bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Friction Behaviour of Titanium Grade 2 after Non-Contact Boriding in Oxygen-Containing Medium with Gas Nitriding
Authors: Lavrys Serhii , Pohrelyuk Iryna , Tkachuk Oleh , Padgurskas Juozas , Trush Vasyl , Proskurnyak Roman
Published: January 2023

The surface characteristics and friction behaviour of titanium Grade 2 with modified nitride (TiN, Ti2N) and boride (TiB) compound layers were investigated. It was shown that during non-contact boriding in oxygen-containing medium of titanium, the diffusion processes take place mainly by the interscale mechanism; however, during nitriding, besides the traditional interscale diffusion mechanism, the grain boundary mechanism of diffusion of nitrogen atoms is also realized. The optimal set of surface roughness parameters (height and step parameters, a combination of kurtosis and asymmetry, and profile reference curve parameters) was obtained after boriding. It was determined that the intensity of the adhesive wear of the tribo-pairs with stainless steel and ultrahigh molecular weight polyethylene under dry sliding conditions was influenced not only by the hardness but also roughness of the modified surface layer. The lowest friction coefficient was fixed for the TiB compound layer in both tribo-pairs.
The Role of Cymodocea nodosa and Caulerpa prolifera Meadows as Nitrogen Sinks in Temperate Coastal Lagoons
Authors: Bernardeau-Esteller Jaime , Sandoval-Gil José Miguel , Belando María Dolores , Ramos-Segura Aranzazu , García-Muñoz Rocío , Marín-Guirao Lazaro , Ruiz Juan Manuel
Published: January 2023

In coastal lagoons, marine benthic macrophyte meadows can be an important element in the resistance to eutrophication of the ecosystem, as they can function as temporary nitrogen sinks, limiting the availability of this nutrient for opportunistic organisms. The role of nitrogen sinks for two dominant macrophyte species of Mediterranean coastal lagoons, the seagrass Cymodocea nodosa and the seaweed Caulerpa prolifera, was analysed by two different approaches: (i) studying nitrate (NO3-) and ammonium (NH4+) uptake kinetics of aboveground tissues in a laboratory and (ii) estimating nitrogen stocks and demands of meadows under natural conditions. The studies were carried out in the coastal lagoon of the Mar Menor, which has been subjected to high anthropogenic nitrogen inputs for decades. While both macrophytes were efficient in exploiting NH4+ from the water column, only C. prolifera showed a high NO3- uptake capacity. Large N pools in the C. nodosa and C. prolifera meadows of the Mar Menor were detected, suggesting that these habitats may have the potential to be essential reservoirs for this nutrient. However, the major role of belowground tissues of the seagrasses in nitrogen accumulation may determine important differences between the two species in temporary N storage and sequestration. The data on N demands for the meadows of both macrophytes in the Mar Menor suggest an important contribution of these habitats in controlling the inputs of this nutrient into the lagoon. We conclude that C. nodosa and C. prolifera meadows can play a key role as a sink for dissolved inorganic nitrogen in temperate coastal lagoons, being an important mechanism of resistance to eutrophication.
Isotopic Space of the House Mouse in the Gradient of Anthropogenic Habitats
Authors: Balčiauskas Linas , Garbaras Andrius , Stirkė Vitalijus , Skipitytė Raminta , Balčiauskienė Laima
Published: January 2023

The house mouse (Mus musculus) is a most extensively distributed omnivorous rodent species, usually living in close association with humans. Its diet includes various vegetable matter, insects and any available human food. For the first time, we assessed the dietary niche of this species by the isotopic (δ15N and δ13C) compositions of animal hair samples in the gradient of habitats, ranging from natural to fully commensal. The main factors explaining the differences in the isotopic niche of the mice, being the proxy of their diet, were the season and the source of available food. Influence of the habitat was weak, while gender, age, body mass and body condition had no influence on the diet differences. We found that M. musculus dietary niches overlap between different habitats if mice have access to human food. Niches diverge when mice forage outdoors on natural food compared to farms where livestock feed is available. Compared to omnivorous bank vole (Clethrionomys glareolus) living synoptically, M. musculus has much wider dietary niche and consumes more foods of animal origin. Variability of the diet increases the ecological plasticity of this strongly commensal species and, together with behavioural and reproductive adaptability, allows irresistibly occupy various environments.
Compilation, Revision, and Annotation of DNA Barcodes of Marine Invertebrate Non-Indigenous Species (NIS) Occurring in European Coastal Regions
Authors: Lavrador Ana S. , Fontes João T. , Vieira Pedro E. , Costa Filipe O. , Duarte Sofia
Published: January 2023

