202.07 mV, respectively, with AlN also showing comparable performance at 184.72 mV. ZnO-based cantilevers demonstrated the highest power output of 1.35 nW without proof masses and 190.5 nW with proof masses, indicating its potential for high-power applications. The addition of proof masses generally reduced resonant frequencies but enhanced power outputs, like for ZnO. This comprehensive analysis underscores the critical impact of material selection and structural modifications on the efficiency of PVEHs, with BaTiO3, PVDF, and ZnO emerging as the most promising candidates for optimizing energy harvesting devices. This research lays a foundation for further advancements in piezoelectric MEMS technology, aiming for more efficient energy harvesting solutions.
A deep learning method for pointer meter reading recognition in inspection robots at refrigeration stations
Authors: Wang Kai , Yu Junqi , Feng Chunyong , Guo Jvgang , Chen Yisheng , Dong Zhenping , Liu Zongyi
Published: October 2024

To improve the intelligent operation and maintenance of large public building refrigeration stations, various automatic reading methods for pointer meters used in inspection robots have been developed. However, most methods exhibit low detection accuracy for pointer meters in refrigeration stations and poor segmentation of pointers and scale lines, ultimately leading to inaccurate readings. To address the challenges posed by the complex environments of refrigeration stations, this study proposes a deep learning-based image recognition method for precise pointer meter readings. Firstly, the pointer meters in the environment are detected and located by the YOLOV8-CBAM-Wise-IoU model. Secondly, an improved Fast Semantic Segmentation Network (Fast-SCNN) is used for image segmentation of the pointers and scale lines of the pointer meters, and a perspective transformation method is employed to correct images of tilted meters. Then, the image is transformed into a rectangular image using polar coordinate transformation. Finally, the accurate reading is calculated using the distance method, based on the relative distances between the pointers and scale lines. This research conducted experimental tests using an inspection robot in the actual environment of a large public building’s refrigeration station. The results demonstrate that the proposed method for pointer meter reading recognition achieves a fiducial error within 0.41%, which can realize the inspection task of the pointer meter in refrigeration stations.
Experimental investigation on optimizing wire-cut EDM process parameters of hybrid MMC(AA7475/ZrO2/Gr) using artificial neural network
Authors: Singuru Madhavarao , V V S Kesava Rao , Chekuri Rama Bhadri Raju
Published: October 2024

Wire cut Electrical discharge machining (WCEDM) is a widely used method for machining complex shapes in advanced materials like metal matrix composites (MMCs) and hybrid metal matrix composites (HMMCs). To address these challenges, this study focusses on the wire-cut EDM (WCEDM) process of a workpiece made from zirconium dioxide and graphite-reinforced aluminium alloy 7475 with a molybdenum electrode. The effects of input process variables such as peak current (IP), pulse-on-time (TON), and flushing pressure (PF) on the output response features are investigated. These output responses include material removal rate (MRR), surface roughness (SR), and wire wear ratio (WWR). To optimise the process parameters, the Taguchi design technique is used. An artificial neural network (ANN) with a feed-forward back propagation architecture is utilised to find the best fit for the optimisation challenges. ANN predicted the results with an accuracy of 97.81% for MRR, 97.95% for SR and 95.865% for WWR. The results reveal that the WCEDM of AA7475/ZrO2/Gr with a molybdenum electrode achieved minimal WWR and SR, while maximizing the MRR.
BayeSMART: Bayesian clustering of multi-sample spatially resolved transcriptomics data
Authors: Guo Yanghong , Zhu Bencong , Tang Chen , Rong Ruichen , Ma Ying , Xiao Guanghua , Xu Lin , Li Qiwei
Published: October 2024

The field of spatially resolved transcriptomics (SRT) has greatly advanced our understanding of cellular microenvironments by integrating spatial information with molecular data collected from multiple tissue sections or individuals. However, methods for multi-sample spatial clustering are lacking, and existing methods primarily rely on molecular information alone. This paper introduces BayeSMART, a Bayesian statistical method designed to identify spatial domains across multiple samples. BayeSMART leverages artificial intelligence (AI)-reconstructed single-cell level information from the paired histology images of multi-sample SRT datasets while simultaneously considering the spatial context of gene expression. The AI integration enables BayeSMART to effectively interpret the spatial domains. We conducted case studies using four datasets from various tissue types and SRT platforms, and compared BayeSMART with alternative multi-sample spatial clustering approaches and a number of state-of-the-art methods for single-sample SRT analysis, demonstrating that it surpasses existing methods in terms of clustering accuracy, interpretability, and computational efficiency. BayeSMART offers new insights into the spatial organization of cells in multi-sample SRT data.
Social-semantic knowledge in frontotemporal dementia and after anterior temporal lobe resection
Authors: Rouse Matthew A , Halai Ajay D , Ramanan Siddharth , Rogers Timothy T , Garrard Peter , Patterson Karalyn , Rowe James B , Lambon Ralph Matthew A
Published: October 2024

