bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tolerance of Ischemia by Testis of Rats - An Experimental Study
Authors: Chatterjee S.S , Majumdar S , Chowdhury S.R. 
Published: September 2023

SummaryAn experimental study was undertaken by subjecting the testis of rats to total ischemia and studying the biopsy specimens obtained serially upto 135 minutes of ischemia. The specimens were examined under light microscope for histopathological changes. The aim was to obtain a guideline of tolerable ischemia time of the various tissues of the testis with maintenance of structural and functional integrity. It was observed that the first signs of irreversible damage i.e., marginal clumping of chromatin appeared in some of the germinal epithelial cells 60 minutes after induction of ischemia, whereas these changes occurred much later in Sertoli and Leydig cells. It is recommended that ischemia time of testis in clinical situation be restricted to lesser than this period to maintain the structural and functional integrity.
Continuous Passive Mobilisation in the Hand - An Inexpensive Small Unit
Authors: Alexander G , Garude H , Thatte M R , Mokal N J 
Published: September 2023

SummaryAn inexpensive device for continuous passive mobilization of the hand has been fabricated for usage in hand physiotherapy units. It is simple to use, effective and can be fabricated easily. 25 digits in 22 patients who suffered from a variety of hand injuries and consequent restricted joint motion were treated with this device. A high patient compliance, decreased pain and significant improvement in the range of motion were observed. The device is suitable for use in a hospital department. The concept and evolution of continuous pasive motion is also discussed.
Isolated Complex Dorsal Dislocation of the Middle Finger Metacarpophalangeal Joint
Authors: Madhusudan H P , Agarwal Anil Kumar , Sabapathy S Raja 
Published: September 2023

SummaryComplex dislocations of the metacarpophalangeal joints are rare injuries. When they, occur, they are relatively common in the thumb, index and little fingers. Isolated complex dislocation of the metacarpophalangeal jont of the middle finger is extremely rare because of the inherent anatomical stability in that joint. We are reporting a case of isolated complex dorsal dislocation of the middle finger.
The Latissimus Dorsi Myocutaneous Flap for the Exposed Cardiac Pacemaker in Children
Authors: Nanda V , Khazanchi R K 
Published: September 2023

SummaryExposure of a cardiac pacemaker implanted subcutaneously in the infraclavicular region is a difficult problem facing the plastic surgeon. The principles of treatment for salvage are control of sepsis, extensive debridement and tension free closure with locoregional flaps. Management in children is complicated by the fact that the pacing unit is of the same size as in the adult and there is little laxity of tissue in this age group. We have treated 7 children and have utilised the latissimus dorsi myocutaneous flap for salvage in 4 patients. Local skin flaps were employed in 2 children while a primary closure was possible in 1 child. Six patients have remained healed over a follow up period ranging from 6 months to 60 months. In one case we have had to explant the unit at 3 months due to persisting sepsis. Salvage of pacemakers should be attempted in all patients with pacemaker exposure. The latissimus dorsi myocutaneous flap that we have employed is a useful option when faced with this problem in children.
Bi2Te3-intercalated MnBi2Te4: ideal candidate to explore intrinsic Chern insulator and high-temperature quantum anomalous Hall effect
Authors: Zhang Yaling , Zhang Jingjing , Yang Wenjia , Zhang Huisheng , Jia Jianfeng 
Published: September 2023

Abstract
The recently discovered magnetic topological insulator of MnBi2Te4 (MBT), has been demonstrated to realize the quantum anomalous Hall (QAH) effect, while the naturally antiferromagnetic (AFM) interlayer coupling in MBT results in that the QAH effect can only be realized in odd-layered systems and at low temperature. Using first-principles calculations, we find that intercalating Bi2Te3 (BT) layers into MBT by forming MBT/(BT)
n
/MBT (n = 1–6) heterostructures can induce magnetic phase transition from AFM to ferromagnetic (FM) interlayer coupling when n⩾ 3. Specifically, MBT/(BT)3/MBT and MBT/(BT)4/MBT respectively host Curie temperatures T
c of 14 K and 11 K, which fits well the experimentally measured T
c of 12 K. Detailed band structure calculations and topological identification show that the QAH phases are well preserved for all FM heterostructures. And the topological mechanism of MBT/(BT)
n
/MBT as a function of n is revealed by employing continuum model analysis. Most importantly, the FM MBT/(BT)4/MBT has already been experimentally fabricated. Thus, our work provides a practical guideline to explore high-temperature QAH effect in MBT family of materials.
A transient heat flux sensor for PbTe thin films based on transverse Seebeck effect
Authors: Liu Songhan , Zhao Jiaxing , Liu Zhipeng 
Published: September 2023

