bluuebunny/crossref_metadata_2025 huggingface dataset:
Electron-Rich Triazine-Conjugated Microporous Polymers for the Removal of Dyes from Wastewater
Authors: Li Bao-Ning , Zhang Xing-Long , Bai Xiao-Hui , Liang Zhen-Jie , Li Jian , Fan Xiao-Yong
Published: June 2023

Conjugated microporous polymers (CMP) as porous functional materials have received considerable attention due to their unique structures and fascinating properties for the adsorption and degradation of dyes. Herein, a triazine-conjugated microporous polymer material with rich N-donors at the skeleton itself was successfully synthesized via the Sonogashira–Hagihara coupling by a one–pot reaction. These two polymers had Brunauer–Emmett–Teller (BET) surface areas of 322 and 435 m2g−1 for triazine-conjugated microporous polymers (T-CMP) and T-CMP-Me, respectively. Due to the porous effects and the rich N-donor at the framework, it displayed a higher removal efficiency and adsorption performance compared to cationic-type dyes and selectivity properties for (methylene blue) MB+ from a mixture solution of cationic-type dyes. Furthermore, the T-CMP-Me could quickly and drastically separate MB+ and (methyl orange) MO− from the mixed solution within a short time. Their intriguing absorption behaviors are supported by 13C NMR, UV−vis absorption spectroscopy, scanning electron microscopy, and X-ray powder diffraction studies. This work will not only improve the development of porous material varieties, but also demonstrate the adsorption or selectivity of porous materials for dyes from wastewater.
Improving the Luminescence and Stability of Carbon-Centered Radicals by Kinetic Isotope Effect
Authors: Ma Zhichao , Zhang Lintao , Cui Zhiyuan , Ai Xin
Published: June 2023

The kinetic isotope effect (KIE) is beneficial to improve the performance of luminescent molecules and relevant light-emitting diodes. In this work, the influences of deuteration on the photophysical property and stability of luminescent radicals are investigated for the first time. Four deuterated radicals based on biphenylmethyl, triphenylmethyl, and deuterated carbazole were synthesized and sufficiently characterized. The deuterated radicals exhibited excellent redox stability, as well as improved thermal and photostability. The appropriate deuteration of relevant C-H bonds would effectively suppress the non-radiative process, resulting in the increase in photoluminescence quantum efficiency (PLQE). This research has demonstrated that the introduction of deuterium atoms could be an effective pathway to develop high-performance luminescent radicals.
Degradation Behavior of Poly(Lactide-Co-Glycolide) Monolayers Investigated by Langmuir Technique: Accelerating Effect
Authors: Kim Gayeon , Gavande Vishal , Shaikh Vasi , Lee Won-Ki
Published: June 2023

Among biodegradable polymers, polylactides (PLAs) have attracted considerable interest because the monomer can be produced from renewable resources. Since their initial degradability strongly affects commercial application fields, it is necessary to manage the degradation properties of PLAs to make them more commercially attractive. To control their degradability, poly(lactide-co-glycolide) (PLGA) copolymers of glycolide and isomer lactides (LAs) were synthesized, and their enzymatic and alkaline degradation rates of PLGA monolayers as functions of glycolide acid (GA) composition were systematically investigated by the Langmuir technique. The results showed that the alkaline and enzymatic degradations of PLGA monolayers were faster than those of l-polylactide (l-PLA), even though proteinase K is selectively effective in the l-lactide (l-LA) unit. Alkaline hydrolysis was strongly affected by their hydrophilicity, while the surface pressure of monolayers for enzymatic degradations was a major factor.
Natural-Product-Inspired Microwave-Assisted Synthesis of Novel Spirooxindoles as Antileishmanial Agents: Synthesis, Stereochemical Assignment, Bioevaluation, SAR, and Molecular Docking Studies
Authors: Sahu Nawal Kishore , Sharma Ritu , Suhas Kshirsagar Prasad , Joshi Jyoti , Prakash Kunal , Sharma Richa , Pratap Ramendra , Hu Xiwen , Kaur Sukhbir , Jain Mukesh , Coluccini Carmine , Coghi Paolo , Chaudhary Sandeep
Published: June 2023

Leishmaniasis is a neglected tropical disease, and there is an emerging need for the development of effective drugs to treat it. To identify novel compounds with antileishmanial properties, a novel series of functionalized spiro[indoline-3,2′-pyrrolidin]-2-one/spiro[indoline-3,3′-pyrrolizin]-2-one 23a–f, 24a–f, and 25a–g were prepared from natural-product-inspired pharmaceutically privileged bioactive sub-structures, i.e., isatins 20a–h, various substituted chalcones 21a–f, and 22a–c amino acids, via 1,3-dipolar cycloaddition reactions in MeOH at 80 °C using a microwave-assisted approach. Compared to traditional methods, microwave-assisted synthesis produces higher yields and better quality, and it takes less time. We report here the in vitro antileishmanial activity against Leishmania donovani and SAR studies. The analogues 24a, 24e, 24f, and 25d were found to be the most active compounds of the series and showed IC50 values of 2.43 µM, 0.96 µM, 1.62 µM, and 3.55 µM, respectively, compared to the standard reference drug Amphotericin B (IC50 = 0.060 µM). All compounds were assessed for Leishmania DNA topoisomerase type IB inhibition activity using the standard drug Camptothecin, and 24a, 24e, 24f, and 25d showed potential results. In order to further validate the experimental results and gain a deeper understanding of the binding manner of such compounds, molecular docking studies were also performed. The stereochemistry of the novel functionalized spirooxindole derivatives was confirmed by single-crystal X-ray crystallography studies.
Deep Learning for Identifying Promising Drug Candidates in Drug–Phospholipid Complexes
Authors: Yoo Soyoung , Lee Hanbyul , Kim Junghyun
Published: June 2023

