bluuebunny/crossref_metadata_2025_split huggingface dataset:
Riemann–Hilbert approach and multiple high-order pole solutions for the AB system
Authors: Li Wenjing , Zhang Yi , Yang Xiaolin 
Published: August 2024

Abstract
This article’s purpose is to investigate multiple high-order pole solutions for the AB system by the Riemann–Hilbert (RH) approach. We establish the RH problem through using spectral analysis to the Lax pair. Then the RH problem can be resolved and the soliton solution’s formula can be given by using the Laurent expansion method. Finally, we get special soliton solutions, including dark solitons, W-type dark solitons and multiple high-pole solutions. In addition, the W-type dark soliton solutions will occur when the spectral parameters are purely imaginary.
Generated genuine tripartite steering and its monogamy in the background of a Kerr-Newman black hole*
Authors: Huang 黄 Xiaoli 晓理 , Wu 吴 Haoyu 浩瑜 , Wu 吴 Shumin 树民 
Published: August 2024

Abstract
We study the redistribution of quantum steering and its monogamy in the presence of a four-dimensional Kerr-Newman black hole. The gravitational effect of the Kerr-Newman black hole is shown to generate genuine tripartite steering between causally disconnected regions, depending on the polar angle, angular momentum, electric charge, and magnetic charge of the black hole. We obtain strong evidence of steering monogamy, that is, the "sudden death" of the A → B steering results in the "sudden birth" of B → B steering. We also obtain the condition of maximal steering asymmetry, that is,

, revealing the transition between two-way and one-way steering in Kerr-Newman spacetime.
Investigating higgsino dark matter in the semi-constrained NMSSM*
Authors: Wang 王 Kun 坤 , Zhu 朱 Jingya 经亚 
Published: August 2024

Abstract
In this study, we explored the characteristics of higgsino-dominated dark matter (DM) within the semi-constrained Next-to-Minimal Supersymmetric Standard Model (scNMSSM), covering a mass range from hundreds of GeV to several TeV. We carefully analyzed the parameter space under existing theoretical and experimental constraints to confirm the viability of higgsino-dominated lightest supersymmetric particles (LSPs) with masses between 100 GeV and 4 TeV. Our study examined various DM annihilation mechanisms, emphasizing the significant role of coannihilation with the next-to-lightest supersymmetric particle (NLSP), which includes other higgsino-dominated particles such as

and

. We categorize the annihilation processes into three main classes:

coannihilation, Higgs funnel annihilation, and

coannihilation. Each class combines interactions with

. Our results indicate that achieving the correct relic density in heavier higgsino LSPs requires a combination of coannihilation and Higgs funnel mechanisms. We also assessed the potential of future experiments, such as XENONnT, LUX-ZEPLIN (LZ), PandaX-xT, and the Cherenkov Telescope Array (CTA), to probe these DM scenarios through direct and indirect detections. In particular, future spin-independent DM detections may cover all samples with the correct DM relic density for

GeV. Furthermore, future colliders such as the International Linear Collider (ILC) and Compact Linear Collider (CLIC) are expected to exceed the detection capabilities of current hadron colliders, especially for higher mass NLSPs. Notably, CLIC, which will operate at 3000 GeV, is anticipated to enable thorough investigation of all samples with insufficient DM relic density for

GeV.
Recent advance progress of HL-3 experiments
Authors: Duan X.R. , Xu M. , Zhong W.L. , Ji X.Q. , Chen W. , Shi Z.B. , Liu X.L. , Lu B. , Li B. , Wang Y.Q. , Li J.Q. , Zheng G.Y. , Liu Yong , Yang Q.W. , Yan L.W. , Cai L.J. , Li Q. , Liu Y. , Bai X.Y. , Cao Z. , Chen X. , Chen H.T. , Chen Y.H. , Dong G.Q. , Du H.L. , Fan D.M. , Gao J.M. , Geng S.F. , Hao G.Z. , He H.M. , Huang M. , Jiang M. , Ke R. , Liang A.S. , Li J.X. , Li Qing , Li Yongge , Li L.C. , Li H.J. , Li W.B. , Liu D.Q. , Long T. , Lu L.F. , Nie L. , Shi P.W. , Peng J.F. , Sun A.P. , Sun T.F. , Tong R.H. , Wei H.L. , Wang S. , Xiao G.L. , Xiao X.P. , Xue L. , Xu H.B. , Yang Z.Y. , Yu D.L. , Yu L.M. , Zhang Y.P. , Zheng X. , Zhang L. , Zhang Y. , Zhang F. , Zhang X.L. ,   HL-3 Team & Collaborators
Published: August 2024

