bluuebunny/crossref_metadata_2025 huggingface dataset:
Antifrictional Effects of Group IVB Elements Deposited as Nanolayers on Anodic Coatings
Authors: Matijošius Tadas , Stalnionis Giedrius , Bikulčius Gedvidas , Jankauskas Sigitas , Staišiūnas Laurynas , Asadauskas Svajus Joseph
Published: January 2023

The utilization of anodized aluminum (Al) components would contribute greatly to combat against dry friction if good tribological properties could be attained. Despite its hardness, the wear rate of anodic coatings presents a major problem in many applications, including automotive, aerospace and high-tech industries. Recently, nanolayers of Ti demonstrated high tribological effectiveness and unusually low dry friction on anodic coatings. However, few researchers focus on the tribological characterization of nanolayers of other elements. In this study, nanolayers of Ti, Zr, Hf, Cu, Cr, Nb and Sn were deposited on anodized 1050 and 6082 alloys by magnetron sputtering and Atomic Layer Deposition. Major attention was devoted to surface roughness and hardness measurements, because of their importance for static friction. The results showed that structural, chemical and other intrinsic properties of nanolayers of Group IVB elements in many cases led to significant friction reduction, when compared to those of Cu, Cr and Hf. Nanolayers of 15 nm to 75 nm thicknesses appeared most effective tribologically, while 180 nm or thicker layers progressively lost their ability to sustain low dynamic friction. Deposition of nanoscale structures could provide advantages for the anodized Al industry in protection against incidental friction and wear.
Insight on Corrosion Prevention of C1018 in 1.0 M Hydrochloric Acid Using Liquid Smoke of Rice Husk Ash: Electrochemical, Surface Analysis, and Deep Learning Studies
Authors: Kaban Agus Paul Setiawan , Soedarsono Johny Wahyuadi , Mayangsari Wahyu , Anwar Mochammad Syaiful , Maksum Ahmad , Ridhova Aga , Riastuti Rini
Published: January 2023

This work reports the anti-corrosion behavior of liquid smoke from rice husk ash to unveil the contribution of its active compounds in 1 M HCl solution. In this study, the developed methodology to test, analyze, and model the novel type of green corrosion inhibitor for C1018 was characterized using Electrochemical impedance spectroscopy (EIS), Potentiodynamic polarization, and deep learning methods. The inhibitor structure was characterized by Fourier transform infrared analysis (FTIR) and Ultraviolet–visible spectroscopy (UV-Vis). The surface characterization of mild steel immersed in blank and 80 ppm solution inhibitor was performed using Atomic force microscopy (AFM) analysis. The corrosion test results show that the inhibitor is considered a mixed-type inhibitor to achieve the optimum inhibition of 80 ppm at 323 K, reaching up to 99% inhibition efficiency. The AFM results show a smoother surface given a lower skewness parameter at −0.5190 nm on the treated mild steel. The artificial neural network demonstrates the lower overfitting on the inhibited steel, a higher accuracy prediction of 81.08%, and a lower loss rate of 0.6001 to model the relationship between the EIS and Potentiodynamic polarization and the evolution of the passive layer on the treated mild steel. The experiment agrees well with the prediction result to model the adsorbed inhibitor. The work can be used as a guideline to pave the way for subsequent applicability in developing green corrosion inhibitors based on experimental and artificial intelligence approaches.
Influence of Vanadium and Niobium Carbide Particles on the Mechanical, Microstructural, and Physical Properties of AA6061 Aluminum-Based Mono- and Hybrid Composite Using FSP
Authors: Abushanab Waheed , Moustafa Essam , Goda Emad , Ghandourah Emad , Taha Mohammed , Mosleh Ahmed
Published: January 2023

The ceramic particle reinforcement process is one of the most utilized techniques to enhance the metal surface. The current investigation uses vanadium and niobium carbides to reinforce the AA6061 alloy using the friction stir process (FSP). The mechanical properties are evaluated using ultrasound and conventional compressive tests; furthermore, the microstructure and physical properties are carried out to show the effect of single and hybrid additives of ceramic particles on the surface composites of aluminum alloy. Scanning electron microscopy (SEM) is utilized to examine the presence and distribution of the reinforcement VC and NbC particles inside the composite matrix. The microstructure examination revealed a good dispersion and homogenized distribution of the reinforcement particles. The results indicated that reinforcement particles significantly enhanced the mechanical and physical properties. The VC and NbC particles play an important role in improving the surface hardening behavior and grain refinement by restricting grain growth during the dynamic recrystallization process in the FSP action. The hybrid composited AA6061/NbC + VC recorded an increase in the compressive stress, yield stress, and hardness of 25%, 20%, and 50%, respectively, relative to the base metal, in addition to a 55% decrease in the coefficient of the thermal expansion (CTE) was reported. Moreover, the hybrid composite AA6061/NbC + VC significantly affected the corrosion rate with a reduction of 45%.
Diatomite and Glucose Bioresources Jointly Synthesizing Anode/Cathode Materials for Lithium-Ion Batteries
Authors: Chen Yun , Jiang Bo , Zhao Yue , Liu Hongbin , Ma Tingli
Published: January 2023