Drug–phospholipid complexing is a promising formulation technology for improving the low bioavailability of active pharmaceutical ingredients (APIs). However, identifying whether phospholipid and candidate drug can form a complex through in vitro tests can be costly and time-consuming due to the physicochemical properties and experimental environment. In a previous study, the authors developed seven machine learning models to predict drug–phospholipid complex formation, and the lightGBM model demonstrated the best performance. However, the previous study was unable to sufficiently address the degradation of test performance caused by the small size of the training data with class imbalance, and it had the limitation of considering only machine learning techniques. To overcome these limitations, we propose a new deep learning-based prediction model that employs variational autoencoder (VAE) and principal component analysis (PCA) techniques to improve prediction performance. The model uses a multi-layer one-dimensional convolutional neural network (CNN) with a skip connection to effectively capture the complex relationship between drugs and lipid molecules. The computer simulation results demonstrate that our proposed model performs better than the previous model in all performance metrics.
Contribution of Processes in SN Electrodes to the Transport Properties of SN-N-NS Josephson Junctions
Authors: Ruzhickiy Vsevolod , Bakurskiy Sergey , Kupriyanov Mikhail , Klenov Nikolay , Soloviev Igor , Stolyarov Vasily , Golubov Alexander
Published: June 2023

In this paper, we present a theoretical study of electronic transport in planar Josephson Superconductor–Normal Metal–Superconductor (SN-N-NS) bridges with arbitrary transparency of the SN interfaces. We formulate and solve the two-dimensional problem of finding the spatial distribution of the supercurrent in the SN electrodes. This allows us to determine the scale of the weak coupling region in the SN-N-NS bridges, i.e., to describe this structure as a serial connection between the Josephson contact and the linear inductance of the current-carrying electrodes. We show that the presence of a two-dimensional spatial current distribution in the SN electrodes leads to a modification of the current–phase relation and the critical current magnitude of the bridges. In particular, the critical current decreases as the overlap area of the SN parts of the electrodes decreases. We show that this is accompanied by a transformation of the SN-N-NS structure from an SNS-type weak link to a double-barrier SINIS contact. In addition, we find the range of interface transparency in order to optimise device performance. The features we have discovered should have a significant impact on the operation of small-scale superconducting electronic devices, and should be taken into account in their design.
Real-World Management of High Stool Output in Patients with Short Bowel Syndrome: An International Multicenter Survey
Authors: Lakananurak Narisorn , Wall Elizabeth , Catron Hilary , Delgado Adela , Greif Sophie , Herlitz Jean , Moccia Lisa , Mercer David , Vanuytsel Tim , Kumpf Vanessa , Berner-Hansen Mark , Gramlich Leah
Published: June 2023

Background: International practice guidelines for high-stool-output (HSO) management in short bowel syndrome (SBS) are available, but data on implementation are lacking. This study describes the approach used to manage HSO in SBS patients across different global regions. Methods: This is an international multicenter study evaluating medical management of HSO in SBS patients using a questionnaire survey. Thirty-three intestinal-failure centers were invited to complete the survey as one multidisciplinary team. Results: Survey response rate was 91%. Dietary recommendations varied based on anatomy and geographic region. For patients without colon-in-continuity (CiC), clinical practices were generally consistent with ESPEN guidelines, including separation of fluid from solid food (90%), a high-sodium diet (90%), and a low-simple-sugar diet (75%). For CiC patients, practices less closely followed guidelines, such as a low-fat diet (35%) or a high-sodium diet (50%). First-line antimotility and antisecretory medications were loperamide and proton-pump inhibitors. Other therapeutic agents (e.g., pancreatic enzymes and bile acid binders) were utilized in real-world practices, and usage varied based on intestinal anatomy. Conclusion: Expert centers largely followed published HSO-management guidelines for SBS patients without CiC, but clinical practices deviated substantially for CiC patients. Determining the reasons for this discrepancy might inform future development of practice guidelines.
Experimental Investigation on Pressure-Control Characteristics of Liquid Hydrogen Tank Based on Active and Passive Thermodynamic Venting System Technology
Authors: Zhou Zhenjun , Wu Jun , Zhang Shaohua , Gong Mengmeng , Liu Xin
Published: June 2023

Pressure control while minimizing the mass loss of liquid hydrogen is one of the key technologies required for the long-term storage of cryogenic propellants in microgravity in space, and the use of a thermodynamic venting system (TVS) has been considered as an effective means to solve this problem. In order to investigate the characteristics of pressure control by TVS technology, a cryogenic test platform for liquid hydrogen that integrated active and passive TVS was set up, a spray-bar exchanger and vapor-cooling screen were used to eliminate thermal stratification and realize the reuse of cold energy. Ten pressure-control tests using passive TVS (PTVS), mixing and active TVS (ATVS) strategies with heating powers of 0 W, 40 W and 80 W, were carried out. The single cycle time under different strategies, the effect of heating power on single cycle time, and the comparison of volume of the venting GH2 in different tests were analyzed in detail, the research showed that TVS technology could accurately control the pressure of cryogenic storage tanks within a predetermined range. An additional evaporation test was carried out using a direct venting method to compare with the above PTVS and ATVS tests, and the results showed that the venting volume of GH2 in unit time by the direct-venting method was close to that of the PTVS test with the heating power of 40 W, and the venting volume in unit time by the ATVS strategy was decreased by 87.3% compared to the direct-venting test.
Evaluation Methods and Measurement Challenges for Industrial Exoskeletons
Authors: Li-Baboud Ya-Shian , Virts Ann , Bostelman Roger , Yoon Soocheol , Rahman Amaan , Rhode Lucia , Ahmed Nishat , Shah Mili
Published: June 2023