The introduction of non-indigenous species (NIS) is one of the major threats to the integrity of European coastal ecosystems. DNA-based assessments have been increasingly adopted for monitoring NIS. However, the accuracy of DNA-based taxonomic assignments is largely dependent on the completion and reliability of DNA barcode reference libraries. As such, we aimed to compile and audit a DNA barcode reference library for marine invertebrate NIS occurring in Europe. To do so, we compiled a list of NIS using three databases: the European Alien Species Information Network (EASIN), the Information System on Aquatic Non-indigenous and Cryptogenic Species (AquaNIS), and the World Register of Introduced Marine Species (WRiMS). For each species, we retrieved the available cytochrome c oxidase subunit I (COI) mitochondrial gene sequences from the Barcode of Life Data System (BOLD) and used the Barcode, Audit & Grade System (BAGS) to check congruence between morphospecies names and Barcode Index Numbers (BINs). From the 1249 species compiled, approximately 42% had records on BOLD, among which 56% were discordant. We further analyzed these cases to determine the causes of the discordances and attributed additional annotation tags. Of the 622 discordant BINs, after revision, 35% were successfully solved, which increased the number of NIS detected in metabarcoding datasets from 12 to 16. However, a fair number of BINs remained discordant. Reliability of reference barcode records is particularly critical in the case of NIS, where erroneous identification may trigger action or inaction when not required.
Plant–Microbe Interactions under the Action of Heavy Metals and under the Conditions of Flooding
Authors: Gladkov Evgeny A. , Tereshonok Dmitry V. , Stepanova Anna Y. , Gladkova Olga V.
Published: January 2023

Heavy metals and flooding are among the primary environmental factors affecting plants and microorganisms. This review separately considers the impact of heavy metal contamination of soils on microorganisms and plants, on plant and microbial biodiversity, and on plant–microorganism interactions. The use of beneficial microorganisms is considered one of the most promising methods of increasing stress tolerance since plant-associated microbes reduce metal accumulation, so the review focuses on plant–microorganism interactions and their practical application in phytoremediation. The impact of flooding as an adverse environmental factor is outlined. It has been shown that plants and bacteria under flooding conditions primarily suffer from a lack of oxygen and activation of anaerobic microflora. The combined effects of heavy metals and flooding on microorganisms and plants are also discussed. In conclusion, we summarize the combined effects of heavy metals and flooding on microorganisms and plants.
Estimating Landslide Surface Displacement by Combining Low-Cost UAV Setup, Topographic Visualization and Computer Vision Techniques
Authors: Yordanov Vasil , Truong Quang Xuan , Brovelli Maria Antonia
Published: January 2023

Many techniques are available for estimating landslide surface displacements, whether from the ground, air- or spaceborne. In recent years, Unmanned Areal Vehicles have also been applied in the domain of landslide hazards, and have been able to provide high resolution and precise datasets for better understanding and predicting landslide movements and mitigating their impacts. In this study, we propose an approach for monitoring and detecting landslide surface movements using a low-cost lightweight consumer-grade UAV setup and a Red Relief Image Map (a topographic visualization technique) to normalize the input datasets and mitigate unfavourable illumination conditions that may affect the further implementation of Lucas–Kanade optical flow for the final displacement estimation. The effectiveness of the proposed approach in this study was demonstrated by applying it to the Ruinon landslide, Northern Italy, using the products of surveys carried out in the period 2019–2021. Our results show that the combination of different techniques can accurately and effectively estimate landslide movements over time and at different magnitudes, from a few centimetres to more than several tens of meters. The method applied is shown to be very computationally efficient while yielding precise outputs. At the same time, the use of only free and open-source software allows its straightforward adaptation and modification for other case studies. The approach can potentially be used for monitoring and studying landslide behaviour in areas where no permanent monitoring solutions are present.
Robust Variable Selection with Exponential Squared Loss for the Spatial Single-Index Varying-Coefficient Model
Authors: Wang Yezi , Wang Zhijian , Song Yunquan
Published: January 2023

As spatial correlation and heterogeneity often coincide in the data, we propose a spatial single-index varying-coefficient model. For the model, in this paper, a robust variable selection method based on spline estimation and exponential squared loss is offered to estimate parameters and identify significant variables. We establish the theoretical properties under some regularity conditions. A block coordinate descent (BCD) algorithm with the concave–convex process (CCCP) is composed uniquely for solving algorithms. Simulations show that our methods perform well even though observations are noisy or the estimated spatial mass matrix is inaccurate.
Protograph Designing of P-LDPC Codes via M3 Method
Authors: Song Dan , Miao Meiyuan , Wang Lin
Published: January 2023

Recently, a mesh model-based merging (M3) method and four basic graph models were proposed to construct the double protograph low-density parity-check (P-LDPC) code pair of the joint source channel coding (JSCC). Designing the protograph (mother code) of the P-LDPC code with both a good waterfall region and lower error floor is a challenge, and few works have existed until now. In this paper, the single P-LDPC code is improved to further verify the availability of the M3 method, and its structure is different from the channel code in the JSCC. This construction technique yields a family of new channel codes with lower power consumption and higher reliability. The structured design and better performance demonstrate that the proposed code is hardware-friendly.
Impact of Major Backgrounds on Student Learning Achievement: A Case Study for Java Programming Course
Authors: Zhu Xiaohui , Yue Yong , Chen Surong
Published: January 2023

