bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic Recognition of Black-Necked Swan (Cygnus melancoryphus) from Drone Imagery
Authors: Jiménez-Torres Marina , Silva Carmen P. , Riquelme Carlos , Estay Sergio A. , Soto-Gamboa Mauricio
Published: January 2023

Ecological monitoring programs are fundamental to following natural-system populational trends. Drones are a new key to animal monitoring, presenting different benefits but two basic re-strictions First, the increase of information requires a high capacity of storage and, second, time invested in data analysis. We present a protocol to develop an automatic object recognizer to minimize analysis time and optimize data storage. We conducted this study at the Cruces River, Valdivia, Chile, using a Phantom 3 Advanced drone with an HD-standard camera. We used a Black-necked swan (Cygnus melancoryphus) as a model because it is abundant and has a contrasting color compared to the environment, making it easy detection. The drone flew 100 m from water surface (correcting AGL in relation to pilot landing altitude) obtaining georeferenced images with 75% overlap and developing approximately 0.69 km2 of orthomosaics images. We estimated the swans’ spectral signature to build the recognizer and adjusted nine criteria for object-oriented classification. We obtained 140 orthophotos classified into three brightness categories. We found that the Precision, Sensitivity, Specificity, and Accuracy indicator were higher than 0.93 and a calibration curve with R2= 0.991 for images without brightness. The recognizer prediction decreases with brightness but is corrected using ND8-16 filter lens. We discuss the importance of this recognizer to data analysis optimization and the advantage of using this recognition protocol for any object in ecological studies.
Acknowledgment to the Reviewers of Entropy in 2022
Authors:   Entropy Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Acknowledgment to the Reviewers of Ecologies in 2022
Authors:   Ecologies Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Acknowledgment to the Reviewers of Econometrics in 2022
Authors:   Econometrics Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
How Sustainable Are Claims about Evidence-Based Content in Australian Courses for Preparing Special Educators?
Authors: Stephenson Jennifer , Ganguly Rahul , Kemp Coral , Salisbury Catherine
Published: January 2023

We reviewed the content of units in master’s-level special and/or inclusive education courses in Australia to determine whether the content relating to instructional practices and behaviour support and intervention included evidence-based practices (practices drawn from sound research). We identified claims about evidence-based practices made in publicly available materials describing unit content and determined whether these claims were supported by the actual content described. Of the 28 courses examined, six made no claims about evidence-based practices, 19 courses included supported claims and 15 courses included unsupported claims. Interpretation of the results should be cautious given the limited material available for some courses, but overall, the results are cause for concern. We believe there is a need for formal standards for special/inclusive education courses and certification for qualified special educators in Australia.
Effective Music Teachers and Effective Music Teaching Today: A Systematic Review
Authors: Concina Eleonora
Published: January 2023

(1) Background: This systematic review focuses on identifying the main features of effective music teachers and teaching recently examined in the educational and psychological literature. It aims to identify how recent studies have discussed the promotion of effectiveness in the context of both preservice and in-service music teachers. (2) Methods: A search in the main scientific databases for educational research (Eric, Science Direct, WWS, Web of Science, JSTOR) was conducted using keywords associated with the topics of effective teachers and teaching in the field of music instruction. In the end, thirty-six papers were identified and analyzed. (3) Results: The main themes were related to various dimensions of music teaching and teachers: teachers’ personal characteristics (self-esteem, resilience, etc.) and personality traits; professional skills; cognitive and psychological aspects of teachers’ professional identity (self-efficacy, professional motivation, beliefs regarding teaching and learning music, etc.); training experiences (pre- and in-service); social competence and the interpersonal relationship between the teacher and the students. (4) Conclusions: These dimensions seem interrelated and contribute to simultaneously define the effective music teacher and effective teaching in music. Specific attention should be paid to the impact of learning contexts on teachers’ activities, leading to a contextualized definition of effective music teachers.
Predicting Path Loss of an Indoor Environment Using Artificial Intelligence in the 28-GHz Band
Authors: Aldossari Saud Alhajaj
Published: January 2023

The propagation of signal and its strength in an indoor area have become crucial in the era of fifth-generation (5G) and beyond-5G communication systems, which use high bandwidth. High millimeter wave (mmWave) frequencies present a high signal loss and low signal strength, particularly during signal propagation in indoor areas. It is considerably difficult to design indoor wireless communication systems through deterministic modeling owing to the complex nature of the construction materials and environmental changes caused by human interactions. This study presents a methodology of data-driven techniques that will be applied to predict path loss using artificial intelligence. The proposed methodology enables the prediction of signal loss in an indoor environment with an accuracy of 97.4%.
A Novel Image Encryption Algorithm Based on Multiple Random DNA Coding and Annealing
Authors: Zhang Tianshuo , Zhu Bingbing , Ma Yiqun , Zhou Xiaoyi
Published: January 2023

