bluuebunny/crossref_metadata_2025 huggingface dataset:
EURAMET.EM.RF-S46 (EURAMET Project No 1538) EURAMET supplementary comparison on magnetic field strength measurements for frequencies up to 30 MHz
Authors: Şen Osman , Aslan Çaǧlar , Ulvr Michal , Pavlíček Tomáš , Baaske Kai , Weickert Franziska , Crotti Gabriella , Osiński Mateusz , AlMojaewel Saleh , Cedheim Mats , Pythoud Frédéric , Harmon Stuart
Published: October 2024

Main text

The results of the supplementary comparison in the area of magnetic field probe calibration of the field strength are presented. This supplementary comparison has been discussed to organize a comparison on magnetic field strength measurements during the EURAMET TC-EM Subcommittee Radiofrequency and Microwave (SC-MW) meeting, including an EMC meeting, organized as a virtual (online) meeting on 20-21 April 2021. The comparison was conducted in accordance with the Technical Protocol of "Comparison of Magnetic Field Strength Measurements for Frequencies up to 30 MHz, EURAMET Project No 1538, EURAMET.EM.RF-S46", which was prepared by the TÜBİTAK UME and approved by the participants. The measurements started in January 2022 and were completed in May 2023. Measurement results reported by nine participants for magnetic field strength values were compared and degrees of equivalence are reported.

To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.

The final report has been peer-reviewed and approved for publication by the CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
A simulation study for enhancing the performance of luminescent organic transistor using reduced voltage and hole blocking layer
Authors: Kumar Vijay , Madhu Charu
Published: October 2024

Eco-friendly and biodegradable technology forms the basis of organic electronics. A luminescent organic transistor (LOT) is a device created using this technology, which is capable of emission of light and acting as switch functions in a single unit. This research seeks to develop and model a nonplanar contact heterostructure-based LOT by employing the defect density of states (DOS) to accurately simulate the amorphous nature of organic semiconductors. This study evaluates two high-k dielectric materials, hafnium oxide (HfO2) and poly(vinylidene fluoride-trifluoroethylene)P(VDF-TrFe), to achieve low-voltage operation at (−10 V). Furthermore, this study investigated the influence of a hole blocking material, 1, 3, 5-Tris(3-pyridyl-3-phenyl)benzene(TmPyPB), on device performance. Simulations revealed p-channel transistor characteristics with a maximum source-drain current of (−1.6 mA) and an on–off current ratio exceeding 104 for HfO2, compared to (−0.75 mA) and approximately 104 for P(VDF-TrFe). The model also demonstrated exceptional electrical properties, including a peak hole mobility of (1.96 cm2 v−1 s−1), a threshold voltage

V

T

of (−0.85 V), and a sub-threshold voltage of 492 mV/dec in saturation. The recombination zone exhibited an electron concentration of 18.0 cm−3, a hole concentration of 19
.
3cm−3, and a Langevin recombination rate of 24.7 cm−3 s−1 near the drain electrode. This model serves as an ideal platform for testing newly developed molecules to enhance the performance of luminescent transistor.
Effects of Al doping on structural, optical, morphological, and low-concentration CO2 gas sensing properties of ZnO nanoparticles synthesized by sol-gel method
Authors: Mishra Manmohan , Kumar Mahendra
Published: October 2024

This work examines the morphological, structural, optical, and gas-sensing characteristics of ZnO thin films doped with Al that were created by the sol-gel spin coating technique. The thin films, doped with varying aluminum concentrations (0%, 2%, and 5%), were characterized using XRD, UV-visible spectroscopy, and FE-SEM to assess their crystallinity, band gap, and surface morphology. XRD analysis confirmed the incorporation of Al into the ZnO lattice without forming secondary phases, while UV-visible spectroscopy revealed an increase in transmittance and band gap with higher Al doping. FE-SEM images showed a transition from agglomerated grains to smoother surfaces with increased Al content. Gas sensing performance was evaluated using low-concentration CO2 as the target gas. The results demonstrated that Al doping significantly enhances the CO2 sensing response, with the 5% Al-doped ZnO exhibiting the optimal sensitivity due to increased carrier concentration and improved surface interaction. These findings suggest that Al-doped ZnO thin films are promising candidates for efficient CO2 gas sensors, combining enhanced structural and optical properties with superior gas sensing capabilities.
Photocatalysis, wettability and optical properties of N-doped Cu2O/CuO thin films for smart coating applications
Authors: Hassaballa S , Aljabri A , Mohamed S H , Bakry A M , El-Rahman A M Abd , Awad M A
Published: October 2024

