bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Non-destructive Testing Method for Aging of Sheds of Composite Insulators
Authors: Wu Zhensheng , Cheng Yibin , Zhang Gang
Published: September 2023

As an important part of external insulation of transmission and distribution lines and substation equipment, silicone rubber insulators are generally used because of their strong anti-pollution flashover ability, excellent hydrophobicity, and lightweight. It is one of the effective means to obtain the aging degree of sheds quickly and accurately to prevent operation accidents. From the micro and macro perspectives, firstly, this paper uses the traditional scanning electron microscopy and dielectric loss factor test to classify the aging degree of 11 high-voltage side sheds samples of silicone rubber insulators running on-site for 0~11 years. According to the different experimental principles, the aging degree of each experimental method is divided into four grades. Then, the detection method based on terahertz time-domain spectroscopy is proposed to realize a nondestructive evaluation of the aging grades of sheds of silicone rubber insulators. Finally, through comparison, it can be found that the THz absorption coefficient spectra can find the characteristic quantity of classification of aging levels of silicone rubber materials: The aging levels of the silicone rubber samples increase, and the absorption peak at 1.32 THz in the absorption spectra show a downward trend. According to the characteristic quantity, 11 samples can also be divided into four aging grades, and the results are consistent with the previous experiments.
Noise Reduction Method for Fiber Optical Current Transformer Based on Mode Decomposition-Sample Entropy
Authors: Wang Shu Gang , Xie Tian Xi , He Mao Hui , Feng Xuan , Zhu Chao
Published: September 2023

When a fiber optic current transformer (FOCT) malfunctions, its output signal is usually accompanied by a large noise, which affects the subsequent fault diagnosis results of the transformer. In response to the above noise issues, this paper constructs a new noise reduction algorithm by combining Complete Ensemble Empirical Mode Decomposition Adaptive Noise (CEEMDAN) and Sample Entropy (SE). Above all, the output signal of FOCT is decomposed into multiple fault components using the CEEMDAN algorithm. Then, by comprehensively considering the frequency domain characteristics and sample entropy calculation value of each component, the characteristics of each component are determined, so the power frequency and low-frequency components are selected as the feature vectors representing the fault mode. Finally, the noise components with high sample entropy are eliminated, and the power frequency current components with medium sample entropy and the low-frequency fault feature components with low sample entropy are recombined and superposed to build a fault signal dataset after noise reduction.
Research on Bidirectional DC-DC Converters in Distributed Electric Propulsion Systems
Authors: Liu Pengcheng , Yang Minsheng
Published: September 2023

This paper investigates bidirectional DC-DC converters in distributed electric propulsion systems, focusing on the dual active bridge (DAB) converter. To minimize voltage fluctuations in aircraft operating under complex conditions, a virtual voltage compensation control strategy based on active disturbance rejection (ADR-VVCC) is presented. The presented control strategy is grounded on the working characteristics under single-phase-shift (SPS) and introduces a virtual voltage to compensate for voltage fluctuations and degraded dynamic performance caused by the inherent uncertainty of converter parameters and power losses during the energy transfer process. The active disturbance rejection control is incorporated to replace traditional PI control, thereby enhancing the converter’s dynamic performance. Simulation outcomes demonstrate that the presented control strategy effectively improves the converter’s dynamic performance and maintains output voltage stability.
Wind-storage-turbine Bundled Technology for the Power Supply of Offshore Oil and Gas Platforms
Authors: Li Zhichuan , Yang Jiping , Sun Zhaoheng , Xiao Shi , Liu Longfei , Liu Jing , Xu Xiandong
Published: September 2023

The offshore oil and gas industry is embracing renewable energy such as wind power to reduce carbon emissions. However, the intermittent characteristics of renewable power generation bring new challenges to the operation of existing offshore oil and gas platforms featured in minor load variation. To address the concern, this paper proposes a coordinative control strategy for offshore oil and gas platforms with floating wind power integrated. A saturated filter controller is applied to decompose the wind power fluctuation and smooth it with energy storage and a gas/oil turbine generator. A feedforward control unit is embedded into the controller to compensate for the wind power variation caused by the floating foundation. The proposed strategy is validated using a model extracted from a real offshore oil and gas platform. The result shows that the proposed strategy can validly eliminate the impact of wind power volatility.
Research on improved Harmonic current detection method based on SOGI-PLL instantaneous reactive Power
Authors: Wu Donglai , Zhao wenlei
Published: September 2023

In view of the traditional instantaneous reactive power detection has low anti-harmonic interference ability, poor real-time performance, and insufficient accuracy when the power grid frequency fluctuates, this paper improved the detection link. The working principle of single-phase harmonic detection is analyzed, and the improved second-order generalized integrator is added to make the phase-locked loop detect the voltage phase accurately and efficiently. Based on the comparison and compensation simulation results of the active compensation device, the quality of grid-connected current of the inverter is improved effectively, and the precision of phase locking is increased.
State Inference and Evaluation Technology of Relay Protection Based on Digital Twinning
Authors: Liu Qingquan , Li Tiecheng , Fan Hui , Zeng Siming , Ren Jiangbo , Wang Xianzhi
Published: September 2023