Degraded semantic memory is a prominent feature of frontotemporal dementia (FTD). It is classically associated with semantic dementia and anterior temporal lobe (ATL) atrophy, but semantic knowledge can also be compromised in behavioural variant FTD. Motivated by understanding behavioural change in FTD, recent research has focused selectively on social-semantic knowledge, with proposals that the right ATL is specialized for social concepts. Previous studies have assessed very different types of social concepts and have not compared performance with that of matched non-social concepts. Consequently, it remains unclear to what extent various social concepts are (i) concurrently impaired in FTD, (ii) distinct from general semantic memory and (iii) differentially supported by the left and right ATL. This study assessed multiple aspects of social-semantic knowledge and general conceptual knowledge across cohorts with ATL damage arising from either neurodegeneration or resection. We assembled a test battery measuring knowledge of multiple types of social concept. Performance was compared with non-social general conceptual knowledge, measured using the Cambridge Semantic Memory Test Battery and other matched non–social-semantic tests. Our trans-diagnostic approach included behavioural variant FTD, semantic dementia and ‘mixed’ intermediate cases to capture the FTD clinical spectrum, as well as age-matched healthy controls. People with unilateral left or right ATL resection for temporal lobe epilepsy were also recruited to assess how selective damage to the left or right ATL impacts social- and non–social-semantic knowledge. Social- and non–social-semantic deficits were severe and highly correlated in FTD. Much milder impairments were found after unilateral ATL resection, with no left versus right differences in social-semantic knowledge or general semantic processing and with only naming showing a greater deficit following left versus right damage. A principal component analysis of all behavioural measures in the FTD cohort extracted three components, interpreted as capturing (i) FTD severity, (ii) semantic memory and (iii) executive function. Social and non-social measures both loaded heavily on the same semantic memory component, and scores on this factor were uniquely associated with bilateral ATL grey matter volume but not with the degree of ATL asymmetry. Together, these findings demonstrate that both social- and non–social-semantic knowledge degrade in FTD (semantic dementia and behavioural variant FTD) following bilateral ATL atrophy. We propose that social-semantic knowledge is part of a broader conceptual system underpinned by a bilaterally implemented, functionally unitary semantic hub in the ATLs. Our results also highlight the value of a trans-diagnostic approach for investigating the neuroanatomical underpinnings of cognitive deficits in FTD.
Comparative Analysis of Deep Learning Techniques for Global Horizontal Irradiance Forecasting in U.S. Cities
Authors: Alkhatib Fathy Yassin , Alsadi Juman , Ramadan Mariam , Nasser Ruba , Awdallah Abeer , Chrysikopoulos Constantinos V , Maalouf Maher
Published: October 2024

Accurate solar radiation estimation is crucial for the optimal design of solar energy systems used in numerous applications. Thus, this research aims to investigate the forecasting of hourly global horizontal irradiance using both univariate and multivariate methods. Deep learning techniques, including long-short-term memory, convolutional neural networks, and a hybrid of convolutional neural networks/long-short-term memory are employed. The effects of fixed and varying learning rates are explored under the condition of a fixed window size of 48 hours. Data collected from three major cities in the US are employed to cover a broad range of annually received solar radiation. The data are divided into three subsets: 60% are used for training, 20% for cross-validation, and 20% for testing. The results revealed that the convolutional neural networks and long-short-term memory models outperform the hybrid convolutional neural networks /long-short-term memory model based on the lower values of the root mean square error (RMSE), mean absolute error (MAE), and higher coefficient of determination (R2). For instance, the multivariate long-short-term memory with fixed learning rate (RMSE=0.345, MAE=0.387, R2=0.994) is the best-performing model for Rochester, the multivariate convolutional neural networks with fixed learning rate (RMSE=32.89, MAE=15.35, R2=0.928) is the best-performing model for Seattle, and the univariate convolutional neural networks with variable learning rate (RMSE=048.2, MAE=23.66, R2=0.959) is the best-performing model for Tucson. Different learning rates were shown to not significantly influence the prediction of sunlight. Furthermore, it was concluded that changing the window size does not necessarily improve performance. This study demonstrates the efficacy of variable learning rates and hybrid models in improving global horizontal irradiance forecast accuracy.
Reconciliation of weak pairwise spike–train correlations and highly coherent local field potentials across space
Authors: Senk Johanna , Hagen Espen , van Albada Sacha J , Diesmann Markus
Published: October 2024