Due to the rapidly increasing number of students at universities in recent years, universities may arrange students from different majors in the same class, which may bring several challenges in teaching and learning for students and teachers, such as poor class experience, less class discussion and more workload for teachers. In this paper, we investigate the learning achievements of students with different major backgrounds based on a large-size course of Introduction to Java Programming. Approaches of difficulty index, incrimination index, failure rate, median average mark, average mark and standard deviation are used to evaluate students’ learning achievements based on students’ coursework assignments, continuous assessment and the final exam. Results show that major backgrounds could significantly affect learning achievements even in the same teaching and learning environment. To achieve a better learning experience and performance, we finally divided the original module into two separate modules for students with different major backgrounds.
Long-Wavelength Luminescence of InSb Quantum Dots in Type II Broken-Gap Heterostructure
Authors: Moiseev Konstantin , Ivanov Eduard , Parkhomenko Yana
Published: January 2023

The features of the electroluminescence spectra of narrow-gap type II InAs/InSb/InAs heterostructures containing a single layer of InSb quantum dots placed into the p-n-InAs junction were studied. The luminescent properties of the heterostructures under a forward and reverse bias in the temperature range of 77–300 K were investigated as a function of the surface density of nano-objects buried in the narrow-gap matrix. When applying the reverse bias to the heterostructures under study, the suppression of negative interband luminescence and the dominance of interface recombination transitions at the InSb/InAs type II heterojunction were observed at room temperature. The radiation, which corresponded to recombination transitions involving localized electron-hole states of the InSb quantum dots, was revealed and recorded at low temperatures.
Design of a Low-Cost Measurement Module for the Acquisition of Analogue Voltage Signals
Authors: Glowinski Sebastian , Pecolt Sebastian , Błażejewski Andrzej , Sobieraj Michał
Published: January 2023

The aim of this work was to design and program a low-cost universal multichannel measurement card from scratch. The constructed device has analog inputs with the possibility of using them as differential inputs. This makes it possible to measure the analog signals for most of the available sensors. Thus, universality of the device is achieved. Simultaneously, the main assumption of the project and its novelty was to develop a measurement module. It is characterized by high measurement parameters, comparable to commercial products available on the market, with a very low production cost. The usability and assumed features of the measurement module were verified and tested using a functional generator and constructed test stand. During the tests, a sampling rate of at least 250 kS/s and a resolution of at least 14 bit were used. The module enables the acquisition of analog signals with voltages in the range of ±10 V and digital signals in the transistor–transistor logic (TTL) 5 V standard with a frequency of at least 250 kS/s. In addition, our device can be controlled via a computer, and data can be downloaded via the USB interface. It has 16 input channels with the possibility of differential measurements. The proposed solution is several times cheaper than commercial solutions while maintaining comparable parameters, as shown in the conclusion of the work.
D-STGCN: Dynamic Pedestrian Trajectory Prediction Using Spatio-Temporal Graph Convolutional Networks
Authors: Sighencea Bogdan Ilie , Stanciu Ion Rareș , Căleanu Cătălin Daniel
Published: January 2023

Predicting pedestrian trajectories in urban scenarios is a challenging task that has a wide range of applications, from video surveillance to autonomous driving. The task is difficult since pedestrian behavior is affected by both their individual path’s history, their interactions with others, and with the environment. For predicting pedestrian trajectories, an attention-based interaction-aware spatio-temporal graph neural network is introduced. This paper introduces an approach based on two components: a spatial graph neural network (SGNN) for interaction-modeling and a temporal graph neural network (TGNN) for motion feature extraction. The SGNN uses an attention method to periodically collect spatial interactions between all pedestrians. The TGNN employs an attention method as well, this time to collect each pedestrian’s temporal motion pattern. Finally, in the graph’s temporal dimension characteristics, a time-extrapolator convolutional neural network (CNN) is employed to predict the trajectories. Using a lower variable size (data and model) and a better accuracy, the proposed method is compact, efficient, and better than the one represented by the social-STGCNN. Moreover, using three video surveillance datasets (ETH, UCY, and SDD), D-STGCN achieves better experimental results considering the average displacement error (ADE) and final displacement error (FDE) metrics, in addition to predicting more social trajectories.
Compact Microstrip Line to Rectangular Waveguide Transition Using Corrugated Substrate Integrated Waveguide
Authors: Liu Zihao , Yao Yuan , Cheng Xiaohe , Li Qi
Published: January 2023

To meet the packaging requirements of terahertz (THz) communication systems, a microstrip line (MSL) to rectangular waveguide (RWG) transition is proposed in this paper. In the transition, the MSL is connected to the corrugated substrate integrated waveguide (CSIW) by a tapered MSL for quasi-TEM to TE10-like mode conversion on substrate, which requires no via holes or shaped dielectric, and is easy to process in THz bands. Then, the CSIW is straightly connected to the RWG transformer and converted to standard RWG, resulting in a compact structure. The working principle of the proposed transition is analyzed, and the influence of several important parameters on the S-parameters of the transition is discussed. A single transition is designed for the 325–500 GHz operation, the S11 better than −14.5 dB and S21 better than −1.03 dB have been achieved in the entire frequency band.
Analysis of Individual User Data Rate in a TDMA-RIS-NOMA Downlink System: Beyond the Limitation of Conventional NOMA
Authors: Tiwari Sourabh , Sengupta Joydeep , Bokde Neeraj Dhanraj
Published: January 2023