Improved encryption devices place higher demands on the randomness and security of encrypted images. Existing image encryption optimization methods based on single- or multi-objectives concentrate on selecting keys and parameters, resulting in relatively fixed parameters and keys that are susceptible to leakage and cracking. Despite the possibility of increasing security, the DNA coding encryption method does not fully take into account the large capacity of image data and the difference between pixels, resulting in a limited level of randomness. To overcome the problems above, this paper proposes a method for generating complex texture features in images using random variation of pixels. With an annealing algorithm that can find an optimal solution in a large search space, the image is optimally optimized in terms of information entropy, pixel correlation, and value of x2. Each iteration involves selecting one of 25632 combinations of DNA coding and operation. In comparison with current encryption algorithms based on optimization algorithms and DNA coding, this method is more secure and unbreakable.
Mapping Outputs and States Encoding Bits to Outputs Using Multiplexers in Finite State Machine Implementations
Authors: Senhadji-Navarro Raouf , Garcia-Vargas Ignacio
Published: January 2023

This paper proposes a new technique for implementing Finite State Machines (FSMs) in Field Programmable Gate Arrays (FPGAs). The proposed approach extends the called column compaction in two ways. First, it is applied to the state-encoding bits in addition to the outputs, allowing a reduction in the number of logic functions required both by the state transition function and by the output function. Second, the technique exploits the dedicated multiplexers usually included in FPGAs to increase the number of columns that can be compacted. Unlike conventional state-encoding techniques, the proposed approach reduces the number of logic functions instead of their complexity. An Integer Linear Programming (ILP) formulation that maximizes the number of compacted columns has been proposed. In order to evaluate the effectiveness of the proposed approach, experimental results using standard benchmarks are presented. In most cases, the proposed approach reduces the number of used Look-Up Tables (LUTs) with respect to the conventional FSM implementation.
3D Hybrid Localization Algorithm for Mitigating NLOS Effects in Flying Ad Hoc Networks
Authors: Pak Jung Min
Published: January 2023

Positions of unmanned aerial vehicles (UAVs) are typically obtained using the global positioning system (GPS). However, in GPS-denied or GPS-degraded environments, ad hoc networks with flying sensor nodes are used for UAV localization. In this study, we propose a novel three-dimensional (3D) localization algorithm for UAVs in flying ad hoc sensor networks. Interacting multiple model probability data association and finite impulse response filters are integrated in our hybrid localization algorithm. The non-line-of-sight condition can be overcome using the proposed algorithm, which is demonstrated through 3D localization simulations based on flying ad hoc networks.
Temperature and Power Supply Compensated CMOS Clock Circuit Based on Ring Oscillator
Authors: Stancu Cristian , Neacsu Andrei , Profirescu Ovidiu , Dobrescu Dragos , Dobrescu Lidia
Published: January 2023

Improved performance operational amplifier demand has continuously increased. IC designers use the charge pump technique as an advanced solution to implement the amplifier’s rail−to−rail input stage, but the need for a large load capacitor is a serious downside. To reduce this passive component value, high−frequency clock circuits with a 50% duty cycle should be implemented. This paper focuses on designing such a circuit that is further compensated with temperature and power supply, maintaining these performances even when process variations occur, starting from a ring oscillator as the architecture core. A pre−layout 50 MHz center frequency at 25 °C with a 1.6 temperature percentage error was achieved. Post−layout simulations to account for parasitic effects were also performed, with a 48.9 MHz center frequency reached. Distinct methods that control the frequency variation were discussed and established. Performance comparison of the designed PLL with previously reported clock circuits in the CMOS process was concluded, with superior results such as power consumption, die area, and temperature range accomplished.
A Hierarchical Estimation Method for Road Friction Coefficient Combining Single-Step Moving Horizon Estimation and Inverse Tire Model
Authors: Wang Guodong , Bai Guoxing , Meng Yu , Liu Li , Gu Qing , Ma Zhiping
Published: January 2023

To improve the real-time performance of the estimation method of road friction coefficient (RFC) based on moving horizon estimation (MHE), a hierarchical estimation method for RFC combining single-step MHE (S-MHE) and inverse tire model (ITM) based on lateral vehicle dynamics is proposed in this study. Firstly, a hierarchical estimation framework is designed to decouple vehicle and tire systems. Secondly, the S-MHE estimator is designed based on the nonlinear vehicle model to estimate the lateral tire force. Thirdly, the ITM is deduced based on the Pacejka model, and the estimator for the RFC based on the ITM is designed. Finally, the estimation accuracy, convergence speed, and real-time performance of the proposed method and the traditional MHE method are compared and discussed through different tests based on CarSim and Simulink. The results show that compared with the traditional MHE method, the proposed method reduces the average computation time to about 0.125 s and improves the real-time performance by more than 30% while ensuring the estimation accuracy and convergence speed.
Phase Change Materials Energy Storage Enhancement Schemes and Implementing the Lattice Boltzmann Method for Simulations: A Review
Authors: Shirbani Milad , Siavashi Majid , Bidabadi Mehdi
Published: January 2023

