bluuebunny/crossref_metadata_2025 huggingface dataset:
A Construction Grammar of the English Language
Authors: Herbst Thomas , Hoffmann Thomas
Published: October 2024

The present book provides an introduction to the linguistic model of Construction Grammar, offering a full analysis of the grammar of the English language. It covers all levels of morpho-syntactic form-meaning units: including sentence types, tense and aspect, argument structure, phrases, idioms, word and morphological constructions.
In line with its usage-based approach, all constructions are discussed using authentic corpus examples. In order to illustrate how constructions can be learnt, the book draws on authentic data from child language. Furthermore, corpus analysis is used to show which lexical items typically occur in the slots of constructions and make up their ‘collo-profile’.
A key feature of the book is that it develops a systematic method for showing how constructions combine to form actual utterances. For this purpose, so-called ‘construction grids’ are developed which contain all the constructions that make up even the most complex sentences and show points of overlap between them.
Myeloid activation clears ascites and reveals IL27-dependent regression of metastatic ovarian cancer
Authors: Murphy Brennah , Miyamoto Taito , Manning Bryan S. , Mirji Gauri , Ugolini Alessio , Kannan Toshitha , Hamada Kohei , Zhu Yanfang P. , Claiborne Daniel T. , Huang Lu , Zhang Rugang , Nefedova Yulia , Kossenkov Andrew , Veglia Filippo , Shinde Rahul , Zhang Nan
Published: October 2024

Patients with metastatic ovarian cancer (OvCa) have a 5-year survival rate of <30% due to the persisting dissemination of chemoresistant cells in the peritoneal fluid and the immunosuppressive microenvironment in the peritoneal cavity. Here, we report that intraperitoneal administration of β-glucan and IFNγ (BI) induced robust tumor regression in clinically relevant models of metastatic OvCa. BI induced tumor regression by controlling fluid tumor burden and activating localized antitumor immunity. β-glucan alone cleared ascites and eliminated fluid tumor cells by inducing intraperitoneal clotting in the fluid and Dectin-1-Syk–dependent NETosis in the omentum. In omentum tumors, BI expanded a novel subset of immunostimulatory IL27+ macrophages and neutralizing IL27 impaired BI efficacy in vivo. Moreover, BI directly induced IL27 secretion in macrophages where single agent treatment did not. Finally, BI extended mouse survival in a chemoresistant model and significantly improved chemotherapy response in a chemo-sensitive model. In summary, we propose a new therapeutic strategy for the treatment of metastatic OvCa.
Chaotic behavior and multistability of a tree trunk structure driven by self-and parametric hydrodynamic forces
Authors: Adéchinan A J , Kpomahou Y J F , Adéyémi C
Published: October 2024

This study investigates the chaotic behavior of a tree trunk under dynamic wind loads, focusing on control strategies and multistability. We consider time-varying wind speeds and analyze a specific case where hydrodynamic drag forces align with the flow velocity. The stability of the model’s equilibrium points is analyzed theoretically and numerically. Melnikov’s method is employed to identify conditions for homoclinic bifurcation. Numerical simulations employing basin of attraction confirm the analytical predictions. Our findings show a decrease in the threshold for chaos with increasing amplitudes of external excitation, damping coefficient, and parametric damping. The global dynamics are explored numerically using a fourth-order Runge-Kutta method. When solely subjected to external excitation, the system exhibits period doubling bifurcations, multiperiodic oscillations, mixed-mode oscillations, and chaos. Conversely, with self- and parametric drag forces, the system displays reverse periodic bifurcations, periodic bubbling oscillations, antimonotonicity, transient chaos, and chaos. Poincaré maps analyze the geometric structure of chaotic attractors, revealing a strong influence of dimensionless drag parameters. These parameters can be manipulated to control or eliminate chaos. Furthermore, the system exhibits multistability, with coexisting attractors. Beyond its application in protecting infrastructure from wind damage, this research can contribute to ecological balance by improving our understanding of tree wind resistance.
Longitudinal one-dimensional mechanical topological insulator
Authors: Carhart Madeleine Hoag , Fairfield Parker , Merlo Juan M , Thatcher Luke , Merlo-Ramírez Lázaro
Published: October 2024

We present a study of a longitudinal one-dimensional mechanical topological insulator based on a slinky spring in the Su-Schrieffer-Heeger (SSH) configuration. The system demonstrates key characteristics of topological insulators, including the existence of edge states in the bandgap, exponential decay of amplitude, and a winding number of 1 for topological phases. By manipulating the stiffness of the spring through the placement of masses, we transition between trivial, metallic, and topological phases. Our findings also show that the edge states are robust against perturbations, and we observe a critical phase transition where the coherence length follows a critical exponent of -1, as predicted by theory. This simple mechanical system provides an accessible platform for studying the special properties of topological insulators and opens up new possibilities for exploring topological phenomena in classical systems.
Crack inhibition to enhance the tensile and impact strength of additively manufactured CuCrZr alloy
Authors: Saravana Kumar M , Jeyaprakash N , Yang Che-Hua
Published: October 2024