Abstract
Since the first plasma realized in 2020, a series of key systems on HL-3 (known as HL-2M before) tokamak have been equipped/upgraded, including in-vessel components (the first wall, lower divertor, and toroidal cryogenic/water-cooling/baking/glow discharge systems, etc.), auxiliary heating system of 11 MW, and 28 diagnostic systems (to measure the plasma density, electron temperature, radiation, magnetic field, etc.). Magnet field systems were commissioned firstly for divertor plasma discharges. During the 2nd experimental campaign of HL-3 tokamak, several great progresses have been achieved. Firstly, the successful operation with plasma current larger than 1 MA was achieved under a divertor configuration. Secondly, the advanced divertor concept with two distinct snowflake configurations was realized. It is found that the distribution of ion saturation current and heat flux on bottom plate becomes wide due to magnetic surface expansion, demonstrating the advantage of such configuration in the heat flux mitigation. In addition, using the combination of NBI, ECRH and LHCD, the standard sawtoothing high confinement mode of megampere plasma was firstly accessed on the HL-3. The successful commissioning of HL-3 is beneficial for the initial operation of ITER.
Modeling and simulation of the capacitive NEMS pressure sensor based on suspended graphene membranes
Authors: Liu Quan , Zhang Zhe , Ding Jie , Zhang Wendong , Fan Xuge 
Published: August 2024

Abstract
Nanoelectromechanical systems (NEMS) employing graphene have garnered significant attention for their potential applications in pressure sensors. Compared to other electrical readout mechanisms, capacitive sensing is a promising alternative one due to its less dependence on material properties and environmental factors. Graphene, with its unique properties, is an excellent candidate for high-performance NEMS pressure sensors. However, there are few studies on theoretical modeling of capacitive NEMS pressure sensors based on suspended graphene membrane. This paper presents the design, modeling and simulation of capacitive NEMS pressure sensors based on circular suspended graphene membrane. The impact of parameters of graphene membrane on the sensor performance is studied through COMSOL finite element analysis software. The results show that the sensitivity increased with the increase of the radius of graphene membrane but decreased with the increase of the thickness of graphene membrane, and the polar plate spacing determines the trade-off between the sensitivity and the measurement range. Further, decreasing the polar plate spacing increases the sensitivity but changes the capacitance-pressure relationship from linear to nonlinear.
Machine Learning-Driven Prediction of DLD Chip Throughput
Authors: Zhang Yidan , Wang Junchao 
Published: August 2024

Abstract
The microfluidic chip technology, capable of manipulating fluids at the micrometer-scale, is increasingly being applied in the fields of cell biology, molecular biology, chemistry, and life sciences. The densely integrated microfluidic chip devices enable high-throughput parallel experiments and integration of various operational units. However, the development of densely integrated microfluidic chips also comes with high demands on driving equipment. Due to manufacturing processes and inherent design limitations, the driving capability of the equipment is restricted. To address potential challenges faced by microfluidic chips in the development towards integrated biological microsystems and to maximize their high-throughput performance, improvements are required not only in selecting appropriate driving equipment but also in design aspects. This study focuses on the DLD chip and delves into the complexity of microfluidic chip design. By combining Bézier curves to characterize arbitrarily shaped micropillars and conducting finite element analysis to compute the pressure field of DLD chips, we explore methods utilizing random forest, XGBoost, LightGBM, and ANN machine learning algorithms to predict the impedance of DLD chips. Our objective is to guide engineers in designing chips with smaller impedance (lower pressure drop) and larger throughput more quickly and efficiently during the design phase. Ultimately, through evaluating the predictive capabilities of the four models on new data, we select the ANN algorithm model to predict the pressure drop under different designs of DLD chips. This offers possibilities for enhancing the efficiency and integration of microfluidic technology in biomedical applications.
Upconversion luminescence and temperature sensing properties of Ba3GdAl2O7.5: Yb3+, Er3+ phosphor
Authors: Wang Ruonan , Luo Tian , Fu Hao 
Published: August 2024