The problems of relay protection equipment in such aspects as the insufficient depth of data mining, not timely grasp of equipment status, and poor timeliness of fault warning restrict the development of the operation and maintenance mode of relay protection, which aims at “autonomous and controllable, safe and reliable, advanced and applicable, intensive and efficient”. This article studies the comprehensive state evaluation and action simulation deduction technology of intelligent substation relay protection equipment based on digital twins. It uses multi-source state monitoring data of relay protection equipment for state quantity correlation analysis. It constructs a key state feature index library and uses digital twin technology to model the relay protection function and software and hardware states. Through the collaborative linkage between physical devices and digital twin models, the twin can dynamically track the operational status of devices and automatically update the twin status. Finally, based on the established high-precision digital twin model, relay protection action deduction and status evaluation are carried out. Then the effectiveness of the scheme is demonstrated through example testing of the relay protection twin system.
A Low Voltage Prediction Based on LSTM-BP Combined Model for Distribution Station Areas
Authors: Yi Chenying , Zhou Yangjun , Huang Weixiang
Published: September 2023

The timely management of low voltage issues in the distribution network relies heavily on accurate predictions of voltage in the station areas. Many current methods for voltage prediction require complex data collection involving power grid topology parameters and electricity information. However, these methods suffer from drawbacks such as the need for extensive data, limited real-time performance, and significant prediction errors. Hence, this study proposes an approach to voltage prediction utilizing a combined LSTM-BP model. Initially, an analysis of the mechanism of low voltage formation in the station areas reveals that the primary factor influencing node points voltage is the power consumption of users. Subsequently, the LSTM neural network is employed to forecast short-term load curves in the distribution station areas, while the self-learning capability of the BP neural network is utilized to establish the correlation between users’ power and their corresponding voltage levels. By effectively combining the above two neural network models, the historical load’s data can be used to accurately and quickly predict the future low voltage situation in the station areas. Finally, taking station areas as the research object and comparing the actual voltage data with the voltage data predicted in this paper, the results show that within the 1V error range, the prediction accuracy is 99.8%. In contrast to the conventional voltage prediction approach, the method put forward in this research paper enables instantaneous and precise anticipation of low voltage levels without relying on details such as station configuration, line characteristics, or user voltage information.
Elman short-term wind power prediction based on the optimized seagull algorithm
Authors: Sui Tao , Liu Guodong , Liu Xiuzhi , Huang Yanzhao , Yan Xiangyu
Published: September 2023

Accurate prediction of wind farm power output can relieve the pressure of grid frequency regulation and peak regulation and improve grid stability. With the goal of improving power prediction accuracy and reducing overall prediction error, this paper proposes an Elman short-term wind power prediction model on the basis of an optimized seagull algorithm. Firstly, the Elman network is used as the base prediction model, and the seagull algorithm is applied to seek the best values for its weights. Secondly, the chaotic circle mapping with better initial characteristics is improved to equalize its sequence distribution for optimizing the population initialization. Then, to address the lack of local search capability, an optimized iterative approach using the sine cosine operator is used to achieve a balance between local exploitation ability and global search capability. Finally, after simulation and analysis of the actual data set, it is verified that the model has a better prediction effect.
Modeling and Simulation of Marine PV Inverter System Based on MPPT Algorithm
Authors: Li Haitao , Zhang Cunxi , Wang Rui
Published: September 2023

Under the influence of the policy of low carbon development, the development of new energy ships is receiving wide attention. Aiming at the fluctuation of the ship power grid caused by the intermittent and random nature of the PV power generation system, this paper builds a set of ship PV power generation microgrid system models based on the Matlab/Simulink simulation platform. Under the conditions of ambient temperature, light intensity, and other factors, the front-stage Boost circuit uses the MPPT conductance increment method to obtain the maximum power point of the PV module. The rear-stage inverter uses SPWM (sinusoidal pulse width modulation) inverter control in the rear stage to observe the output effect under different solar radiance, and the system is also designed to automatically switch the DC load when the light intensity is too low, which reduces the system energy loss and improves the operation efficiency of the marine PV system.
Frequency diversity of the power line time service system
Authors: Zou Yun , Ma Xin-ze , Hua Yu , Liu Shi-yao
Published: September 2023