Undoped and nitrogen (N)_doped Cu2O/CuO thin films were deposited via reactive DC magnetron sputtering. The deposition was carried out by sputtering the Cu targets under various Ar/N2/O2 gas flow ratios. The structural, optical, wettability, and photocatalytic performance of the deposited films were investigated. A simple cubic Cu2O crystallographic phase is observed for the undoped film, whereas mixed cubic Cu2O and monoclinic CuO phases (Cu2O/CuO) are observed for the N_doped films. EDAX revealed that as the N2 flow rate increased the amount of nitrogen incorporated into the film increased. The transmittance and reflectance are affected by the incorporation of nitrogen into the films. The transmittance values decreased with increasing N2 flow rate, whereas the reflectance values increased. Both the refractive index and extinction coefficient almost increased with increasing N2 flow rate. A noticeable optical band gap narrowing from 2.55 eV to 2.39 eV was detected upon increasing the N2 flow from 0.0 to 190 sccm. The photoluminescence spectrum of the undoped sample contains five distinct bands at 518, 612, 654, 714 and 825 nm. These five maxima are attributed to the radiative decay of bound and free excitons, and oxygen vacancies (VO) After nitrogen incorporation, the photoluminescence intensity decreases and then increases again with increasing N2 flow rate. A reduction in the water contact angle was observed with increasing N2 flow rate. Upon Vis-light illumination, the N_doped Cu2O/CuO films reached superhydrophilicity faster than the undoped film did. The photocatalytic performance of the deposited Cu2O/CuO films was strongly enhanced with a small amount of N doping. The deposited films are promising for self-cleaning and photocatalytic degradation of organic wastes.
Thermally-induced diffusion and structural phase transitions in Pt/Mn and Pt/Mn/Pt thin films
Authors: Voloshko Svitlana , Kruhlov Ivan , Pedan Roman , Garrido-Segovia María , Orlov Andrii , Dubikovskyi Oleksandr , García-Martín José Miguel , Kaidatzis Andreas , Vladymyrskyi Igor
Published: October 2024

We demonstrate the possibility of diffusion formation of the chemically ordered L1
0-MnPt phase through the vacuum annealing of Pt(24 nm)/Mn(20 nm) and Pt(12 nm)/Mn(20 nm)/Pt(12 nm) layered stacks at 400 °C for 30 min. For the bi-layered stack annealed at 400 °C, the effect of Pt atoms segregation at the film/substrate interface was detected, which remained after annealing even at higher temperatures (500 °C and 600 °C) and prevented the whole homogenization of the chemical composition through the film depth. By contrast, for the tri-layered stack annealed at 400 °C, the presence of the additional Pt bottom layer enabled to change the rate and mechanism of reactive diffusion, leading to homogeneous distribution of components and enhanced crystallinity of the ordered L1
0-MnPt phase compared to the bi-layered sample. An explanation of the obtained experimental data is provided based on the fundamentals of mass transfer theory and its quantitative parameters (e.g. activation energy and diffusion coefficients).
Exploring the inverse line-source scattering problem in dielectric cylinders with deep neural networks
Authors: Pallikarakis Nikolaos , Kalogeropoulos Andreas , Tsitsas Nikolaos L
Published: October 2024

This study presents a novel approach utilizing deep neural networks to address the inverse line-source scattering problem in dielectric cylinders. By employing Multi-layer Perceptron models, we intend to identify the number, positions, and strengths of hidden internal sources. This is performed by using single-frequency phased data, from limited measurements of real electric and real magnetic surface fields. Training data are generated by solving corresponding direct problems, using an exact solution representation. Through extended numerical experiments, we demonstrate the efficiency of our approach, including scenarios involving noise, reduced sample sizes, and fewer measurements. Additionally, we examine the empirical scaling laws governing model performance and conduct a local analysis to explore how our neural networks handle the inherent ill-posedness of the considered inverse problems.
Efficient implementation of quantum permutation algorithm using a polar SrO molecule in pendular states
Authors: Hu Jie-Ru , Zhang Zuo-Yuan , Liu Jin-Ming
Published: October 2024

Quantum algorithms offer more enhanced computational efficiency in comparison to their classical counterparts when solving specific tasks. In this study, we implement the quantum permutation algorithm utilizing a polar molecule within an external electric field. The selection of the molecular qutrit involves the utilization of field-dressed states generated through the pendular modes of SrO. Through the application of multi-target optimal control theory, we strategically design microwave pulses to execute logical operations, including Fourier transform, oracle U

f
operation, and inverse Fourier transform within a three-level molecular qutrit structure. The observed high fidelity of our outcomes is intricately linked to the concept of the quantum speed limit, which quantifies the maximum speed of quantum state manipulation. Subsequently, we design the optimized pulse sequence to successfully simulate the quantum permutation algorithm on a single SrO molecule, achieving remarkable fidelity. Consequently, a quantum circuit comprising a single qutrit suffices to determine permutation parity with just a single function evaluation. Therefore, our results indicate that the optimal control theory can be well applied to the quantum computation of polar molecular systems.
A hybrid method integrating Green’s function Monte Carlo and projected entangled pair states
Authors: Lin 林 He-Yu 赫羽 , He 贺 Rong-Qiang 荣强 , Guo 郭 Yibin 奕斌 , Lu 卢 Zhong-Yi 仲毅
Published: October 2024

