bluuebunny/crossref_metadata_2025_split huggingface dataset:
The pro-environmental behavioral intention of villagers in rural tourist destinations under China’s environmental remediation policy
Authors: Tang Hongjiu , Hu Di , Long Yuelin , Zhao Yuqi 
Published: August 2023

AbstractThis study examined villagers’ intention of pro-environmental behavior while supporting the Landcare Policy in China. The research team conducted field surveys of villagers from four famous scenic spots of Cili, which is near the world natural heritage site of the Zhangjiajie natural landscape core area. This area has developed rural tourism, many local villagers rely on tourism to obtain their livelihood income. However, the area is now affected by the environmental remediation policy called Landcare Policy. Cultivated land near the tourist area needs to be repaired, which affects the tourism income of some local villagers. Therefore, local villagers are facing a contradiction between tourism development and environmental protection. The study chose the change in local villagers’ pro-environmental intention as the research content. Then we adopted an empirically validated norm activation model (NAM) from Schwartz, and merged the NAM with the expectancy theory of Vroom, based on 511 valid responses from the field questionnaire surveys, we aimed to develop a theoretical framework for researchers to understand the change in villagers' pro-environmental behaviors, concerning the balance between rural tourism livelihood benefits and environmental remediation behavior. Structural equation modeling was conducted for each index of the responses, the findings showed that the merged model had 76.46% better predictive accuracy of villagers’ pro-environmental intentions than applying Schwartz’s NAM independently. This study found that the motivational force of this new theory significantly influences environmental personal norms due to the joint impact of valence, instrumentality, and expectancy. Villagers with a positive pro-environmental behavior intention expect good tourism benefits and environmental living conditions under the impact of the Landcare policy in rural tourism destinations near the famous natural heritage site.
An investigation on removal of ciprofloxacin and norfloxacin by phycoremediation with an emphasis on acute toxicity and biochemical composition
Authors: Ricky R. , Shanthakumar S. 
Published: August 2023

AbstractCiprofloxacin (CIP) and norfloxacin (NOR) belong to the class of emerging contaminants that are frequently detected in the aquatic environment as a binary mixture, responsible for the development of antibiotic-resistant genes and antibiotic-resistant bacteria. This study aims to investigate five different algal species Chlorella vulgaris (Cv), Chlorella pyrenoidosa (Cp), Scenedesmus obliquus (So), Tetradesmus sp (T) and Monoraphidium sp (M) for their tolerance and removal of binary mixture. The effects on biochemical composition in the algal species concerning the binary mixture and its removal efficiency are first reported in this study. The acute toxicity (96 h EC50) values are in the order of So > Cp > T > M > Cv, Chlorella vulgaris is the most sensitive algal species with 17.73 ± 0.24 mg/L and Scenedesmus obliquus is the least sensitive algal species with 39.19 ± 0.79 mg/L. The removal efficiency of the binary mixture was found to be in the order of So > Cp > T > M > Cv, Scenedesmus obliquus removed CIP (52.4%) and NOR (87.5%) with biodegradation as the major contributing removal mechanism. Furthermore, less toxic biotransformed products were detected in Scenedesmus obliquus and the biochemical characterization revealed that the growth-stimulating effect is higher with lipid (35%), carbohydrate (18%), and protein (33%) providing an advantage in the production of valuable biomass.
Speech and Music Therapy in the Treatment of Childhood Apraxia of Speech: An Introduction and a Case Study
Authors: van Tellingen Mirjam , Hurkmans Joost , Terband Hayo , van de Zande Anne Marie , Maassen Ben , Jonkers Roel 
Published: August 2023

Purpose:
Speech–Music Therapy for Aphasia (SMTA), a method that combines speech therapy and music therapy, is introduced as a treatment method for childhood apraxia of speech (CAS). SMTA will be evaluated in a proof-of-principle study. The first case study is presented herein.

Method:
SMTA was evaluated in a study with a single-subject experimental design comparing 10 weeks of treatment with 2 months of no treatment. The research protocol included a pretest, baseline phase, treatment phase, posttest, no-treatment phase, and follow-up test. The participant was a boy with CAS aged 5;8 (years;months). Outcome measures were selected to reflect both intelligibility in daily communication as well as features of CAS and speech motor planning and programming.