In recent years, exoskeleton test methods for industrial exoskeletons have evolved to include simulated laboratory and field environments. Physiological, kinematic, and kinetic metrics, as well as subjective surveys, are used to evaluate exoskeleton usability. In particular, exoskeleton fit and usability can also impact the safety of exoskeletons and their effectiveness at reducing musculoskeletal injuries. This paper surveys the state of the art in measurement methods applied to exoskeleton evaluation. A notional classification of the metrics based on exoskeleton fit, task efficiency, comfort, mobility, and balance is proposed. In addition, the paper describes the test and measurement methods used in supporting the development of exoskeleton and exosuit evaluation methods to assess their fit, usability, and effectiveness in industrial tasks such as peg in hole, load align, and applied force. Finally, the paper includes a discussion of how the metrics can be applied towards a systematic evaluation of industrial exoskeletons, current measurement challenges, and future research directions.
Reconstruction of Range-Doppler Map Corrupted by FMCW Radar Asynchronization
Authors: Lee Kyung-Min , Lee In-Seong , Shin Hee-Sub , Ok Jae-Woo , Youn Jae-Hyuk , You Eung-Noh , Yang Jong-Ryul , Kim Kyung-Tae
Published: June 2023

Frequency-modulated continuous wave (FMCW) radar system synchronization using external clock signals can cause repeated Range-Doppler (R-D) map corruption when clock signal asynchronization problems occur between the transmitter and receiver. In this paper, we propose a signal processing method for the reconstruction of the corrupted R-D map owing to the FMCW radar’s asynchronization. After calculating the image entropy for each R-D map, the corrupted ones are extracted and reconstructed using the normal R-D maps acquired before and after the individual maps. To verify the effectiveness of the proposed method, three target detection experiments were conducted: a human target detection in an indoor environment and a wide place and a moving bike-rider target detection in an outdoor environment. The corrupted R-D map sequence of observed targets in each case was reconstructed properly and showed the validity by comparing the map-by-map range and speed changes in the detected target with the ground-truth information of the target.
Automated Multi-Wavelength Quality Assessment of Photoplethysmography Signals Using Modulation Spectrum Shape Features
Authors: Tiwari Abhishek , Gray Gordon , Bondi Parker , Mahnam Amin , Falk Tiago H.
Published: June 2023

Photoplethysmography (PPG) is used to measure blood volume changes in the microvascular bed of tissue. Information about these changes along time can be used for estimation of various physiological parameters, such as heart rate variability, arterial stiffness, and blood pressure, to name a few. As a result, PPG has become a popular biological modality and is widely used in wearable health devices. However, accurate measurement of various physiological parameters requires good-quality PPG signals. Therefore, various signal quality indexes (SQIs) for PPG signals have been proposed. These metrics have usually been based on statistical, frequency, and/or template analyses. The modulation spectrogram representation, however, captures the second-order periodicities of a signal and has been shown to provide useful quality cues for electrocardiograms and speech signals. In this work, we propose a new PPG quality metric based on properties of the modulation spectrum. The proposed metric is tested using data collected from subjects while they performed various activity tasks contaminating the PPG signals. Experiments on this multi-wavelength PPG dataset show the combination of proposed and benchmark measures significantly outperforming several benchmark SQIs with improvements of 21.3% BACC (balanced accuracy) for green, 21.6% BACC for red, and 19.0% BACC for infrared wavelengths, respectively, for PPG quality detection tasks. The proposed metrics also generalize for cross-wavelength PPG quality detection tasks.
Flexible Antenna with Circular/Linear Polarization for Wideband Biomedical Wireless Communication
Authors: Yassin Mohammed E. , Hussein Khaled F. A. , Abbasi Qammer H. , Imran Muhammad A. , Mohassieb Shaimaa A.
Published: June 2023