A frequency diversity technique is proposed for OFDM-modulated power line time service systems, and a variety of frequency diversity reception processing schemes are investigated to address the problem of interference caused by power line channel noise. Simulation results show that selecting the appropriate frequency diversity order can effectively reduce the system received signal bit error rate, while using the maximum ratio combining diversity reception scheme has the best effect on improving the system bit error rate performance.
Coil Position Control Technology in Magnetic Coupled Wireless Power Transmission
Authors: Yang Wei , Chen Xiyou
Published: September 2023

This article mainly studies the issue of power and efficiency fluctuations at the receiving end caused by changes in the relative positions of the transmitting coil and the receiving coil in a magnetic coupled radio energy transmission system. A circuit model was built to analyze the logical relationship of energy transmission in a wireless energy transmission system, and the optimal transmission position of the two-coil system was calculated. Simulation analysis and experimental measurements were conducted to obtain the transmission power of the coil at different distances. Based on the microcontroller, a closed-loop automatic control algorithm is designed for the laser rangefinder and the stepping motor. When the position of the receiving coil changes, the transmitting coil can move with the position of the receiving coil so that the system can quickly stabilize at the optimal power transmission point. The method used in this article can achieve stable transmission power of over 7 W when the receiving coil moves 0-100 cm along the axis.
Research on Daily Load Curve Classification Based on Improved Fuzzy C-means Clustering Algorithm
Authors: Li Mingcong , Hu Heng , Shi Haoran , Wang Xi , Ye Lan , Zhou Feng
Published: September 2023

For the problem of severe unpredictability and three-phase unbalance of user demand in low-voltage distribution networks, a daily load curve clustering technique integrating the sparrow search algorithm (SSA) and the fuzzy C-mean clustering algorithm (FCM) is presented. The initial load data set is pre-processed to lessen the interference of classification results. The load characteristic index of the daily load curve is removed to produce a reduced dimensional data set. The clustering validity index is introduced to solve the optimal number of clusters, and the early warning mechanism of the sparrow search algorithm is adopted to improve the global search capability. These improvements are made to improve the sensitivity of the initial clustering center of the FCM algorithm and the problem of local optimum in the process of finding the optimum. The simulation used to validate the revised clustering algorithm’s accuracy and efficacy for daily load categorization is a reference for resolving the three-phase load unbalance issue.
Multi-channel and high-precision analog-to-digital converter chips for power grid detection
Authors: Liu Xiaolu , Shao Jin , Zhang Peng , Cui Guoyu , Qian Haifeng
Published: September 2023

This project focuses on the research of high-precision multi-channel analog-to-digital converter chips for power grid detection and system applications. There have been breakthroughs made in a series of key technologies, such as successive approximation ADC architecture, oversampling ADC architecture, and digital calibration technology. By combining it with multi-channel ADC to achieve high-precision multi-channel analog-to-digital converter design, it provides strong support for China to achieve autonomous and controllable high-precision multi-channel ADC chips and has extremely high application value.
Feature Extraction of Speech Signal Based on MFCC (Mel cepstrum coefficient)
Authors: Zhang Hongxing , Li Hu , Chen Wenxin , Han Hongjun
Published: September 2023

Smart power plant is to establish a modern energy power system to achieve safe, efficient, green, and low-carbon power generation. Its characteristics are that the production process can be independently optimized, the relevant systems can collect, analyze, judge, and plan their own behavior, and intelligently and dynamically optimize equipment configuration and its parameters. This paper focuses on the optimal recognition state of MFCC in smart power plants. In this paper, we propose that by changing the number of filters and the order of MFCC to view the expression effect of the final MFCC parameter, the evaluation index of the effect is “accuracy”, the evaluation index—accuracy in the neural network. In this paper, the network is built through a Python programming environment, and the comparative experiment is adopted to analyze the influence of each parameter on the speech information expression effect of MFCC parameters.
Fuzzy control based adaptive rotational inertia VSG grid integration research
Authors: Li Qijun , Liu Li , Wang Yanping
Published: September 2023

Compared with the traditional inverter grid-connected control strategy, virtual synchronous generator (VSG) has received attention because it can effectively reduce the current shock to the grid caused by load fluctuation during grid-connected process by adding rotational inertia and damping parameters. A fuzzy control scheme is added to the rotor equation of motion of VSG to establish fuzzy rules by finding the relationship between frequency fluctuation and rotational inertia during grid connection. To improve the immunity of the frequency converter to interference during grid connection, and then improve the stability of the output power in the grid-connection process. The feasibility of the proposed method is verified by simulink model construction for simulation and comparison with the conventional virtual synchronous generator system.
A Line Loss Separation Method Based on Topology-aware Correlations and Nonlinear Impedance
Authors: Li Tengbin , Chang Junchao , Qi Jiaqi , Yang Sen
Published: September 2023