Results:
Results on the Intelligibility in Context Scale–Dutch (ICS-Dutch) and in the analysis of a spontaneous speech sample suggest generalization of treatment effects. Improvements were found in measures that reflect complex speech motor skills, that is, the production of consonant clusters and consistency.

Conclusions:
This case study showed that speech production of the participant improved after treatment with SMTA. Although intelligibility as measured with the ICS-Dutch improved over the study period, objectifying changes at the level of intelligibility in daily communication proved to be difficult. Additional measures may be necessary to gain more insight into treatment effects at this level.
Overall, the results of this first case study provide sufficient support and important leads for further evaluation of SMTA in the treatment of CAS in a proof-of-principle study.
Recover all coefficients in second-order hyperbolic equations from finite sets of boundary measurements
*
Authors: Liu Shitao , Pierrottet Antonio , Scruggs Scott 
Published: August 2023

Abstract
We consider the inverse hyperbolic problem of recovering all spatial dependent coefficients, which are the wave speed, the damping coefficient, potential coefficient and gradient coefficient, in a second-order hyperbolic equation defined on an open bounded domain with smooth enough boundary. We show that by appropriately selecting finite pairs of initial conditions we can uniquely and Lipschitz stably recover all those coefficients from the corresponding boundary measurements of their solutions. The proofs are based on Carleman estimate, continuous observability inequality and regularity theory for general second-order hyperbolic equations.
Coexistence of spin liquid state and magnetic correlations in 3d-5d based triangular-lattice antiferromagnet Sr3CuIr2O9
Authors: Gondh Shobha , Kumar Kranti , Saravanan M P , Pramanik A K 
Published: August 2023

Abstract
Here, we report detailed lattice structure, magnetization (dc and ac) and specific heat measurements on a 3d-5d based new triple-perovskite material Sr3CuIr2O9. The Sr/Cu forms a layered structure of triangular-lattice while the Ir forms Ir2O9 dimers which lie in chain as well as simultaneously makes layered triangular-lattice with neighboring atoms. Due to random site-sharing with Sr2+, the Cu2+ (3d
9, spin-1/2) forms a diluted magnetic lattice, thus giving a disordered in-plane exchange interaction. Opposed to conventional

J

e
f
f

model, the Ir5+ (5d
4,

J

e
f
f

= 0) is believed to be magnetic here which participates both in-chain and in-plane magnetic interactions. This complex lattice structure driven competing exchange interaction leads the ground state to a gapless quantum-spin-liquid state which coexists with (weak) ferromagnetic spin correlations. While underling the importance of spin state (spin-1/2), we believe that the combined effect of lattice structure, geometric frustration, spin–orbit coupling and spin state has given rise this interesting ground state in this material.
A multi-frequency and multi-mode metasurface energy harvester for RF energy harvesting
Authors: Huang Xiaojun , Wang Kun , Sun Cuizhen , Li Chuan , Zhang Jianchen , Li Shouqing 
Published: August 2023

Abstract
Metasurface energy harvesters (MEHs) lessen the dependence of wireless communication devices on batteries or other external power sources by capturing untapped electromagnetic energy in the surroundings. In this paper, we propose a multi-frequency and multi-mode microwave metasurface for efficient radio frequency (RF) and microwave energy harvesting. The MEH is comprised of a sub-wavelength resonant ring array, which can harvest RF energy in both Wi-Fi and 5 GHz bands. A feeding network is designed to integrate the TE and TM wave energy collected by the MEH into two separate networks that each gather AC energy and deliver them to the resistive loads. In terms of the simulation’s results, the efficiency of energy harvesting at frequencies of 2.4 GHz, 3.1 GHz, as well as 3.6 GHz is 91.3%, 88.9%, and 73.9%, specifically. We manufactured a 6 × 6 array sample and conducted experiments utilizing a microwave anechoic chamber. The simulation results and results from experiments were approximately identical. The proposed design has potential applications in various fields, such as efficient wireless energy harvesting systems, self-powered devices, which has a significant potential on the environment and the energy sector by reducing carbon emissions and reducing reliance on non-renewable energy sources.
A flexible metamaterial absorber with temperature-insensitive design at microwave frequencies
Authors: Li Kai , Lu Haipeng , Bi Mei , Qi Lun , Weng Xiaolong 
Published: August 2023