Non-orthogonal multiple access (NOMA) is playing a pivotal role in 5G technology and has the potential to be useful in future developments beyond 5G. Although the effectiveness of NOMA has largely been explored in the sum throughput maximization, the identification of individual user data rate (IDR) still remained an unexplored area. Previously, it has been shown that reconfigurable intelligent surfaces (RIS) can lead to an overall improvement in the data rate by enhancing the effective channel gain of the downlink NOMA system. When time division multiple access (TDMA) is clubbed with multiple RISs in a distributed RIS-assisted NOMA (TDMA-RIS-NOMA) downlink system, a point-to-point communication model is created between access point-to-RIS-to-user device. Due to this point-to-point communication model, optimization of the phase shifts provided by meta-atoms of each RIS is facilitated. The optimized phase shifts of meta-atoms maximize the equivalent channel gain between the access point to the user. In this scenario, the channel becomes saturated and signal-to-interference plus noise ratio (SINR) becomes a function of power coefficients only. In this study, the power coefficients are calculated to maximize the SINR of each user belonging to a NOMA cluster using a geometric progression-based power allocation method such that IDR reaches its upper bound. These observations are also verified using the recently published magic matrix-based power allocation method. There are two observations from this study: (i) the IDR is better in the case of the TDMA-RIS-NOMA downlink system than using downlink NOMA alone and (ii) irrespective of the number of meta-atoms and total cluster power, the upper bound of IDR cannot be increased beyond a certain limit for all users except the highest channel gain user. Because of the restricted upper bound for IDR, we suggest that the RIS-assisted downlink TDMA-NOMA system is more suitable for IoT applications, where minimum IDR can also suffice
A Novel Dynamic Transmission Power of Cluster Heads Based Clustering Scheme
Authors: Nie Mengchu , Huang Pingmu , Zeng Jie , Lu Yueming , Zhang Tao , Lv Tiejun
Published: January 2023

Clustering methods are promising tools for ensuring the network scalability and maintainability of large-scale flying ad hoc networks (FANETs). However, due to the high mobility and limited energy resources of unmanned aerial vehicles (UAVs), it is difficult to maintain the network reliability and extend the network life of FANETs. In this paper, a new K-means algorithm is developed, and a dynamic transmission power of the cluster heads based clustering (DTPCH-C) scheme is proposed. The goal of this scheme is presented for FANETs to improve the reliability and lifetime of FANETs. Firstly, the optimal number of clusters is calculated and the initial UAV clusters are set up by a K-means algorithm. Then, using a weighted clustering algorithm, the adaptive node degree, the node energy and the distance from the cluster head are weighted and summed for the cluster head election. In the process of inter-cluster communication, the cluster head adjusts its transmit power in real-time through meshing and mobile prediction, thus saving the energy consumption and improving the network lifetime. The proposed DTPCH-C simultaneously optimizes the cluster number, the cluster head energy consumption, the selected cluster head, and the cluster maintenance process. The simulation results show that compared with traditional clustering methods, the proposed DTPCH-C has obvious advantages in terms of the network reliability, network life, and energy consumption.
Performance Characteristic Analysis of Metallic and Non-Metallic Oxide Nanofluids for a Compound Parabolic Collector: Improvement of Renewable Energy Technologies in Buildings
Authors: Kaleem Muhammad , Ali Muzaffar , Sheikh Nadeem , Akhtar Javed , Tariq Rasikh , Krzywanski Jaroslaw
Published: January 2023

The building sector is targeting net-zero emissions through the integration of renewable energy technologies, especially for space cooling and heating applications. In this regard, the use of solar thermal concentrating collectors is of vital importance. The performance of these collectors increases by using an efficient fluid such as a nanofluid due to their high thermal conductivity. This research addresses the preparation, stability analysis, and characterisation of metallic and non-metallic oxide nanofluids and their experimental analysis in a compound parabolic collector (CPC) system. Five different combinations of nanofluids are used with different volumetric concentrations (0.025%, 0.05%, and 0.075%) including multi-wall carbon nanotube with water (MWCNT–H2O), multi-wall carbon nanotube with ethylene glycol (MWCNT–EG), aluminium oxide with water (Al2O3–H2O), aluminium oxide with ethylene glycol (Al2O3–EG), and magnesium oxide with ethylene glycol (MgO–EG). The prepared nanofluids are characterised in terms of thermal conductivity and viscosity. Detailed experimentation is performed to investigate the CPC system integrated with the nanofluids. The results obtained from the detailed characterisation of the MWCNT–H2O nanofluid showed that the nanofluids have a 37.17% better thermal conductivity than distilled water as a primary fluid, and the MWCNT–EG nanofluid has demonstrated an increase in viscosity by 8.5% compared to ethylene glycol (EG). The experimental analysis revealed that the thermal efficiency of the collector integrated with the MWCNT–H2O nanofluid is increased by 33% compared to water. Meanwhile, the thermal efficiency of the collector with MWCNT–EG was increased by 24.9% compared to EG. Moreover, a comparative analysis among metallic nanofluids was also performed, i.e., Al2O3–H2O, Al2O3–EG, and MgO–EG. In each case, the thermal efficiency of the collector was recorded, which was greater than the base fluid by percentages of 29.4%, 22.29%, and 23.1%, respectively. The efficiency of non-metallic nanofluids is better than metallic nanofluids by 7.7%. From the obtained results, it can be concluded that the CPC system performed best with MWCNT–H2O compared to any other combination of nanofluids.
An Efficient Variable Step Solar Maximum Power Point Tracking Algorithm
Authors: Meng Yang , Chen Zunliang , Cheng Hui , Wang Enpu , Tan Baohua
Published: January 2023