A wideband low-profile radiating G-shaped strip on a flexible substrate is proposed to operate as biomedical antenna for off-body communication. The antenna is designed to produce circular polarization over the frequency range 5–6 GHz to communicate with WiMAX/WLAN antennas. Furthermore, it is designed to produce linear polarization over the frequency range 6–19 GHz for communication with the on-body biosensor antennas. It is shown that an inverted G-shaped strip produces circular polarization (CP) of the opposite sense to that produced by G-shaped strip over the frequency range 5–6 GHz. The antenna design is explained and its performance is investigated through simulation, as well as experimental measurements. This antenna can be viewed as composed of a semicircular strip terminated with a horizontal extension at its lower end and terminated with a small circular patch through a corner-shaped strip extension at its upper end to form the shape of “G” or inverted “G”. The purpose of the corner-shaped extension and the circular patch termination is to match the antenna impedance to 50 Ω over the entire frequency band (5–19 GHz) and to improve the circular polarization over the frequency band (5–6 GHz). To be fabricated on only one face of the flexible dielectric substrate, the antenna is fed through a co-planar waveguide (CPW). The antenna and the CPW dimensions are optimized to obtain the most optimal performance regarding the impedance matching bandwidth, 3dB Axial Ratio (AR) bandwidth, radiation efficiency, and maximum gain. The results show that the achieved 3dB-AR bandwidth is 18% (5–6 GHz). Thus, the proposed antenna covers the 5 GHz frequency band of the WiMAX/WLAN applications within its 3dB-AR frequency band. Furthermore, the impedance matching bandwidth is 117% (5–19 GHz) which enables low-power communication with the on-body sensors over this wide range of the frequency. The maximum gain and radiation efficiency are 5.37 dBi and 98%, respectively. The overall antenna dimensions are 25 × 27 × 0.13 mm3 and the bandwidth-dimension ratio (BDR) is 1733.
Recent Progress in Lithium-Ion Battery Safety Monitoring Based on Fiber Bragg Grating Sensors
Authors: Chen Dongying , Zhao Qiang , Zheng Yi , Xu Yuzhe , Chen Yonghua , Ni Jiasheng , Zhao Yong
Published: June 2023

Lithium-ion batteries are widely used in a variety of fields due to their high energy density, high power density, long service life, and environmental friendliness. However, safety accidents with lithium-ion batteries occur frequently. The real-time safety monitoring of lithium-ion batteries is particularly important during their use. The fiber Bragg grating (FBG) sensors have some additional advantages over conventional electrochemical sensors, such as low invasiveness, electromagnetic anti-interference, and insulating properties. This paper reviews lithium-ion battery safety monitoring based on FBG sensors. The principles and sensing performance of FBG sensors are described. The single-parameter monitoring and dual-parameter monitoring of lithium-ion batteries based on FBG sensors are reviewed. The current application state of the monitored data in lithium-ion batteries is summarized. We also present a brief overview of the recent developments in FBG sensors used in lithium-ion batteries. Finally, we discuss future trends in lithium-ion battery safety monitoring based on FBG sensors.
Resistive Multi-Gas Sensor for Simultaneously Measuring the Oxygen Stoichiometry (λ) and the NOx Concentration in Exhausts: Engine Tests under Dynamic Conditions
Authors: Steiner Carsten , Wöhrl Thomas , Steiner Monika , Kita Jaroslaw , Müller Andreas , Eisazadeh Hessam , Moos Ralf , Hagen Gunter
Published: June 2023

Due to increasingly stringent limits for NOx emissions, there is now more interest than ever in cost-effective, precise, and durable exhaust gas sensor technology for combustion processes. This study presents a novel multi-gas sensor with resistive sensing principles for the determination of oxygen stoichiometry and NOx concentration in the exhaust gas of a diesel engine (OM 651). A screen-printed porous KMnO4/La-Al2O3 film is used as the NOx sensitive film, while a dense ceramic BFAT (BaFe0.74Ta0.25Al0.01O3–δ) film prepared by the PAD method is used for λ-measurement in real exhaust gas. The latter is also used to correct the O2 cross-sensitivity of the NOx sensitive film. This study presents results under dynamic conditions during an NEDC (new European driving cycle) based on a prior characterization of the sensor films in an isolated sensor chamber with static engine operation. The low-cost sensor is analyzed in a wide operation field and its potential for real exhaust gas applications is evaluated. The results are promising and, all in all, comparable with established, but usually more expensive, exhaust gas sensors.
Fixed-Time Recurrent NN Learning Control of Uncertain Robotic Manipulators with Time-Varying Constraints: Experimental Verification
Authors: Shi Qingxin , Li Changsheng , He Rui , Zhu Xiaolong , Duan Xingguang
Published: June 2023

This paper proposes a learning control framework for the robotic manipulator’s dynamic tracking task demanding fixed-time convergence and constrained output. In contrast with model-dependent methods, the proposed solution deals with unknown manipulator dynamics and external disturbances by virtue of a recurrent neural network (RNN)-based online approximator. First, a time-varying tangent-type barrier Lyapunov function (BLF) is introduced to construct a fixed-time virtual controller. Then, the RNN approximator is embedded in the closed-loop system to compensate for the lumped unknown term in the feedforward loop. Finally, we devise a novel fixed-time, output-constrained neural learning controller by integrating the BLF and RNN approximator into the main framework of the dynamic surface control (DSC). The proposed scheme not only guarantees the tracking errors converge to the small neighborhoods about the origin in a fixed time, but also preserves the actual trajectories always within the prescribed ranges and thus improves the tracking accuracy. Experiment results illustrate the excellent tracking performance and verify the effectiveness of the online RNN estimate for unknown dynamics and external disturbances.
Optimization of Tungsten Heavy Alloy Cutting Parameters Based on RSM and Reinforcement Dung Beetle Algorithm
Authors: Zhu Xu , Ni Chao , Chen Guilin , Guo Jiang
Published: June 2023