This paper introduces a hybrid approach combining Green’s function Monte Carlo (GFMC) method with projected entangled pair state (PEPS) ansatz. This hybrid method regards PEPS as a trial state and a guiding wave function in GFMC. By leveraging PEPS’s proficiency in capturing quantum state entanglement and GFMC’s efficient parallel architecture, the hybrid method is well-suited for the accurate and efficient treatment of frustrated quantum spin systems. As a benchmark, we applied this approach to study the frustrated J
1–J
2 Heisenberg model on a square lattice with periodic boundary conditions (PBCs). Compared with other numerical methods, our approach integrating PEPS and GFMC shows competitive accuracy in the performance of ground-state energy. This paper provides systematic and comprehensive discussion of the approach of our previous work [Phys. Rev. B
109 235133 (2024)].
Influence of crystal dimension on performance of spherical crystal self-emission imager
Authors: Zhang 张 Chenglong 成龙 , Zhang 张 Yihang 翌航 , Gu 谷 Haochen 昊琛 , Chen 陈 Nuo 诺 , Yuan 远 Xiaohui 晓辉 , Zhang 张 Zhe 喆 , Xu 徐 Miaohua 妙华 , Li 李 Yutong 玉同 , Li 李 Yingjun 英骏 , Zhang 张 Jie 杰
Published: October 2024

The spherical crystal imaging system, noted for its high energy spectral resolution (monochromaticity) and spatial resolution, is extensively applied in high energy density physics and inertial confinement fusion research. This system supports studies on fast electron transport, hydrodynamic instabilities, and implosion dynamics. The x-ray source, produced through laser–plasma interaction, emits a limited number of photons within short time scales, resulting in predominantly photon-starved images. Through ray-tracing simulations, we investigated the impact of varying crystal dimensions on the performance of a spherical crystal self-emission imager. We observed that increasing the crystal dimension leads to higher imaging efficiency but at the expense of monochromaticity, causing broader spectral acceptance and reduced spatial resolution. Furthermore, we presented a theoretical model to estimate the spatial resolution of the imaging system within a specific energy spectrum range, detailing the expressions for the effective size of the crystal. The spatial resolution derived from the model closely matches the numerical simulations.
Research on an Intelligent Perception Data Collection Method
Authors: Meng Qingjia , Guo Wei , Chen Xiaofei , li Kang , Yang Kai
Published: October 2024

This article proposes a sensor anomaly event intelligent perception monitoring technology to address the problem of insufficient intelligent perception of landslides. This method achieves real-time dynamic monitoring of abnormal deformation in landslide disasters from deformation, accelerated deformation to instability and failure stages. This article proposes an algorithm that triggers acquisition by sensing abnormal deformation and adjusts the acquisition frequency autonomously. By embedding the algorithm into the monitoring system, real-time monitoring of abnormal event data of disaster bodies can be achieved. The system achieves low-power sleep monitoring mode by adjusting the working mode. This method provides a good real-time understanding of the dynamic evolution laws of landslide bodies and improves the effectiveness of disaster prevention and reduction.
Nonlinear terminal sliding mode trajectory tracking control algorithm for industrial robots based on dung beetle optimizer
Authors: Tu Yating , Huang Deqi , Zhang Zhenhua , Wu Jianhui , Ye Zikuang
Published: October 2024

To enhance the precision of trajectory tracking control in industrial robots, a nonlinear end-to-end sliding mode trajectory tracking control algorithm for industrial robots based on the dung beetle algorithm is proposed. By employing nonlinear terminal sliding mode control to resolve the issue of inadequate trajectory tracking control performance in industrial robots, and integrating the dung beetle optimizer (DBO) algorithm for control parameter adjustment, significant enhancements are achieved in trajectory tracking accuracy.
YOLO-based thyroid ultrasound for assisted diagnosis
Authors: Yang Xu , Geng Hongliang , Wang Zhilin , Cong Zhibin
Published: October 2024

Real-time intelligent diagnosis of thyroid ultrasound images using deep learning techniques can mitigate the impact of human subjective factors on diagnostic outcomes. Three thousand and fifty-five thyroid ultrasound images were acquired from 205 selected patients aged 10 to 77 years who underwent ultrasound examinations between 2019 and 2023. Each image contained at least one area of thyroid nodules, totaling 3, 088 nodules, including 1, 752 benign and 1, 336 malignant nodules. YOLOV8 is the baseline model for developing an end-to-end architecture for thyroid nodule detection. This architecture automatically identifies nodule lesions in ultrasound images, classifies them as benign or malignant, and enables real-time detection in video frames. The experimental results on 611 clinical thyroid ultrasound images demonstrate that our method can accurately diagnose benign and malignant nodal lesions in thyroid ultrasound with 88.1% and 84.6% accuracy, respectively. The mean average accuracy is as high as 91.1%, indicating a 5.1% improvement compared to the baseline model.
Tailoring emission spectra by using core-shell nanostructures with a random forest algorithm
Authors: Chen Guoping , Jiang Chun
Published: October 2024

We propose a scheme to tailor emission spectra through the engineering of the local density of states by using core-shell nanostructures. A random forest algorithm is used to train a forward model for spectrum prediction and an inverse model for the construction of core-shell nanostructures. From the simulation results, it can be seen that we can predict the spectra very well and achieve good effects for tailoring the emission spectra with core-shell nanostructures based on the established models, eliminating the time-consuming and laborious design process with manual intervention.
SDS-YOLOv8n: A lightweight detection method for flames and smoke
Authors: Guo Shijing , Li Bohan , Zhang Jinjing , Zhu Enjiang , Liang Yan , Sun Jianzhi
Published: October 2024