This research focuses on enhancing the tensile and impact strength (IS) of the LPBF-based CuCrZr alloy parts based on crack inhibition. Also, it focuses on reducing the gas entrapment percentage while printing the parts which was the primary cause for crack nucleation. Three influential LPBF constraints, such as Print Orientation (PO), Layer Thickness (LT), and Hatching Range (HR), were examined to eliminate the gas entrapment, which was the primary reason affecting the structural integrity of the printed parts. Entropy - Deng’s similarity approach was embraced to find satisfactory conditions for printing the copper alloy parts. The overlapped, un-overlapped, and fused particle nano hardness analyses were examined. The results show that the overlapping zone had 17.5% greater nano-hardness than the fused particles. Moreover, the UTS of 376.57 MPa and IS of 14.85 J with a reduced gas entrapment percentage of 0.17% was witnessed during the implementation of 90° print orientation with reduced layer thickness and hatching range of 25 μm and 0.03 mm.
A generalized method of constraining Warm Inflation with CMB data
Authors: Kumar Umang , Das Suratna
Published: October 2024

A thorough MCMC analysis of any inflationary model against the current cosmological data is essential for assessing the validity of such a model as a viable inflationary model. Warm Inflation, producing both thermal and quantum fluctuations, yield a complex form of scalar power spectrum, which, in general, cannot be directly written as a function of the comoving wavenumber k, an essential step to incorporate the primordial spectra into CAMB to do an MCMC analysis through CosmoMC/Cobaya. In this paper, we devised an efficient generalized methodology to mould the WI power spectra as a function of k, without the need of slow-roll approximation of the inflationary dynamics. The methodology is directly applicable to any Warm Inflation model, including the ones with complex forms of the dissipative coefficient and the inflaton potential.
Preface
Authors: Lorenz Pascal
Published: October 2024

During June 21-22, 2024, the 2nd International Conference on Computer Technology and Information Science (CTIS2024) was successfully held online. This conference included keynote speeches, invited speeches, oral and poster presentations.

Prof. Yong Yue from Xi’an Jiaotong-Liverpool University (XJTLU), China; Assoc. Prof. Lei Chen from Shandong University, China and Dr. Binqiang Wang from Inspur (Beijing) Electronic Information Industry Co. Ltd attended the conference and delivered keynote speeches. In addition, experts and scholars from the Guizhou Normal University, Guiyang, China; Harbin Institute of Technology; IEIT SYSTEMS Co., Ltd.; Kansai University, Osaka, Japan and other universities and institutes shared wonderful speeches.

This conference proceedings included 7 accepted articles selected from 39 submissions, all the papers have been through rigorous review and process to meet the requirements of international publication standard. We would like to express our gratitude to the reviewers of these manuscripts, who provided constructive criticism and stimulated comments and suggestions to the authors. We are extremely grateful as organizers, technical program committee and editors and extend our most sincere thanks to all the authors for their excellent contribution and work. Our sincere gratitude also goes to the IOP Publishing editors and managers for their helpful cooperation during the preparation of the proceedings.

On behalf of the Organizing Committee of CTIS2024.

List of Technical Program Committee is available in this Pdf.
Optimizing resource utilization in cloud and fog computing environments using Hidden Markov Model
Authors: Hussein Awlla Ardalan , Barzan Abdalla Hemn
Published: October 2024

The massive volumes of data IoT devices generate are processed on the cloud. Fog computing, a hybrid cloud, and IoT solution, is used to distribute workloads and allocate resources efficiently, but it requires much research to implement. The study investigates load balancing in fog and cloud computing environments, which is crucial for managing IoT data. Cloud computing centralizes data processing and storage in remote storage facilities, whereas fog computing decentralizes functions to intermediary nodes closer to data generation and consumption. This close proximity facilitates optimal bandwidth usage, decrease delay, and faster computing. This study uses Hidden Markov Model (HMM) to examine task behaviour’s across diverse computing nodes and consider resource requirements. This study captures the probabilistic nature of load distribution by constructing emission and transition matrices from observed task dynamics and node-specific information. This research demonstrates the effectiveness of HMM in describing and optimizing load-balancing tactics, HMM play a vital role in optimizing load balancing tactics, as they model resource utilization, providing insights into enhancing resource allocation efficiency within complex computing infrastructures. The accuracy of the proposed method is approximately 92%.
Better approximation of sigmoid function for privacy-preserving neural networks
Authors: Zhao Yunran , Li Xuelei
Published: October 2024