Tungsten heavy alloys (WHAs) are an extremely hard-to-machine material extensively used in demanding applications such as missile liners, aerospace, and optical molds. However, the machining of WHAs remains a challenging task as a result of their high density and elastic stiffness which lead to the deterioration of the machined surface roughness. This paper proposes a brand-new multi-objective dung beetle algorithm. It does not take the cutting parameters (i.e., cutting speed, feed rate, and depth of cut) as the optimization objects but directly optimizes cutting forces and vibration signals monitored using a multi-sensor (i.e., dynamometer and accelerometer). The cutting parameters in the WHA turning process are analyzed through the use of the response surface method (RSM) and the improved dung beetle optimization algorithm. Experimental verification shows that the algorithm has better convergence speed and optimization ability compared with similar algorithms. The optimized forces and vibration are reduced by 9.7% and 46.47%, respectively, and the surface roughness Ra of the machined surface is reduced by 18.2%. The proposed modeling and optimization algorithms are anticipated to be powerful to provide the basis for the parameter optimization in the cutting of WHAs.
Nanocomposite Co3O4-ZnO Thin Films for Photoconductivity Sensors
Authors: Petrov Victor V. , Sysoev Victor V. , Ignatieva Irina O. , Gulyaeva Irina A. , Volkova Maria G. , Ivanishcheva Alexandra P. , Khubezhov Soslan A. , Varzarev Yuri N. , Bayan Ekaterina M.
Published: June 2023

Thin nanocomposite films based on zinc oxide (ZnO) added with cobalt oxide (Co3O4) were synthesized by solid-phase pyrolysis. According to XRD, the films consist of a ZnO wurtzite phase and a cubic structure of Co3O4 spinel. The crystallite sizes in the films increased from 18 nm to 24 nm with growing annealing temperature and Co3O4 concentration. Optical and X-ray photoelectron spectroscopy data revealed that enhancing the Co3O4 concentration leads to a change in the optical absorption spectrum and the appearance of allowed transitions in the material. Electrophysical measurements showed that Co3O4-ZnO films have a resistivity up to 3 × 104 Ohm∙cm and a semiconductor conductivity close to intrinsic. With advancing the Co3O4 concentration, the mobility of the charge carriers was found to increase by almost four times. The photosensors based on the 10Co-90Zn film exhibited a maximum normalized photoresponse when exposed to radiation with wavelengths of 400 nm and 660 nm. It was found that the same film has a minimum response time of ca. 26.2 ms upon exposure to radiation of 660 nm wavelength. The photosensors based on the 3Co-97Zn film have a minimum response time of ca. 58.3 ms versus the radiation of 400 nm wavelength. Thus, the Co3O4 content was found to be an effective impurity to tune the photosensitivity of radiation sensors based on Co3O4-ZnO films in the wavelength range of 400–660 nm.
ReIPS: A Secure Cloud-Based Reputation Evaluation System for IoT-Enabled Pumped Storage Power Stations
Authors: Zong Yue , Wu Yuechao , Luo Yuanlin , Xu Han , Hu Wenjian , Yu Yao
Published: June 2023

Reputation evaluation is an effective measure for maintaining secure Internet of Things (IoT) ecosystems, but there are still several challenges when applied in IoT-enabled pumped storage power stations (PSPSs), such as the limited resources of intelligent inspection devices and the threat of single-point and collusion attacks. To address these challenges, in this paper we present ReIPS, a secure cloud-based reputation evaluation system designed to manage intelligent inspection devices’ reputations in IoT-enabled PSPSs. Our ReIPS incorporates a resource-rich cloud platform to collect various reputation evaluation indexes and perform complex evaluation operations. To resist single-point attacks, we present a novel reputation evaluation model that combines backpropagation neural networks (BPNNs) with a point reputation-weighted directed network model (PR-WDNM). The BPNNs objectively evaluate device point reputations, which are further integrated into PR-WDNM to detect malicious devices and obtain corrective global reputations. To resist collusion attacks, we introduce a knowledge graph-based collusion device identification method that calculates behavioral and semantic similarities to accurately identify collusion devices. Simulation results show that our ReIPS outperforms existing systems regarding reputation evaluation performance, particularly in single-point and collusion attack scenarios.
Improved Robot Path Planning Method Based on Deep Reinforcement Learning
Authors: Han Huiyan , Wang Jiaqi , Kuang Liqun , Han Xie , Xue Hongxin
Published: June 2023

With the advancement of robotics, the field of path planning is currently experiencing a period of prosperity. Researchers strive to address this nonlinear problem and have achieved remarkable results through the implementation of the Deep Reinforcement Learning (DRL) algorithm DQN (Deep Q-Network). However, persistent challenges remain, including the curse of dimensionality, difficulties of model convergence and sparsity in rewards. To tackle these problems, this paper proposes an enhanced DDQN (Double DQN) path planning approach, in which the information after dimensionality reduction is fed into a two-branch network that incorporates expert knowledge and an optimized reward function to guide the training process. The data generated during the training phase are initially discretized into corresponding low-dimensional spaces. An “expert experience” module is introduced to facilitate the model’s early-stage training acceleration in the Epsilon–Greedy algorithm. To tackle navigation and obstacle avoidance separately, a dual-branch network structure is presented. We further optimize the reward function enabling intelligent agents to receive prompt feedback from the environment after performing each action. Experiments conducted in both virtual and real-world environments have demonstrated that the enhanced algorithm can accelerate model convergence, improve training stability and generate a smooth, shorter and collision-free path.
Subjective Quality Assessment of V-PCC-Compressed Dynamic Point Clouds Degraded by Packet Losses
Authors: Dumic Emil , da Silva Cruz Luis A.
Published: June 2023