In flame and smoke image processing scenarios, real-time detection of translucent flames and smoke targets is a difficult task. In the process of optimizing accuracy and speed, this study proposed an SDS-YOLOv8n lightweight detection network by using YOLOv8n as a benchmark. First, SimAM was integrated into the SPPF feature pyramid pooling layer to improve the weight attention of the 3D feature map. Secondly, Slim-Neck is used to replace the neck network layer to reduce the parameters and calculations of the model. Finally, the dynamic upsampling operator DySample was used to improve Slim-Neck, integrated into the YOLOv8n lightweight network. Experimental results on the constructed flames and smoke dataset show that the precision rates increased to 81.7%, recall rates increased to 79.2%, and parameters and calculations were reduced by 8% and 18%, respectively. While reducing computing costs, accuracy is improved, and all indicators surpass comparison methods.
Adaptive anchor learner for object detection
Authors: Wang Xiaobin , Zhu Dekang , Yan Ye
Published: October 2024

There is a growing interest in advancing object detection and its various applications. Promising performance is achieved by using anchor-based detectors while the difficulty is encountered. The performance is sensitive to the hyper-parameters related to anchor boxes, which are manually determined and are task-specific. To address the issue, an anchor learner is proposed in the paper, which automatically learns adaptive anchor from the data, and the difficulty of anchor design for a specific task is thus avoided. Specifically, the method we propose comprises a backbone network and two fully connected branches, and these two branches learn anchor scales and aspects ratios, respectively. We use RGB and ground-truth mask image data as the network input. Importantly, the anchor learner can be embedded into any anchor-based object detector. Experiments are performed on the datasets Visdrone 2019, UAVDT, and DOTA, respectively. Experimental results demonstrate that our proposed method markedly enhances object detection performance.
Research on irregular sponge layout system based on heuristic algorithms
Authors: Zhang Wenle , Chen Tian
Published: October 2024

A layout optimization method that integrates No-Fit Polygons (NFP) positioning and a genetic algorithm is proposed for the two-dimensional irregular sponge packing problem. Firstly, according to the geometric characteristics of the parts, they are classified and encoded to calculate the NFP between part classes, avoiding redundant NFP calculations. Simultaneously, heuristic rules aimed at minimizing the packing height are introduced to provide a comprehensive evaluation function for part positioning strategies, thus improving packing efficiency. Secondly, in the optimization of part sorting, a genetic algorithm is introduced to optimize the sponge packing algorithm. Finally, several standard cases provided by the European Special Interest Group on Cutting and Packing (ESICUP) are used to test the proposed packing method. The results show that compared to the traditional Bottom-Left algorithm, the computational efficiency of the proposed packing method is improved by 4.20% to 22.73%.
Layer multiplexing and DNA based color image encryption
Authors: Zhang Zhenhua , Huang Deqi , Tu Yating , Ye Zikuang
Published: October 2024

A layer multiplexing-based encrypted image scheme for DNA color images is proposed. Firstly, a memristor is added to the Sprott-B chaotic system to make it a fourth-order memristorised hyper-chaotic system. The hyperchaotic system has better pseudo-randomness. The encryption system proposed generates the initial value of the system by SHA3-256 function to achieve “One image, one secret”. The chaotic sequence is generated by a memory hyperchaotic system for encrypting the image. The encryption process includes image zero complements, image chunking, DNA encryption, layer multiplexing, DNA decryption, and improved XOR diffusion. The encrypted images are analyzed by Matlab. The pixel distribution of the encrypted image is verified to be homogeneous by pixel histogram analysis. The encryption system is tested to have good resistance to shear attacks and noise attacks. The encryption system also has a good encryption effect by information entropy test. Experiments show that the encryption system proposed has a short encryption time and decryption time.
Spatial identification of public spaces’ functions: a case study of Bach Dang Wharf Park in Ho Chi Minh City, Vietnam
Authors: Lan N H M , Hung L K , Huong D N T , Van P D B
Published: October 2024

Urban public spaces serve various functions and roles, such as physical, symbolic, ecological, economic, political, social, psychological, and aesthetic. Each function has specific design requirements and holds different meanings for space users. This study aims to identify the location of various functions within Bach Dang Wharf Park, one of the famous central riverside parks of Ho Chi Minh City, Vietnam, and test hypotheses about the concentration of hotspots for each function. To achieve these, we combined participatory GIS methods and face-to-face interviews using quantitative questionnaires and then used SPSS software to examine the relationship between park users’ identification of functions and other factors. We conducted two surveys, each lasting one week, in June 2022 and April 2023, with a total of 223 respondents and 1,413 marked points for park functions. The results showed that how people perceive park functions significantly relates to the characteristics of their park visitation rather than personal information. The hotspots of physical, symbolic, ecological, economic, and political functions appeared with high confidence levels and differed in size and location between the survey times. Meanwhile, in the 2022 survey, hotspots of social function appeared at the old pier near the high-speed boat station and opposite Nguyen Hue walking street. Later in 2023, these areas were mostly concentrated by markers of psychological function. At the same time, hotspots of aesthetic function were recorded in the space in front of the ASEAN flagpole. This approach effectively promotes community involvement in urban planning by better understanding citizens’ needs for public space.
Conflict between Tourism and Conservation at Nui Chua National Park, Ninh Thuan Province, Vietnam
Authors: Le Nguyen H
Published: October 2024

