bluuebunny/crossref_metadata_2025 huggingface dataset:
Online detection method for magnetic suspension concentration based on machine vision
Authors: Yang Yun , Han Baohu , Zuo Jinzhao , Li Long , Li Kenan
Published: July 2024

With the intelligent development of magnetic particle inspection, the quality of magnetic indications formed at cracks is closely related to the accuracy of magnetic particle inspection image analysis results. The concentration of magnetic suspension is a key process parameter affecting the quality of magnetic indication formation. Hence, this study presents an online detection method based on machine vision for measuring magnetic suspension concentration. The method initially enhances the contrast of images of the pear-shaped measuring tube containing magnetic suspension and then extracts scale lines through feature analysis and morphological processing. A method for extracting the magnetic particle sedimentation area of magnetic suspension based on a dual-threshold segmentation algorithm is proposed. The contour filtering algorithm and pixel calibration method are used to obtain the magnetic particle concentration of the non-estimation and estimation areas based on scale line extraction, ultimately forming an online accurate detection method for magnetic suspension concentration values. Experiments were conducted to validate the method against different concentrations, turbidity levels, tilting angles of the pear-shaped measuring tube, and ambient brightness. The results show that the error in magnetic suspension concentration detection based on this method is within 5%. This has certain reference value for the stable control of magnetic suspension concentration and for enhancing the reliability of intelligent decision-making results in magnetic particle inspection.
Domain generalized open-set intelligent fault diagnosis based on feature disentanglement meta-learning
Authors: Zhou Xiangdong , Deng Xiao , Liu Zhengwu , Shao Haidong , Liu Bin
Published: July 2024

Existing domain generalization (DG) -based intelligent fault diagnosis methods mainly focus on learning domain-invariant features. However, in practical scenarios, these features are difficult to extract and effectively distinguish from class-related features. Moreover, these methods often assume identical label distributions between the source and target domain, making it challenging to handle scenarios where unknown classes exist in the target domain. To address these issues, this paper proposes a domain generalized open-set intelligent fault diagnosis method based on feature disentanglement meta-learning. A binary mask feature disentanglement module is constructed to overcome the information loss caused by feature reconstruction, enabling the separation of domain-specific and class-related features. Additionally, a meta-purification loss function is defined, incorporating a correlation loss term to remove impurity features from the class-related features, and further purifying class information through feature combination pairing. The method is trained on multiple source domains using a meta-learning strategy and generalized to target domains with unknown classes. The method is utilized for bearing fault diagnosis, designing multi-task experimental scenarios under different rotational speeds, and compared with existing DG methods. Experimental results show that the proposed method exhibits excellent generalization ability and effectively addresses the issue of domain generalized open-set fault diagnosis.
Autonomous ground vehicle gravity anomaly measurement and dynamic error compensation
Authors: Li Xinyu , Zhou Zhaofa , Zhang Zhili , Chang Zhenjun , Hao Shiwen , Duan Hui
Published: July 2024

To address the issue that dynamic gravity anomaly measurement is overly dependent on GNSS and cannot be measured autonomously at this stage, this paper proposes an autonomous ground vehicle dynamic gravity anomaly measurement method based on a strapdown inertial navigation system (SINS), odometer (OD), barometer and platform gravimeter. The SINS/OD/barometer integrated navigation solution delivers high-precision navigation parameters, completes the calculation of correction terms, and performs the autonomous dynamic gravity anomaly measurement combined with the primary measurement results of the platform gravimeter. Numerical calculations provide the requirements for the application of the proposed method, and the cut-off frequency for extracting gravity anomalies is 0.02 Hz, as determined by power spectral density analysis. In order to further improve the measurement accuracy and account for dynamic errors caused by vehicle maneuvering, a long-short-term memory (LSTM) model of recurrent neural network is introduced. A series of experiments under multiple circumstances with repeated lines were conducted in Tianjin, China, and the static measurements along the line were taken using CG-5 to provide true values of gravity anomalies. The results demonstrate that the autonomous measurement scheme can achieve accuracy comparable to GNSS-assisted, and that dynamic error compensation algorithm based on LSTM improves the dynamic gravity measurements accuracy significantly without sacrificing the spatial resolution of gravity anomalies.
Systematic investigation on the rational design and optimization of bi-based metal oxide semiconductors in photocatalytic applications
Authors: Song Yuan-Jun , Xia Peng , Zhang Xiao-Yang , Zhang Tong
Published: July 2024