Utilizing phase change materials (PCMs) is one of the most effective methods of storing thermal energy and is gaining popularity in renewable energy systems. In order to analyze PCM performance, various numerical methods have been deployed to study the transient behaviour during phase changes. PCMs’ low thermal conductivity prevents their use as pure PCMs in industrial applications. There are various efficient methods of enhancing PCM thermal conductivity, which are addressed in this article. On the other hand, the lattice Boltzmann method (LBM) is very inclusive in the numerical simulation of complex fluid flows, thermal transport, and chemical interactions because of its ability to simply represent various complex physical phenomena, suitability for parallel programming, and easy coding and implementation. Many numerical studies have been conducted on PCMs using the LBM. This study aims to review these studies and categorize them in a way so that one may thoroughly understand the LBM’s capabilities in the simulation of PCM-related investigations. First, PCM characteristics and applications are presented, then the LBM implementation in PCM problems is addressed. Afterward, the fabrication and types of PCMs are mentioned. Next, the improvement of thermal energy storage methods of PCMs is stated. Furthermore, governing equations are reviewed. Lastly, the opportunities and challenges of the LBM in PCMs are discussed.
Microstructure and Hydrogen Storage Performance of Ball-Milled MgH2 Catalyzed by FeTi
Authors: Révész Ádám , Paramonov Roman , Spassov Tony , Gajdics Marcell
Published: January 2023

A high-energy ball-milling method was applied for different milling times (1 h, 3 h, and 10 h) to synthetize nanocrystalline MgH2 powder samples catalyzed by Fe2Ti. Morphology and microstructure of the powders were characterized by scanning electron microscopy and X-ray diffraction. The recorded diffraction profiles were evaluated by the convolutional multiple whole profile fitting algorithm, in order to determine microstructural parameters of the composites, such as average crystallite size and average dislocation density. Differential scanning calorimetry was performed to investigate the dehydrogenation characteristics of the alloys. It was obtained that there exists an optimal milling time (3 h) when desorption occurs at the lowest temperature. X-ray diffraction of partially dehydrided states confirmed a two-step H-release, including the subsequent desorption of γ-MgH2 and α-MgH2. The effect of milling time on the H-sorption performance was investigated in a Sievert-type apparatus. The best overall hydrogenation performance was obtained for the composite milled for 3 h.
HVDC Fault Detection and Classification with Artificial Neural Network Based on ACO-DWT Method
Authors: Jawad Raad Salih , Abid Hafedh
Published: January 2023

Unlike the more prevalent alternating current transmission systems, the high voltage direct current (HVDC) electric power transmission system transmits electric power using direct current. In order to investigate the precise remedy for fault detection of HVDC, this research proposes a method for the HVDC fault diagnostic methodologies with their limits and feature selection-based probabilistic generative model. The main contribution of this study is using the wavelet transform based on ant colony optimization and ANN to detect the different types of faults in HVDC transmission lines. In the proposed method, ANN uses optimum features obtained from the voltage, current, and their derivative signals. These features cannot be accurate to use in ANN because they cannot give reliable accuracy results. For this reason, first, the wavelet transform applies to the fault and non-fault signals to remove the noise. Then the ACO reduces unimportant features from the feature vector. Finally, the optimum features are used in the training of ANN as faulty and non-faulty signals. The multi-layer perceptron used in the suggested method consists of many layers, enabling the creation of a probability reconstruction over the inputs by the model. A supervised learning method is used to train each layer based on the selected features obtained from the ant colony optimization-discrete wavelet transform metaheuristic method. The artificial neural network technique is used to fine-tune the model to reduce the difference between true and anticipated classes’ error. The input signal and sampling frequencies are changed to examine the suggested strategy’s effectiveness. The obtained results demonstrate that the suggested fault detection and classification model can accurately diagnose HVDC faults. A comparison of the Support vector machine, Decision Tree, K-nearest neighbor algorithm (K-NN), and Ensemble classifier Machine techniques is made to verify the suggested method’s unquestionably higher performance.
Efficiency Improvement of Photovoltaic Panels: A Novel Integration Approach with Cooling Tower
Authors: Abdelsalam Emad , Alnawafah Hamza , Almomani Fares , Mousa Aya , Jamjoum Mohammad , Alkasrawi Malek
Published: January 2023

Overheating of photovoltaic (PV) panels decreases their efficiency and lifetime, and subsequently increases the levelized cost of energy (LCOE). Passive PV cooling would enhance the PV operational stability and durability. The cooling tower (CT) technology offers an attractive approach for zero-cost capability. In this work, we developed and customized a CT specific for passive PV cooling. Since the dense downdrafted cooled air gained high velocity, a turbine was installed at the bottom of the CT for power production. At the height’s ambient temperature, the CT cooled the air from 50 °C down to 30 °C. The cooled air at 30 °C has enough capacity to cool the PV panels. This cooling capacity improved the average annual efficiency of the PV panels by 6.83%. The design specifications of the CT have the highest performance, with the maximum radius of PV area of panels that can be cooled at 50 m. Furthermore, the current design could operate during the night for power production with minimum operational cost.
Simulation and Experimental Evaluation of a Refractive-Reflective Static Solar Concentrator
Authors: Luque-Zuñiga Guillermo , Vázquez-Medina Rubén , Ramos-López G. , Pérez-Márquez David Alejandro , Yee-Madeira H.
Published: January 2023