In protected areas, particularly in national parks, tourism management requires a trade-off between ensuring the key values that support conservation and permitting visitors to appreciate those values. This conflict between conservation and tourism exploitation exists in most national parks around the world. Nui Chua National Park is in the most arid region of Vietnam. Despite that, it has a combination of forest, sea, and semi-desert landscapes that put it into the protected area system of Vietnam. Nui Chua National Park is open to tourists for various purposes. As such, the clash between tourism and conservation maintains as an issue at the park. This paper offers some insights about this conflict at Nui Chua National Park and proposes solutions to tackle this matter. The research is conducted using a qualitative approach. The data is collected using expert interview and in-depth interview method. Expert interview is used to extract information from park’s authority and experts. In-depth interview is used to ask the Raglai people who live within the park’s boundary and participate in some tourism activities. The results suggest that the conflict between conservation and tourism exploitation is in existence but not intensively. The author proposes a more scientific approach in managing tourist activities at Nui Chua National Park.
Factors Affecting the Students’ Usage Intention towards Electric Transportation in Ho Chi Minh City, Vietnam
Authors: Nho TT N , Vy N T
Published: October 2024

Emissions from vehicles are increasingly causing serious consequences to the environment. Therefore, most countries around the world have implemented action plans to reduce and prevent such a bad situation. One of the most popular solutions is electrification of the transportation system. Ho Chi Minh City is no exception to that trend by deploying electric transportation with a variety of vehicles. However, the level of social consumption of this friendly means of transportation is still limited, including among students. This current article is aimed at identifying factors that affect students’ intention to use electric transportation, including: (1) Personal factors (environmental attitude, green consumption attitude, knowledge, perception towards green products, environmental responsibility, capabilities), (2) interpersonal factors (social values) and (2) external factors (public policy, availability, price). By using questionnaires, the research carried out a direct survey of 300 students studying at Vietnam National University, Ho Chi Minh City. Research results show that public policy, green consumption attitudes, environmental responsibility, and social values have a significant relationship with student’s intention to use electric transportation, in which public policy is the biggest motivator. From the research results, the paper is solutions to promote use aimed at improving environmental quality.
Indigenous Knowledge in Tourism Development: The Case of Hô River Island, Tra Vinh Province, Vietnam
Authors: Van Chat Nguyen
Published: October 2024

Climate change is affecting various aspects people’s lives in the Mekong Delta, Vietnam, especially those who are living in the low-elevation terrain such as small river islands. Some studies revealed that indigenous knowledge can assist local people in mitigating the damage to agricultural production caused by climate change. Thus, this paper analyzes the application of indigenous knowledge of the people in Hô Island, Tra Vinh province in tourism development in the context of climate change. The qualitative approach was utilized in this paper including 35 semi-in-depth interviews and participant observations in 13 events. The results showed that indigenous knowledge not only greatly contributed to creating impressive tourism products and services but also formed secondary livelihoods aside from agriculture, which improved the living standards for the people in Hô Island. This research implies that there is a need for policies and training courses to raise general awareness of the adaptation of indigenous knowledge in economic development, and particularly, tourism development in vulnerable geographic areas (such as small river islands) in the context of climate change observed in the Mekong Delta.
Regional Governance in Ho Chi Minh City Metropolitan Area: Mechanisms and Challenges
Authors: Truong T H , Khanh N N
Published: October 2024

This article explores regional governance in Ho Chi Minh City Metropolitan Area, a mechanism established by the central government to encourage collaboration among local authorities in the context of this metropolitan area becoming a large polycentric metropolitan region. We employ the content analysis method, collect and analyze secondary data, including theoretical research articles, legal documents, research papers, and news reports etc, to assess current regional governance mechanisms, identify challenges, and propose solutions to enhance the effectiveness of governance in Ho Chi Minh City Metropolitan Area. The regional governance mechanism includes a Central Steering Committee directing a Local Council at the regional level. The research results indicate that the current regional governance mechanism is characterized by a top-down approach, with provinces within the metropolitan area being under the direct management of the central government, lacking horizontal coordination among local authorities. This leads to various issues and challenges such as sluggish operation, inefficiency, and a lack of encouragement for voluntary collaboration among localities. Therefore, in the future, it is essential to introduce innovations in the governance of this metropolitan area.
Context-aware coupler reconfiguration for tunable coupler-based superconducting quantum computers
Authors: Hour Leanghok , Heng Sengthai , Heng Sovanmonynuth , Go Myeongseong , Han Youngsun
Published: October 2024

Crosstalk, caused by unwanted interactions from the surrounding environment, remains a fundamental challenge in existing superconducting quantum computers (SQCs). We propose a method for qubit placement, connectivity, and logical qubit allocation on tunable-coupler SQCs to eliminate unnecessary qubit connections and optimize resources while reducing crosstalk errors. Existing mitigation methods carry trade-offs, like increasing qubit connectivity or software-based gate scheduling. Our method, the Context-Aware COupler REconfiguration (CA-CORE) compilation method, aligns with application-specific design principles. It optimizes the qubit connections for improved SQC performance, leveraging tunable couplers. Through contextual analysis of qubit correlations, we configure an efficient coupling map considering SQC constraints. We then apply the SWAP-based Bidirectional Heuristic Search (SABRE) qubit mapping method and crosstalk-adaptive scheduling to further optimize the quantum circuit. Our architecture reduces depth by an average of 18% and 27%, and by up to 50% and 60%, compared to lattice and heavy-hex architectures, respectively. With crosstalk optimization through adaptive scheduling, we achieve performance improvements of 35%, 20%, and 160% on fully-enabled grid, lattice, and heavy-hex topologies, respectively.
A comprehensive study on a tapered Paul trap: from design to potential applications
Authors: Deng Bo , Göb Moritz , Masuhr Max , Roßnagel Johannes , Jacob Georg , Wang Daqing , Singer Kilian
Published: October 2024