Abstract
Developing a metamaterial absorber (MA) with both flexibility and temperature insensitivity continues to be a challenge in the field of radar stealth. In this paper, we propose a compensation method for designing flexible and temperature-insensitive MA. This method is revealed through the relationship between the square resistance of the resistive film, the permittivity of the substrate, and the temperature. Importantly, the compensation method is applicable to both the MA in the plane state and the bending state. By utilizing the benefits of the compensation mechanism and the flexible designability of the bilayer cross-shaped structure, the flexible MA proposed in this paper can achieve temperature-insensitive absorption across a broad frequency range. Experimental results indicate that the absorption peaks achieve an absorptivity greater than 90% within the frequency of 7.2–9.4 GHz, exhibiting excellent temperature stability from 25 °C to 300 °C. In comparison to previous studies on flexible MAs, this design offers a distinct advantage in high-temperature environments and provides valuable guidelines for the design of integrated multi-functional absorbers in practical applications.
Improved two-mode dynamic model for external-cavity quantum cascade lasers under strong optical feedback
Authors: Yousefvand Hossein Reza 
Published: August 2023

Abstract
In this paper, we propose an improved model for describing the dynamical behavior and mode selection mechanism of an external-cavity quantum-cascade laser (EC-QCL) when subject to strong optical feedback. Theoretical analysis including the dynamical effective reflectivity model, two-mode rate-equation model and Lang-Kobayashi equations are employed to carry out the laser output characteristics under the multiple feedback effects. A main aspect of the model is that the excess mirror loss caused by the EC effective reflectivity is incorporated into the laser dynamical equations as a nonlinear dynamical variable. Because of accounting the multiple round-trip feedback terms in the EC effective reflectivity, the analysis is valid for the arbitrary feedback regimes from weak to strong levels. Besides the stationary characteristics, the model accurately predicts the dynamical competition between the fundamental laser-cavity mode and the desired EC mode that reflected strongly by external diffraction grating. The results are in well agreement with theoretical and experimental data reported earlier for the EC-QCLs.
Performance of hollow hyperbolic sinusoidal Gaussian beam in weak turbulent optical communication links
Authors: Secilmis Gamze Nur , Bayraktar Mert , Elmabruk Kholoud 
Published: August 2023

Abstract
The performance of hollow hyperbolic sinusoidal Gaussian beam (HHsGB) propagating in weak turbulent optical communication link is examined by analysing the beam scintillation indices. System parameters’ effect on point-like and aperture-averaged scintillation index values is investigated. The obtained results show that HHsGBs with small source sizes improve the link performance by reducing the scintillation level. In communication systems with a big receiver aperture radius, HHsGBs with high orders significantly minimize the scintillation level. Thus, the provided results will have significant potential in improving free-space optical communication performance in a wide range of applications.
Research on Aircraft Wheel Hub Pose Detection Method Based on Machine Vision
Authors: Ren Wenbo , Zhu Yiwen , Zhang Ning 
Published: August 2023

Abstract
In order to achieve the action of lifting and clamping the aircraft wheel by the wheel holding device, machine vision is innovatively introduced to detect the position and pose of the wheel hub during the wheel holding process. The overall process design was systematically carried out, and an industrial camera was selected and calibrated. Then, the generalized Hough transform was used to extract the target from the processed image, and its center position was calculated. Based on the data of the number and position of the target’s center, it was determined whether the wheel hub was intact. If it was incomplete, more photos were taken. If the number of targets met the standard and the wheel hub was intact, the PnP pose calculation algorithm was adopted to calculate the position and pose of the wheel hub. The results showed that the calculated position and pose met the requirements proposed by the project design.
Detection of Agricultural Pests Based on YOLO
Authors: Luo Yingjie , Ni Lei , Cai Fangkai , Wang Daming , Luo Yang , Li Xiaoyu , Fu Ning , Tang Jiangwen , Xue Liang 
Published: August 2023