To address the global energy shortage and mitigate greenhouse gas emissions on a massive scale, it is critical to explore novel and efficient photocatalysts for the utilization of renewable resources. Bi-based metal oxide (Bi
x
MO
y
) semiconductors composed of bismuth, transition metal, and oxygen atoms have demonstrated improved photocatalytic activity and product selectivity. The vast number of element combinations available for Bi
x
MO
y
materials provides a huge compositional space for the rational design and isolation of promising photocatalysts for specific applications. In this study, we have systematically investigated the electronic and optical properties over Bi2O3 and a series of selected Bi
x
MO
y
group materials (BiVO4, BiFeO3, BiCoO3, and BiCrO3) by calculating band structure, basic optical property features, mobility and separation of charge carriers. It is clearly noted that the band gap and band edge position of the Bi
x
MO
y
group materials can be tuned in a wide range in comparison to Bi2O3. Similarly, the light response of Bi
x
MO
y
also can be broadened from the ultraviolet to the visible light region by adjusting the selection of transition metals. Additionally, the analysis of the effective mass of charge carriers of these materials further confirms their possibility in photocatalytic reaction applications because of the appropriate separation efficiency and mobility of carriers. A selection of experimental investigations on the crystal structure, composition, and optical properties of Bi2O3, BiVO4, and BiFeO3 as well as their catalytic performance in the degradation of methylene blue over was also conducted, which agree well with the theoretical predictions.
Monte Carlo simulation of initial and volume ion recombination correction factor in plane parallel ionization chambers exposed to ion beams
Authors: Orts Marina , Rossomme Severine , Souris Kevin , Sterpin Edmond
Published: July 2024

Objective. Accurate reference dosimetry with ionization chambers (ICs) relies on correcting for various influencing factors, including ion recombination. Theoretical frameworks, such as the Boag and Jaffe theories, are conventionally used to describe the ion recombination correction factors. Experimental methods are time consuming, the applicability may be limited and, in some cases, impractical to be used in clinical routine. The development of simulation tools becomes necessary to enhance the understanding of recombination under circumstances that may differ from conventional use. Before progressing, it is crucial to benchmark novel approaches to calculate ion recombination losses under known conditions. In this study, we introduce and validate a versatile simulation tool based on a Monte Carlo scheme for calculating initial and volume ion recombination correction factors in air-filled ICs exposed to ion beams with clinical dose rates. Approach. The simulation includes gaussian distribution of ion positions to model the distribution of charge carriers along the chamber volume. It accounts for various physical transport effects, including drift, diffusion, space charge screening and free electron fraction. To compute ion recombination, a Monte Carlo scheme is used due to its versatility in multiple geometries, without exhibiting convergence problems associated with numerically solved procedures. Main results. The code is validated in conventional dose rates against Jaffe’s theory for initial recombination and Boag’s theory for volume recombination based on parameters derived from experimental data including proton, helium and carbon ion beams measured with a plane parallel IC. Significance. The simulation demonstrates excellent agreement, typically 0.05% or less relative difference with the theoretical and experimental data. The current code successfully predicts ion recombination correction factors, in a large variety of ion beams, including different temporal beam structures.
FAST (fast analytical simulator of tracer)-PET: an accurate and efficient PET analytical simulation tool
Authors: Li Suya , Hamdi Mahdjoub , Dutta Kaushik , Fraum Tyler J , Luo Jingqin , Laforest Richard , Shoghi Kooresh I
Published: July 2024

Objective. Simulation of positron emission tomography (PET) images is an essential tool in the development and validation of quantitative imaging workflows and advanced image processing pipelines. Existing Monte Carlo or analytical PET simulators often compromise on either efficiency or accuracy. We aim to develop and validate fast analytical simulator of tracer (FAST)-PET, a novel analytical framework, to simulate PET images accurately and efficiently. Approach. FAST-PET simulates PET images by performing precise forward projection, scatter, and random estimation that match the scanner geometry and statistics. Although the same process should be applicable to other scanner models, we focus on the Siemens Biograph Vision-600 in this work. Calibration and validation of FAST-PET were performed through comparison with an experimental scan of a National Electrical Manufacturers Association (NEMA) Image Quality (IQ) phantom. Further validation was conducted between FAST-PET and Geant4 Application for Tomographic Emission (GATE) quantitatively in clinical image simulations in terms of intensity-based and texture-based features and task-based tumor segmentation. Main results. According to the NEMA IQ phantom simulation, FAST-PET’s simulated images exhibited partial volume effects and noise levels comparable to experimental images, with a relative bias of the recovery coefficient RC within 10% for all spheres and a coefficient of variation for the background region within 6% across various acquisition times. FAST-PET generated clinical PET images exhibit high quantitative accuracy and texture comparable to GATE (correlation coefficients of all features over 0.95) but with ∼100-fold lower computation time. The tumor segmentation masks comparison between both methods exhibited significant overlap and shape similarity with high concordance CCC > 0.97 across measures. Significance. FAST-PET generated PET images with high quantitative accuracy comparable to GATE, making it ideal for applications requiring extensive PET image simulations such as virtual imaging trials, and the development and validation of image processing pipelines.
MANTA: a negative-triangularity NASEM-compliant fusion pilot plant
Authors:   The MANTA Collaboration, Rutherford G , Wilson H S , Saltzman A , Arnold D , Ball J L , Benjamin S , Bielajew R , de Boucaud N , Calvo-Carrera M , Chandra R , Choudhury H , Cummings C , Corsaro L , DaSilva N , Diab R , Devitre A R , Ferry S , Frank S J , Hansen C J , Jerkins J , Johnson J D , Lunia P , van de Lindt J , Mackie S , Maris A D , Mandell N R , Miller M A , Mouratidis T , Nelson A O , Pharr M , Peterson E E , Rodriguez-Fernandez P , Segantin S , Tobin M , Velberg A , Wang A M , Wigram M , Witham J , Paz-Soldan C , Whyte D G
Published: July 2024