With the development of artificial intelligence technology, privacy protection has become a prominent research direction. Homomorphic encryption is an important and promising technology in the construction of privacy-preserving neural networks. However, computing nonlinear activation functions remains a challenging task in the context of homomorphic encryption. Considering Sigmoid is one of the most commonly used activation functions, this paper proposes a polynomial approximation method for the Sigmoid function and applies it to the homomorphic encryption scheme of CKKS. We design polynomial approximation functions using Improved Taylor Expansion Segmentation (ITES), Least Squares method (LS), and Random Noise Addition method, respectively. These methods are implemented through the CKKS scheme in the homomorphic encryption library of SEAL. The experimental results show that the ITES achieves high fitting accuracy, reducing the average absolute error by 11.09% and the mean squared error by 38.06% compared to previous fitting methods. Therefore, experiments have identified methods with better fitting results in the CKKS scheme, which can meet the requirements of using homomorphic encryption in deep learning technologies. Finally, our analysis points out that different technologies have unique advantages and adapt to different scenarios, e.g., ITES has higher accuracy, LS has higher performance in scenarios with limited computing resources.
Application on ac station service system for gathering station based on roof photovoltaic system
Authors: Du Shaofei , Xiong Zaibao , Su Guang , Jing Tian , Zhang Yingying , Zhang Tong
Published: October 2024

With the increasingly severe global energy crisis and environmental pollution, it is imperative to develop and utilize clean and renewable energy. In order to achieve carbon peak and carbon neutrality as soon as possible, and reduce the proportion of fossil energy generation, decarbonization in the power industry is imperative. This article focuses on the design of rooftop photovoltaic systems at gathering stations. By installing solar photovoltaic panels on the roof of the gathering station building, a photovoltaic power generation system is constructed to convert solar energy radiated into electricity. The DC power generated by the solar photovoltaic power generation system is converted by an inverter and connected to the 380V bus of the station power system as a supplementary power supply for the station load, thereby increasing the proportion of green electricity consumption in the collection station and achieving the goal of carbon reduction
Research on the application of distributed smart grid protection technology scheme
Authors: Xiong Zaibao , Zhao Weibo , Zhang Yong , Gao Yu , Jiang Taoning , Xiao Bing
Published: October 2024

Distributed smart grid is an organic carrier for achieving renewable energy substitution and promoting new energy consumption. It is an important component of the construction of new power systems. To meet the current operational needs of distributed smart grid construction, a distributed smart grid protection method based on AC/DC hybrid distribution network is proposed. The distributed smart grid protection and application method proposed in this article, has good promotion and application value.
The experimental research of which different types of impact signals affect the bifurcation chaos behavior of three-degree-of-freedom collision system
Authors: Wang Qiang , Zhang Xin , Xing Zhikai , Li Mo , Liu Yongbao
Published: October 2024

Collision is a faulty behavior in mechanical equipment, which greatly affects the safety of equipment. In this paper, aiming at the collision failures that are prone to occur in mechanical equipment, the nonlinear fault collision behavior of a class of three-degree-of-freedom collision systems is studied. A three-degree-of-freedom piecewise non-smooth collision experiment platform system has been established to facilitate further analysis of the bifurcations and chaos inherent to the bearings system. This analysis is conducted through the use of Poincaré mapping on the collision plane. The excitation signals employed, which include sinusoidal, triangular, and rectangular signals, result in the emergence of specific types and orders of bifurcation behaviours within the system, as evidenced by the establishment of a Poincaré mapping at the collision surface, and this is observed to occur as the vibration frequency increases. The characteristics of impact signals generated by force sensors and the influence of impact signal type on the system are investigated. The nonlinear impact behavior of three-degree-of-freedom collision systems provides a reliable foundation for the design, fault diagnosis, and theoretical guidance of large-scale high-speed rotating machinery, as well as technical support for safe and stable operation of high-speed rotating machinery, which is essential for failure analysis and vibration reduction in equipment.
Research on magnetic fluid precise localized lubrication thrust cylindrical roller bearing with low-friction micro-vibration and high load-bearing capacity
Authors: Rui Hu , Hansheng Chen , Haoran Zhang , Humao Wei , Junpeng Gui , Songshan Yan , Hougen Luo , Yi Guo , Chunxia Xu , Jianwu Yan , Lei Zhang , Guoliang Liu
Published: October 2024

As the magnetic field that is difficult to be distributed in the existing magnetic fluid thrust cylindrical roller bearing structure, it is more difficult for the magnetic fluid to be evenly distributed inside the bearing raceway with the axial localized lubrication, which seriously affects the engineering application of the magnetic fluid bearing. To solve the magnetic field control problem that the magnetic fluid is uneasy to be accurately localized and adsorbed, a new type of magnetic fluid thrust cylindrical roller bearing is designed in this study, which shows good characteristics of low-friction, micro-vibration and high load-bearing capacity. The seat-ring is set as an annular raceway that can be used for magnetic fluid storage and matching with the roller lubrication system, and an annular permanent magnet is designed as an external magnetic field source to be placed below the annular raceway to adsorb the magnetic fluid on the friction surface. The structure design of the axial magnetic fluid localized lubrication bearing is reasonable, which is especially suitable for precision instruments with strict operating-conditions and precision-lubrication.
Theoretical analysis for dynamic model of U-shaped electrothermal microactuator based on Chebyshev spectral method
Authors: Tang Yujuan , Chen Hao , Wang Xinjie
Published: October 2024