The classic Photovoltaic system maximum power point tracking technique cannot concurrently take into account the dynamic response speed and steady-state accuracy when the light intensity changes. To address this issue, a new composite variable step MPPT control algorithm is developed in this study. Based on the three-stage variable step incremental conductance method, the algorithm adds the Kalman filtering algorithm to pre-process the photovoltaic cells output signal, and uses a new calculation approach to adjust the variable step coefficient. As a result, the perturbation step can be automatically modified according to changes in the external environment, which resolves the issues with poor dynamic reaction speed when the classic variable step algorithm started and the light changed. Compared to conventional MPPT control algorithms, the improved MPPT strategy can be easily realized using a hardware control system since it has a simplified control logic and requires less data to be calculated. In this study, the hardware circuit of the enhanced MPPT control algorithm is built using the ESP32 as the primary control chip. This chip can be utilized in conjunction with the Internet of Things to enable remote monitoring of the solar power system’s operational state. According to test results, the algorithm can instantly detect the maximum power point in all lighting circumstances with tracking accuracy of up to 99.6% and a reduction in dynamic response time of the system to 0.12 s.
A Hybrid Analytical Model for the Electromagnetic Analysis of Surface-Mounted Permanent-Magnet Machines Considering Stator Saturation
Authors: Lu Wenbiao , Zhu Jie , Fang Youtong , Pfister Pierre-Daniel
Published: January 2023

This article presents the process of building a hybrid analytical model (HAM) for surface-mounted permanent-magnet machines. The HAM couples a reluctance network (RN) model in the stator region with a magnetic scalar potential analytical model in the air gap and magnets regions. This hybrid model can deal with the slotting effect with straight teeth, and takes magnetic saturation into account in the stator iron material using the RN model. It is calculated under open-circuit and loaded conditions. The magnetic flux density, flux linkage, back electromotive force (EMF), and torque of the machines are also calculated. This hybrid model is compared with the subdomain method. It is also compared with the finite element method (FEM) both in terms of the size of the matrix that needs to be calculated and in terms of the torque error. We analyzed this method for two surface-mounted permanent-magnet machines, one with a symmetry factor of four and another with a symmetry factor of three. In both cases, HAM reduced the size of the matrix that needed to be solved compared to FEM. In the machine with a symmetry factor of three, when the matrix size of both FEM and HAM was around 1700 × 1700, the torque error of FEM was 2.62% compared to the high-mesh-density FEM simulation, while the torque error of HAM was only 0.17% compared to the same simulation. HAM also had significant advantages over the subdomain method, as it reduced the torque error from 16.8% to 0.08% in the case of high magnetic saturation. The HAM can, hence, play a significant role in the design and optimization of surface-mounted permanent-magnet machines, especially in cases where magnetic saturation is present.
A GIS-Based Multidimensional Evaluation Method for Solar Energy Potential in Shanxi Province, China
Authors: Cui Liang , Zhang Junrui , Su Yongyong , Li Siyuan
Published: January 2023

Solar energy is considered one of the most hopeful alternative sources to avoiding dependence on fossil fuels, and it does not cause any air pollution. GIS-based solar energy potential evaluation is mainly focused on regional scale; further, more solar energy potential evaluation with building scale is calculated through observation data and mathematical model. Therefore, in this paper, a GIS-based joint solar energy potential evaluation is developed to evaluate the distributed photovoltaic potential and centralized photovoltaic potential. Shanxi province in China, which has abundant coal resources, is used as the study area. The raster grid scale is used as the minimum research scale, which could not only deal with the distributed photovoltaic potential but could also calculate the centralized photovoltaic potential. The obtained results indicate that the developed method could effectively deal with problems associated with the distributed photovoltaic potential and centralized photovoltaic potential in the raster grid scale.
Analysis and Comparison of Permanent Magnet Synchronous Motors According to Rotor Type under the Same Design Specifications
Authors: Jung Woo-Sung , Lee Hoon-Ki , Lee Young-Keun , Kim Su-Min , Lee Jeong-In , Choi Jang-Young
Published: January 2023