Large-scale popularization and application make the role of lithium-ion batteries increasingly prominent and the requirements for energy density have increased significantly. The silicon-based material has ultra-high specific capacity, which is expected in the construction of next-generation high specific-energy batteries. In order to improve conductivity and maintain structural stability of the silicon anode in application, and further improve the energy density of the lithium-ion battery, we designed and synthesized carbon-coated porous silicon structures using diatomite and polysaccharides as raw materials. The electrode materials constructed of diatomite exhibit porous structures, which can provide fast transport channels for lithium ions, and effectively release the stress caused by volume expansion during cycling. At the same time, the electrical conductivity of the materials has been significantly improved by compounding with biomass carbon, so the batteries exhibit stable electrochemical performance. We systematically studied the effect of different contents of biomass carbon on the Li2MnSiO4/C cathode, and the results showed that the carbon content of 20% exhibited the best electrochemical performance. At a current density of 0.05C, the capacity close to 150 mAh g−1 can be obtained after 50 cycles, which is more than three times that of without biomass carbon. The silicon-based anode composited with biomass carbon also showed excellent cycle stability; it could still have a specific capacity of 1063 mAh g−1 after 100 cycles at the current density of 0.1 A g−1. This study sheds light on a way of synthesizing high specific-capacity electrode materials of the lithium-ion battery from natural raw materials.
Corrosion Behavior of Selective Laser Melted Ti-6Al-4V in 0.1 mol/L NaOH Solution
Authors: Huang Lei , Zheng Shunli , Qin Yue , Han Jianyang , Qiao Yanxin , Chen Jian
Published: January 2023

In this work, the corrosion behavior of a Ti-6Al-4V alloy prepared using selective laser melting (SLM) in a 0.1 mol/L NaOH solution was studied by means of corrosion electrochemical testing, X-ray diffraction analysis and X-ray photoelectron spectroscopy (XPS), and its corrosion process was compared with the commercially forged Ti-6Al-4V alloy. The results show that the corrosion resistance of the commercially forged Ti-6Al-4V alloy was higher than the SLMed Ti-6Al-4V alloy, which is closely correlated with the presence of more active spots on the alloy surface and more defects in the passive films.
Effect of Coating Thickness on the Atomic Oxygen Resistance of Siloxane Coatings Synthesized by Plasma Polymerization Deposition Technique
Authors: Zhao Lin , Leng Xuesong , Bai Bowen , Zhao Rui , Cai Zeyun , He Jianchao , Li Jin , Chen Hongsheng
Published: January 2023

Atomic oxygen in the low Earth orbit (LEO) environment is highly oxidizing. Due to the high flight speed of spacecraft, the relative kinetic energy of high-flux atomic oxygen bombarding the spacecraft surface can reach up to about 5 eV. Therefore, atomic oxygen is one of the most dangerous space environment factors in LEO, which seriously affects the safe operation and service life of spacecraft in orbit. In order to meet the requirements for the high reliability and long lifetime of spacecraft, effective protection measures must be taken on their sensitive surfaces. Siloxane is a coating with an organic–inorganic hybrid structure. Compared with SiO2 and other inorganic atomic oxygen protective coatings, it has better flexibility and is better at anti-atomic oxygen performance. In this paper, the plasma polymerization deposition technique was used to prepare large-area siloxane coatings on different substrates with different thicknesses for improving atomic oxygen resistance by optimizing the process parameters. The thickness of the coating was measured by different methods, and the results showed that the thickness distribution was consistent. By observing the surface morphology of the coating, it was uniform and compact without obvious defects, so the uniformity of large-area coating was also ideal. The adhesion and heat/humidity resistance of siloxane coatings were examined by pull-off testing and damp-heat testing, respectively. The results showed that the siloxane coatings with a thickness of about 400 nm exhibited better physical properties. At the same time, the ground simulation testing of atomic oxygen confirmed that siloxane coatings with a thickness of 418 nm presented the best performance of atomic oxygen resistance. The atomic oxygen erosion yield of siloxane coatings with a thickness of 418 nm was as low as 5.39 × 10−27 cm3/atoms, which was three orders of magnitude lower than that of the uncoated Kapton substrate and presented a good anti-atomic oxygen performance. Meanwhile, it has also successfully passed the damp-heat test. The coating thickness is only several hundred nanometers and does not increase the weight of the spacecraft, which makes it a relatively ideal LEO atomic oxygen protection material. Furthermore, a possible mechanism was proposed to explicate the physicochemical process of atomic oxygen attacking the coating materials.
Effects of Nitrogen Content and Strain Rate on the Tensile Behavior of High-Nitrogen and Nickel-Free Austenitic Stainless Steel
Authors: Shi Feng , Zhang Xinyue , Li Tianzeng , Guan Xianjun , Li Xiaowu , Liu Chunming
Published: January 2023