Abstract
In recent years, lanthanide-doped upconversion materials have received abundant attentions due to their long fluorescence lifetime, narrow emission bandwidths, and large anti-Stocks shift. However, weak brightness generally exists in upconversion materials and it becomes one of the major bottlenecks in the practical applications. Therefore, developing more materials with excellent upconversion luminescence properties is urgent. Herein, a green phosphor Ba3GdAl2O7.5: Yb3+, Er3+ is obtained by high-temperature solid-state method. The crystal structure is characterized by the X-ray powder diffraction. The upconversion luminescence properties are displayed under the excitation of 980 nm near-infrared laser, and the optimal doping concentrations of Yb3+ and Er3+ ions in the crystal are determined by the control variable method. In addition, the excellent temperature sensing performance of Ba3GdAl2O7.5: 0.2Yb3+, 0.02Er3+ indicates that it is a candidate for practical applications as an optical temperature sensor.
Wearable gait recognition system based on time domain features of Bluetooth inertial sensor network
Authors: Wan Rui , Wang Qisong , Liu Dan , Zhang Meiyan , Luo Jikui 
Published: August 2024

Abstract
As an important part of medical monitoring, gait recognition has been used in lower limb rehabilitation diagnosis and gait assessment. To meet practical requirements, we designed a wearable gait recognition system based on time domain features of Bluetooth inertial sensor network, which can be used for real-time acquisition and evaluation of gait signals. In this research, we used 6 sensor units to integrate 10 kinds of gait information, and designed a gait monitoring system covering the main joints of lower limbs based on Bluetooth network. The gait monitoring system can collect the inertial sensing data of lower limbs at a maximum rate of 90 Hz through the 6 sensor units, and has good electrical performance. In daily use, each unit can work for more than 3 hours and maintain a received signal strength indicator (RSSI) of more than -90 dBm at a spatial distance of 10 meters. On the gait dataset collected in the experiment, we used sliding window to segment the time domain signals and extract 10 kinds of time domain features for classification algorithm. We achieved 97.1% average identification accuracy of 7 different gait patterns by support vector machine (SVM).
A microfluidic integrated microliter millimeter wave biosensor based on a cell interception structure
Authors: Wang Qinyu , Sun Wen , Wang Jianhua , You Bin , Sun Lingling 
Published: August 2024

Abstract
The millimeter wave frequency band has the characteristics of high resolution, high sensitivity, label free, non-invasive [1], etc. Therefore, this detection technology has broad application prospects in the detection of microliter biological liquid samples. This article is based on the design of coplanar waveguides. A stepped interception structure is designed at the center of the microfluidic path of millimeter wave sensors to intercept and capture tumor cells entering the microfluidic path during fluid injection. This structure is used to improve the accuracy of detection by controlling the similar concentration of each cell. This broadband microfluidic sensor is used to measure the S parameters of different biological liquid samples, including tumor cell suspension HepG2 and THP-1 cell suspension (concentration 1E6 cells/mL), and data processing and error elimination are carried out using Matlab software. In the measurement results, the difference in transmission coefficients between different cell suspensions is aroun 0.4dB.
In vivo imaging of microvasculature in human finger skin using SV-OCT
Authors: Zhong Cheng , Zheng Jiawei , Li Wangbiao , Wu Shulian , Lin Hui , He Youwu , Li Zhifang 
Published: August 2024

Abstract
Speckle variance optical coherence tomography (SV-OCT) enables non-invasive visualization of the three-dimensional vascular information within the microcirculatory tissue bed by utilizing flowing red blood cells as intrinsic contrast agents, without the need for dye injection. This study evaluated the feasibility of using the SV-OCT device for monitoring the microvascular system in human finger skin. An adaptive wavelet Fourier transform filtering algorithm was applied to remove stripe noise from the images of finger vasculature. The results demonstrate that SV-OCT systems can be used to extract the vascular system of finger skin. By employing an adaptive wavelet Fourier transform filtering (AWFTF)algorithm to process the vascular data, stripe noise can be effectively removed, thereby enhancing the imaging quality of the blood vessels.
Growth of High-Quality InP Nanowires with PN Junctions Using an Improved Chemical Vapor Deposition
Authors: Yao Xinliang , Liu Xingpeng , Yuan Kui , Su Jiande , Song Shuxiang , Liu Linsheng 
Published: August 2024