A surface-mounted permanent magnet synchronous motor (SPMSM) is an electric motor with a simple magnetic circuit design, fast responsiveness, linear torque–current characteristics, speed–voltage characteristics, and constant operating speed. SPMSMs use only magnetic torque; however, interior PMSMs (IPMSMs) have high power densities because they can use reluctance torque. In addition, when flux-weakening control is used, the operating range is wide compared with the SPMSM. This study presents a comparative analysis of the characteristics of SPMSM and bar-type IPMSM. Characteristic analyses are performed by setting the same stator shape, rated speed, number of turns, winding specifications, voltage limit, and magnet usage in a pole/slot combination of six poles and 27 slots. Next, we compare the no-load back electromotive force, cogging torque, and loss characteristics, and perform a characteristic analysis of each model while satisfying the design specifications. No-load and load tests are performed using a back-to-back system. The results of the analysis and experimental results are in good agreement, and the reliability of the analysis results is guaranteed. The SPMSM is approximately 8.5% superior to the IPMSM in terms of core loss, and the eddy current loss is greater than that of the IPMSM.
Application of the Generalized Normal Distribution Optimization Algorithm to the Optimal Selection of Conductors in Three-Phase Asymmetric Distribution Networks
Authors: Vega-Forero Julián Alejandro , Ramos-Castellanos Jairo Stiven , Montoya Oscar Danilo
Published: January 2023

This article addresses the problem of the optimal selection of conductors in asymmetric three-phase distribution networks from a combinatorial optimization perspective, where the problem is represented by a mixed-integer nonlinear programming (MINLP) model that is solved using a master-slave (MS) optimization strategy. In the master stage, an optimization model known as the generalized normal distribution optimization (GNDO) algorithm is proposed with an improvement stage based on the vortex search algorithm (VSA). Both algorithms work with discrete-continuous coding that allows us to represent the locations and gauges of the different conductors in the electrical distribution system. For the slave stage, the backward/forward sweep (BFS) algorithm is adopted. The numerical results obtained in the IEEE 8- and 27-bus systems demonstrate the applicability, efficiency, and robustness of this optimization methodology, which, in comparison with current methodologies such as the Newton metaheuristic algorithm, shows significant improvements in the values of the objective function regarding the balanced demand scenario for the 8- and 27-bus test systems (i.e., 10.30% and 1.40% respectively). On the other hand, for the unbalanced demand scenario, a reduction of 1.43% was obtained in the 27-bus system, whereas no improvement was obtained in the 8-bus grid. An additional simulation scenario associated with the three-phase version of the IEEE33-bus grid under unbalanced operating conditions is analyzed considering three possible load profiles. The first load profile corresponds to the yearly operation under the peak load conduction, the second case is associated with a daily demand profile, and the third operation case discretizes the demand profile in three periods with lengths of 1000 h, 6760 h, and 1000 h with demands of 100%, 60% and 30% of the peak load case. Numerical results show the strong influence of the expected demand behavior on the plan’s total costs, with variations upper than USD/year 260,000.00 between different cases of analysis. All implementations were developed in the MATLAB® programming environment.
Triboelectric Nanogenerator-Based Vibration Energy Harvester Using Bio-Inspired Microparticles and Mechanical Motion Amplification
Authors: Satpute Nitin , Iwaniec Marek , Iwaniec Joanna , Mhetre Manisha , Arawade Swapnil , Jabade Siddharth , Banaś Marian
Published: January 2023

In this work, the novel design of a sliding mode TriboElectric Nano Generator (TENG)—which can utilize vibration amplitude of a few hundred microns to generate useful electric power—is proposed for the first time. Innovative design features include motion modification to amplify relative displacement of the TENG electrodes and use of biological material-based micron-sized powder at one of the electrodes to increase power output. The sliding mode TENG is designed and fabricated with use of polyurethane foam charged with the biological material micropowder and PolyTetraFluoroEthylene (PTFE) strips as the electrodes. Experimentations on the prototype within frequency range of 0.5–6 Hz ensured peak power density of 0.262 mW/m2, corresponding to the TENG electrode size. Further numerical simulation is performed with the theoretical model to investigate the influence of various design parameters on the electric power generated by the TENG. Lastly, application of the proposed TENG is demonstrated in a wearable device as an in-shoe sensor. Conceptual arrangement of the proposed in-shoe sensor is presented, and numerical simulations are performed to demonstrate that the real size application can deliver peak power density of 0.747 mW/m2 and TENG; the voltage will accurately represent foot vertical force for various foot force patterns.
Biofuel Production Using Cultivated Algae: Technologies, Economics, and Its Environmental Impacts
Authors: Alazaiza Motasem Y. D. , Albahnasawi Ahmed , Al Maskari Tahra , Abujazar Mohammed Shadi S. , Bashir Mohammed J. K. , Nassani Dia Eddin , Abu Amr Salem S.
Published: January 2023