Abstract
Focus on the problem of the species pests are difficult to identify in agricultural production an application based on the YOLO algorithm is presented. The algorithm extracts features fastly and complete detection task simultaneously. Through collecting agricultural pests, the algorithm establishes a data-set build target object detection model and train them, the problem of difficulties in identifying agricultural pest species and locating them has been solved. The result shows that the mAP’value of YOLO algorithm is 92.42%, the prediction precision is 96.8%. The algorithm has a high recognition rate, and identify the species of pests fastly and accurately, it can meet the detection and identification requirements.
Study on Facial Recognition Method Based on YOLOv5
Authors: Xu Wenjin , Li Bo , Du Yonghui , Dong Shaokang 
Published: August 2023

Abstract
This study focuses on the facial recognition algorithm. To address limitations of facial recognition, this paper proposes a deep learning method called YOLOv5-Attention for facial feature extraction, recognition. The algorithm in the article is designed based on YOLOv5 and incorporates an attention mechanism module to enhance the expression ability of the model’s eyebrow features and improve its overall performance. The experimental results demonstrate that the algorithm proposed in this paper achieves a harmonic mean of 94% for eyebrow recognition accuracy. This highlights the effectiveness and reliability of the algorithm, which can be applied to eyebrow recognition and dramatic character facial recognition, as well as the research of general facial recognition.
Object Detection Based on Fusion of Visible and Infrared Images
Authors: Yongshi Ye , Haoyu Ma , Tashi Nima , Xinting Liu , Yuchen Yuan , Zihang Shang 
Published: August 2023

Abstract
In consideration of the complementary characteristics between visible light and infrared images, this paper proposes a novel method for object detection based on the fusion of these two types of images, thereby enhancing detection accuracy even under harsh environmental conditions. Specifically, we employ an improved AE network, which encodes and decodes the visible light and infrared images into dual-scale image decomposition. By reconstructing the original images with the decoder, we highlight the details of the fused image. Yolov5 network is then constructed based on this fused image, and its parameters are adjusted accordingly to achieve accurate detection of objects. Due to the complementary information features that are missing between the two image types, our method effectively enhances the precision of object detection.
Typical Fault Characteristics Analysis of Distribution Network
Authors: Yu Xiaoxi , Huang Jianqiong , Zhou Bin , Zahir Muhammad Zeeshan 
Published: August 2023

Abstract
China has built the largest power network in the world, forming a pattern of “nationwide interconnection, sending power from west to east, mutual supply between south and north.” As the user-oriented terminal power network, the safe operation of distribution network is the basis of power system stability. However, the distribution network system is huge, widely distributed and prone to failure. In order to quickly and accurately judge the fault category, improve the efficiency of fault location and reduce the non-fault outage area after the fault occurs in the distribution network system. Four typical faults of distribution network, namely single-phase grounding fault, phase-to-phase short circuit fault, ferromagnetic resonance and magnetizing inrush current, are studied in this paper, their fault characteristics are analyzed, and fault simulation analysis is carried out by MATLAB. Finally, the theoretical analysis results are verified by the actual on-site fault recording data, which proves the scientific and feasibility of the theoretical analysis.
An Intelligent Optimization Method for Wireless Communication Network Resources Based on Reinforcement Learning
Authors: Tian Di 
Published: August 2023

Abstract
The scarcity of spectrum resources is becoming increasingly severe, and the traditional static spectrum allocation method leads to low spectrum utilization. To address these issues, this article introduces reinforcement learning (RL) into wireless communication systems and proposes an optimization method for wireless resource allocation in deep Q networks (DQN). This paper uses the deep reinforcement learning (DRL) method to model the selection process of cluster heads and relay nodes as a Markov decision process, and then uses DQN to establish a cluster head and relay node selection mechanism aimed at maximizing the life cycle of wireless sensor network (WSN). Experimental results show that compared with the existing algorithms, the proposed algorithm effectively reduces the energy consumption of the network and extends the life cycle of WSN. Ultimately, it is possible to reconfigure relevant spectrum resources to obtain available spectrum resources, and idle spectrum resources can be discovered at any time.
Named Entity Recognition of Electronic Medical Records based on BERT-BiLSTM-Biaffine Model
Authors: Wang Peng , Gu Jinguang 
Published: August 2023