Abstract
Nanowires grown by traditional chemical vapor deposition (CVD) systems often suffer from low crystal quality and difficulties in realizing complex device structures. To address these issues, we propose an improved CVD system with a source switching unit to enhance the controllability of source materials. By combining reverse gas flow and high-temperature degassing processes, high-quality InP nanowires with pn junctions were successfully grown. Scanning electron microscopy and photoluminescence spectroscopy revealed that the as-grown nanowires exhibit smooth surfaces, no significant defects, and high crystal quality. Furthermore, a single InP nanowire with a pn junction demonstrated rectifying characteristics and fast photoswitch response (less than 14.2 ms). These results suggest that the improved CVD method provides a new approach for low-cost fabrication of high-quality nanodevices.
Miniaturized spectroscopy system based on a semiconductor nanofilm
Authors: Zhou Zhurong , Ma Zhi , Ahmed Mian Aizaz , Guo Xin , Tong Limin , Yang Zongyin 
Published: August 2024

Abstract
Spectroscopy plays a pivotal role in various applications for industrial and commercial analysis. Conventional spectroscopy instruments include various discrete optical components like light sources, monochromators and detectors. These components are mechanically intricate and require space for the mechanisms that adjust and calibrate them, which increases the instrument’s footprint and make them less adjustable for portable applications. This drawback initiated the increase in the demand for miniatured spectral detection systems. Here, we present a low-cost ultra-compact miniaturized spectral detection system, which integrates both linear variable light sources, sample chambers and detectors within a centimetre-scale chip. The linear variable light generation across wavelengths ranging from 480 nm to 600 nm is achieved by stimulating different regions of the ZnCdSeS bandgap-graded semiconductor nanofilm with ultraviolet light. We demonstrate the capability of the system with precise identification of liquids. Our device overcomes the typical miniaturization limits imposed by discrete optical components, and long light paths in conventional spectroscopy instruments and opens up numerous potential applications across various fields due to its portability, ease of use, and lower cost.
A method for extracting the 1-60 GHz dielectric spectrum of trace liquids using standard design coplanar waveguide sensing devices
Authors: Wang Jianhua , Sun Wen , Chen Binkai , Sun Lingling 
Published: August 2024

Abstract
This paper introduces a sensor designed for measuring the dielectric constant of small amounts of liquid. The sensor consists of a coplanar waveguide transmission line and an open container for the liquid, enabling broadband dielectric spectroscopy measurements for milliliter-scale liquids in the 1-60 GHz range. To improve the accuracy of dielectric spectroscopy testing, the sensor is calibrated using air and deionized water to obtain a coefficient matrix relating the sensor’s distributed parameters to the sample’s dielectric constant. This matrix is then used to calculate the dielectric spectroscopy of subsequent test samples. Tests on the dielectric spectroscopy of deionized water with this sensor and algorithm indicate that over the 1-60 GHz band, the error compared to previous literature results is within 5%, demonstrating the reliability of the proposed sensor and dielectric spectroscopy extraction algorithm.
Co-Design of a Low-Noise Amplifier and SPDT SW for Band 42 T/R Modules with Low NF, High Gain, and 50-ohm Matching in Bulk CMOS Technology
Authors: Yang Jilong , Cui Qiang , Cheng Zhiyuan 
Published: August 2024

Abstract
The vast deployment of 5G communication system calls for low-cost, easy-to-integrate RF Front End Integrated Circuits (RFFE ICs) design. For better system performance, specific processes, such as SOI/GaN/GaAs, are widely used for RFFE receiver IC design. However, these specific processes are costly and hard to integrate with baseband ICs which are typically fabricated in bulk CMOS process. To overcome the high cost and integration challenges, this paper designed a Band 42 low-noise power amplifier (LNA) together with a single-pole double-throw switch (SDPT SW) in a 55nm bulk CMOS process. For the LNA, we integrated source degeneration inductance and gate-source capacitance feedback, which provides significant stability, matching and noise figure benefits. For LNA and SW co-optimization, we reduced the overall noise by reusing the input matching network. The B42 receiver’s minimum return loss(SW included) is better than -20dB, gain higher than 28dB, and the noise figure is better than 2.4dB; the switch’s off-state isolation is better than 30dB. To our knowledge, this B42 receiver RFFE design is the best combination of performance and cost in the Bulk CMOS process. This work demonstrated the possibility of fully integrating RFFE circuits in low cost bulk CMOS process with good performance.
Comparison of Multiple Machine Learning Models for the Classification of Cell States Based on Impedance Features
Authors: Tian Dongze , Wei Jian , Yang Xinlong , Su Fei , Xing Xiaoxing 
Published: August 2024