Abstract
Among thermoelectric materials with thermoelectric effect, lead telluride (PbTe) is widely used because of its high performance and chemical stability in the medium temperature region. In this study, PbTe was creatively employed to develop a transient thin films heat flux sensor (THFS) using magnetron sputtering technique based on the transverse Seebeck effect. After static and dynamic calibration, the rise time of the THFS is 35 μs and the sensitivity is up to 7.9 μV(kW·m−2)−1, it can be measured in transient high heat flux testing environments without the need for a signal amplifier. In the experiment of measuring transient heat flux with explosion driven shock tube, the THFS has the advantages of high resolution and high dynamic response, which provides scientific basis for the study of explosion thermal damage effect and has important significance.
Spatial weighted graph-driven fault diagnosis of complex process industry considering technological process flow
Authors: Zhang Fengyuan , Liu Jie , Lu Xiang , Li Tao , Li Yi , Liu Yingwei , Tang Lei , Wang Hu 
Published: September 2023

Abstract
Each chemical process industry system possesses unique process knowledge, which serves as a representation of the system’s state. As graph-theory based methods are capable of embedding process knowledge, they have become increasingly crucial in the field of process industry diagnosis. The fault representation ability of the diagnosis model is directly associated with the quality of the graph. Unfortunately, simple fully connected graphs fail to strengthen the internal connections within the same process but weaken the interactive connections between different processes. Moreover, each node in the graph is considered equally important, making it impossible to prioritize crucial system monitoring indicators. To address the above shortcomings, this paper presents a spatial weighted graph (SWG)-driven fault diagnosis method of complex process industry considering technological process flow. Initially, the physical space sensor layout of the technological process flow is mapped into the spatial graph structure, where each sensor is regarded as a node and these nodes are connected by the k nearest neighbor algorithm. Subsequently, according to the mechanism knowledge, the sensors in the process are divided into different importance categories and weight coefficients are assigned to their nodes. The similarities between these weighted nodes are calculated, and the resulting edge information are used to construct the SWGs. Finally, the SWGs are input to a graph convolutional network, facilitating fault representation learning for fault diagnosis of complex process industry. Validation experiments are conducted using public industrial datasets, and the results demonstrate that the proposed method can effectively integrate the process knowledge to improve the fault diagnosis accuracy of the model.
Flexible rotor unbalance fault location method based on transfer learning from simulation to experiment data
Authors: Han Shuo , Wang Zihuimin , Zhang Hao , Zhang Fanyu , Han Qingkai 
Published: September 2023

Abstract
In the study of the high-speed dynamic balance of flexible rotors, rotor unbalance positioning is a challenging topic. Particularly for slender rotors, the axial position of the unbalance has an important influence on the high-speed dynamic balance. The unbalance at different axial positions is not the same or even opposite in different rotor mode vibration behaviors. If the unbalance position of a rotor can be identified, the actual unbalance of the rotor can be reduced from the root. This balance method has the same effect in each vibration mode of the rotor; hence, low-speed dynamic balance can be realized to replace high-speed dynamic balance, considerably saving on costs. Deep learning based on few labeled samples can achieve good results for the identification of unbalanced positions; however, there are infinite potential positions of unbalance in the actual rotor. It is difficult to collect sufficient labeled samples to train a reliable intelligent diagnostic model. Fortunately, a large number of rotor vibration datasets labeled with different unbalance positions are available using the rotor dynamic model, and the unbalance position data calculated using the dynamic model contain diagnostic knowledge related to the rotor unbalance position data measured in the rig. Hence, inspired by transfer learning, this study proposed a transfer learning method using dynamic model simulation and experiment data for flexible rotor unbalance fault location. Cross-domain deep transfer recognition of rotor unbalance position was realized.
A highlight removal method for autonomous recovery of cable-free seismographs in field environments
Authors: Fan Yiyao , Lin Jun , Liu Yang 
Published: September 2023