Due to the varying order and hierarchical relationship of different meters on the same line, the variation pattern of line loss and electricity consumption is not obvious, making it difficult to separate them accurately. To address this issue, an innovative method for line loss separation based on topological relationship perception and nonlinear impedance is proposed. Firstly, based on the topology recognition algorithm, we identify the order of the electricity meters and the relationship between the father and child-level electricity meters. Then, using the principle of topology relationship, we accurately measure the impact of the father and child level electricity meters on the overall line loss electricity quantity. Combined with data difference and matrix difference methods, the fixed loss value is offset. On this basis, a sliding window method is used to draw the curve change of nonlinear impedance and loss of electricity quantity. By analyzing the approximate continuous relationship between electricity consumption and line loss rate through curves, the line loss electricity consumption can be effectively separated. The results indicate that the proposed method has a better performance compared to other methods.
Fast Frequency Control Strategy for Direct Drive Wind Turbines Considering the Suppression of Secondary Frequency Drop in the Power Grid
Authors: Bao Xianwen
Published: September 2023

Inertia and damping in the power system are important parameters in frequency regulation and oscillation suppression. Inertia will reduce the rate and amplitude of frequency changes after active power sudden changes. Damping in the system can effectively suppress low-frequency oscillations after grid disturbances. As the penetration rate of wind turbines increases, it will significantly reduce the effective inertia in the power grid and reduce the friendliness of wind power grid connection. To provide better frequency support for the power grid in the event of large disturbances in the power system, this paper proposes a fast frequency control strategy for wind farms that considers the suppression of secondary frequency dips in the power grid. The strategy combines frequency droop control with grid frequency bias control and evaluates the kinetic energy reserve online based on wind power prediction and hourly speed, thus balancing the frequency regulation and suppression of secondary frequency dips in the power grid. A 2.5 MW direct drive wind turbine simulation model was built based on the PSCAD simulation platform, verifying the effectiveness of the proposed comprehensive control strategy.
Monitoring information transmission topology of high voltage transmission line
Authors: Zheng Wenlei , Miao Chuanhui , Guo Zhigang , Han Jinfu
Published: September 2023

High-voltage transmission lines are long and may cross areas without mobile networks. The transmission tower is equipped with monitoring equipment. The monitoring information of the transmission tower located in the non-mobile network area is difficult to return. What topology is used for transmission is an important engineering problem. When the number of transmission towers passing through the area without a mobile network is large, the traditional information transmission topology design method based on engineer experience cannot be applied. Aiming at the urgent demand of monitoring information transmission of high-voltage transmission lines in strip-shaped non-mobile network areas, an information transmission topology design method based on a unidirectional layered search algorithm is proposed. Firstly, the objective function and constraint function are designed. Then the unidirectional layered search algorithm is used to realize the planning of communication nodes and complete the design of the information transmission topology. The simulation results show that compared with the traditional information transmission topology design method, the design method proposed in this paper is suitable for complex networks, and the transmission delay of the designed information transmission topology is small.
Improvement of FDR Methods for Identifying Defects of Jointed HV Cable
Authors: Luo Chuansheng
Published: September 2023

This paper considers frequency domain reflectometry (FDR) as an effective way to locate high voltage (HV) cable defects. The formula relating FDR to cable local equivalents impedance value is presented, and critical methods such as window function, frequency step, and bandwidth to process FDR data before Inverse fast fourier transform (IFFT) are also demonstrated. Finally, a multi-periods reflection analysis from the IFFT curve is introduced with illustrations from fields measurement to improve the identification of defects for cables with multiple joints.
Open capacity measurement and evaluation of n-1 security criteria considering distribution network dispatching security
Authors: Wang Weiyuan , Cheng Jinmin
Published: September 2023

In order to ensure the safety of distribution network dispatching, the open capacity evaluation, one of the distribution network operation and maintenance tools, is analyzed. Aiming at the shortcomings of traditional reactive power capacity evaluation that is too simple and cannot effectively handle multiple interconnected feeders, a new method is proposed to consider N-1 to establish security and network reconfiguration. Considering the safety factor and the minimum network loss, the open capacity is evaluated, and the interconnection switch is regenerated, which provides the best scheme for the maintenance of the distribution network. This model not only considers the power flow constraints during normal operation but also considers the switching operation constraints under fault conditions. It has the advantages of high solution quality and feasible calculation results. In order to solve the model, a two-level hybrid algorithm based on generalized Benders decomposition, a dichotomous approximation is proposed. The algorithm adopts the idea of upper approximation, lower test, and two-layer interaction. It continuously reduces the solution space through alternate iterations until the optimal solution is obtained. The test results of 22-node and 70-node systems verify the correctness and effectiveness of the model and algorithm in this paper.
A single-phase ground fault intelligent wire selection method based on an ant colony algorithm
Authors: Liu Kang
Published: September 2023