Abstract
Microfluidic impedance flow cytometry (IFC) enables high-throughput single-cell analysis in label-free manner. Tens of thousands of cells can be measured in several minutes under multiple frequencies, which give rise to impedance features with rich information ideal for machine learning (ML)-based cell classification. Conventional data processing approach for IFC typically exploits the scattered distribution of the measured cells which correlates the impedance features (e.g., the impedance amplitude and phase at different frequencies, the amplitude ratio between high to low frequencies) and exhibits resolved cell clusters in scatter plot. By manually gating on the distributed dots plot, the cell subgroups get mapped to different cell type or cellular states. ML-based data processing for IFC not only reduces the human workload, and more importantly, it also eliminates the human interference to manual gating strategy, and thus potentially leading to more concise and accurate cell classification results. Here, we demonstrate the ML-based classification of different cell states for tumor cells subject to anticancer drug treatment. IFC-measured impedance data of H1650 cells and Hela cells under drug-induced mitosis block state and apoptosis state have been applied for ML-based cell state identification. Three machine learning models, including the random forest (RF), support vector machine (SVM) and K-nearest neighbours (KNN) have been trained for impedance features extracted from cell signals at both 500 kHz and 10 MHz. In comparison, the RF model give rise to the highest classification accuracies among all trained models here. For H1650 cells, 84.01% and 85.96% accuracies have been respectively achieved for G1/S state vs. apoptosis and G2/M vs. apoptosis. For the classification between G2/M vs. apoptosis for the paclitaxel-treated Hela cells, the RF model produces high accuracy of 98.70%.
Inorganic Pb-Sn Perovskite Solar Cells with CF3-PA Internal Defect Passivation Strategy
Authors: Xu Jingyi , Zhang Kai , Zhao Lin , Yang Shihe , Zhou Hang 
Published: August 2024

Abstract
The volatile organic components and heavy metal components in traditional perovskite solar cells (PSCs) have raised environmental and stability concerns for their large scale application. To solve the above two problems, the advancement of inorganic Pb-Sn PSCs technology has progressed at a remarkable pace over a relatively short period. Replacing Pb with Sn in PSCs not only significantly improves the environmental problems caused by the high toxicity of Pb, but also forms solar cells with lower bandgap, which is beneficial for light absorption and utilization, especially in the near-infrared band. In this work, a composite inorganic perovskite was utilized, CsPb0.6Sn0.4I3, and enhanced the PSCs performance by passivating the perovskite using 4-trifluoromethyl-phenylammonium (CF3-PA) additives. The highest efficiency of the champion device reached 13.04%, demonstrating its potential as a candidate for low bandgap PSCs.
Rapid Detection Technology for Cocaine and Methamphetamine Acute Abuse based on EEG
Authors: Xia Jie , Yuan Hongwen , Pan Jiadong , Li kan , Zhang Luxi , Dong Shurong 
Published: August 2024

Abstract
Multi-domain characterization and a new fast detection method for acute illegal psychostimulants abuse detection based on waking-state EEG of mice is proposed in this paper. To get corftical electroencephalogram (EEG), three groups of mice were injected with cocaine (Coca), methamphetamine (Meth), and saline (Sali) respectively following the experimental paradigm of drug abuse. The EEG features were extracted out by multi-domain views, including time, frequency, complexity, dynamics, and independent domains to obtain acute drug abuse effects on the brain. New strategy combing time domain with frequency domain is developed as multi-domain input and by means of dimension transformation approach preserving temporal information, the performance of drug abuse detection is greatly improved with deep learning models of ResNet50. Results show that comparing to support vector machine (SVM), k nearest neighbor (kNN), random forest (RF), and long short-term memory fully convolutional networks (LSTM-FCN), Res-Net50 based on our proposed multi-domain features has best F1-score of 95.10%. This promising method provides a low-cost, fast, and widely assisted technology for psychostimulants abuse identification.