Abstract
The cable-free seismograph is an instrument for capturing seismic wave signals, which is popularly employed in underground resource exploration tasks in complex field environments due to its high flexibility. However, the efficiency of exploration operations is low because the arrangement and recovery of instruments are done manually. Therefore, autonomously arranging and recovering cable-free seismographs will hold great significance. Nevertheless, the instrument surface will produce highlight under intense illumination in field environments, which can have a negative impact on the accuracy of segmentation and contour extraction of the instrument. It will significantly reduce the visual positioning accuracy of the instrument and ultimately fail in recovery tasks. To address this problem, we analyze the characteristics of highlight on cable-free seismographs in field environments and develop a method to remove the highlight by weighting the color features of the non-highlight pixels in the neighborhoods of highlight pixels. We realize the detection of highlight pixels based on the classical modified specular-free model and propose an image terrain map model to select the weighted neighborhoods of highlight pixels to ensure that no background pixels are involved in the process of highlight removal. The experimental results show that our method meets the requirements for contour extraction and object segmentation in the autonomous instrument recovery tasks. Furthermore, it outperforms currently existing highlight removal methods in the task of highlight removal for cable-free seismographs in field environments.
An effective source number detection method for single-channel signals based on signal reconstruction and deep learning at low SNR
Authors: Zhang Yunwei , Wei Zixuan , Gao Yong 
Published: September 2023

Abstract
Determining the number of sources under low signal-to-noise ratio (SNR) and signal interference with the same frequency and modulation presents a significant challenge. To address this challenge, we propose a novel method for detecting the number of signal sources from single-channel that leverages signal reconstruction and deep learning. The method employs subspace projection based on the Hankel matrix to reconstruct the measured single-channel signals, effectively suppressing noise. Furthermore, we incorporate the correlation of information and the integrity of feature in the signal, by fusing the in-phase component, quadrature component, and frequency spectrum feature of the reconstructed complex signal into a one-dimensional feature suitable for convolutional neural network (CNN). To address the source number detection task, we design a one-dimensional CNN based on convolutional block attention module, transforming it into a classification problem. Finally, experimental measurements demonstrate the effectiveness of our proposed method, with an detection accuracy of 94% even at an SNR of −10 dB.
Fault diagnosis in asynchronous motors based on an optimal deep bidirectional long short-term memory networks
Authors: Xu Bo , Li Huipeng , Liu Yi , Zhou Fengxing , Yan Baokang 
Published: September 2023

Abstract
Fault diagnosis of asynchronous motors has become a pressing need in the metallurgical industry. Due to the complex structure of asynchronous motors, fault types and fault characteristics are diverse, with strong nonlinear relationships between them, which leads to the difficulty of fault diagnosis. To efficiently and accurately diagnose various motor faults, we propose a fault diagnosis method based on an optimal deep bidirectional long short-term memory neural network. First, the three-phase current, multidimensional vibrational signal, and acoustic signal of the asynchronous motor are collected and construct diverse and robust data sample set to enhance the generalization ability of the model. Next, a modified 3D logistics-sine complex chaotic map (3D LSCCM) is constructed to improve the global and local search capabilities of the pigeon swarm optimization algorithm (PIO). Then, we construct a deep bidirectional long short-term memory network (Bid-LSTM) with attention mechanism to mine high-value fault characteristic information. Meanwhile, the optimal hyper-parameters of the deep ABid-LSTM are explored using the modified PIO to improve the training performance of the model. Finally, the fault data samples of asynchronous motor are induced to train and test the proposed framework. By fusing diverse data samples, the proposed method outperforms conventional deep Bid-LSTM and achieves fault diagnosis accuracy of 99.13%. It provides a novel diagnostic strategy for motor fault diagnosis.
Small blind-area, high-accuracy ultrasonic rangefinder using a broadband multi-frequency piezoelectric micromachined ultrasonic transducer array
Authors: Luo Guoxi , He Kang , Wang Yongliang , Zhou Wenke , Chen Ke , Zhao Libo , Xu Tingzhong , Li Zhikang , Li Min , Yang Ping , Wang Kaifei , Jiang Zhuangde 
Published: September 2023