For the single-phase ground fault, which has the highest probability of occurrence in a 10 kV distribution network, the ant colony algorithm is combined with a neural network for fault line selection, and the algorithm is optimized. The study builds a 10 kV distribution network model in MATLAB and simulates the neutral ground fault. It compares the results of the optimized line selection algorithm, and the traditional line selection algorithm proves that the accuracy of the method in identifying faulty lines is significantly better than that of the traditional method.
Research on rural power grid planning method based on improved genetic annealing algorithm
Authors: Ye Linhao , Yang Zhengang
Published: September 2023

Current power grid planning mainly relies on planning experience in personnel selection schemes. Planning results of subjectivity are stronger, making the planning after the network loss difficult to meet the requirements. According to the above defects, research on rural power grid planning methods based on an improved genetic annealing algorithm is proposed. Using the directed graph, the operation mode of the rural power grid is analyzed, and the network load of different distributed power sources is calculated. The multi-objective programming model is established from two aspects of the economy and environmental protection of the rural power grid. The annealing algorithm is introduced in the crossover and mutation stage of the genetic algorithm. In the example experiment, the cost reduction of the improved genetic annealing algorithm is 57.45%, and the network loss rate is lower than that of the other planning methods, which makes the network power supply more reliable.
Power communication digital flow prediction method based on VMD-LSTM-SVM model
Authors: Wang Kai , Zhang Xu , Zhang Qian , Hao Meiwei , Yang Dandan
Published: September 2023

Under the current trend of abundant information on power business, large data concentration, and large flow explosion, aiming at the randomness, volatility, and uncertainty of massive flow of electric power communication network, a digital power flow prediction method based on VMD-LSTM-SVM model is proposed. The interaction between the values of each traffic index before and after time is considered. LSTM is used to process traffic data and make an accurate prediction of future traffic. The power communication network can make dispatch responses to possible communication congestion by using link resources according to traffic prediction results and ensuring the transmission quality of power service data.
220 kV grid optimization in Shengli Oilfield
Authors: Du Lei , Wu Yue
Published: September 2023

As an important oil industry base in China, Shengli oilfield has infrastructure supporting facilities for power generation, transmission, substation, and distribution. Based on the grid data, a BPA simulation model is built for the oilfield area, and a grid optimization scheme is proposed for the problems of the existing 220 kV grid in the Shengli oilfield. The simulation results show that the safety and stability of the oilfield grid are improved under the optimized scheme, which verifies the feasibility and effectiveness of the scheme.
Motorbike Vibrations Induced by Surface Irregularities in Road Pavements
Authors: Cavacece M
Published: September 2023

The author proposes a multi-axis equivalent mechanical system with two degrees of freedom on the horizontal plane and five degrees of freedom along the vertical axis to evaluate the accelerations on a motorbike’s seat using the state- space representation. The experimental investigations evaluate three types of routes to analyze the comfort vibrational of the motorcycle: paved roads with poor maintenance, road surface with crushed stone, and a road with an artificial bump. Experimental processing considers the gyroscopic and accelerometric signals to deduce the Euler angles. The error analysis evaluates the discrepancy between the accelerations predicted, using the calibrated multi-axis mathematical model, and those obtained in the experimental investigations. The multi-axis model estimates the vibrations on the seat induced by surface irregularities in road pavements. The mathematical prediction obtained by the multi-axis model and experimental investigations analyzes the accelerations in the resonance frequencies of the human spine between 4-12 Hz.
Supercritical water injection in a single cylinder research engine: a PIV study
Authors: Piras M , Marchitto L , Tornatore C
Published: September 2023

This work presents the experimental results of a fluid dynamic investigation to characterize the injection of supercritical water in the combustion chamber of an internal combustion engine. Particle Image Velocimetry (PIV) analysis is carried out in an optically accessible 2-stroke Diesel engine. A prechamber, equipped with two optical accesses is connected to the main cylinder through a tangential duct so that the piston stroke induces a swirled motion field with angular velocities typical of light duty engines for automotive application. The engine is equipped with an injection system for the production and injection of supercritical water, with the possibility to independently regulate the injection pressure, temperature, duration, and timing. Tests have then been carried out under different operating conditions to evaluate the impact of the fluid dynamics in the combustion chamber on the water spray. First, the airflow velocity field has been characterized at different engine crank train angles. The water spray has been macroscopically characterized for an injection temperature of 300°C and pressure of 30Mpa. Then, the supercritical water/air interaction has been explored, at different injection pressure, temperature, and Start of Injection (SOI) to provide global information in terms of spray morphology, tip penetration, and velocity vector distribution of the water droplets within the combustion chamber for different injection strategies.
Perspectives on research on laser driven proton-boron fusion and applications
Authors: Batani K.
Published: September 2023

Recent experiments with high-intensity lasers have shown record production of α-particles by irradiating boron-hydrogen targets. This opened the way to completely new studies on proton-boron fusion with multiple goals:

i) studies related to nuclear fusion. The proton-boron fusion reaction produces 3 α-particles and releases a large energy. It is considered an interesting alternative to deuterium-tritium fusion because it produces no neutrons, therefore no activation and radioactive wastes.

ii) generation of novel laser-driven α-particle sources. Laser-driven α-particle sources are promising for their potential high brightness while remaining compact. They could be used for multidisciplinary applications, including medical ones.