The MANTA (Modular Adjustable Negative Triangularity ARC-class) design study investigated how negative-triangularity (NT) may be leveraged in a compact, fusion pilot plant (FPP) to take a ‘power-handling first’ approach. The result is a pulsed, radiative, ELM-free tokamak that satisfies and exceeds the FPP requirements described in the 2021 National Academies of Sciences, Engineering, and Medicine (NASEM) report ‘Bringing Fusion to the U.S. Grid’ (2021 Bringing Fusion to the U.S. Grid). A self-consistent integrated modeling workflow predicts a fusion power of 450 MW and a plasma gain of 11.5 with only 23.5 MW of power to the scrape-off layer (SOL). This low P
SOL together with impurity seeding and high density at the separatrix results in a peak heat flux of just 2.8 MW m−2. MANTA’s high aspect ratio provides space for a large central solenoid (CS), resulting in ∼15 minute inductive pulses. In spite of the high B fields on the CS and the other REBCO-based magnets, the electromagnetic stresses remain below structural and critical current density limits. Iterative optimization of neutron shielding and tritium breeding blanket yield tritium self-sufficiency with a breeding ratio of 1.15, a blanket power multiplication factor of 1.11, toroidal field coil lifetimes of

3100
±
400

MW · yr, and poloidal field coil lifetimes of at least

890
±
40

MW · yr. Following balance of plant modeling, MANTA is projected to generate 90 MW of net electricity at an electricity gain factor of

∼

2.4

. Systems-level economic analysis estimates an overnight cost of US$3.4 billion, meeting the NASEM FPP requirement that this first-of-a-kind be less than US$5 billion. The toroidal field coil cost and replacement time are the most critical upfront and lifetime cost drivers, respectively.
Parsimonious statistical techniques for the detection of drifts toward dangerous operational conditions in tokamaks
Authors: Craciunescu Teddy , Murari Andrea ,   on behalf of JET Contributors,   the EUROfusion Tokamak Exploitation Team
Published: July 2024

The approaching initial operation of major new tokomaks is rendering more pressing the need for effective disruption prediction techniques. The required tools should be not only accurate but also capable of operating with a minimum number of signals, because in the first campaigns of new devices typically only a very limited number of diagnostics is available. The present work reports the results obtained with two advanced statistical techniques, chaos onset and concept drift (CD). These methods are capable of detecting the plasma drifting towards dangerous regions of the operational space using only global signals such as the plasma current or the locked mode amplitude. The obtained performances meet the requirements of mitigation in devices such as JT60-SA and ITER at the beginning of their operation. The computational times of the chaos onset approach are already of the order of 1 ms on laptop computers, whereas the CD technique requires implementation on FPGAs or GPUs to be compatible with real time requirements.
2D axisymmetric electromagnetic modeling of HTS coils based on T-A formulation with modified Newman boundary conditions
Authors: Chen Yong , Wang Qiuliang , Wang Kangshuai , Zhou Benzhe , Liu Shixian , Ji Xiaoyu , Wang Lei , Liu Jianhua
Published: July 2024

The T-A formulation based on thin film approximation has been widely used in electromagnetic modeling of high temperature superconducting (HTS) coated conductors (CCs). However, with the emergence of no-insulation (NI) HTS coils and its variant HTS coils, the electrical connection of HTS coils has become increasingly complex, and the traditional T-A formulation is challenging to handle the problems of conductors with non-negligible thickness and current sharing. This paper firstly describes the Neumann boundary condition of the T-A formulation under 2D axisymmetric symmetry in detail, as well as the conversion of different boundary conditions. And additional voltage variable is added to correct the Newman boundary condition from the perspective of circuit. Then, considering HTS CCs series or parallel stacking to carry current, the effectiveness of this method is verified by comparing with benchmark model. Finally, we extend the application range of the T-A formulation with modified Newman boundary conditions to simulate thick superconductors, and naturally process current sharing of azimuthal and radial current in circular NI HTS coils.
Complex Branch Pipe Layout Optimization Based on Machine Learning and Improved Grey Wolf Algorithm
Authors: Ming Y R , Liu S B
Published: July 2024

Branch pipes are widely found in complex equipment, and its layout planning and design has an important impact on the quality and efficiency of equipment design. In this paper, a branch pipe layout planning method based on machine learning and improved grey wolf algorithm is proposed. Firstly, the branch pipe layout problem is decomposed into a series of “between two points” pipe layout and “point to line” pipe layout problems to reduce the complexity of the problem. Secondly, the Q-learning algorithm is applied to solve the “between two points” pipe layout path solving problem, and then combined with the improved grey wolf algorithm to optimize the “point to line” pipe path solving. Finally, a simulation system is built based on Siemens NX and MATLAB platform, and the validity of the proposed method is verified by simulation cases.
Research on Multi-type and Multi-level Real-time Simulation and Optimization of New Power System
Authors: Xu Changqing
Published: July 2024