Static solar devices have advantages over solar tracking systems. In pure reflective systems, solar reception is limited by the entry angle of the reflector. Many reflective systems are based on mirror Compound Parabolic Concentrators. The solar collection can be improved by placing a lens on top of the reflector. In this work, a static system is proposed, consisting of a mirror funnel concentrator with a prism on top. The system is designed using ray-tracing software and is subsequently built and experimentally evaluated. The system designed for an effective concentration factor of 4× reaches an effective concentration of 3.2× at 11:30 a.m. and has an acceptance angle of 60°. Considering the time interval from 8 a.m. to 4 p.m., the system harvests 30.7% more energy than the flat surface. If the time interval considered is from 9:30 a.m. to 2:30 p.m., the increase in harvest is ∼77%. The incorporation of the prism represents an increase of ∼6% compared to the bare reflective system.
A Comprehensive Review of Artificial Intelligence (AI) Companies in the Power Sector
Authors: Franki Vladimir , Majnarić Darin , Višković Alfredo
Published: January 2023

There is an ongoing, revolutionary transformation occurring across the globe. This transformation is altering established processes, disrupting traditional business models and changing how people live their lives. The power sector is no exception and is going through a radical transformation of its own. Renewable energy, distributed energy sources, electric vehicles, advanced metering and communication infrastructure, management algorithms, energy efficiency programs and new digital solutions drive change in the power sector. These changes are fundamentally altering energy supply chains, shifting geopolitical powers and revising energy landscapes. Underlying infrastructural components are expected to generate enormous amounts of data to support these applications. Facilitating a flow of information coming from the system′s components is a prerequisite for applying Artificial Intelligence (AI) solutions in the power sector. New components, data flows and AI techniques will play a key role in demand forecasting, system optimisation, fault detection, predictive maintenance and a whole string of other areas. In this context, digitalisation is becoming one of the most important factors in the power sector′s transformation process. Digital solutions possess significant potential in resolving multiple issues across the power supply chain. Considering the growing importance of AI, this paper explores the current status of the technology’s adoption rate in the power sector. The review is conducted by analysing academic literature but also by analysing several hundred companies around the world that are developing and implementing AI solutions on the grid’s edge.
Online Multiphase Flow Measurement of Crude Oil Properties Using Nuclear (Proton) Magnetic Resonance Automated Measurement Complex for Energy Safety at Smart Oil Deposits
Authors: Kashaev Rustem , Ahn Nguyen Duc , Kozelkova Valeriya , Kozelkov Oleg , Dudkin Valentin
Published: January 2023

The necessity of a flow express control of oil dispersed system (ODS) properties, such as crude oil, oil products, water–oil emulsions, and polluted waters, is substantiated. This control is necessary for the production and preparation of oil for transportation through the pipeline and oil refining, oil products, and wastewater treatment systems. A developed automatic measuring complex (AMC) is used to implement the concept of digital oil deposits. The primary measuring device is a relaxometer developed by us based on nuclear (proton) magnetic resonance (PMR). The design and operation algorithm of the AMC and the relaxometer are described. Equations have been developed to determine the ODS characteristics using the measured PMR parameters. This makes it possible to determine the flow rates of crude oil, the concentration of water in the oil, the concentration of asphaltene, resins, and paraffins in the oil, as well as the density, viscosity, and molecular weight of the oil. Additionally, it is possible to determine the dispersed distribution of water droplets in emulsions in oil production and treatment units. Data on this distribution will improve the management of separation processes. It has been established that the implemented control of multiphase ODS using PMR parameters (relaxation times, populations of proton phases, and amplitudes of spin-echo signals) makes it possible, using AMC, to assess the consumption of electricity in technological processes at the digital oil deposits, as well as during the transportation of oil and oil products through pipelines. AMC makes it possible to reduce electrical energy consumption in technological installations and reduce pollution emissions into wastewater. The advantages of using the developed AMC are shown in examples of its application. Such as an assessment of the influence of the gas factor on electricity consumption during oil transportation through pipelines or compensation for the additional moment of resistance on the shaft of the submersible motor, which is caused by surface tension forces at the interface of water droplets in the emulsion.
Advanced Methods for Wind Turbine Performance Analysis Based on SCADA Data and CFD Simulations
Authors: Castellani Francesco , Pandit Ravi , Natili Francesco , Belcastro Francesca , Astolfi Davide
Published: January 2023