Abstract
This paper presents a broadband ultrasonic rangefinder, with merits of a small blind area and high accuracy, based on a multi-frequency piezoelectric micromachined ultrasonic transducer (MF-PMUT) array. The coupling bandwidth between six types of resonant cells with adjacent resonant frequencies was studied and optimized, and these cells were then integrated into an array to broaden the bandwidth of the device. The array device showed a wide −6 dB fractional bandwidth of 108% in silicon oil. A wide bandwidth can contribute to obtaining the maximum steady-state with less excitation and reducing its residual ring-down, resulting in a small blind area. Pulse-echo ranging experiments demonstrated that the blind area was effectively reduced to 5 mm due to the multi-frequency array. For short distance measurements (<250 mm), the error was well controlled within ±0.3 mm and the 3σ accuracy was 0.445 mm. Compared with earlier reported PMUTs designed for bandwidth enhancement, the proposed broadband MF-PMUT array is much simpler in design and fabrication, revealing it as a promising candidate for short-distance high-accuracy measurements.
Hydride formation and dynamic phase changes during template-assisted Pd electrodeposition
Authors: Abbondanza Giuseppe , Grespi Andrea , Larsson Alfred , Dzhigaev Dmitry , Glatthaar Lorena , Weber Tim , Blankenburg Malte , Hegedüs Zoltan , Lienert Ulrich , Over Herbert , Harlow Gary S , Lundgren Edvin 
Published: September 2023

Abstract
We investigated the structural evolution of electrochemically fabricated Pd nanowires in situ by means of grazing-incidence transmission small- and wide-angle x-ray scattering (GTSAXS and GTWAXS), x-ray fluorescence (XRF) and two-dimensional surface optical reflectance (2D-SOR). This shows how electrodeposition and the hydrogen evolution reaction (HER) compete and interact during Pd electrodepositon. During the bottom-up growth of the nanowires, we show that β-phase Pd hydride is formed. Suspending the electrodeposition then leads to a phase transition from β-phase Pd hydride to α-phase Pd. Additionally, we find that grain coalescence later hinders the incorporation of hydrogen in the Pd unit cell. GTSAXS and 2D-SOR provide complementary information on the volume fraction of the pores occupied by Pd, while XRF was used to monitor the amount of Pd electrodeposited.
High-energy quasi-monoenergetic proton beam from micro-tube targets driven by Laguerre–Gaussian lasers
Authors: Jin S , Yao Y L , Lei B F , Chen G Y , Zhou C T , Zhu S P , He X T , Qiao B 
Published: September 2023

Abstract
High-energy proton beams with low energy spread and angular divergence are highly valuable in various applications, such as proton therapy, ultrafast science, and nuclear physics. Laser-driven ion sources are being explored as a more compact and cost-effective alternative to conventional accelerators. However, producing high-quality proton beams using lasers has been a significant challenge. In this study, we propose a novel approach to achieve high-energy quasi-monoenergetic proton beams by utilizing a Laguerre–Gaussian (LG) laser to irradiate a solid hollow tube target. Our three-dimensional particle-in-cell simulations demonstrate that the LG laser efficiently pulls out and accelerates electrons. As these electrons exit the rear side of the tube, a charge-separation electric field for proton acceleration is self-established. Meanwhile, a considerable part of the electrons are confined to the laser axis by the ponderomotive force of the LG laser, generating a longitudinal bunching field and transverse focusing field. As a result, protons are accelerated and focused in these fields, producing a high- quality proton beam with high energy (247 MeV) and low energy spread (∼2%) using an LG laser with an intensity of