This paper presents a largely and accurate analysis for dynamic model of U-shaped actuator that considers the material parameters dependent on temperature. The electro-thermal analysis for temperature distribution and thermo-mechanical analysis for deflection is carried out. The electro-thermal dynamic behaviour is described by piecewise one-dimensional (1D) heat transfer partial differential equations (PDE) for each beam of U-shaped actuator. A combination of Chebyshev spectral method for space domain and Euler forward difference method for time domain is used to solve these equations. The convergence test is first done to ensure the result convinced.
Design and research of serial communication system based on virtual instrument technology
Authors: Zhang Qingqing
Published: October 2024

In the measurement and automation control system, serial communication has been connected between the acquisition hardware (lower computer) and the upper computer between the easiest to realize and the most economical way. In view of the traditional instrument itself is relatively bulky, inconvenient to carry, this paper adopts the virtual instrument development environment to realize the realization of serial communication, in order to complete the subsequent data acquisition. When compared with other software development environment, LabWindows/CVI platform comes with a function library to make the program writing simple and flexible. In this paper, we designed the realization method of serial communication based on virtual instrument Labwindows/CVI environment, completed the design and realization of serial communication between PC and lower computer (microcontroller) based on Labwindows/CVI environment, and applied it to the example of serial communication with microcontroller to realize the data communication function. Practical results prove that the serial communication system based on virtual instrument technology has the advantages of friendly user interface, high stability, convenience and reliability, and can reliably and accurately complete the communication, and provide strong technical support for the system to follow up data acquisition.
A radar array expansion design method based on modular subarray layout
Authors: Yang Chunpeng , Dai Ye , Zhou Hanxuan , Zhou Bufeng
Published: October 2024

This paper introduces a design method for expandable subarray structures used in phased array radar arrays. Based on the structural characteristics of modular subarray layout for large radar arrays, this paper analyzes the assembly dimension chain tolerance based on subarray expansion. One third of the allowable deviation of the radar array is used as the subarray design tolerance, and the size tolerance of each installation surface of the subarray is designed according to the design tolerance. Finally, the subarray array is assembled into any size of radar array, and the probability of the radar array assembly accuracy meeting the allowable deviation is 99.73%. For large radar arrays, adopting this design method can significantly reduce the tolerance span between the sub array and the area array, greatly reducing the difficulty of design and processing. This paper provides a fundamental design method for the expansion design of radar arrays with similar systems, which has universal applicability.
Modelling and control of the lower hook mechanism for fishing net weaving machine based on active disturbance rejection controller
Authors: Ming Cankun , Sun Zhijun , Hao Zhichang , Sun Yize
Published: October 2024

The lower hook mechanism of the fishing net weaving machine has significant impact on its weaving velocity and net quality. This study incorporated a multi-motor based lower hook mechanism, which is driven by multi-motors instead of mechanical cams. Compared with the traditional lower hook mechanism, the multi-motor based lower hook mechanism has the advantages of fewer mechanical wear and faster running speed. However, the working condition of the lower hook mechanism places a very high demand on its following accuracy and resistance to disturbance, so the servo motor should be highly accurate and highly robust. The commonly used controller of the servo motor is three closed loop proportion-integral (PI) controller. In this paper, we modelled and experimentally verified the multi-motor based lower hook mechanism, and rebuilt the servo motor controller by replacing the position loop PI and speed loop PI of the three closed loop PI controller with position-velocity joint active disturbance rejection controller. Simulations suggest that the active disturbance rejection controller performs better on both following accuracy and resistance to disturbance compared with the traditional PI controller in the application of lower hook mechanism.
Hybrid multiscale computational approach for heat transfer in GaN semiconductors
Authors: Rao Xixin , Yan Yuancheng , Xiao Chengdi , Tian Qing
Published: October 2024

With ongoing advancements in semiconductor technology, understanding thermal transport in semiconductor devices—where phonons are the primary charge carriers—is crucial. This involves a multiscale process in which phenomena at different scales are governed by distinct control equations, necessitating various numerical methods. In this context, this paper introduces a novel multiscale simulation method called the Second-Order Reconstruction Operator Finite Difference Lattice Boltzmann Method (ROsFDLBM). This method effectively combines the Lattice Boltzmann Method (LBM) with the Finite Difference Method (FDM). ROsFDLBM employs reconstruction operators to accurately map the relationship between distribution functions and macroscopic physical quantities, significantly reducing errors caused by the transmission of interface information. The efficacy of this coupling scheme has been confirmed through an interface-coupled thermal diffusion model. Comparative analyses have revealed that the relative error of ROsFDLBM does not exceed 1.2%, demonstrating its superior accuracy. Further simulations of GaN devices have confirmed that traditional macroscopic methods tend to underestimate the temperature in the heat source area at micro-nano scales, with discrepancies reaching up to 60.9 K. Overall, the ROsFDLBM aligns with current research findings and offers an accurate and efficient simulation strategy for addressing complex heat transfer problems.
Design and analysis of large displacement bidirectional device based on multi-electrothermal co-actuation
Authors: Ding Yujiao , Wang Xinjie , Wang Xujian
Published: October 2024