The COST Action CA21128 — PROBONO (PROton BOron Nuclear fusion: from energy production to medical applicatiOns) is the first international programme which aims at understanding the physics involved in laser-driven pB fusion, including the study of Equation of State of boron and boron compounds. Action's goals are to facilitate access to experimental infrastructures, maximize production of new knowledge, boost the career of young researchers by fostering opportunities for training, and finally interconnect researchers across countries building a well-organized community focused on pB research.
Fully 3D-printed tortoise-like soft mobile robot with muti-scenario adaptability
Authors: Sun Lechen , Wan Jingjing , Du Tianhao
Published: September 2023

Soft robotic systems are well suited to unstructured, dynamic tasks and environments, owing to their ability to adapt and conform without damaging themselves or their surroundings. These abilities are crucial in areas such as human-robot interaction, simplification of control system and weight reduction. At present, the existing soft mobile robots still have the disadvantages of single motion mode and application scenario, difficult manufacturing and low energy conversion efficiency. Based on the current shortcomings of soft robots, this paper designs and proposes a fully 3D-printed tortoise-like soft mobile robot with muti-scenarios adaptability. The robot uses a Bionic Tortoise Leg Actuator structure that enables simultaneous bending of the actuator in both directions, simplifying robot control and increasing the maximum bending angle achievable. In addition, a reconfiguration design solution has been proposed to enable the robot to implement two bionic modes for land and sea turtles, adapting to move on hard and soft surfaces and in water, enabling it to move in amphibious and complex environments. The performance of the pneumatic soft actuator is also improved by an improved Digital Light Processing method that enhances the maximum strain of the 3D printed soft material. The prototype was tested to give maximum movement speeds for different gaits and environments, demonstrating that the fully 3D printed tortoise-like soft-mobile robot designed in this paper is highly adaptable to multiple scenarios. The robot studied in this paper has a wide range of applications, with potential applications including navigation in a variety of domain environments, inspection of large underground oil and gas pipelines, and navigation in high temperature, high humidity and strong magnetic field environments or in military alert conditions.
Development of a hyaluronic acid—collagen bioink for shear-induced fibers and cells alignment
Authors: Palladino Sara , Schwab Andrea , Copes Francesco , D’Este Matteo , Candiani Gabriele , Mantovani Diego
Published: September 2023

Human tissues are characterized by complex composition and cellular and extracellular matrix (ECM) organization at microscopic level. In most of human tissues, cells and ECM show an anisotropic arrangement, which confers them specific properties. In vitro, the ability to closely mimic this complexity is limited. However, in the last years, extrusion bioprinting showed a certain potential for aligning cells and biomolecules, due to the application of shear stress during the bio-fabrication process. In this work, we propose a strategy to combine collagen (col) with tyramine-modified hyaluronic acid (THA) to obtain a printable col-THA bioink for extrusion bioprinting, solely-based on natural-derived components. Collagen fibers formation within the hybrid hydrogel, as well as collagen distribution and spatial organization before and after printing, were studied. For the validation of the biological outcome, fibroblasts were selected as cellular model and embedded in the col-THA matrix. Cell metabolic activity and cell viability, as well as cell distribution and alignment, were studied in the bioink before and after bioprinting. Results demonstrated successful collagen fibers formation within the bioink, as well as collagen anisotropic alignment along the printing direction. Furthermore, results revealed suitable biological properties, with a slightly reduced metabolic activity at day 1, fully recovered within the first 3 d post-cell embedding. Finally, results showed fibroblasts elongation and alignment along the bioprinting direction. Altogether, results validated the potential to obtain collagen-based bioprinted constructs, with both cellular and ECM anisotropy, without detrimental effects of the fabrication process on the biological outcome. This bioink can be potentially used for a wide range of applications in tissue engineering and regenerative medicine in which anisotropy is required.
The untold story of missing data in disaster research: a systematic review of the empirical literature utilising the Emergency Events Database (EM-DAT)
Authors: Jones Rebecca Louise , Kharb Aditi , Tubeuf Sandy
Published: September 2023