Deep comprehension of wind farm performance is a complicated task due to the multivariate dependence of wind turbine power on environmental variables and working parameters and to the intrinsic limitations in the quality of SCADA-collected measurements. Given this, the objective of this study is to propose an integrated approach based on SCADA data and Computational Fluid Dynamics simulations, which is aimed at wind farm performance analysis. The selected test case is a wind farm situated in southern Italy, where two wind turbines had an apparent underperformance. The concept of a space–time comparison at the wind farm level is leveraged by analyzing the operation curves of the wind turbines and by comparing the simulated average wind field against the measured one, where each wind turbine is treated like a virtual meteorological mast. The employed formulation for the CFD simulations is Reynolds-Average Navier–Stokes (RANS). In this work, it is shown that, based on the above approach, it has been possible to identify an anemometer bias at a wind turbine, which has subsequently been fixed. The results of this work affirm that a deep comprehension of wind farm performance requires a non-trivial space–time comparison, of which CFD simulations can be a fundamental part.
Multi-Object Detection Algorithm in Wind Turbine Nacelles Based on Improved YOLOX-Nano
Authors: Hu Chunsheng , Zhao Yong , Cheng Fangjuan , Li Zhiping
Published: January 2023

With more and more wind turbines coming into operation, inspecting wind farms has become a challenging task. Currently, the inspection robot has been applied to inspect some essential parts of the wind turbine nacelle. The detection of multiple objects in the wind turbine nacelle is a prerequisite for the condition monitoring of some essential parts of the nacelle by the inspection robot. In this paper, we improve the original YOLOX-Nano model base on the short monitoring time of the inspected object by the inspection robot and the slow inference speed of the original YOLOX-Nano. The accuracy and inference speed of the improved YOLOX-Nano model are enhanced, and especially, the inference speed of the model is improved by 72.8%, and it performs better than other lightweight network models on embedded devices. The improved YOLOX-Nano greatly satisfies the need for a high-precision, low-latency algorithm for multi-object detection in wind turbine nacelle.
Wind-Tunnel Experiments on the Interactions among a Pair/Trio of Closely Spaced Vertical-Axis Wind Turbines
Authors: Jodai Yoshifumi , Hara Yutaka
Published: January 2023

To elucidate the wind-direction dependence of the rotor performance in closely spaced vertical-axis wind turbines, wind-tunnel experiments were performed at a uniform wind velocity. In the experiments, a pair/trio of three-dimensional printed model turbines with a diameter of D = 50 mm was used. The experiments were performed systematically by applying incremental adjustments to the rotor gap g and rotational direction of each rotor and by changing the wind direction. For tandem layouts, the rotational speed of the downwind rotor is 75–80% that of an isolated rotor, even at g/D = 10. For the average rotational speed of the rotor pair, an origin-symmetrical and a line-symmetrical distribution are observed in the co-rotating and inverse-rotating configurations, respectively, thereby demonstrating the wind-direction dependence for the rotor pair. The inverse-rotating trio configuration yields a higher average rotational speed than the co-rotating trio configuration for any rotor spacing under the ideal bidirectional wind conditions. The maximum average rotational speed should be obtained for a wind direction of θ = 0° in the inverse-rotating trio configuration. The wind-direction dependence of the rotational speeds of the three turbines was explained via flow visualization using a smoke-wire method and velocity field study using two-dimensional computational fluid dynamics.
Study on the Evolution Pattern of the Aromatics of Lignin during Hydrothermal Carbonization
Authors: Sun Wendi , Bai Li , Chi Mingshu , Xu Xiuling , Chen Zhao , Yu Kecheng
Published: January 2023

Waste straw contains a large amount of lignin, and its resource utilization is not only in line with the national double carbon development strategy, but also to alleviate environmental pollution. Hydrothermal carbonization is a new thermochemical conversion technology, which has attracted much attention because it can directly transform carbon containing waste raw materials with high moisture content and low energy density. To investigate the physicochemical properties and aromatization changes of lignin hydrochar, hydrothermal carbonization experiments were carried out at 290 °C and a solid–liquid ratio of 1:20 for 0.00, 0.25, 0.50, 1.00, 1.50, 2.00, 4.00, 8.00 h, respectively. The experimental results shows that hydrothermal carbonization can increase the combustion quality of lignin. Physical and chemical properties analysis shows that with the increase of hydrothermal carbonization time from 0 to 2 h, the hydrochar content increased from 21.21% to 26.02% and the HHV of hydrochar increased from 20.01 MJ/Kg to 26.32 MJ/Kg. When the holding time exceeded 2 h, the carbon content and calorific value of hydrothermal tended to be stable. With the increase of holding time, FTIR analysis and XRD analysis show that the free hydroxyl groups in water-soluble lignin were easily combined with intramolecular and intermolecular hydrogen bonds, thus forming an ordered crystal arrangement. Subsequently, the crystal structure formed a well-arranged long chain through a strong hydrogen bond network, forming a ring structure in the process of aromatization. Aromatic ring structure accumulated, aromatization wave peak increased with holding time and aromatization intensified. Hydrochar crystal particles became larger and arranged in order. At the same time, the surface functional group detection and degree of crystallization were almost unchanged when holding time exceeded 2 h. The surface morphology of hydrochar was observed by SEM as follows: when the hydrothermal carbonization reaction of lignin entered the insulation stage, the microsphere structure began to aggregate and then became larger. When the holding time reached 2 h, the growth rate of carbon microspheres noticeably slowed. Therefore, the optimal hydrothermal carbonization time of lignin is 2 h, and hydrochar fuel has the best performance and aromatization.
Research on Magnetic Field and Force Characteristics of a Novel Four-Quadrant Lorentz Force Motor
Authors: Meng Xiangrui , Wang Changhong , Zhong Jiapeng , Xia Hongwei , Song Liwei , Yang Guoqing
Published: January 2023