Aiming at the problem that the current real-time simulation algorithm is difficult to improve the performance and accuracy of multi-type and multi-level real-time simulation when dealing with new power systems, we propose a new multi-type and multi-level real-time simulation and optimization algorithm for power systems. Firstly, the efficiency and accuracy of the solution are improved by directly updating the conductance nodes (Gnodes) and current nodes (Inodes) on power system components, and the updating of Gnodes and Inodes is replaced by the prior calculation based on the inverse matrix (Ginv) of admittance matrix, thus further optimizing the simulation solution process and reducing the computational complexity. Then, the efficient numerical method, data structure optimization, and parallel computing technology are used to optimize the construction process of the inverse matrix (Ginv) of the admittance matrix to reduce the computational complexity and memory consumption of electromagnetic transient simulation. Finally, the idea of the sparse matrix is introduced to optimize the operation process of Gstruct and improve the calculation speed of the simulation solution. The research proves that the multi-type and multi-level real-time simulation solution and its optimization method of new power systems can be studied more systematically through the above technical route, which can improve the efficiency and accuracy of power system simulation solutions and provide strong support for practical application.
Wind turbine blade fault diagnosis technology based on Efficient-YOLOv5s algorithm
Authors: Qingze Shen , Hongjiang Wang , Qin Dai , Yingcai Gao
Published: July 2024

The daily operation and maintenance of wind turbine blades in wind power plants requires the application of target detection algorithms that are both accurate in detection and fast in training. For the current wind turbine blade fault detection algorithms in the dataset when the number of samples of the problem of slow training time through the bi-directional feature pyramid network of the fast weighted normalised fusion to improve the training speed, for the small size of the fault detection of the low accuracy of the problem through the bi-directional feature pyramid network of the better use of multiscale information to improve the detection accuracy and through the coordinate attention to generate bidirectional complementary feature maps to enhance the object of interest to further improve the accuracy of detection. In this way, an efficient wind turbine blade fault detection model (Efficent-YOLOv5s) is proposed on the basis of the YOLOv5s model. Through the experimental validation of the homemade dataset, the results show that compared with the YOLOv5s model, the detection map0.5 value and accuracy of the efficient wind turbine blade fault detection model are improved by 0.5% and 0.6%, respectively, and the average training time is shortened by 4s/epoch, which verifies that the model is effective.
Research on key technologies of digital sensing and fault warning of isolation switch in GIS
Authors: Jiuye Zhang , Yubo Zhao , Haoli Liu , Jing Xu , Shaoqing Peng , Liang Wang
Published: July 2024

GIS device is a small electrical device. It is widely used in power systems due to its small size, easy installation, reliable operation, and anti-noise. In recent years, GIS isolation switches have frequently caused power grid accidents due to their own reasons, causing great economic losses to the power grid and users. Therefore, in GIS, in order to improve the stability of the power system, the isolation switch in GIS must be monitored and fault diagnosed. This article analyzes the primary and secondary working mechanisms of GIS. Starting from the basic principles of primary and secondary, this paper conducts a theoretical analysis of various parameters in GIS, and conducts a simple analysis of its sensing performance and monitoring system. It also briefly introduces common faults in GIS, providing a theoretical basis for research on key technologies of digital sensing and fault warning of isolation switch in GIS.
Optimal allocation of offshore wind power and energy storage considering source-load power stochasticity
Authors: Zhang Xiaohu , Zhang Mengyao , Xu Ling , Huang Ruanming , Li Canbing
Published: July 2024

Large-scale offshore wind generation has been integrated to power grids in China. The annual increase in electric vehicles, air conditioning systems, and other electrical facilities has intensified the randomness and volatility of power supply and demand, presenting significant challenges to the safe and economical operation of power systems. Energy storage systems serve as regulators in the power grid, yet the electrical performance and costs associated with various storage technologies differ considerably. Consequently, the strategic planning and development of energy storage solutions tailored to specific local conditions have emerged as critical areas of research. This paper presents an in-depth analysis of power characteristics across source loads, explores an optimized configuration approach for energy storage, and validates this method through a numerical example. The findings confirm the effectiveness of the proposed configuration strategy and offer pertinent recommendations for the implementation of energy storage solutions.
Mechanisms of middle-frequency oscillations in an offshore wind farm induced by the converter current inner loops
Authors: Chen Yong , Huang Hui , Yang Ruixiong , Ren Xingwang , Sang Yawei , Wu Haobin
Published: July 2024

Middle-frequency oscillation instability is one of the important issues that threats the safe integration of offshore wind farms. However, analytical explanations to key affecting factors and laws for the middle-frequency oscillation are not clear yet, which makes it difficult to avoid this kind of oscillation effectively. Therefore, in this paper, mechanism for the middle-frequency oscillation induced by the dynamics of converter current inner loops is studied in-depth. First, small-signal transfer function model for a general offshore wind farm integrated via AC submarine cable is established. Then impact of the AC submarine cable and control parameters of the converter current inner loops on oscillation stability of the wind farm is analysed via eigenvalue analysis. It is found that with the length of AC submarine cable increases, frequency for the open-loop pole of the AC grid decreases. When open-loop pole of the AC grid gets close that of the PMSGs on complex plane, the near strong mode resonance can cause middle-frequency oscillation of the system. Finally, effectiveness of the conclusions drawn is evaluated through nonlinear simulations.
A Method for Identifying Power Equipment in Foggy Substation Based on Improved YOLOv4
Authors: Bao Meiling , Zhang Bin , Li Dongyu , Wu Linqiao , Jing Lantao , Wang Liang
Published: July 2024