The process of looking for alternative energy sources is driven by the increasing demand for energy and environmental contamination caused by using fossil fuels. Recent investigations reported the efficiency of microalgae for biofuel production due to its low cost of production, high speed of growth, and ability to grow in harsh environments. In addition, many microalgae are photosynthetic, consuming CO2 and solar light to grow in biomass and providing a promising bioenergy source. This review presents the recent advances in the application of microalgae for biofuel production. In addition, cultivation and harvesting systems and environmental factors that affect microalgae cultivation for biofuel production have also been discussed. Moreover, lipid extraction and conversion technologies to biofuel are presented. The mixotrophic cultivation strategy is promising as it combines the advantages of heterotrophy and autotrophy. Green harvesting methods such as using bio-coagulants and flocculants are promising technologies to reduce the cost of microalgal biomass production. In the future, more investigations into co-cultivation systems, new green harvesting methods, high lipids extraction methods, and the optimization of lipid extraction and converting processes should be implemented to increase the sustainability of microalgae application for biofuel production.
A Review of the Energy Policy and Energy Transition Objectives for 2040 in the Canary Islands (Spain)
Authors: Escamilla-Fraile Santiago , Ramos-Real Francisco J. , Calero-García Francisco J. , González-Díaz Benjamín
Published: January 2023

The objective of this work is to analyze the possibility of compliance with the objectives committed to by the Canary Islands authorities, which aim to reach a completely decarbonized economy by 2040, meaning ten years earlier than the entire EU. Since historically, energy planning in the Canary Islands did not achieve its objectives by far, we will first identify the historical obstacles which had prevented the achievement of this planification, to later highlight the main differences between the energy transition foreseen by the current planning instruments of the government of the Canary Islands and the expected evolution of the energy transition of the archipelago. Beyond this point, and, within the frame of energy governance, we will understand how the root of this failure lies in planning instruments developed hierarchically, without including the view of the different stakeholders involved in the process. The final goal, after identifying the main barriers faced by the energy transition in the Canary Islands, is to provide a set of recommendations contributing to supporting a successful energy transition for the archipelago.
Orchard Net Covers Improve Resistance to Cherry Cracking Disorder
Authors: Gonçalves Berta , Silva Vânia , Bacelar Eunice , Guedes Francisco , Ribeiro Carlos , Silva Ana Paula , Pereira Sandra
Published: January 2023

Orchard net cover improves plant physiology, yield and fruit quality, pest and disease control, and anticipates fruit ripening. Moreover, this crop technology has been used to reduce natural cherry cracking (NCC). This is a serious physiological disorder that cracks the epidermis, the hypodermis, and the storage parenchyma layers of the fruit due to rainfall events near the harvest and it is related to low fruit osmotic potential and/or high fruit water permeability. This work aims to study the effect of orchard net cover on sweet cherry trees, cv. Early Bigi, in two harvesting years (2019 and 2021). The NCC, the induced cracking index (CI), and the cracking type incidence were determined. In addition, epicuticular and intra-cuticular wax content, biometric and physicochemical parameters were also evaluated. Net cover reduced the natural cracking index by 40%. High fruit weight values were observed in covered trees comparing to the control ones, with increases of 45% and 13%, in 2019 and 2021, respectively. A positive correlation was observed between CI and total soluble solids and a negative correlation between CI and wax content. Therefore, with forecasts of worsening heavy precipitation events near harvest, protecting cherry trees with nets will increase resistance to fruit cracking.
‘Superfoods’: Reliability of the Information for Consumers Available on the Web
Authors: Cobos Ángel , Díaz Olga
Published: January 2023

The term ‘superfoods’, used frequently with marketing purposes, is usually associated with foodstuffs with beneficial health properties. ‘Superfoods’ appears in many information sources, including digital media. The information they provide is easily accessible for consumers through Internet search engines. The objective of this work is to investigate the data that web pages offer to consumers and their accuracy according to current scientific knowledge. The two main search engines were utilized for English language websites search, introducing the term ‘superfoods’. In total, 124 search results were found. After applying the selection criteria, 45 web pages were studied. A total of 136 foods were considered as ‘superfoods’ by sites; 10 of them (kale, spinach, salmon, blueberries, avocado, chia, walnuts, beans, fermented milks and garlic) were mentioned on at least 15 sites. Nutritional and healthy properties displayed on sites were compared to scientific information. In conclusion, websites present the information in a very simplified manner and it is generally not wrong. However, they should offer to consumers comprehensible information without raising false expectations regarding health benefits. In any case, ‘superfoods’ consumption can have salutary effects as part of a balanced diet.
Visual Detection of Water Content Range of Seabuckthorn Fruit Based on Transfer Deep Learning
Authors: Xu Yu , Kou Jinmei , Zhang Qian , Tan Shudan , Zhu Lichun , Geng Zhihua , Yang Xuhai
Published: January 2023