The uniaxial tensile behaviors of Fe-19Cr-16Mn-2Mo-0.49N and Fe-18Cr-16Mn-2Mo-0.85N high-nitrogen and nickel-free austenitic stainless steels at two strain rates of 10−2 s−1 and 10−4 s−1 were comparatively investigated. The related deformation microstructure was characterized and fracture mechanism was analyzed. The results show that the nitrogen content and strain rate both have significant effects on the tensile properties of the tested steels. As the strain rate is the same, the tested steel containing a higher nitrogen content has higher Rm and Rp0.2. However, Rm is higher at a lower strain rate and Rp0.2 is higher at a higher strain rate in the case of the same nitrogen content. The tested steel with a lower nitrogen content (0.49 wt.%N) tensioned at a lower strain rate of 10−4 s−1 obtains the highest elongation, while the tested steel with a higher nitrogen content (0.85 wt.%N) tensioned at a higher strain rate of 10−2 s−1 has the lowest elongation. The tensile plastic deformation is mainly governed by slip and twinning, affected jointly by stacking fault energy and short-range order. Dislocation slip featured by planar slip bands and twin-like bands is the main deformation structure in the tested steel containing a higher nitrogen content (0.85 wt.%N) tensioned at a lower strain rate of 10−4 s−1, whereas twinning deformation becomes more prominent with decreasing nitrogen content and increasing strain rate.
Population Subdivision in the Gopher Frog (Rana capito) across the Fragmented Longleaf Pine-Wiregrass Savanna of the Southeastern USA
Authors: Devitt Thomas J. , Enge Kevin M. , Farmer Anna L. , Beerli Peter , Richter Stephen C. , Hall Jeffrey G. , Lance Stacey L.
Published: January 2023

Delineating genetically distinct population segments of threatened species and quantifying population connectivity are important steps in developing effective conservation and management strategies aimed at preventing extinction. The gopher frog (Rana capito) is a xeric-adapted, pond-breeding species endemic to the Gulf and Atlantic coastal plains of the southeastern United States. This species has experienced extensive habitat loss and fragmentation in the formerly widespread longleaf pine-wiregrass savanna where it lives, resulting in individual abundance declines and population extinctions throughout its range. We used individual-based clustering methods along with Bayesian inference of historical migration based on almost 1500 multilocus microsatellite genotypes to examine genetic structure in this taxon. Clustering analyses identified panhandle and peninsular populations in Florida as distinct genetic clusters separated by the Aucilla River, consistent with the division between the Coastal Plain and peninsular mitochondrial lineages, respectively. Analysis of historical migration indicated an east–west population divergence event followed by immigration to the east. Together, our results indicate that the genetically distinct Coastal Plain and peninsular Florida lineages should be considered separately for conservation and management purposes.
Robustness of Radiomic Features: Two-Dimensional versus Three-Dimensional MRI-Based Feature Reproducibility in Lipomatous Soft-Tissue Tumors
Authors: Sudjai Narumol , Siriwanarangsun Palanan , Lektrakul Nittaya , Saiviroonporn Pairash , Maungsomboon Sorranart , Phimolsarnti Rapin , Asavamongkolkul Apichat , Chandhanayingyong Chandhanarat
Published: January 2023