In foggy weather, inspection robots detect low visibility and unclear targets in substation power equipment, and the commonly used target detection algorithms have too many parameters, making it difficult to achieve real-time requirements when deployed on inspection robots. To this end, a lightweight substation power equipment identification method combining Cycle Dehaze defogging algorithm is proposed. Pre process the collected fog map of the substation to improve the clarity and visibility of the target power equipment; Introducing MobileNetv3 and deep separable convolution in YOLOv4 network to achieve model lightweight; To increase the precision of power equipment identification, incorporate the SE attention mechanism into the target detection network. Based on the testing results, it is possible to reach a recognition mAP of 92.5% by combining Cycle Dehaze and improved YOLOv4, as the improved YOLOv4 has a detection speed that is 15.59 frames/second faster than the YOLOv4 method. The model parameter quantity has been reduced by 80.21%, which is more conducive to deployment on substation inspection robots.
Multi-Target Recognition of Substation Infrared Image Based on Improved Faster RCNN
Authors: Zhang Bin , Li Dongyu , Zhang Jiaxin , Wu Linqiao , Qiu Bingbing , Bao Meiling , Jing Lantao , Wang Liang
Published: July 2024

This study presents a multi-target recognition approach for substation infrared images based on enhanced Faster RCNN, which addresses the challenge of identifying several high-voltage electrical equipment in substation infrared images simultaneously. This method uses VGG16 to extract image features of a variety of electrical equipment in infrared images. Generate regional suggestions through the regional suggestion network and adjust the regional suggestions through border regression. ROI Pooling maps regional suggestions of different scales to fixed-size output vectors and sends them to Softmax for classification, and corrects the incorrectly identified parts categories according to the inclusion relationship of the regional suggestions. In the experiment, 27586 infrared photos are chosen to create an infrared data set in the voc207 format. Then, statistical analysis is performed on the recognition outcomes of 5517 infrared images in the test set. Based on the testing data, the upgraded rapid RCNN has a 92.8% recognition accuracy, which is 9.7% higher than that before, and has higher engineering practical value.
Ultra-wideband Imaging of Breast Tumors Based on Global Back Projection Algorithm
Authors: Fan Yucheng , Li Xiaoshuang , Li Zhiqiang , Wang Jingjing , Xu Huaqiang
Published: July 2024

Tumor imaging in medicine requires consideration of human safety, image quality clarity, and cost of imaging. Ultra-wideband (UWB) technology employs large bandwidth channels that enable high-speed data transmission. This determines that it can provide high-quality images quickly while still being a harmless imaging method. Therefore, it is essential to construct a UWB microwave detection tumor system. The creation of a vector network analyzer (VNA) based microwave imaging system in this work. To adapt to breast imaging, this paper improved the imaging algorithm of global back projection (GBP) based on the classical back projection algorithm. To verify the system’s feasibility, this paper performed UWB detection experiments using a breast tumor model. By comparing the simulation results, the final imaging results show that the UWB imaging system can detect tumors located at two different locations in the model and that high-quality images can be obtained in the near field using the GBP algorithm. This paper provides a reliable and low-cost method for medical diagnosis.
Focal plane imaging system based on CMOS terahertz detector
Authors: Lin Yue , Zhang Hui , Qi Feng , Liu Zhaoyang , Wang Guanwen , Wang Ningbo
Published: July 2024

Terahertz technology has shown remarkable potential for application in the field of imaging since it offers several particular advantages such as great penetration capabilities, non-ionization and high instantaneous bandwidth. This paper presents a focal plane imging system based on CMOS terathertz detector for forward-looking detection. The focal plane imaging system has several advantages, including fast scanning, simple composition, low cost, and easy integration of a CMOS detector. It is composed of a terahertz radiation source, a Polytetrafluoroethylene (PTFE) lens and a broadband CMOS detector. The detector was fabricated in a 65 nm CMOS process. The operating frequency range of the detector covers 75 GHz to 1000 GHz. Measurement results have shown that the focal plane imaging system is capable of stably imaging at frequencies of 100 GHz and 220 GHz. To address the issue of missing information in measurement images, the morphological closing algorithm is employed to process the original image, successfully filling in the missing information and improving image quality.
Physics event classification using Large Language Models
Authors: Fanelli C. , Giroux J. , Moran P. , Nayak H. , Suresh K. , Walter E.
Published: July 2024

The 2023 AI4EIC hackathon was the culmination of the third annual AI4EIC workshop at The Catholic University of America. This workshop brought together researchers from physics, data science and computer science to discuss the latest developments in Artificial Intelligence (AI) and Machine Learning (ML) for the Electron Ion Collider (EIC), including applications for detectors, accelerators, and experimental control. The hackathon, held on the final day of the workshop, involved using a chatbot powered by a Large Language Model, ChatGPT-3.5, to train a binary classifier neutrons and photons in simulated data from the GlueX Barrel Calorimeter. In total, six teams of up to four participants from all over the world took part in this intense educational and research event. This article highlights the hackathon challenge, the resources and methodology used, and the results and insights gained from analyzing physics data using the most cutting-edge tools in AI/ML.
Development and performance testing of a chamber for absorbed dose in water absolute measurement for 125I brachytherapy seeds
Authors: Hang Zhongbin , Liu Yuntao , Song Mingzhe , Wei Kexin , Wang Hongyu , Li Qingran , Ni Ning , Zhao Xu , Sun Tao , Gao Fei
Published: July 2024