To realize the classification of sea buckthorn fruits with different water content ranges, a convolution neural network (CNN) detection model of sea buckthorn fruit water content ranges was constructed. In total, 900 images of seabuckthorn fruits with different water contents were collected from 720 seabuckthorn fruits. Eight classic network models based on deep learning were used as feature extraction for transfer learning. A total of 180 images were randomly selected from the images of various water content ranges for testing. Finally, the identification accuracy of the network model for the water content range of seabuckthorn fruit was 98.69%, and the accuracy on the test set was 99.4%. The program in this study can quickly identify the moisture content range of seabuckthorn fruit by collecting images of the appearance and morphology changes during the drying process of seabuckthorn fruit. The model has a good detection effect for seabuckthorn fruits with different moisture content ranges with slight changes in characteristics. The migration deep learning can also be used to detect the moisture content range of other agricultural products, providing technical support for the rapid nondestructive testing of moisture contents of agricultural products.
Characterization of Growth Performance, Pork Quality, and Body Composition in Mangalica Pigs
Authors: Roberts Morgan M. , Perkins Stephanie D. , Anderson Brian L. , Sawyer Jason T. , Brandebourg Terry D.
Published: January 2023

European heritage breeds, such as the Blonde (B), Red (R), and Swallow-bellied (SB) Mangalica pig, display an extreme propensity to fatten and are reputed to produce superior quality pork. This suggests that Mangalica pork should command a higher price, and the Mangalica is a candidate breed to target niche markets within the United States. Our objectives were to test this hypothesis by (1) directly comparing growth performance and carcass merit of purebred Yorkshire (Y), B, R, and SB Mangalica pigs to identify the best breed for adoption, and (2) comparing indices of pork quality in purebred R, Y, and crossbred (R × Y) pigs to determine if crossbreeding represented a viable alternative to the adoption of purebred Mangalica. Daily feed intake, average daily gain (ADG), and feed efficiency were highest in Y and lowest in SB pigs with B and R ranked intermediately (p < 0.001). Backfat thickness was greatest in B and lowest in Y with R and SB ranked intermediately (p < 0.001). Marbling score was greatest in R pigs and lowest in Y pigs with B and SB ranked intermediately (p < 0.01). In contrast, loin eye area (LEA) was greatest in Y pigs compared to B, R, and SB (p < 0.001). Indices of meat quality were then compared in R, R × Y, and Y pigs. Backfat thickness and marbling scores were greater in R than R × Y and Y pigs (p < 0.001) while LEA was greater in Y than R × Y and R pigs (p < 0.001). Loin and ham ultimate pH, color, and firmness scores were significantly greater in R than R × Y or Y pigs (p < 0.05). Meanwhile, cook loss was significantly less in R than Y pigs (p < 0.007) while Warner-Bratzler Shear Force (WBS) was not different in chops between groups (p < 0.11). These data indicate that though Mangalica exhibit poorer growth performance, Mangalica pork exhibits superior pork quality attributes, suggesting that higher price points for Mangalica pork in niche markets are justified.
Stability Properties of Multi-Term Fractional-Differential Equations
Authors: Brandibur Oana , Kaslik Éva
Published: January 2023

Necessary and sufficient stability and instability conditions are reviewed and extended for multi-term homogeneous linear fractional differential equations with Caputo derivatives and constant coefficients. A comprehensive review of the state of the art regarding the stability analysis of two-term and three-term fractional-order differential equations is provided, which is then extended to the case of four-term fractional-order differential equations. The stability and instability properties are characterized with respect to the coefficients of the multi-term fractional differential equations, leading to both fractional-order-dependent and fractional-order-independent characterizations. In the general case, fractional-order-independent stability and instability properties are described for fractional-order differential equations with an arbitrary number of fractional derivatives.
The Adaptive Evolution in the Fall Armyworm Spodoptera frugiperda (Lepidoptera: Noctuidae) Revealed by the Diversity of Larval Gut Bacteria
Authors: Wang Yan-Ping , Liu Xu , Yi Chun-Yan , Chen Xing-Yu , Liu Chang-Hua , Zhang Cui-Cui , Chen Qing-Dong , Chen Song , Liu Hong-Ling , Pu De-Qiang
Published: January 2023

Insect gut microbes have important roles in host feeding, digestion, immunity, development, and coevolution with pests. The fall armyworm, Spodoptera frugiperda (Smith, 1797), is a major migratory agricultural pest worldwide. The effects of host plant on the pest’s gut bacteria remain to be investigated to better understand their coevolution. In this study, differences in the gut bacterial communities were examined for the fifth and sixth instar larvae of S. frugiperda fed on leaves of different host plants (corn, sorghum, highland barley, and citrus). The 16S rDNA full-length amplification and sequencing method was used to determine the abundance and diversity of gut bacteria in larval intestines. The highest richness and diversity of gut bacteria were in corn-fed fifth instar larvae, whereas in sixth instar larvae, the richness and diversity were higher when larvae were fed by other crops. Firmicutes and Proteobacteria were dominant phyla in gut bacterial communities of fifth and sixth instar larvae. According to the LDA Effect Size (LEfSe) analysis, the host plants had important effects on the structure of gut bacterial communities in S. frugiperda. In the PICRUSt2 analysis, most predicted functional categories were associated with metabolism. Thus, the host plant species attacked by S. frugiperda larvae can affect their gut bacterial communities, and such changes are likely important in the adaptive evolution of S. frugiperda to host plants.