This retrospective study aimed to compare the intra- and inter-observer manual-segmentation variability in the feature reproducibility between two-dimensional (2D) and three-dimensional (3D) magnetic-resonance imaging (MRI)-based radiomic features. The study included patients with lipomatous soft-tissue tumors that were diagnosed with histopathology and underwent MRI scans. Tumor segmentation based on the 2D and 3D MRI images was performed by two observers to assess the intra- and inter-observer variability. In both the 2D and the 3D segmentations, the radiomic features were extracted from the normalized images. Regarding the stability of the features, the intraclass correlation coefficient (ICC) was used to evaluate the intra- and inter-observer segmentation variability. Features with ICC > 0.75 were considered reproducible. The degree of feature robustness was classified as low, moderate, or high. Additionally, we compared the efficacy of 2D and 3D contour-focused segmentation in terms of the effects of the stable feature rate, sensitivity, specificity, and diagnostic accuracy of machine learning on the reproducible features. In total, 93 and 107 features were extracted from the 2D and 3D images, respectively. Only 35 features from the 2D images and 63 features from the 3D images were reproducible. The stable feature rate for the 3D segmentation was more significant than for the 2D segmentation (58.9% vs. 37.6%, p = 0.002). The majority of the features for the 3D segmentation had moderate-to-high robustness, while 40.9% of the features for the 2D segmentation had low robustness. The diagnostic accuracy of the machine-learning model for the 2D segmentation was close to that for the 3D segmentation (88% vs. 90%). In both the 2D and the 3D segmentation, the specificity values were equal to 100%. However, the sensitivity for the 2D segmentation was lower than for the 3D segmentation (75% vs. 83%). For the 2D + 3D radiomic features, the model achieved a diagnostic accuracy of 87% (sensitivity, 100%, and specificity, 80%). Both 2D and 3D MRI-based radiomic features of lipomatous soft-tissue tumors are reproducible. With a higher stable feature rate, 3D contour-focused segmentation should be selected for the feature-extraction process.
A Novel Multi-Task Learning Network Based on Melanoma Segmentation and Classification with Skin Lesion Images
Authors: Alenezi Fayadh , Armghan Ammar , Polat Kemal
Published: January 2023

Melanoma is known worldwide as a malignant tumor and the fastest-growing skin cancer type. It is a very life-threatening disease with a high mortality rate. Automatic melanoma detection improves the early detection of the disease and the survival rate. In accordance with this purpose, we presented a multi-task learning approach based on melanoma recognition with dermoscopy images. Firstly, an effective pre-processing approach based on max pooling, contrast, and shape filters is used to eliminate hair details and to perform image enhancement operations. Next, the lesion region was segmented with a VGGNet model-based FCN Layer architecture using enhanced images. Later, a cropping process was performed for the detected lesions. Then, the cropped images were converted to the input size of the classifier model using the very deep super-resolution neural network approach, and the decrease in image resolution was minimized. Finally, a deep learning network approach based on pre-trained convolutional neural networks was developed for melanoma classification. We used the International Skin Imaging Collaboration, a publicly available dermoscopic skin lesion dataset in experimental studies. While the performance measures of accuracy, specificity, precision, and sensitivity, obtained for segmentation of the lesion region, were produced at rates of 96.99%, 92.53%, 97.65%, and 98.41%, respectively, the performance measures achieved rates for classification of 97.73%, 99.83%, 99.83%, and 95.67%, respectively.
Wearable Orofacial Technology and Orthodontics
Authors: Prasad Sabarinath , Arunachalam Sivakumar , Boillat Thomas , Ghoneima Ahmed , Gandedkar Narayan , Diar-Bakirly Samira
Published: January 2023

Wearable technology to augment traditional approaches are increasingly being added to the arsenals of treatment providers. Wearable technology generally refers to electronic systems, devices, or sensors that are usually worn on or are in close proximity to the human body. Wearables may be stand-alone or integrated into materials that are worn on the body. What sets medical wearables apart from other systems is their ability to collect, store, and relay information regarding an individual’s current body status to other devices operating on compatible networks in naturalistic settings. The last decade has witnessed a steady increase in the use of wearables specific to the orofacial region. Applications range from supplementing diagnosis, tracking treatment progress, monitoring patient compliance, and better understanding the jaw’s functional and parafunctional activities. Orofacial wearable devices may be unimodal or incorporate multiple sensing modalities. The objective data collected continuously, in real time, in naturalistic settings using these orofacial wearables provide opportunities to formulate accurate and personalized treatment strategies. In the not-too-distant future, it is anticipated that information about an individual’s current oral health status may provide patient-centric personalized care to prevent, diagnose, and treat oral diseases, with wearables playing a key role. In this review, we examine the progress achieved, summarize applications of orthodontic relevance and examine the future potential of orofacial wearables.
Ensuring Budgetary Resources at the Level of Local Communities in the Current Social-Economic Context: Evidence for Romanian Municipalities
Authors: Onofrei Mihaela , Bostan Ionel , Cigu Elena , Vatamanu Anca Florentina
Published: January 2023