The 6-DOF vibration isolation platform (VIP) is used to isolate vibration in the processing and manufacturing of semiconductor chips, especially electric vehicle chips. The 6-DOF VIP has the characteristics of high position accuracy, fast dynamic response, and short motion travel. In this paper, a novel four-quadrant Lorentz force motor (FQLFM) applied on the 6-DOF VIP is proposed. The structure of this LFM has a high force density, low force fluctuation, and low coupling force. First, the basic structure and operating principle of the proposed FQLFM are presented. Secondly, the expressions of the magnetic field and electromagnetic force are obtained based on an equivalent current model and the permanent magnet mirror-image method (PMMIM). Thirdly, the magnetic field and electromagnetic force characteristics of the proposed FQLFM and an LFM with a traditional bilateral structure are analyzed and compared. The relationship between the force and displacement of the FQLFM is investigated. Moreover, the PMMIM is verified by a 3D finite element analysis (FEA). Finally, the experimental platform for a force test is built and the above results are validated by an experiment.
Power Conversion Interface for a Small-Capacity Photovoltaic Power Generation System
Authors: Wu Jinn-Chang , Jou Hurng-Liahng , Chang Chung-Hsun
Published: January 2023

A power conversion interface for a small-capacity photovoltaic power generation system (PPGS) is proposed in this paper. The proposed power conversion interface is composed of a DC–DC converter (DDC), a battery pack and a buck–boost inverter (BBI). The battery pack is integrated to the power conversion interface to store or release energy for smoothing the power fluctuation of the small-capacity PPGS. The battery pack is only activated when a large power change occurs in the photovoltaic array (PV array). The DC power, no matter whether is from the PV array or the battery pack, needs to be converted into AC power only by the BBI in the proposed power conversion interface. Moreover, the PV array charges the battery pack only through the DDC, which simplifies the power circuit and improves the power conversion efficiency. To verify the feasibility of the proposed power conversion interface, a hardware prototype is established for practical experiments.
Analysis of the Suitability of the EOLO Wind-Predictor Model for the Spanish Electricity Markets
Authors: Martínez-Lastras Saray , Frías-Paredes Laura , Prieto-Herráez Diego , Gastón-Romeo Martín , González-Aguilera Diego
Published: January 2023

Wind energy forecasting is a critical aspect for wind energy producers, given that the chaotic nature and the intermittence of meteorological wind cause difficulties for both the integration and the commercialization of wind-produced electricity. For most European producers, the quality of the forecast also affects their financial outcomes since it is necessary to include the impact of imbalance penalties due to the regularization in balancing markets. To help wind farm owners in the elaboration of offers for electricity markets, the EOLO predictor model can be used. This tool combines different sources of data, such as meteorological forecasts, electric market information, and historic production of the wind farm, to generate an estimation of the energy to be produced, which maximizes its financial performance by minimizing the imbalance penalties. This research study aimed to evaluate the performance of the EOLO predictor model when it is applied to the different Spanish electricity markets, focusing on the statistical analysis of its results. Results show how the wind energy forecast generated by EOLO anticipates real electricity generation with high accuracy and stability, providing a reduced forecast error when it is used to participate in successive sessions of the Spanish electricity market. The obtained error, in terms of RMAE, ranges from 8%, when it is applied to the Day-ahead market, to 6%, when it is applied to the last intraday market. In financial terms, the prediction achieves a financial performance near 99% once imbalance penalties have been discounted.
Numerical Study of Heat and Mass Transfer in the Original Structure and Homogeneous Substitution Model for Three Dimensional Porous Metal Foam
Authors: Ke Hanbing , Zhou Xuzhi , Liu Tao , Wang Yu , Wang Hui
Published: January 2023

In many applications, such as the miniaturization and cooling of high-power electronics in aerospace, a new thermal management solution is needed, and metal foam radiators may be a valuable solution. In this work, X-ray scanning was applied to obtain the original structure of the metal foam. The real structure calculation model of the metal foam was obtained through a series of modeling, and high-precision numerical simulation was built to study heat and mass transfer in the original structure and homogeneous substitution model for three-dimensional porous metal foam. The distribution of velocity, pressure and temperature field is investigated. The results show that the heat transfer characteristics increase and flow resistance decreases with an increase in the Reynolds number. The heat transfer performance and flow resistance increase with the decrease of porosity. The porous media homogenization model can be consistent with the original real calculation results of metal foam by using appropriate values of resistance coefficient and porosity. The variation of resistance coefficient and porosity with the working condition in the porous homogenization model is identified.
Advances in Biodiesel Production from Microalgae
Authors: Neag Emilia , Stupar Zamfira , Maicaneanu S. Andrada , Roman Cecilia
Published: January 2023