This article describes an empirical exploration on the effect of information loss affecting compressed representations of dynamic point clouds on the subjective quality of the reconstructed point clouds. The study involved compressing a set of test dynamic point clouds using the MPEG V-PCC (Video-based Point Cloud Compression) codec at 5 different levels of compression and applying simulated packet losses with three packet loss rates (0.5%, 1% and 2%) to the V-PCC sub-bitstreams prior to decoding and reconstructing the dynamic point clouds. The recovered dynamic point clouds qualities were then assessed by human observers in experiments conducted at two research laboratories in Croatia and Portugal, to collect MOS (Mean Opinion Score) values. These scores were subject to a set of statistical analyses to measure the degree of correlation of the data from the two laboratories, as well as the degree of correlation between the MOS values and a selection of objective quality measures, while taking into account compression level and packet loss rates. The subjective quality measures considered, all of the full-reference type, included point cloud specific measures, as well as others adapted from image and video quality measures. In the case of image-based quality measures, FSIM (Feature Similarity index), MSE (Mean Squared Error), and SSIM (Structural Similarity index) yielded the highest correlation with subjective scores in both laboratories, while PCQM (Point Cloud Quality Metric) showed the highest correlation among all point cloud-specific objective measures. The study showed that even 0.5% packet loss rates reduce the decoded point clouds subjective quality by more than 1 to 1.5 MOS scale units, pointing out the need to adequately protect the bitstreams against losses. The results also showed that the degradations in V-PCC occupancy and geometry sub-bitstreams have significantly higher (negative) impact on decoded point cloud subjective quality than degradations of the attribute sub-bitstream.
Application and Development of Fiber Optic Gyroscope Inertial Navigation System in Underground Space
Authors: Xu Hang , Wang Lu , Zu Yutong , Gou Wenchao , Hu Yuanbiao
Published: June 2023

Fiber Optic Gyroscope Inertial Navigation System (FOG-INS) is a navigation system using fiber optic gyroscopes and accelerometers, which can offer high-precision position, velocity, and attitude information for carriers. FOG-INS is widely used in aerospace, marine ships, and vehicle navigation. In recent years, it has also played an important role in underground space. For example, in the deep earth, FOG-INS can be used in directional well drilling, which can enhance recovery in resource exploitation. While, in shallow earth, FOG-INS is a high-precision positioning technique that can guide construction in trenchless underground pipelaying. This article extensively reviews the application status and latest progress of FOG-INS in underground space from three aspects—FOG inclinometer, FOG drilling tool attitude measurement while drilling (MWD) unit, and FOG pipe-jacking guidance system. First, measurement principles and product technologies are introduced. Second, the research hot spots are summarized. Finally, the key technical issues and future trends for development are put forward. The findings of this work are useful for further research in the field of FOG-INS in underground space, which not only provides new ideas and directions for scientific research, but also offers guidance for subsequent engineering applications.
Synthesis of ZnO Nanoflower Arrays on a Protrusion Sapphire Substrate and Application of Al-Decorated ZnO Nanoflower Matrix in Gas Sensors
Authors: Zhao Xin , Jheng Jang-Cheng , Chou Ni-Ni , Wang Fang-Hsing , Yang Cheng-Fu
Published: June 2023

In this study, we utilized a sapphire substrate with a matrix protrusion structure as a template. We employed a ZnO gel as a precursor and deposited it onto the substrate using the spin coating method. After undergoing six cycles of deposition and baking, a ZnO seed layer with a thickness of 170 nm was formed. Subsequently, we used a hydrothermal method to grow ZnO nanorods (NRs) on the aforementioned ZnO seed layer for different durations. ZnO NRs exhibited a uniform outward growth rate in various directions, resulting in a hexagonal and floral morphology when observed from above. This morphology was particularly evident in ZnO NRs synthesized for 30 and 45 min. Due to the protrusion structure of ZnO seed layer, the resulting ZnO nanorods (NRs) displayed a floral and matrix morphology on the protrusion ZnO seed layer. To further enhance their properties, we utilized Al nanomaterial to decorate the ZnO nanoflower matrix (NFM) using a deposition method. Subsequently, we fabricated devices using both undecorated and Al-decorated ZnO NFMs and deposited an upper electrode using an interdigital mask. We then compared the gas-sensing performance of these two types of sensors towards CO and H2 gases. The research findings indicate that sensors based on Al-decorated ZnO NFM exhibit superior gas-sensing properties compared to undecorated ZnO NFM for both CO and H2 gases. These Al-decorated sensors demonstrate faster response times and higher response rates during the sensing processes.
Detection of Failures in Metal Oxide Surge Arresters Using Frequency Response Analysis
Authors: Zacarias Tiago Goncalves , Martins Rafael , Xavier Carlos Eduardo , Castioni Julio Cezar Oliveira , Sant’Ana Wilson Cesar , Lambert-Torres Germano , Gama Bruno Reno , Areias Isac Antonio dos Santos , Bonaldi Erik Leandro , Assuncao Frederico De Oliveira
Published: June 2023