As an important part of the MEMS safety system of fuze, the micro-actuator is responsible for the important functions of energy conversion, motion, force transmission and response to system information, etc. However, due to the size limitation of MEMS and the characteristics of electrothermal actuator itself, it is difficult for a single electrothermal actuator to drive the flameproof slider to achieve the target displacement. This paper aims to study and analyze the performance of the large displacement bidirection device based on multi-electrothermal co-actuation. After finite element analysis, the results show that the large displacement bidirection device can drives the flameproof slider to achieve the displacement up to 162.6μm within one cycle time, which is about 1.4 times displacement of the single V-shaped actuator outputs at 1.5V voltage. The error of response time between the theoretical calculation and the simulation analysis is less than 5.88%. The correctness of simulation and the feasibility of the large displacement bidirection device based on multi-electrothermal co-actuation is verified.
Dynamic modelling and a model-based control strategy of joint servo system for power transmission line inspection robot
Authors: Fan Xing , Li Xiaopeng , Shi Bing , Yang Hexu , Liu Wenwen , Ye Cunliang
Published: October 2024

The time-varying load inertia is one of the important dynamic characteristics of the power transmission line inspection robots (PTLIRs) in joint space, which can heavily affect the stability of the robot in the inspection process. In this paper, with considering the time-varying characteristics of load inertia, a method for modelling and control of the flexible joint servo system of the PTLIR is studied. First, the control system of the PTLIR is established based on the two inertia system. In order to calculate the load inertia, a dynamic model of the inspection robot is established. Then, the model-based notch filter is designed to improve dynamic performance of the robot, and suppress the vibration amplitude change which caused by the time-varying load inertia. Finally, the comparison of the control performance between the traditional control strategy and the model-based control strategy with notch filter are compared. The simulation results show that the paper can provide an effective tool for modelling and improving the stability of the PTLIR.
Vibration modal analysis of adaptive grinding and polishing tools
Authors: Xie Guosheng , Xu Yang , Sheng Xiaowei , Zhang Yixin , Yuan Qiuwei , Lv Xiao
Published: October 2024

Adaptive grinding and polishing tools have a compact structure, fast response, and stable performance, and they can improve the efficiency of polishing and grinding large welded parts. The vibration frequency of the AGP600 adaptive grinding and polishing tool is abnormal after switching from the blade grinding head to the nylon grinding head, and the vibration is noticeable when the rotational speed is more significant than 4, 000 r/min, which seriously affects the quality of grinding. To analyze the cause of its vibration, this paper adopts HyperWorks to analyze the modal frequency of AGP600, carries out the vibration modal test, and analyses the reasons for the different vibration harmonic frequencies of AGP600. Finally, improvement measures for AGP600 are proposed, through which the vibration of AGP600 grinding tools can be reduced.
Research progress on constructability of 3D printed concrete
Authors: Liu Bo , Wang Liuyan
Published: October 2024

3D printing concrete technology is an innovative building technology for green manufacturing, but in order to achieve better performance requirements, there is still a need for continuous in-depth research on 3D printing parameters, theory and the use of admixtures. In this paper, the effects of three printing parameters, interlayer interval time, nozzle travel speed and height, and nozzle shape on the constructability of 3D printed concrete were discussed, and the effects of bonding properties on the constructability of 3D printed concrete were analyzed. The study found that shortening the interval time between layers, reducing the travel speed and height of the nozzle, and choosing a triangular nozzle can improve the interlayer bond strength of 3D printed concrete, and thus improve the constructability of 3D printed concrete.
Point cloud-based feature extraction and surface reconstruction for parts paring in high-precision assembly
Authors: Li Xuezhen , Chen Zhehan , Lu Xiao , Zhao Ning
Published: October 2024

Assembly plays a crucial role in industrial manufacturing in industrial manufacturing, but the efficiency of conventional manual methods for parts pairing is limited. Previous research has demonstrated the feasibility of deep learning for point cloud feature extraction and 3D reconstruction. An innovative method utilizing deep learning for high-precision feature extraction and surface reconstruction is introduced to optimize parts pairing in this paper. Geometric dimensions and surface topography data are obtained by defining key assembly features and utilizing the Random Sample Consensus method. Deep learning is then used to directly regress the Surface Distance Function from point samples, facilitating comprehensive part surface modeling and supporting assembly simulation in the digital twin. To validate this approach, a case study demonstrates successful matching of 30 shaft parts and 30 hole parts after optimization, with an increase in average uniformity by 0.024. This highlights the proposed method’s superior effectiveness and accuracy in feature extraction and surface reconstruction.
Finite element analysis of hysteretic characteristics of steel member under cyclic loading
Authors: Zhao Jianwen , Fang Jianjun , Li Wang , Jun Peng , Chen Sun
Published: October 2024