Biofuels, as a renewable, eco-friendly, and cost-effective energy source, can reduce the dependence on fossil fuels. The researchers considered different approaches for obtaining high biodiesel yields from microalgae biomass. This work aims to present an overview of the feasibility of microalgae use in biodiesel production. Therefore, biodiesel production from microalgae oil via the transesterification process was explained in detail. The application of non-catalytic transesterification and catalytic transesterification was reviewed. The achievements in the application of homogenous catalysts, heterogeneous catalysts, and enzymatic catalysts for microalgae oil transesterification were discussed. The present technologies for biodiesel production from microalgae need more improvements to increase their efficiencies and reduce costs. Therefore, future research should focus on the development of effective catalysts for biodiesel production from microalgae biomass.
Acknowledgment to the Reviewers of Endocrines in 2022
Authors:   Endocrines Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Plant Community Degradation Inquiry and Ecological Restoration Design in South Lake Scenic Area of China
Authors: Zhang Xue , Hu Haitao , Wang Xuhui , Tian Qianqian , Zhong Xingyao , Shen Lina
Published: January 2023

The most visited provincially administered park in Hanzhong City, the South Lake Scenic Area, is degrading the Masson Pine forest communities. Determining and repairing the landscape degradation and impacts on recreational value due to the degraded community structure is essential for restoring the environment of the southern Qinling Mountains. By evaluating the degree, trend, and pattern (DTP) of impacts, we identified the degradation status of the plant community in the South Lake Scenic Area in the past 20 years. We show that the scenic area has experienced an increase in the degradation of vegetation cover in the last 20 years. The area of degraded vegetation cover is significantly larger than the area of improvement, and the overall area is changing, with fewer stable areas. The area of reduced forest cover in the South Lake Scenic Area from 2000–2010 and 2010–2020 has been expanding, and the area of forest land transferred to nonforest land from 2010–2020 has been accelerating compared with 2000–2010; the landscape pattern index has decreased year over year, fragmentation has become serious, landscape connectivity is declining, woodland patches are subject to human disturbance, and patch shapes are simplifying. Based on theories of natural succession and moderate disturbance, the Miyawaki method and interlogging are used to promote plant community renewal and biodiversity restoration. This is intended to shorten the natural succession process in the scenic area and to rapidly restore the ecological foundation of the scenic area. Recovery will meet the aesthetic and ecological values of the South Lake Scenic Area.
Influence of Tree, Stand, and Site Attributes on Hardwood Product Yield: Insights into the Acadian Forests
Authors: Bennemann Caroline , Labelle Eric R. , Lussier Jean-Martin
Published: January 2023

Acadian forests of New Brunswick, Canada, are highly variable both in terms of species composition and quality. This is particularly accurate for hardwoods, for which value recovery is closely influenced by wood quality and a proper understanding of tree attributes. Therefore, based on several databases created between 2012 and 2021, the objectives of this study were to (1) characterize the stand-level distribution of species, size, form, and risk according to site factors and (2) determine the influence of different tree, stand, and site factors on the recovery of merchantable, sawlog, and veneer volumes. In total, 287,984 trees stemming from 9233 plots were analyzed for objective 1. For a subset of trees (743), tree, stand, and site attributes were also related to the product output of harvesting operations through a comprehensive inventory of standing trees and their associated products. Analyses were performed with linear and multinomial logistic regressions as well as factor analysis of mixed data (FAMD). Key results indicated that tree attributes and product recovery were significantly influenced by (1) environmental factors (soil, temperature, and precipitation), summarized by ecoregion in this study and (2) tree size and form. These findings suggest that the inclusion of site factors in supply planning could improve product recovery during forest operations.
Overexpression of the Poplar WRKY51 Transcription Factor Enhances Salt Tolerance in Arabidopsis thaliana
Authors: Zhou Yangyan , Li Qing , Zhang Yue
Published: January 2023

Salt is a severe environmental stressor that affects growth and development in plants. It is significant to enhance the salt tolerance in plants. In this study, a salt-responsive WRKY transcription factor PtrWRKY51 was isolated from Populus trichocarpa (clone ‘Nisqually-1′). PtrWRKY51 was highly expressed in mature leaves and root and induced by salt stress. The PtrWRKY51 was overexpressed in Arabidopsis to investigate its biological functions. Compared with Col-0 lines, Overexpressed lines had an increase in germination rate of seed, root length, higher photosynthetic rate, instantaneous leaf WUE, chlorophyll content to improve salt tolerance under salt stress conditions. In contrast, compared to overexpressed and Col-0 lines, the mutant wrky51 was more sensitive to salt stress with lower photosynthetic rate and WUE. Additionally, it was found that the complementary lines (wrky51/ PtrWRKY51) had almost the same salt response as Col-0. In conclusion, PtrWRKY51 is a potential target in the enhancement of poplar tolerance by genetic engineering strategies.
Acknowledgment to the Reviewers of Fire in 2022
Authors:   Fire Editorial Office
Published: January 2023