This work presents an innovative application of Frequency Response Analysis (FRA) in order to detect early degradation of Metal Oxide Surge Arresters (MOSAs). This technique has been widely used in power transformers, but has never been applied to MOSAs. It consists in comparisons of spectra, measured at different instants of the lifetime of the arrester. Differences between these spectra are an indicator that some electrical properties of the arrester have changed. An incremental deterioration test has been performed on arrester samples (with controlled circulation of leakage current, which increases the energy dissipation over the device), and the FRA spectra correctly identified the progression of damage. Although preliminary, the FRA results seemed promising, and it is expected that this technology could be used as another diagnostic tool for arresters.
Toward Improvements in Pressure Measurements for Near Free-Field Blast Experiments
Authors: Lavayssière Maylis , Lefrançois Alexandre , Crabos Bernard , Genetier Marc , Daudy Maxime , Comte Sacha , Dufourmentel Alan , Salsac Bruno , Sol Frédéric , Verdier Pascal , Pons Patrick
Published: June 2023

This paper proposes two ways to improve pressure measurement in air-blast experimentations, mostly for close-in detonations defined by a small-scaled distance below 0.4 m.kg−1/3. Firstly, a new kind of custom-made pressure probe sensor is presented. The transducer is a piezoelectric commercial, but the tip material has been modified. The dynamic response of this prototype is established in terms of time and frequency responses, both in a laboratory environment, on a shock tube, and in free-field experiments. The experimental results show that the modified probe can meet the measurement requirements of high-frequency pressure signals. Secondly, this paper presents the initial results of a deconvolution method, using the pencil probe transfer function determination with a shock tube. We demonstrate the method on experimental results and draw conclusions and prospects.
Intelligent Fault Diagnosis of Liquid Rocket Engine via Interpretable LSTM with Multisensory Data
Authors: Zhang Xiaoguang , Hua Xuanhao , Zhu Junjie , Ma Meng
Published: June 2023

Fault diagnosis is essential for high energy systems such as liquid rocket engines (LREs) due to harsh thermal and mechanical working environment. In this study, a novel method based on one-dimension Convolutional Neural Network (1D-CNN) and interpretable bidirectional Long Short-term Memory (LSTM) is proposed for intelligent fault diagnosis of LREs. 1D-CNN is responsible for extracting sequential signals collected from multi sensors. Then the interpretable LSTM is developed to model the extracted features, which contributes to modeling the temporal information. The proposed method was executed for fault diagnosis using the simulated measurement data of the LRE mathematical model. The results demonstrate the proposed algorithm outperforms other methods in terms of accuracy of fault diagnosis. Through experimental verification, the method proposed in this paper was compared with CNN, 1DCNN-SVM and CNN-LSTM in terms of LRE startup transient fault recognition performance. The model proposed in this paper had the highest fault recognition accuracy (97.39%).
Spatially Resolved Protein Binding Kinetics Analysis in Microfluidic Photonic Crystal Sensors
Authors: Lehmann Stefanie , Kraft Fabio Aldo , Gerken Martina
Published: June 2023

Organ-on-a-Chip systems are emerging as an important in vitro analysis method for drug screening and medical research. For continuous biomolecular monitoring of the cell culture response, label-free detection within the microfluidic system or in the drainage tube is promising. We study photonic crystal slabs integrated with a microfluidic chip as an optical transducer for label-free biomarker detection with a non-contact readout of binding kinetics. This work analyzes the capability of same-channel reference for protein binding measurements by using a spectrometer and 1D spatially resolved data evaluation with a spatial resolution of 1.2 μm. A cross-correlation-based data-analysis procedure is implemented. First, an ethanol–water dilution series is used to obtain the limit of detection (LOD). The median of all row LODs is (2.3±0.4)×10−4 RIU with 10 s exposure time per image and (1.3±0.24)×10−4 RIU with 30 s exposure time. Next, we used a streptavidin–biotin binding process as a test system for binding kinetics. Time series of optical spectra were recorded while constantly injecting streptavidin in DPBS at concentrations of 1.6 nM, 3.3 nM, 16.6 nM and 33.3 nM into one channel half as well as the whole channel. The results show that localized binding within a microfluidic channel is achieved under laminar flow. Furthermore, binding kinetics are fading out at the microfluidic channel edge due to the velocity profile.
Backscattering Echo Intensity Characteristics of Laser in Soil Explosion Dust
Authors: Gao Lijuan , Lien Fue-Sang , Chen Huimin , Chen Guang , Yang Shangxian , Deng Jiahao
Published: June 2023

Soil dust generated by explosions can lead to the absorption and scattering of lasers, resulting in low detection and recognition accuracy for laser-based devices. Field tests to assess laser transmission characteristics in soil explosion dust are dangerous and involve uncontrollable environmental conditions. Instead, we propose using high-speed cameras and an indoor explosion chamber to assess the backscattering echo intensity characteristics of lasers in dust generated by small-scale explosive blasts in soil. We analyzed the influence of the mass of the explosive, depth of burial, and soil moisture content on crater features and temporal and spatial distributions of soil explosion dust. We also measured the backscattering echo intensity of a 905 nm laser at different heights. The results showed that the concentration of soil explosion dust was highest in the first 500 ms. The minimum normalized peak echo voltage ranged from 0.318 to 0.658. The backscattering echo intensity of the laser was found to be strongly correlated with the mean gray value of the monochrome image of soil explosion dust. This study provides experimental data and a theoretical basis for the accurate detection and recognition of lasers in soil explosion dust environments.
YOLO-Weld: A Modified YOLOv5-Based Weld Feature Detection Network for Extreme Weld Noise
Authors: Gao Ang , Fan Zhuoxuan , Li Anning , Le Qiaoyue , Wu Dongting , Du Fuxin
Published: June 2023