In this paper, the square, H-shaped and C-shaped steel members with three cross-section forms are selected. Considering the cross-section form, slenderness ratio and constraints at both ends, the force-displacement curve and single-ring energy consumption of steel members under cyclic loading are simulated and analysed. The buckling performance and hysteresis characteristics of steel members with different properties are compared. The results show that the section form has the greatest influence on the energy dissipation level of the component. The hysteretic performance of H-shaped section member is the best, followed by C-shaped section member and square section member. The energy consumption level of the component is negatively correlated with the slenderness ratio, and the single-cycle energy consumption of the steel component decreases with the increase of the slenderness ratio. The constraint condition has the smallest influence on the energy consumption level of the component, and the energy consumption of the component under the end solid-solid constraint and solid-hinge constraint is similar.
Nonintrusive load disaggregation by fusion of graph signal processing and CNN
Authors: Chen Zhigang , Peng Haotian , Su Yongxin
Published: October 2024

Nonintrusive load disaggregation techniques play a pivotal role in power system planning and decision making for demand response. The sparsity of low frequency total power data features, coupled with the model’s challenge in effectively extracting and utilizing spatial and temporal correlations in diverse load data, presents obstacles to achieving high precision disaggregation in nonintrusive load disaggregation. To address these challenges, this paper proposes a disaggregation framework that integrates graph signal processing (GSP) with a convolutional neural network (CNN). In this framework, the GSP module tackles the issue of sparse load features, while the CNN disaggregation module extracts and exploits various features, such as spatial and temporal correlations between different loads. The GSP module directly provides load features to the CNN disaggregation module, assigning weights to the outputs for selection and thereby enhancing the accuracy of the disaggregation process. Our method is trained and validated using real datasets, demonstrating satisfactory performance when compared to existing methods.
Investigations on collision entropy and its variant for machine condition monitoring
Authors: Wei Lan , Wang Dong , Wang Yu , Yan Ming
Published: October 2024

The efficacy of sparsity measures and complexity measures in machine condition monitoring is well acknowledged. However, a comprehensive exploration of their theoretical underpinnings and interrelations remains incomplete. This study endeavors to address this gap by employing collision entropy as an illustrative case and establishing its relationship with sparsity measures. Through mathematical derivations, it is demonstrated that collision entropy exhibits a phenomenon termed as “bilateral reduction,” a characteristic indicative of complexity measures. Motivated by foundational concepts such as Shannon entropy and relative entropy, this paper introduces the concept of variation in collision entropy, which serves as a sparsity measure. Notably, both Shannon entropy and collision entropy, as specific cases of Rényi entropy, manifest the “bilateral reduction” effect and can be transformed into sparsity measures through certain methodologies. These insights contribute significantly to the exploration of the theoretical properties of Rényi entropy and its conversion into a cluster of sparse measures. This research augments the understanding of sparsity measures and complexity measures, offering theoretical insights crucial for their practical deployment in real-world applications.
Multi-objective optimization of helical gear transmission geometric parameters using MOPSO
Authors: Tang Huadong , Lv Gang , Luo Zongyuan , Zhang Ruiliang , Wang Wei , Wang Xiang , Liu Zhijian , Wang Gang
Published: October 2024

Helical gears are widely used in mechanical devices, but insufficient tooth strength can easily lead to premature failure, which is an urgent problem to be solved. To overcome this challenge, this paper introduces a multi-objective particle swarm optimization algorithm, which comprehensively considers the comprehensive effects of modification coefficient, number of teeth, and modulus on the performance of helical gears. By constructing a mathematical model with the geometric parameters of helical gears as the core design variables, aiming to minimize the difference between the maximum bending stress of helical gear roots and the contact stress on the tooth surface, we have achieved optimization of gear performance. Using MATLAB for algorithm programming, the established model was efficiently optimized and solved. After optimization, the bending strength difference and tooth surface bearing capacity of the gear pair have been significantly improved, ensuring the stability and reliability of the operation of the high-pressure sleeve disassembly transmission device.
A research and application of a digital failure knowledge model for nuclear power plant
Authors: Yu Na , Yang Xiaohu , Qing Chen , Wang Qiang
Published: October 2024

The accumulation and application of knowledge about equipment component failures in nuclear power plant unit systems is an important way for domestic and foreign nuclear power plants to improve unit availability and economic benefits. Based on the existing equipment component knowledge models in China and the experience of digital transformation, this paper proposes a digital fault knowledge model construction process and method for nuclear power plant components, which is of great significance for standardizing and guiding domestic nuclear power plant knowledge models.
Characterization and novel application of power over fiber for electronics in a harsh environment
Authors: Arroyave M.A. , Behera B. , Cavanna F. , Feld A. , Guo F. , Heindel A. , Jung C.K. , Koch K. , Leon Silverio D. , Martinez Caicedo D.A. , McGrew C. , Paudel A. , Pellico W. , Rivera R. , Rodríguez Rondon J. , Sacerdoti S. , Shanahan P. , Shi W. , Torres Muñoz D. , Totani D. , Uy C. , Vermeulen C. , Vieira de Souza H.
Published: October 2024