High-quality academic publishing is built on rigorous peer review [...]
Effect of Stocking Density on Growth, Water Quality Changes and Cost Efficiency of Butter Catfish (Ompok bimaculatus) during Seed Rearing in a Biofloc System
Authors: Majhi Snigdha S. , Singh Soibam Khogen , Biswas Pradyut , Debbarma Reshmi , Parhi Janmejay , Ngasotter Soibam , Waikhom Gusheinzed , Meena Dharmendra Kumar , Devi Ayam Gangarani , Mahanand Sudhanshu S. , Xavier K. A. Martin , Patel Arun Bhai
Published: January 2023

Biofloc technology is a modern-day high-density fish culture system employing heterotrophic conversion of nitrogenous waste into useful flocs for water quality control and improved welfare. However, optimization of the stocking density for the target species during seed rearing is the key to a successful farming operation. The study evaluated the effect of different stocking density on the growth, feed utilization, digestive physiology and economics in a biofloc-based seed rearing of butter catfish, O. bimaculatus. Advanced fry (1.21 ± 0.08 g) was reared in a zero-water exchange biofloc system for 90 days at stocking densities of 0.5 g/L(T1), 1.0 g/L(T2), 1.5 g/L(T3) and 2.0 g/L(T4). The observed water quality indicates a reduction in DO and pH in T4, while the total ammonia nitrogen and nitrite levels remained low in T1. Among the groups, highest weight gain was noticed in the lowest stocking density (0.5 g/L) (p < 0.05), which coincides with a better feed conversion ratio. Similarly, the digestive enzyme (protease, amylase, and lipase) secretion was higher in T1. Profitability assessment describes the possibility of low profit in T4, in the case where the fish’s sale price is based on harvested size. T1 showed higher individual growth and higher profit. Overall, a low stocking density of 0.5 g/Lis optimum for augmenting growth, feed utilization, physiological function and economic performance of O. bimaculatus. The study provides direction for a low-stocking oriented ecological and economically sustainable method of seed production of butter catfish in a biofloc system.
A Novel C-Type Lectin and Its Potential Role in Feeding and Feed Selection in Ruditapes philippinarum
Authors: Chen Sentao , Shi Peng , Feng Qingkai , Qiu Xiaoting , Xu Jilin , Yan Xiaojun , Zhou Chengxu
Published: January 2023

In recent years, the role of lectins in the feed selection of bivalve has become hot research topic. Manila clam Ruditapes philippinarum is a species of marine bivalve with important economic value. A new C-type lectin (Rpcl) from the clam was obtained and its potential role in feeding and feed selection was studied. Rpcl cDNA was 929 bp in length and had 720 bp of open reading frame. Rpcl encoded 235 amino acids, comprising a carbohydrate recognition domain (CRD) as well as an N-terminal signal peptide. Rpcl contained a conserved CRD disulfide bond including five cysteine residues (Cys125, Cys142, Cys213, Cys219, and Cys237) and the QPN motif (GLN204-PRO205-ASN206). Phylogenetic analysis revealed that the amino acid sequence of Rpcl was closely related to that of Vpclec-1 from R. philippinarum and C-type lectin from Mercenaria. The qPCR analysis indicated that Rpcl expression was observed in all examined tissues and was the highest in gills followed by in the hepatopancreas, and to a lesser extent in the mantle and lip. The in vitro agglutination experiments showed that, the purified Rpcl protein could selectively agglutinate with different microalgae. The strongest agglutinating effect with Chlorella sp. was observed, followed by Karlodinium veneficum and Chaetoceros debilis Cleve. No agglutination with Prorocentrum minimum was observed. In the feeding experiment, compared with that of the starvation group, Rpcl expression in the lip and gill of the clam fed with C. debilis and K. veneficum showed a significant upward trend with the change of time. In addition, it was found that the changes in the expression of the Rpcl gene in the gill and lip, the main feeding tissues, were consistent with the slope of the decrease in the number of algal cells in the water body. In summary, the structure of a new C-type lectin (Rpcl) was reported in this study and its correlation with the feeding and feed selection in R. philippinarum was confirmed.
Instability Problems and Density-Driven Convection in Saturated Porous Media Linking to Hydrogeology: A Review
Authors: Soboleva Elena
Published: January 2023

Investigations of fluid instability and density-driven convection in soils and rocks are motivated by both natural phenomena giving rise to ecological problems, and human activities. Knowledge about the admixture transportation by underground fluid flows driven by the gravity force is relevant, for example, to succeed in preventing degradation of soil quality or to improve the efficiency of carbon capture and sequestration technologies. We focus on fully saturated porous media containing two-component miscible fluid systems and consider the dynamic processes, which can be reduced to one of three principal problems, namely one-sided convection, two-sided convection, or convection caused by evaporation. This work reviews the main achievements in the field with more attention to the recent literature. Dependence of the convection onset on perturbations of physical parameters, asymmetric development of the Rayleigh–Taylor instability, appearance of salt drops under the evaporation surface, and other important findings are reported in the review.