We present a tapered Paul trap whose radio frequency electrodes are inclined to the symmetric axis of the endcap electrodes, resulting in a funnel-shaped trapping potential. With this configuration, a charged particle confined in this trap has its radial degrees of freedom coupled to that of the axial direction. The same design was successfully used to experimentally realize a single-atom heat engine, and with this setup amplification of zeptonewton forces was implemented. In this paper, we show the design, implementation, and characterization of such an ion trap in detail. This system offers a high level of control over the ion’s motion. Its novel features promise applications in the field of quantum thermodynamics, quantum sensing, and quantum information.
Reactive power compensation applications of matrix converter: a systemic review
Authors: Ishaq Muhammad , Ullah Kifayat , Abbass Muhammad Jamshed , Awais Muhammad
Published: October 2024

Matrix converters are bi-directional power electronic devices consisting of an array of solid-state switches directly connecting a source and load without an intermediate DC link. Historically, matrix converters have seen limited industrial adoption due to the complexity of their control mechanisms. However, in recent decades, matrix converter-based systems have emerged as viable alternatives for reactive power management because of the development of reliable and straightforward commutation methods. This paper provides a comprehensive analysis of matrix converter control strategies for reactive power compensation. Initially, an overview of matrix converter technology is provided. Then, Flexible Alternating Current Transmission System (FACTS) devices, renewable energy integration systems, and electric drives adopted in the last decade for reactive power compensation are discussed. The various ways these topologies have been employed for reactive power management are investigated, and an overview of direct and indirect matrix converter topologies is given. The application of control techniques such as model predictive control, space vector modulation, direct torque control, and others for reactive power compensation is then explored and their performance compared. Finally, directions for future research are identified. The analysis shows that matrix converter technology and control mechanisms have advanced substantially, demonstrating promise for wider industrial reactive power compensation applications. The continued development of cutting-edge matrix converter topologies and increasingly sophisticated control strategies will further broaden their reactive power compensation potential.
Enhancing thermal management systems: a machine learning and metaheuristic approach for predicting thermophysical properties of nanofluids
Authors: Saha Aritra , Basu Ankan , Banerjee Sumanta
Published: October 2024

In thermal engineering, predicting nanofluid thermophysical properties is essential for efficient cooling systems and improved heat transfer. Traditional methods often fall short in handling complex datasets. This study leverages machine learning (ML) and metaheuristic algorithms to predict key nanofluid properties, such as specific heat capacity (SHC), thermal conductivity (TC), and viscosity. By utilizing Artificial Neural Networks (ANN), Support Vector Regression (SVR), Gradient Boosting (GB), and Linear Regression (LR), alongside metaheuristic models like Differential Evolution (DE) and Particle Swarm Optimization (PSO), we achieve superior prediction accuracy compared to traditional models. The integration of these computational techniques with empirical data demonstrates their effectiveness in capturing the complex dynamics of thermofluids. Our results validate the precision of ML and metaheuristic models in predicting nanofluid properties and underscore their potential as robust tools for researchers and practitioners in thermal engineering. This work paves the way for future exploration of ML algorithms in thermal management, marking a significant advancement in optimizing nanofluid applications in industry and research.
Advanced optimization of elastic sheets for solar parabolic trough concentrators: integrating particle swarm optimization and genetic algorithms
Authors: Guo Pengzhen , Xia Zhou , Li Heng , Zhang Yanlong , Wu Hongyu , Li Lifang , Liu Rongqiang
Published: October 2024

The fabrication of solar parabolic trough concentrators using flat elastic sheets presents a straightforward and cost-effective method. This paper introduces an optimization technique centered on stiffness adjustment, harnessing elastic buckling to attain precise parabolic shapes in these concentrators. Through an enhanced Particle Swarm Optimization-Genetic Algorithm (PSO-GA), strategically punched holes are optimized on the flat sheet, allowing for the attainment of perfect parabolic shapes by controlling the chord length with a positional rod or cable. The efficacy of this approach is showcased not only through interactive finite element analysis and ray tracing software simulations but also via experimental sunlight concentration. A geometric concentration ratio of up to 145.16 is achieved, underscoring the effectiveness of this innovative concept. This approach facilitates the simple fabrication and transportation of flat mirror elements to field sites, where they can be assembled into parabolic trough concentrators, offering potential cost reductions and highly efficient solar energy solutions.
Advancing high-volume GaN manufacturing: precision simulation of electrical and geometrical deviations through current spreading
Authors: Ahmad Fajri Faris Azim , Kopp Fabian , Ahmad Noorden Ahmad Fakhrurrazi , Gomez-Iglesias Alvaro
Published: October 2024