Power-over-Fiber (PoF) technology has been used extensively
in settings where high voltages require isolation from ground. In a
novel application of PoF, power is provided to photon detector
modules located on a surface at ∼ 300 kV with respect to
ground in the planned DUNE experiment. In cryogenic environments,
PoF offers a reliable means of power transmission, leveraging
optical fibers to transfer optical power. PoF technology excels in
maintaining low noise levels when delivering power to sensitive
electronic systems operating in extreme temperatures and high
voltage environments. This paper presents the R&D effort of PoF in
extreme conditions and underscores its capacity to revolutionize
power delivery and management in critical applications, offering a
dependable solution with low noise, optimal efficiency
(∼ 51%), and superior isolation.
Anisotropic odd elasticity with Hamiltonian curl forces
Authors: Zhang (张一恒) Yi-Heng , Yao (姚振威) Zhenwei
Published: October 2024

A host of elastic systems consisting of active components exhibit path-dependent elastic behaviors not found in classical elasticity, which is known as odd elasticity. Odd elasticity is characterized by antisymmetric (odd) elastic modulus tensor. Here, from the perspective of geometry, we construct the Hamiltonian formalism to show the origin of the antisymmetry of the elastic modulus that is intrinsically anisotropic. Furthermore, both non-conservative stress and the associated nonlinear constitutive relation naturally arise. This work also opens the promising possibility of exploring the physics of odd elasticity in dynamical regime by Hamiltonian formalism.
Clean energy challenges and innovation opportunities in Kazakhstan
Authors: Xenarios Stefanos , Sembayeva Aliya , Tsani Stella , Orazagaliyev Serik , Ansaganova Zhanat
Published: October 2024

Kazakhstan has pledged to transition to a low-carbon economy by implementing national policies and strategies that promote clean energy innovation. However, Kazakhstan is still falling short of its expected targets for energy transition, and there is a lack of knowledge regarding the country’s challenges and opportunities for clean energy development. Towards this end, the current study identifies and assesses the enablers and barriers related to clean energy innovation in Kazakhstan. Using the combination of SWOT analysis, survey data from 41 experts and the DEMATEL decision support tool, we evaluated the key factors affecting Kazakhstan’s clean energy innovation and their implications for energy transition. Assessment results show that the immature business environment, underpinned by technological, institutional, and socioeconomic factors, is perceived as a high-impact constraint for clean energy innovation and green finance deployment in Kazakhstan. Skilled labour shortages, high reliance on hydrocarbons and low retail energy prices are significant challenges to Kazakhstan’s clean energy innovation. The low-profit margin and high investment risk in clean energy projects are identified as transition barriers in the power and energy-intensive industries. In contrast, Kazakhstan’s endowments of resources critical for developing clean energy technologies (rare earth metals, uranium, gas) and the potential of low-carbon investments (e.g. carbon storage) are perceived as prominent enablers of clean energy innovation. Results are consistent across expert subgroups (academia, industry, NGOs, etc). Findings call for policy support to modern and attractive business environments, capacity, and human capital development. The findings can provide helpful insights for countries in Central Asia and beyond with similar socioeconomic structures that aim for a timely energy transition.
A classification and recognition model for multiple fruit tree leaf diseases
Authors: Du Bingbing , Li Wei , Qin Xue
Published: October 2024

Fruit tree leaf diseases affect both fruit survival rate and orchard revenue. Rapid and accurate classification of tree leaf diseases not only prevents the spread of diseases but also ensures healthy tree growth and improves fruit quality. Existing models mainly focus on individual types of tree leaf diseases, with limited applications in identifying multiple tree leaf diseases. To address the insensitivity of current classification models to disease region features and the issue of increased error rates due to the presence of similar diseases, this study proposes a residual network model combining channel attention mechanism (ECA) and meta-Acon adaptive activation function. The model employs ResNet34 as the backbone network and incorporates the ECA channel attention module after each residual block to focus on relevant feature information. Additionally, a new activation function called meta-Acon is introduced to enhance the model’s generalization ability through its dynamic learning capability. Finally, the model’s recognition performance is improved by fusing bottom-level features with features from other layers using the Feature Pyramid Network (FPN). Experimental results on a dataset augmented with Mosaic processing show that the FPEM-ResNet34 model achieves a classification accuracy of 98.46%. Compared to other common models such as VGG-16, Inception-V1, ResNet50, and Yolo-V8 m, the proposed method in this paper demonstrates more effective improvement in the accuracy of fruit tree leaf classification, making it highly valuable for practical applications.
Nonlinear associations and threshold effects between agricultural industrial development and carbon emissions: insights from China
Authors: Yi Chuanjian , Xu Bo , Lin Fumin , Lin Kejun
Published: October 2024