Global disaster databases are prone to missing data. Neglect or inappropriate handling of missing data can bias statistical analyses. Consequently, this risks the reliability of study results and the wider evidence base underlying climate and disaster policies. In this paper, a comprehensive systematic literature review was conducted to determine how missing data have been acknowledged and handled in disaster research. We sought empirical, quantitative studies that utilised the Emergency Events Database (EM-DAT) as a primary or secondary data source to capture an extensive sample of the disaster literature. Data on the acknowledgement and handling of missing data were extracted from all eligible studies. Descriptive statistics and univariate correlation analysis were used to identify trends in the consideration of missing data given specific study characteristics. Of the 433 eligible studies, 44.6% acknowledged missing data, albeit briefly, and 33.5% attempted to handle missing data. Studies having a higher page count were significantly (p < 0.01) less prone to acknowledge or handle missing data, whereas the research field of the publication journal distinguished between papers that simply acknowledged missing data, with those that both acknowledged and handled missing data (p < 0.100). A variety of methods to handle missing data (n = 24) were identified. However, these were commonly ad-hoc with little statistical basis. The broad method used to handle missing data: imputation, augmentation or deletion was significantly (p < 0.001) correlated with the geographical scope of the study. This systematic review reveals large failings of the disaster literature to adequately acknowledge and handle missing data. Given these findings, more insight is required to guide a standard practice of handling missing data in disaster research.
The role of high conservation value areas to maintaining ecological balance in oil palm plantations PT. Waimusi Agroindah, South Sumatera
Authors: Nurjannah S , Kwatrina R T
Published: September 2023

Currently, oil palm plantations must carry out environmentally friendly plantation activities, one of which is by maintaining the biodiversity in or around the plantation area. Biodiversity can also reduce pest attacks that can reduce oil palm productivity. The research activities were carried out at PT. Waimusi Agroindah by conducting an inventory of plant, mammal, and bird species in HCV areas and oil palm plantations (young, medium, and mature palms). The results of the research in the HCV area showed that there were 4 types of trees, 10 types of poles, 7 types of saplings, 4 understorey plants and seedlings, 4 types of mammals, and 34 species of birds. Within the HCV area, three species of mammals protected by the government were found, namely the silvery lutung (Trachypithecus cristatus) as many as 3 individuals, and three species of birds, namely Haliastur indus, Elanus caerulaus, and Anhinga melanogaster. In the oil palm plantation area, only understorey stands were found, but various types of mammals and birds were found. The number of species of mammals and birds found in HCV areas is higher than in oil palm plantations. The number of vegetation types in the HCV area is more diverse so that it can be used as a place for wildlife to live, both for forage plants and nests. This shows the need for HCV areas in biodiversity conservation and as an ecological balancer in oil palm plantation areas.
The role of Leguminosae plants for soil fertility in oil palm plantations
Authors: Al Manar P , Hikmat A , Zuhud E A M
Published: September 2023

The greatest and most lucrative plantation product in Indonesia is palm oil. The availability of nutrients in the soil affects how oil palm plants grow and develop. To overcome the low availability of nutrients in the soil to meet the needs of plants, fertilization operations are required. The concept of a green economy necessitates that the palm oil industry limits its usage of chemical fertilizers as well as chemical pest and disease management. Oil palm plants require a variety of fertilizers that are rich in macronutrients (N, P, and K), secondary nutrients (Ca and Mg), and micronutrients (B, Zn, and Cu). The potential use of biodiversity as a soil fertility agent, such as Leguminosae plants, must be researched. The purpose of this study is to define the function of Leguminosae plants in oil palm farms’ soil fertility. Several scientific papers that were pertinent to the research issue were studied for literature as part of the data collection process. Oil palm plantations in Indonesia have implemented the planting of legume cover crops (LCC). Planting LCC suppresses weed growth, protects the soil from direct sunlight and raindrops, reduces surface runoff, maintains soil moisture, and increases soil fertility. Neustanthus phaseoloides var. javanicus, Calopogonium caeruleum, C. mucunoides, Mucuna bracteata, M. pruriens var. utilis, and Centrosema pubescens are a few Leguminosae plants that can be used as cover crops. In addition to these species, planting Parkia timoriana, P. speciosa, and Archidendron pauciflorum trees can help improve soil fertility. Oil palm plantations with legumes have a higher clay texture, an average pH of 6.0, and high levels of N-total, P, K, and C-organic, whereas non-legume oil palm plantations have a sandy texture and high dust, an average pH of 5.3, and very low levels of N-total, P, K, and C-organic. Legumes, in addition to being a cover crop, can also be used as animal feed and to increase nutrient levels in plants. Planting LCC in oil palm plantations can affect the nutrient content of forages that grow under oil palm trees because the root nodules of LCC contain rhizobium bacteria that function to fix nitrogen from the air and are converted by the nitrogenase enzyme into ammonium and nitrate as a source of N for the LCC. The concept of integrated plantations can be applied to oil palm plantations by using LCC, which has hampered the growth of oil palm plants as animal feed, and P. timoriana, P. speciosa, and A. pauciflorum trees as economically valuable food plants.
Using machine learning to predict dinitrogen molecule density by analyzing transient-dependent nonlinear pulse propagation in an air-filled hollow core photonic crystal fiber
Authors: Jimenez-Mejia R E , Alvarez Ocampo Carlos , Acuna Herrera Rodrigo
Published: September 2023