Manufacturing process deviations pose significant challenges in GaN manufacturing especially when modern technologies demand extreme chip densities. More than a thousand of each of three distinct GaN-based flip-chips were manufactured where the standard deviations of the measured voltages ranged from 13 to 23 mV. By integrating Monte Carlo and finite element methods in the simulations which relies on the theoretical models, the results were validated by comparing the voltage measurements of the three thousand manufactured chips. Validation was even successful considering the voltage deviations of the three distinct designs equivalently, i.e., affected each wafer’s geometrical and electrical properties. In addition, comparing the three designs, Chip A emerged as the optimal choice for low current resistivity. Looking ahead, our theoretical modeling and simulation hold promise for high-accuracy predictions in high-volume GaN-based chip manufacturing, enhancing reliability and performance.
Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired neural networks for the 3D microstructure evolution of materials via Cahn–Hilliard flow
Authors: Lanzoni Daniele , Fantasia Andrea , Bergamaschini Roberto , Pierre-Louis Olivier , Montalenti Francesco
Published: October 2024

A Convolutional Recurrent Neural Network (CRNN) is trained to reproduce the evolution of the spinodal decomposition process in three dimensions as described by the Cahn–Hilliard equation. A specialized, physics-inspired architecture is proven to provide close accordance between the predicted evolutions and the ground truth ones obtained via conventional integration schemes. The method can accurately reproduce the evolution of microstructures not represented in the training set at a fraction of the computational costs. Extremely long-time extrapolation capabilities are achieved, up to reaching the theoretically expected equilibrium state of the system, consisting of a layered, phase-separated morphology, despite the training set containing only relatively-short, initial phases of the evolution. Quantitative accordance with the decay rate of the free energy is also demonstrated up to the late coarsening stages, proving that this class of machine learning approaches can become a new and powerful tool for the long timescale and high throughput simulation of materials, while retaining thermodynamic consistency and high-accuracy.
Integration type operators and point evaluation on weighted Bergman spaces of Dirichlet series
Authors: Gómez-Cabello Carlos , Lefèvre Pascal , Queffélec Hervé
Published: October 2024

The theory of Banach spaces of Dirichlet series has drawn an increasing attention in the recent 25 years. One of the main interest of this new theory is that of defining analogues of the classical spaces of analytic functions on the unit disc. In this sense, Bergman spaces were introduced several years ago contributing to broaden the picture of this theory. In the paper presenting these new family of spaces, some of its most essential questions were considered. Among them, some partial estimates of the norm of the pointwise evaluation functional were given. In this work, we introduce a version of the Riemann-Liouville semigroup acting on these spaces, and, with this new tool, we are able to estimate the norm of this functional.
FAP20 is required for flagellum assembly in Trypanosoma brucei
Authors: Shimogawa Michelle M. , Jonnalagadda Keya , Hill Kent L.
Published: October 2024

Trypanosoma brucei is a human and animal pathogen that depends on flagellar motility for transmission and infection. The trypanosome flagellum is built around a canonical “9+2” axoneme, containing nine doublet microtubules (DMTs) surrounding two singlet microtubules. Each DMT contains a 13-protofilament A-tubule and a 10-protofilament B-tubule, connected to the A-tubule by a conserved, non-tubulin inner junction (IJ) filament made up of alternating PACRG and FAP20 subunits. Here we investigate FAP20 in procyclic form  T. brucei. A FAP20-NeonGreen fusion protein localized to the axoneme as expected. Surprisingly, FAP20 knockdown led to a catastrophic failure in flagellum assembly and concomitant lethality. This differs from other organisms, where FAP20 is required for normal flagellum motility, but generally dispensable for flagellum assembly and viability. Transmission electron microscopy demonstrates failed flagellum assembly in FAP20 mutants is associated with a range of DMT defects and defective assembly of the paraflagellar rod, a lineage-specific flagellum filament that attaches to DMT 4-7 in trypanosomes. Our studies reveal a lineage-specific requirement for FAP20 in trypanosomes, offering insight into adaptations for flagellum stability and motility in these parasites and highlighting pathogen versus host differences that might be considered for therapeutic intervention in trypanosome diseases.
Risk Factors Associated With Exaggerated Blood Pressure Response at the Time of Exercise Treadmill Stress Test
Authors: Katsi Vasiliki , Ioakeimidis Nikolaos , Dimitroglou Yannis , Vlachopoulos Charalambos , Tsioufis Konstantinos
Published: October 2024

BACKGROUND

Exaggerated blood pressure response (EBPR) to exercise stress testing (EST) may be a marker of future hypertension and carry valuable information for the prediction of cardiovascular events. We sought to evaluate the clinical and resting EST parameters associated with an increased likelihood of EBPR.

METHODS

The records of 14,073 patients (mean age: 55 ± 11 years) without known cardiovascular disease who underwent a treadmill EST were analyzed.