The application of more and more low-energy, low-dose-rate
photon radiation seeds in brachytherapy. According to the TG43 report
and TG43-U1 report issued by the American Association of Physicists
in Medicine, both apparent activity and air kerma strength are
physical characterization parameters of brachytherapy seed
strength,which are needed to convert into water absorbed dose at the
depth of 1 cm. At present, the method of obtaining the water
absorbed dose is to convert the air kerma strength, the uncertainty
of results exceeds 5% (k = 1), which could reduce the cure rate
of the treatment. In order to address this issue ,the China
Institute of Atomic Energy has designed a device that can directly
replicate the water absorbed dose of 125I brachytherapy
seeds,which is an extrapolation chamber embedded with water
equivalent material. In order to evaluate the performance of the
extrapolation chamber, a series of experiments were carried out,
including partial pressure test, leakage current, saturation curve,
response linearity, collection area and zero point position. The
test results show that the performance parameters of the
extrapolation chamber meet the relevant requirements.
Spatial resolution improvements with finer-pitch GEMs
Authors: Flöthner K.J. , Scharenberg L. , Brask A. , Brunbauer F. , Garcia F. , Janssens D. , Ketzer B. , Lisowska M. , Muller H. , Oliveri E. , Orlandini G. , Pfeiffer D. , Ropelewski L. , Samarati J. , van Stenis M. , Veenhof R.
Published: July 2024

Gas Electron Multipliers (GEMs) are used in many particle physics experiments, employing
their `standard' configuration with amplification holes of 140 μm pitch in a
hexagonal pattern. However, the collection of the charge cloud from the primary ionisation
electrons from the drift region of the detector into the GEM holes affects the position
information from the initial interacting particle. In this paper, the results from studies with a
triple-GEM detector with an X-Y-strip readout anode are presented. It is demonstrated that GEMs
with a finer hole pitch of here 90 μm improve the detector's spatial resolution.
Within these studies, also the impact of the front-end electronics on the spatial resolution was
investigated, which is briefly discussed in the paper.
Burn-in test and thermal performance evaluation of Silicon Photomultipliers for the JUNO-TAO experiment
Authors: Chen X. , Cao G.F. , Qu M.H. , Wang H.W. , Anfimov N. , Rybnikov A. , Xu J.Y. , Su A.Q. , Chen Z.L. , Cao J. , Li Y.C. , Qi M.
Published: July 2024

This study evaluates more than 4,000 tiles made of Hamamatsu
visual-sensitive silicon photomultipier (SiPM), each with dimensions
of 5 × 5 cm2, intended for the central detector of the
Taishan Anti-neutrino Observatory (TAO), a satellite experiment of
the Jiangmen Underground Neutrino Observatory (JUNO) aimed at
measuring the reactor anti-neutrino energy spectrum with
unprecedented energy resolution. All SiPM tiles underwent a room
temperature burn-in test in the dark for two weeks, while cryogenic
testing analyzed the thermal dependence of parameters for some
sampled SiPMs. Results from these comprehensive tests provide
crucial insights into the long-term performance and stability of the
10 square meters of SiPMs operating at -50°C to detect
scintillation photons in the TAO detector. Despite some anomalies
awaiting further inspection, all SiPMs successfully passed the
burn-in test over two weeks at room temperature, which is equivalent
to 6.7 years at -50°C. Results are also used to guide
optimal SiPM selection, configuration, and operation, ensuring
reliability and sustainability in reactor neutrino
measurements. This work also provides insights for a rapid and
robust quality assessment in future experiments that employ
large-scale SiPMs as detection systems.
An 11-bit SAR ADC for high frame rate and high-dynamic X-ray imaging at future XFELs
Authors: Ji Z. , Ju X. , Lu S. , Liu S. , Sun T. , Zhang S. , Sheng Z. , Gan F. , Liu Z. , Wang T.
Published: July 2024

The paper presents the design and test results of an 11-bit
successive approximation register (SAR) ADC, suitable for massive
on-chip integration in a pixel readout chip. The objective is to
establish new digital readout architectures for X-ray pixel
detectors at future X-ray free electron laser (XFEL) facilities,
enabling high frame rates and a high dynamic range
simultaneously. The prototype chip has been designed and fabricated
in a 130 nm CMOS process, with the core circuit occupying an area
of ~ 0.034 mm2. The measured differential nonlinearity (DNL)
and integral nonlinearity (INL) are +0.78/-0.78 LSB and
+0.58/-0.52 LSB, respectively. The signal-to-noise-and-distortion
ratio (SINAD) is 61.6 dB at 2 MS/s, achieving an effective number
of bit (ENOB) of ~ 9.94-bit. The core circuit power consumption
is 47 μW at 2 MS/s with a 1.2 V supply.
Research on methods to suppress the error accumulation in the elevation direction for accelerator tunnel control network
Authors: Li Xiao , Wu Enchen , Zhang Qiuyu , Ding Ting , Cheng Zhubing , Wang Wei , He Xiaoye
Published: July 2024