Weld feature point detection is a key technology for welding trajectory planning and tracking. Existing two-stage detection methods and conventional convolutional neural network (CNN)-based approaches encounter performance bottlenecks under extreme welding noise conditions. To better obtain accurate weld feature point locations in high-noise environments, we propose a feature point detection network, YOLO-Weld, based on an improved You Only Look Once version 5 (YOLOv5). By introducing the reparameterized convolutional neural network (RepVGG) module, the network structure is optimized, enhancing detection speed. The utilization of a normalization-based attention module (NAM) in the network enhances the network’s perception of feature points. A lightweight decoupled head, RD-Head, is designed to improve classification and regression accuracy. Furthermore, a welding noise generation method is proposed, increasing the model’s robustness in extreme noise environments. Finally, the model is tested on a custom dataset of five weld types, demonstrating better performance than two-stage detection methods and conventional CNN approaches. The proposed model can accurately detect feature points in high-noise environments while meeting real-time welding requirements. In terms of the model’s performance, the average error of detecting feature points in images is 2.100 pixels, while the average error in the world coordinate system is 0.114 mm, sufficiently meeting the accuracy needs of various practical welding tasks.
A Cycle Slip Detection and Repair Method Based on Inertial Aiding for BDS Triple-Frequency Signals
Authors: Fu Xiyu , Sun Yongrong , Wu Ling , Wang Kaifeng , Zhao Kedong
Published: June 2023

Cycle slip detection and repair is a prerequisite to obtain high-precision positioning based on a carrier phase. Traditional triple-frequency pseudorange and phase combination algorithm are highly sensitive to the pseudorange observation accuracy. To solve the problem, a cycle slip detection and repair algorithm based on inertial aiding for a BeiDou navigation satellite system (BDS) triple-frequency signal is proposed. To enhance the robustness, the INS-aided cycle slip detection model with double-differenced observations is derived. Then, the geometry-free phase combination is united to detect the insensitive cycle slip, and the optimal coefficient combination is selected. Furthermore, the L2-norm minimum principle is used to search and confirm the cycle slip repair value. To correct the INS error accumulated over time, the extended Kalman filter based on the BDS/INS tightly coupled system is established. The vehicular experiment is conducted to evaluate the performance of the proposed algorithm from a few aspects. The results indicate that the proposed algorithm can reliably detect and repair all cycle slips that occur in one cycle, including the small and insensitive cycle slips as well as the intensive and continuous cycle slips. Additionally, in signal-challenged environments, the cycle slips occurring 14 s after a satellite signal outage can be correctly detected and repaired.
A Mid-Infrared Quantum Cascade Laser Ultra-Sensitive Trace Formaldehyde Detection System Based on Improved Dual-Incidence Multipass Gas Cell
Authors: Wu Tao , Hu Renzhi , Xie Pinhua , Zhang Lijie , Hu Changjin , Liu Xiaoyan , Wang Jiawei , Zhong Liujun , Tong Jinzhao , Liu Wenqing
Published: June 2023

Formaldehyde (HCHO) is a tracer of volatile organic compounds (VOCs), and its concentration has gradually decreased with the reduction in VOC emissions in recent years, which puts forward higher requirements for the detection of trace HCHO. Therefore, a quantum cascade laser (QCL) with a central excitation wavelength of 5.68 μm was applied to detect the trace HCHO under an effective absorption optical pathlength of 67 m. An improved, dual-incidence multi-pass cell, with a simple structure and easy adjustment, was designed to further improve the absorption optical pathlength of the gas. The instrument detection sensitivity of 28 pptv (1σ) was achieved within a 40 s response time. The experimental results show that the developed HCHO detection system is almost unaffected by the cross interference of common atmospheric gases and the change of ambient humidity. Additionally, the instrument was successfully deployed in a field campaign, and it delivered results that correlated well with those of a commercial instrument based on continuous wave cavity ring-down spectroscopy (R2 = 0.967), which indicates that the instrument has a good ability to monitor ambient trace HCHO in unattended continuous operation for long periods of time.
Conditional Tabular Generative Adversarial Based Intrusion Detection System for Detecting Ddos and Dos Attacks on the Internet of Things Networks
Authors: Alabsi Basim , Anbar Mohammed , Rihan Shaza
Published: June 2023

The increasing use of Internet of Things (IoT) devices has led to a rise in Distributed Denial of Service (DDoS) and Denial of Service (DoS) attacks on these networks. These attacks can have severe consequences, resulting in the unavailability of critical services and financial losses. In this paper, we propose an Intrusion Detection System (IDS) based on a Conditional Tabular Generative Adversarial Network (CTGAN) for detecting DDoS and DoS attacks on IoT networks. Our CGAN-based IDS utilizes a generator network to produce synthetic traffic that mimics legitimate traffic patterns, while the discriminator network learns to differentiate between legitimate and malicious traffic. The syntactic tabular data generated by CTGAN is employed to train multiple shallow machine-learning and deep-learning classifiers, enhancing their detection model performance. The proposed approach is evaluated using the Bot-IoT dataset, measuring detection accuracy, precision, recall, and F1 measure. Our experimental results demonstrate the accurate detection of DDoS and DoS attacks on IoT networks using the proposed approach. Furthermore, the results highlight the significant contribution of CTGAN in improving the performance of detection models in machine learning and deep learning classifiers.