Pulse propagation in air-filled hollow core photonic crystal fibers has been well investigated within the last decade to generate nonlinear phenomena such as pulse compression, frequency conversion, supercontinuum (SC) generation, among others, in a highly reliable and reproducible manner. In this work, we extend the analysis to take into account the recently evidenced pulsewidth dependency of the nonlinear refraction index of air and the effects of its molecular composition, showing that this latter plays a drastic influence on the rotational Raman response as well as the nonlinear refractive index. Our study focuses on the dispersive wave and SC generation, presenting distinct effects on the spectrum due to the pulsewidths dependency along the propagation path, evidencing different spectral broadening features depending on the initial pulsewidth. Based on these results we propose a deep learning algorithm that can predict the dinitrogen molecule particle-density of an air sample from different atmospheric conditions with a relative error lower than 3%.
Effect of angle interlocking/plain weave compound fabric system on mechanical properties of aramid epoxy resin composites
Authors: Xu Zhenzhen , Ma Xiang , Yang Li , Hu Qiaole
Published: September 2023

Preform is one of the important factors affecting the mechanical properties of textile composites. To further reflect the influence of the preform structure on the mechanical properties of composite materials, the angle interlocking and plain weave structures are configured in a certain proportion to form a composite fabric with both structures. The results show that the compound fabric preform has a positive effect on the improvement of the mechanical properties of AERC. An increase in the proportion of angle interlocking organization configuration in the compound fabric system is beneficial to the increase in tensile strength of AERC. In this experiment, when the ratio of angle interlocking structure and plain weave structure in the compound fabric system is 3:1, the tensile strength of AERC increases significantly, which is 80.98% higher than that of AERC with angle interlocking preformed structure. When the preform is made of compound fabric, the bending properties of AERC are greatly improved, and the bending strength is also increased 1.20 times compared to the AERC with angle interlock structure as the preform. When the ratio of angle interlock weave and plain weave in the compound fabric system is 1:3, the bending strength of AERC increases 1.81 times the maximum. The proportion of two fabric structures in the compound fabric system has a significant impact on the impact properties of AERC. The increase in the proportion of plain weave in the compound fabric system is not conducive to the increase in impact strength of AERC, and the large proportion of corner interlock configuration is conducive to the increase in bending strength of AERC. When the ratio of angle interlocking structure to plain weave structure is 2:1, the AERC has the maximum impact strength of 33.14 KJ/m2, which is increased by 26.28%.
Direct evidence for atmospheric carbon dioxide removal via enhanced weathering in cropland soil
Authors: Holzer Iris O , Nocco Mallika A , Houlton Benjamin Z
Published: September 2023

Enhanced weathering of soil-applied crushed silicate rocks may remove substantial atmospheric carbon dioxide; however, field testing of this negative emission technology is lacking. Models have suggested that enhanced weathering could, in principle, remove billions of tons of CO2 each year across global croplands, but methodological limitations have hindered direct measurement of CO2 sequestration via crushed rock amendments in agriculture. Further questions remain concerning the efficacy of this technology in arid climates. Here we provide direct evidence of rapid CO2 removal via enhanced weathering in soil pore water samples from a corn (Zea mays L.) cropping system in California. From December through February, during an extreme drought in our study region, we demonstrate a 2.6 to 2.9-fold increase in in situ bicarbonate alkalinity in response to additions of metabasalt and olivine fines. We provide a field analysis of carbon removal via silicate rock amendments and suggest enhanced weathering can remove carbon dioxide even under moisture-limited conditions.
Device design principles and bioelectronic applications for flexible organic electrochemical transistors
Authors: Gao Lin , Wu Mengge , Yu Xinge , Yu Junsheng
Published: September 2023

Organic electrochemical transistors (OECTs) exhibit significant potential for applications in healthcare and human-machine interfaces, due to their tunable synthesis, facile deposition, and excellent biocompatibility. Expanding OECTs to the flexible devices will significantly facilitate stable contact with the skin and enable more possible bioelectronic applications. In this work, we summarize the device physics of flexible OECTs, aiming to offer a foundational understanding and guidelines for material selection and device architecture. Particular attention is paid to the advanced manufacturing approaches, including photolithography and printing techniques, which establish a robust foundation for the commercialization and large-scale fabrication. And abundantly demonstrated examples ranging from biosensors, artificial synapses/neurons, to bioinspired nervous systems are summarized to highlight the considerable prospects of smart healthcare. In the end, the challenges and opportunities are proposed for flexible OECTs. The purpose of this review is not only to elaborate on the basic design principles of flexible OECTs, but also to act as a roadmap for further exploration of wearable OECTs in advanced bio-applications.