Multi-electrode arrays covering several square millimeters of neural tissue provide simultaneous access to population signals such as extracellular potentials and spiking activity of one hundred or more individual neurons. The interpretation of the recorded data calls for multiscale computational models with corresponding spatial dimensions and signal predictions. Multi-layer spiking neuron network models of local cortical circuits covering about $1\,{\text{mm}^{2}}$ have been developed, integrating experimentally obtained neuron-type-specific connectivity data and reproducing features of observed in-vivo spiking statistics. Local field potentials can be computed from the simulated spiking activity. We here extend a local network and local field potential model to an area of $4\times 4\,{\text{mm}^{2}}$, preserving the neuron density and introducing distance-dependent connection probabilities and conduction delays. We find that the upscaling procedure preserves the overall spiking statistics of the original model and reproduces asynchronous irregular spiking across populations and weak pairwise spike–train correlations in agreement with experimental recordings from sensory cortex. Also compatible with experimental observations, the correlation of local field potential signals is strong and decays over a distance of several hundred micrometers. Enhanced spatial coherence in the low-gamma band around $50\,\text{Hz}$ may explain the recent report of an apparent band-pass filter effect in the spatial reach of the local field potential.
Impact of sex-specific thresholds for low flow in assessment of prognosis in concordantly and discordantly graded aortic valve stenosis
Authors: Bahlmann Edda , Gerdts Eva , Einarsen Eigir , Midtbø Helga , Pedersen Eva R , Rossebø Anne , Willems Stephan , Cramariuc Dana
Published: October 2024

Aims

Sex-specific low flow was recently defined as stroke volume index (SVi) ≤ 40 mL/m² in men and ≤32 mL/m² in women. We tested the prognostic association of these cut-offs in patients with aortic stenosis (AS) with concordantly and discordantly graded AS [concordantly graded AS by energy loss (CGASEL) and discordantly graded AS by energy loss (DGASEL)] based on pressure recovery adjusted aortic valve area [energy loss (EL)].

Methods and results

Data from 1351 patients with asymptomatic AS, peak jet velocity <4 m/s, and preserved left ventricular ejection fraction enrolled in the Simvastatin and Ezetimibe in Aortic Stenosis study were used. DGASEL was defined as EL <1.0 cm² with mean aortic gradient <40 mmHg and CGASEL as EL ≥1.0 cm² with mean aortic gradient <40 mmHg. Patients were further grouped into normal and low flow. The outcome was combined all-cause death and hospitalization for heart failure (HF). CGASEL with normal/low flow was present in 915/253 patients, and DGASEL with normal/low flow was present in 57/126 patients. During a median follow-up of 4.3 years, event-free survival was lower in patients with DGASEL irrespective of flow compared to CGASEL with normal flow (P < 0.05). In Cox regression analysis, DGASEL with normal or low flow were both associated with increased risk of all-cause death and hospitalization for HF after adjustment for age, sex, heart rate, randomized study treatment, hypertension, aortic valve replacement, and aortic valve calcification (P < 0.05). No survival difference was found between patients with normal vs. low flow within groups of DGASEL or CGASEL.

Conclusion

Identification of low flow by the proposed sex-specific thresholds of SVi needs more prognostic validation before application in clinical practice.

ClinicalTrials.gov identifier

NCT00092677.
Extremely rare coronary anomaly as cause of palpitations: a case report of single right coronary artery—multimodality imaging and its impact on treatment decisions
Authors: Suchodolski Alexander , Millan Natasza , Mykieta Katarzyna , Głowacki Jan , Szulik Mariola
Published: October 2024

Background

We report the case of a 63-year-old white Caucasian male patient admitted to the clinic because of atypical angina and palpitations. Other comorbidities included hypertension, hyperuricaemia, and hypercholesterolaemia. He was admitted to a tertiary cardiac centre for deepened diagnostics of his complaints.

Case summary

Echocardiography revealed no pathology, but due to high calcium score (Agatston > 400 units), signs of arrhythmia during exercise, and atypical angina complaints, further investigations were performed. Invasive coronary angiography revealed stenosis up to 53% in the middle part of the right coronary artery (RCA), and computed tomography angiography showed no left coronary artery, only malignant-coursed vessel, running from the proximal part of the RCA. Single-photon emission tomography findings allowed to come to a decision not to perform invasive treatment (coronary artery bypass grafting), due to acceptable perfusion and viability of the heart muscle.

Discussion

Single coronary artery is an extremely rare anomaly. This requires highly individualized diagnostic approaches, which include multiple imaging modalities, as each adds different information. While the only coronary vessel was narrowed in 53%, no significant ischaemia was detected. Left ventricular function remained preserved.