With the inevitability of global climate change, it has become increasingly important to understand the relationship between Agro-industrial Development (AID) and Agricultural Carbon Emissions (ACE) to promote the development of low carbon production in agriculture. Using a panel of datasets, as based on the ‘element-structure-function’ framework of 30 Chinese provinces over the period from 2011–2021, the entropy weight method was used to calculate the level of AID in each province. With this approach, it was possible to assess correlations and mechanisms between AID and ACE. Here, with use of fixed-effect, regulatory and threshold models, we determined some of the critical factors contributing to the effects of AID and ACE. Our findings revealed: (1) AID displays an inverse U-shape relationship with ACE, as verified through endogeneity and robustness assessment, (2) A review of the mechanisms suggests that the crossing of the turning point of the inverted u-curve can be accelerated by the moderating effect of agricultural finance. and (3) As based on the threshold effect analysis, a two-tier effect of the digital economy, rural human capital and farmers’ net income on AID, with facilitating effects on carbon emission reductions was obtained after the threshold crossing. The significance of this effect increases as a function of the post-threshold interval. Taken together, these findings demonstrate the long-standing interplay between AID and ACE. Thus, additional insights and empirical evidence that can inform the ongoing development of sustainable agricultural practices can be realized.
Comparison of energy prediction models for residential buildings: a case study in Himachal Pradesh, India
Authors: Nainwal Rajat , Sharma Aniket
Published: October 2024

Since the beginning of the 21st century, the demand for the consumption of energy has been increasing globally with the tremendous increase in population. Different studies have proved that inadequate energy management and planning may lead to energy crisis which is a result of inadequacies in energy prediction. Accurate prediction of energy demand is important as underestimation may lead to shortage in supply and overestimation may lead to overinvestment in energy generation. Various available literature has been reviewed for determining the various factors responsible for affecting the energy consumption of residential buildings. Based on the factors determined, a survey questionnaire has been formulated and survey was conducted in the 400 residential buildings in one of the northern states of India, i.e. Himachal Pradesh. It was observed by reviewing various studies that the different models developed for energy consumption by the different researchers were based on either of the three approaches, namely, engineering-based, AI-based, and hybrid approaches. Three tools namely, case-based reasoning, artificial neural network, and multilinear regression, based on these approaches were individually used for developing the model in this study, and their prediction results were compared. It was observed that the accuracy in the overall predicted results was highest in the proposed ANN model, followed by CBR model, and MLR model, with an overall accuracy of 99.93%, 96.3%, and 91.7%, respectively. The error obtained in the predicted results using ANN, CBR and MLR ranges from −4.0% to +3.0%, −15.0% to +26.0%, −30.0% to 20.0%, respectively. The overall RMSE of ANN, CBR, and MLR model was 1.44%, 11.7%, and 19.5%, respectively. It is concluded that ANN model is best suitable for predicting the short and long-term energy consumption with very high accuracy, as compared to the CBR and MLR. The results discussed in this study can be advantageously used for enhancing the consumption of operational energy in the existing as well as proposed buildings.
Glass catfish inspired subaquatic abrasion-resistant anti-fouling window fabricated by femtosecond laser electrodeposition
Authors: Zhang Jialiang , Ren Fangzheng , Yang Qing , Ma Qingyun , Liang Jie , Meng Yizhao , Gou Xiaodan , Xia Chongxiao , Chen Feng
Published: October 2024

Transparent materials utilized as underwater optical windows are highly vulnerable to various forms of pollution or abrasion due to their intrinsic hydrophilic properties. This susceptibility is particularly pronounced in underwater environments where pollutants can impede the operation of these optical devices, significantly degrading or even compromising their optical properties. The glass catfish, known for its remarkable transparency in water, maintains surface cleanliness and clarity despite exposure to contaminants, impurities abrasion, and hydraulic pressure. Inspired by the glass catfish’s natural attributes, this study introduces a new solution named subaquatic abrasion-resistant and anti-fouling window (SAAW). Utilizing femtosecond laser ablation and electrodeposition, the SAAW is engineered by embedding fine metal bone structures into a transparent substrate and anti-fouling sliding layer, akin to the sturdy bones among catfish’s body. This approach significantly bolsters the window’s abrasion resistance and anti-fouling performance while maintaining high light transmittance. The sliding layer on the SAAW’s surface remarkably reduces the friction of various liquids, which is the reason that SAAW owns the great anti-fouling property. The SAAW demonstrates outstanding optical clarity even after enduring hundreds of sandpaper abrasions, attributing to the fine metal bone structures bearing all external forces and protecting the sliding layer of SAAW. Furthermore, it exhibits exceptional resistance to biological adhesion and underwater pressure. In a green algae environment, the window remains clean with minimal change in transmittance over one month. Moreover, it retains its wettability and anti-fouling properties when subjected to a depth of 30 m of underwater pressure for 30 d. Hence, the SAAW prepared by femtosecond laser ablation and electrodeposition presents a promising strategy for developing stable optical windows in liquid environments.