Abstract
In the case of the specific task of identifying named entities within electronic medical record, it is hard to determine the boundary of nested entities, and existing NER systems have insufficient decoding performance. Based on the pre training model BERT, this paper introduces a novel network structure called Biaffine Layer using a bidirectional LSTM layer. The network uses a dual affine attention mechanism for semantic information learning, which can better interact with the semantic information of entity heads and entity tails, thereby achieving better recognition results for entities. Due to the sparsity of named entity datasets and the uneven distribution of entity categories, traditional binary cross entropy loss functions require multiple rounds of training to decode entities. In this paper, we have modified the binary cross entropy loss function to make the proposed model faster decode the entities that need to be identified. The model performs well, according to the experimental findings. The approach suggested in this paper offers a fresh approach to the NER issue raised by electronic medical records, and it is anticipated to considerably boost the effectiveness and caliber of clinical medical research.
Research on Resource Allocation Strategies for Wireless Powered Sensor Network
Authors: Yuan Lina , Huang Mingjuan , Wen Xianli , Wang Rong 
Published: August 2023

Abstract
Wireless powered sensor network (WPSN) solves the problem of difficult battery replacement of sensor nodes in some environments. The unreasonable distribution of network resources in the energy transmission environment will lead to a sharp decline in the energy collected by sensor nodes, reduce the network life, and cause resource waste. In this paper, by introducing hybrid relay nodes to transmit energy to passive terminals and forward terminal information, the distance between passive terminals and final receiving nodes of information is reduced, and the contradiction between passive terminals’ data transmission requirements and “double path loss” of radio frequency energy transmission in WPSN is alleviated. At the same time, in the relay-powered WPSN, the life span of the relay node is equal to the life span of the whole network. This paper studies the energy efficiency transmission scheme of the relay node to maximize the energy utilization efficiency of the relay node and improve the life span of the WPSN.
Temperature drop for CO2 gas flowing through multilayer micro-pin fin arrays
Authors: Hua Chaoyue , Weng Jiahua , Yan Jia’ning , Cui Xiaoyu 
Published: August 2023

Abstract
A reasonable theoretical calculation model is established, and an appropriate correlation formula is selected to calculate the flow and heat transfer of CO2 gas flowing through micro-pin fin arrays in a micro-cooler respectively under different working conditions. The inlet pressure of CO2 gas is 1.0 MPa, 1.5 MPa, and 2.0 MPa respectively, and the inlet temperature is 12 °C and 16 °C respectively. The results show that the cold end temperature of the gas decreases with the increase of CO2 gas inlet pressure and the decrease of inlet temperature, and the lowest temperature reaches -29.93 °C. The calculated results have the same trend as the experimental data, and the calculated values are consistent with the experimentally measured values, which demonstrates the calculation model’s logic.
Power quality transient disturbances detection system based on db5 wavelet
Authors: Liu Dongmei , Zhu Weiyuan , Wang Yanhui , Chang Ziyi , Xie Kaikai , Wang Shun 
Published: August 2023

Abstract
To improve the real-time and accuracy of transient disturbance localization in the power grid, this paper designs an FPGA-based transient disturbance detection system based on the good time-frequency local analysis capability, multi-resolution analysis characteristics of wavelet decomposition, and the selection of db5 (Daubechies 5) wavelets. The system acquires the original disturbance signal through an external high-speed AD/DA board, implements the wavelet transform algorithm by the EP4CE10F17C8 FPGA, and then feeds back to the high-speed AD/DA board to output the location of the singularities in the high-frequency detail signal that corresponds to the start and end moments of the disturbance. Simulation and actual test results together show that the system can accurately and quickly locate the start and end moments of typical single disturbances such as voltage sag and short interruption, with a measurement deviation of within 3ms, meeting the real-time requirements.