In recent years, the 4th generation synchrotron radiation
light sources have gradually emerged. However, the accumulated
errors in Laser Tracker multi-station measurements make it
challenging to meet the accuracy requirements for the control
network measurement, especially in the direction of elevation. To
address this issue, this paper proposes to utilize the Hydrostatic
Leveling System (HLS) to provide high-precision external constraints
for the control network measurement. Firstly, based on the
measurement principle of capacitive HLS sensor, a system is designed
and constructed which was used to optimize the measurement accuracy
of the HLS for level difference between difference points and to
obtain the external reference. Comparison of the HLS measured values
with the nominal values measured by the CMM shows that the optimized
HLS can achieve a level difference measurement accuracy of
5 μm. On this basis, some constraint methods are proposed,
which have been verified by simulations and measurements. The
results show that the error accumulation in the elevation direction
is suppressed compared with the classical adjustment. For the 70 m
linear tunnel control network of Hefei Light Source, the maximum
error of the measurement is reduced by 90 μm (23%
improvement in accuracy) and the standard deviation of the error is
reduced by 26 μm (35% improvement in accuracy) after adding
constraint.
Visually guided swarm motion coordination via insect-inspired small target motion reactions
Authors: Billah Md Arif , Faruque Imraan A
Published: July 2024

Despite progress developing experimentally-consistent models of insect in-flight sensing and feedback for individual agents, a lack of systematic understanding of the multi-agent and group performance of the resulting bio-inspired sensing and feedback approaches remains a barrier to robotic swarm implementations. This study introduces the small-target motion reactive (STMR) swarming approach by designing a concise engineering model of the small target motion detector (STMD) neurons found in insect lobula complexes. The STMD neuron model identifies the bearing angle at which peak optic flow magnitude occurs, and this angle is used to design an output feedback switched control system. A theoretical stability analysis provides bi-agent stability and state boundedness in group contexts. The approach is simulated and implemented on ground vehicles for validation and behavioral studies. The results indicate despite having the lowest connectivity of contemporary approaches (each agent instantaneously regards only a single neighbor), STMR achieves collective group motion. STMR group level metric analysis also highlights continuously varying polarization and decreasing heading variance.
Phosphorus speciation in coastal sediment of Osaka Bay: relation to anthropogenic phosphorus loading
Authors: Rahman Muhammad Shahinur , Onodera Shin-ichi , Saito Mitsuyo , Ishida Takuya , Wang Kunyang , Hosono Takahiro , Umezawa Yu
Published: July 2024

This study assessed the effect of increased anthropogenic phosphorus (P) loading on P speciation in coastal sediments in Osaka Bay, an urbanized enclosed bay, and one of Japan’s most industrialized regions. The study analyzed Total P (TP) and determined the accumulations of five different P species Exchangeable P (Ex-P), Iron-bound P (Fe-P), Calcium-bound P (Ca-P), Detrital P (Det-P) and Organic P (Org-P)in the sediment using the sequential extraction method. We also estimated the historical P loading into Osaka Bay from major river catchments (the Yodo and Yamato Rivers) using the Soil and Water Assessment Tool. This study identified peak P loading values for the Yodo River in 1965 and the Yamato River in 1968, with the Yodo River being the primary anthropogenic source of P inflow for Osaka Bay. The concentration of TP ranges from 290.5 to 353.1 mg Kg−1 respectively, and the order of concentrations of the different P species is Org-P > Det-P > Ca-P > Fe-P > Ex-P. The results indicate a positive relationship between total P loading and Ca-P during the rapid growth period. We examined two potential mechanisms (adsorption-precipitation process and sink switching) for Ca-P formation and hypothesized that the adsorption-precipitation process is the dominant process, indicating that high anthropogenic P loading causes the accumulation of immobile Ca-P species in coastal sediments and serves as a permanent sink for P, as well as for water quality restoration. This result also suggests the possibility of reconstructing historical human-induced P loadings based on Ca-P in coastal sediments.
Effects of tropical cyclone intensity on spatial footprints of storm surges: an idealized numerical experiment
Authors: Deng Chuangwu , Tu Shifei , Gao Guoping , Xu Jianjun
Published: July 2024

Storm surges caused by tropical cyclones (TCs) have long ranked first among all types of marine disasters in casualties and economic losses, and can lead to further regional exacerbation of consequences stemming from these losses along different coastlines. Understanding the spatial footprints of storm surges is thus highly important for developing effective risk management and protection plans. To this end, we designed an ideal storm surge model based on Finite Volume Community Ocean Model to explore the relationship between TC intensity and the spatial footprint of storm surges, and its intrinsic mechanism. The spatial footprints of both positive and negative storm surges were positively correlated with TC intensity; however, the latter was more sensitive to the intensity when the TC intensity is weaker than CAT3 TC’s. The average positive storm surge footprint of CAT1 was 574 km, with CAT3 and CAT5 increasing by 6% and 25%, respectively, compared to CAT1. The average spatial footprint of the negative storm surge of CAT1 was 1407 km, with CAT3 and CAT5 increasing by 18% and 29%, respectively, compared to CAT1. The decomposition and mechanism analysis of the storm surge show that the main contributing component of the total surge at the south end of the storm’s landfall and during the time of the forerunner was the Ekman surge, whereas the contribution of the normal surge component to the north and during the time of the main surge and resurgence was dominant. In addition, not all the spatial footprints of the storm surge components increased with the TC intensity, as the total surge did, similar to the Ekman surge. These quantitative analyses and intrinsic mechanisms provide a theoretical basis for predicting and evaluating storm surge risks.
Can Nth order Born approximation be exact?
Authors: Loran Farhang , Mostafazadeh Ali
Published: July 2024