RESULTS

The overall prevalence of arterial hypertension was 44%. A considerable proportion (24%) of patients exhibited EBPR. Multivariate analysis of the entire study population showed that middle-aged individuals (40–60 years old), resting systolic BP > 130 mmHg and/or diastolic BP > 80 mmHg, known arterial hypertension, current cigarette smoking, and family history of premature coronary artery disease are all independent risk factors for EBPR (all P < 0.001). Although the presence of arterial hypertension increased the likelihood of EBPR in the analysis of the entire population, the relevant association in subjects above 60 years old is statistically nonsignificant (P = 0.120). Notably, the pre-test systolic BP > 130 mmHg and/or diastolic BP > 80 mmHg level increased significantly the likelihood of manifesting EBPR in all age categories (<40, 40–60, and >60 years old) independent of hypertension presence and in all hypertensive patients independently of antihypertensive treatment intake (all P < 0.001).

CONCLUSIONS

Considering the diagnostic and prognostic utility of EBPR during treadmill EST the clinical and resting hemodynamic parameters that increase the likelihood of EBPR are targets for interventions and preventive measures to modify lifestyle risk behaviors and reduce hypertension and cardiovascular risk factors in the early stages.
Increased beta synchronization underlies perception-action hyperbinding in functional movement disorders
Authors: Pastötter Bernhard , Weissbach Anne , Takacs Adam , Moyé Josephine , Verrel Julius , Chwolka Fabian , Friedrich Julia , Paulus Theresa , Zittel Simone , Bäumer Tobias , Frings Christian , Beste Christian , Münchau Alexander
Published: October 2024

Functional movement disorders are amongst the most common and disabling neurological conditions, placing a significant burden on the healthcare system. Despite the frequency and importance of functional movement disorders, our understanding of the underlying pathophysiology is limited, hindering the development of causal treatment options. Traditionally, functional movement disorders were considered as a psychiatric condition, associated with involuntary movements triggered by psychological stressors. Recent neurophysiological studies have unveiled cognitive alterations in affected individuals, suggesting that functional movement disorders might be better characterized by overarching neural principles governing cognitive functions. For instance, recent research has shown that the retrieval of stimulus-response bindings is altered in patients with functional movement disorders. Building upon these recent findings, our study delves into whether the initial integration of stimulus and response information is also disrupted in patients with functional movement disorders. To accomplish this, we reanalysed previously collected EEG data using refined analysis methods that provide insights into oscillatory activity and functional neuroanatomy associated with the integration of stimulus-response bindings. Our results demonstrate that post-movement beta synchronization (i) predicts behavioural stimulus-response binding and (ii) is significantly increased in patients with functional movement disorders compared to healthy controls. Utilizing beamformer analysis, we localized the difference effect to a cluster centred around the left supplementary motor area and the correlation effect to the right supplementary motor area. Extending beyond recent research that focused on the retrieval of stimulus-response bindings, our present findings reveal that the integration of stimulus and response information is already impaired in patients with functional movement disorders. These results uncover a phenomenon of hyperbinding between perception and action, which may represent a fundamental mechanism contributing to the movement impairments in patients with functional movement disorders.
Diagnostic performance of quantitative perfusion cardiac magnetic resonance imaging in patients with prior coronary artery disease
Authors: Hoek Roel , Borodzicz-Jazdzyk Sonia , van Diemen Pepijn A , Somsen Yvemarie B O , de Winter Ruben W , Jukema Ruurt A , Twisk Jos W R , Raijmakers Pieter G , Knuuti Juhani , Maaniitty Teemu , Underwood S Richard , Nagel Eike , Robbers Lourens F H J , Demirkiran Ahmet , von Bartheld Martin B , Driessen Roel S , Danad Ibrahim , Götte Marco J W , Knaapen Paul
Published: October 2024

Aims

The diagnostic performance of quantitative perfusion cardiac magnetic resonance (QP-CMR) imaging has scarcely been evaluated in patients with a history of coronary artery disease (CAD) and new onset chest pain. The present study compared the diagnostic performance of automated QP-CMR for the detection of fractional flow reserve (FFR) defined hemodynamically significant CAD with visual assessment of first-pass stress perfusion CMR (v-CMR) and quantitative [15O]H2O positron emission tomography (PET) imaging in a true head-to-head fashion in patients with prior CAD.

Methods and results

This PACIFIC-2 substudy included 145 symptomatic chronic coronary symptom patients with prior myocardial infarction and/or percutaneous coronary intervention. All patients underwent dual-sequence, single-bolus perfusion CMR, and [15O]H2O PET perfusion imaging followed by invasive coronary angiography with three-vessel FFR. Hemodynamically significant CAD was defined as an FFR ≤ 0.80. QP-CMR, v-CMR, and PET exhibited a sensitivity of 66, 67, and 80%, respectively, whereas specificity was 60, 62, and 63%. Sensitivity of QP-CMR was lower than that of PET (P = 0.015), whereas the specificity of QP-CMR and PET was comparable. Diagnostic accuracy and area under the curve of QP-CMR (64% and 0.66) was comparable to both v-CMR [66% (P = not significant [NS]) and 0.67 (P = NS)] and PET [74% (P = NS) and 0.78 (P = NS)].

Conclusion

In patients with prior myocardial infarction and/or percutaneous coronary intervention, the diagnostic performance of QP-CMR was comparable to visual assessment of first-pass stress perfusion CMR and quantitative [15O]H2O PET for the detection of hemodynamically significant CAD as defined by FFR.