1.9
×

10

21

W cm−2 and a tube target with an electron density of 40nc
. In comparison to a standard Gaussian laser, the LG laser exhibits superior performance in terms of proton cut-off energy, energy spread, and angular divergence.
An improved multi-state constraint kalman filter based on maximum correntropy criterion
Authors: Liu Xuhang , Guo Yicong 
Published: September 2023

Abstract
In recent years, the multi-state constraint Kalman filter has been widely used in the visual-inertial navigation of unmanned systems. However, in most previous studies, the measurement noise of the navigation system was assumed to be Gaussian noise, but this is not the case in practice. In this paper, the maximum correntropy criterion is introduced into the multi-state constraint Kalman filter to improve the robustness of the visual-inertial system. First, the new maximum correntropy criterion-based Kalman filter is introduced, it uses the maximum correntropy criterion to replace the minimum mean square error criterion to suppress the interference of measurement outliers on the filtering results, and it has no numerical problem in the presence of large measurements outliers. Then, an improved multi-state constraint Kalman filter is designed by applying the new maximum correntropy criterion-based Kalman filter to the multi-state constraint Kalman filter, which improved the robustness of the multi-state constraint Kalman filter. The results of numerical simulation and dataset experiments show that the proposed filter improves the accuracy and robustness of the visual-inertial system.
Investigation of performance enhancement by balanced double-null shaping in KSTAR
Authors: Kim Boseong , Park M.S. , Lee Y.H. , Kim S.K. , Lee C.Y. , Hong S.C. , Seo J. , Lee J.G. , Park S.J. , Kim H.-S. , Na Yong-Su 
Published: September 2023

Abstract
We report experimental observations on the effect of plasma boundary shaping towards balanced double-null (DN) configuration on the plasma performance in KSTAR. The transition from a single-null to a DN configuration resulted in improved plasma performance, manifested through changes in the pedestal region, decreased density, and core MHD activity variation. Specifically, the DN transition led to a wider and higher pedestal structure, accompanied by grassy edge-localized modes (ELMs) characteristics. The density decrease was a prerequisite for performance enhancement during DN shaping, increasing fast ion confinement. Optimizing the plasma near the core region was associated with the suppression of sawtooth instabilities and the occurrence of fishbone modes during the DN transition. Integrated modeling demonstrated that secondary effects of the DN shaping could increase core thermal energy confinement.
Connecting physical and social science datasets: challenges and pathways forward
Authors: Shah Sameer H , O’Lenick Cassandra R , Wan Jessica S , Ramos-Valle Alexandra , Ash Kevin D , Wilhelmi Olga V , Edgeley Catrin M , Molina Maria J , Moulite Jessica , Chunga Pizarro Carlo Andre , Emard Kelsey , Cameron Olivia Z , Done James M , Hazard Cleo Wölfle , Hopson Thomas M , Jones Mikah , Lacey Forrest , Lachaud Michée Arnold , Lombardozzi Danica , Méndez Michael , Morss Rebecca E , Ricke Katharine , Tormos-Aponte Fernando , Wieder William R , Williams Christopher L 
Published: September 2023

Abstract
The integration of physical and social science data can enable novel frameworks, methodologies, and innovative solutions important for addressing complex socio-environmental problems. Unfortunately, many technical, procedural, and institutional challenges hamper effective data integration—detracting from interdisciplinary socio-environmental research and broader public impact. This paper reports on the experiences and challenges of social and physical data integration, as experienced by diverse Early Career Researchers (ECRs), and offers strategies for coping with and addressing these challenges. Through a workshop convened by the National Center for Atmospheric Research (NCAR) Innovator Program, 33 participants from different disciplines, career stages, and institutions across the United States identified four thematic data integration challenges related to complexity and uncertainty, communication, scale, and institutional barriers. They further recommended individual, departmental, and institutional scale responses to cope with and address these integration challenges. These recommendations seek to inform faculty and department support for ECRs, who are often encouraged—and even expected—to engage in integrative, problem-focused, and solutions-oriented research.