For the scattering of scalar waves in two and three dimensions and electromagnetic waves in three dimensions, we identify a condition on the scattering interaction under which the Nth order Born approximation gives the exact solution of the scattering problem for some

N
⩾
1

.
Degradation of ciprofloxacin hydrochloride in a multiphase mixed system by subaquatic gas-liquid discharge plasma
Authors: WANG 王 Mengyu 梦雨 , LIANG 梁 Jianping 建平 , LU 卢 Ke 可 , ZHOU 周 Zikai 子凯 , LIU 刘 Qinghua 清华 , YUAN 袁 Hao 皓 , WANG 王 Wenchun 文春 , YANG 杨 Dezheng 德正
Published: July 2024

In recent years, antibiotic pollution has become a serious threat to human health. In this study, a gas-liquid discharge plasma is developed to degrade ciprofloxacin hydrochloride in a multiphase mixed system containing inorganic and organic impurities. The discharge characteristics are analyzed by diagnosing the applied voltage and discharge current waveforms, as well as the optical emission spectra. The work investigates how degradation efficiency is affected by applied voltage, gas flow rate, treatment time, initial concentration as well as the addition of γ-Al2O3 pellets and peanut straw. After 70 min, the degradation efficiency of ciprofloxacin hydrochloride in the multiphase mixed system reached 99.6%. Its removal efficiency increases as the initial concentration decreases and the applied voltage increases. Besides, there is still a good degradation efficiency of ciprofloxacin hydrochloride with the addition of peanut straw. The degradation mechanism of ciprofloxacin hydrochloride is investigated through the analysis of degraded intermediates and reactive species.
Climate change considerations in environmental impacts assessment (EIA) practices: learning from climate sensitive projects in Rufiji Basin Tanzania
Authors: Shimwela Ntule , Lema Godwin
Published: July 2024

The assessment of climate change mitigation and adaptation in environmental impact assessment (EIA) practices has been mostly inconsistently addressed. Studies that use data validation from experts and relevant authorities to address the socio-political context that influence the process have been inadequate. This study aimed to bridge the gap by examining the extent to which climate change mitigation and adaptation in EIA practices in Tanzania have been considered and the broader social-political context that influence the process. A mixed research design employing sequential methods was adopted. Both primary and secondary data was used. Primary data was obtained from 22 environmental experts through a close-ended questionnaire and interview with six key informants, while secondary data was obtained from 19 EIA reports issued between January 2020 and January 2022. Purposive sampling was used to select key informants and simple random sampling was used to select environmental experts and EIA reports. Content analysis was employed to assess qualitative text data to generate descriptive information. Statistical Package for Social Sciences enabled the processing and analysis of quantitative data through frequencies and percentages. The findings revealed that 23.3% and 10.5% of reviewed reports considered climate change mitigation, and adaptation respectively, reflecting that the degree of consideration was low and was mainly limited to mitigation. A close link between the EIA legal frameworks and the EIA practices was observed and it was recommended for a review of basic frameworks to mandate and include details on climate change mitigation and adaptation assessment in environmental impacts assessment practices. The study recommends building capacity of experts and authority, preparing clear climate change assessment guidelines, and availing reliable climate data at the local level to facilitate modelling.
The Apocrypha: A Guide
Authors: Goff Matthew
Published: July 2024

Many readers of scripture, particularly in North America, are not aware that a substantial number of books were removed from their Old Testament. These books, often known collectively as the Apocrypha, were considered scripture for centuries by Christians, and for millions of Christians today still are. This book is an introduction to the Apocrypha. It discusses ancient and early modern disputes about scripture, providing context for the formation of the category “Apocrypha.” Each chapter focuses on a specific book, examining its core themes and ideas, the historical context of its composition, and later reception. This book is designed to be read along with the texts of the Apocrypha themselves, as presented in the New Oxford Annotated Bible. This volume is written not primarily for scholars, but rather for anyone who would like to learn more about these texts.
The Rehabilitation of a Wicked King
Authors: Goff Matthew
Published: July 2024

The Prayer of Manasseh is a short psalm. It is in the Old Testament of the Eastern Orthodox Church, not in the Catholic or Protestant Bibles. In 2 Kings 21, King Manasseh is depicted as a horrible king who promotes the worship of various deities. 2 Chronicles 33, by contrast, recounts him praying to God in Babylon and asking for forgiveness. God accepts his prayer and he is restored as a king of Judah. The chapter does not give the text of Manasseh’s successful prayer but does state that it was written down. The Prayer of Manasseh purports to be that prayer. The Dead Sea Scrolls include a different hymn of repentance attributed to Manasseh. The presentation of Manasseh’s repentance in 2 Chronicles generated in antiquity prayers attributed to Manasseh.