This paper aims to examine whether the status of fiscal decentralization generates efficiency in local spending behavior and leads to local fiscal performance and local economic growth, revealing not only the status of Romania from the point of vertical fiscal imbalance but also the fiscal implication of spending decentralization and local government effectiveness. The methodological background includes qualitative sequential methodology, involving empiric analysis that provides coherence and viability for our study, but also quantitative methods, including Ordinary Least Squares regression (OLS). The empirical results show that fiscal decentralization determines more responsible and efficient local spending, enhancing local performance and contributing to economic growth. Furthermore, the analysis provides evidence on the importance of local fiscal consolidation and gives an overview in terms of spending responsibilities between the central government and local government. The paper contributes to the literature that studies fiscal imbalance, as well as the fiscal implications of decentralized spending and the effectiveness of local governments in driving economic growth. It also contributes to the literature that studies the relationship between fiscal decentralization and local economic growth, as well as the effectiveness of government reforms and strategies.
Does Pre-Service Teacher Preparation Affect Students’ Academic Performance? Evidence from China
Authors: Liu Xinqiao , Gao Wenjuan , Chen Luxi
Published: January 2023

Pre-service teacher preparation (PSTP) is generally considered a significant predictor of student achievements. This paper adopted a multi-tier linear model to estimate the PSTP effects on student performance by taking teachers and students in the high schools of Haidian District, Beijing, China, as the research population. It used exploratory factor analysis to classify PSTP into two categories: content knowledge preparation and pedagogical content knowledge preparation; and described the status of PSTP in three subjects: Chinese, mathematics, and chemistry. The study found differences in PSTP by subject. In Chinese, teachers’ content knowledge preparation significantly negatively affected student performance, and their pedagogical content knowledge preparation significantly positively influenced student performance. In mathematics, PSTP had no significant effect on student performance. In chemistry, teachers’ pedagogical content knowledge preparation had a significantly negative effect on student performance. Based on the findings of the empirical study, the study proposes further identifying PSTP’s role in student performance by subject, strengthening the focus on pre-service preparation skills in recruiting Chinese and chemistry teachers, and developing a more suitable system for teacher selection and training.
FPGA-Based Pulse Compressor for Ultra Low Latency Visible Light Communications
Authors: Ricci Stefano , Caputo Stefano , Mucchi Lorenzo
Published: January 2023

Visible Light Communication (VLC) represents an emerging technology where a short-range data connection is obtained by modulating the energy radiated by Light Emitting Diodes (LEDs) at frequencies from a few kHz up to hundreds of MHz. The bandwidth/distance performance of such links is a compromise related to the available Signal-to-Noise ratio (SNR). At present, VLC links with bandwidth beyond the Gb/s and distance limited to a few cm or distances up to 100 m but data rates of a few kb/s have been demonstrated. Chirp coding with pulse compression is a well-known technique capable of recovering useful data from low SNR signals, widely employed, for example, in radar. In spite of the possible advantages, its application in VLC has never been investigated. Unfortunately, the pulse compressor is quite calculation-intensive, and only devices like Field-Programmable-Gate-Arrays (FPGAs) can support a low-latency real-time implementation. In this paper we demonstrate a real-time VLC link based on chirp coding and pulse compression coded in FPGA. For example, a chirp with bandwidth and length of 1.7 MHz and 17.92 µs, respectively, is demonstrated to support a link at 1.56 Mb/s over 2.8 m distance and a latency below 40 µs. Moreover, the communication-distance increase achievable by chirps of increasing temporal length is demonstrated and compared to the theoretical background.
Examination of a Method for Estimating Solid Fraction at Flow Cessation from Flow Velocity of Mushy Formation Molten Alloys
Authors: Mu Kuiyuan , Nikawa Makoto , Yamashita Minoru
Published: January 2023

The purpose of this study was to experimentally estimate the solid fraction at which the cessation of the flow of a molten Al–7%Si–0.3%Mg alloy and Cu–8%Sn alloy occurs in casting. The flow cessation mechanism of two alloys is known as the “mushy” formation type, which means that the flow ceases when the solid fraction at the molten metal tip reaches a certain critical value. Therefore, the flow velocity at the molten metal tip is assumed to decrease gradually. Thus, a new method for calculating the solid fraction at flow cessation based on computer simulations was examined using experimental measurements of the flow velocity and flow length. The result of the experiment shows the experimental flow length is consistent with the simulation results, the calculated solid fraction at flow cessation. The flow velocity gradually decreased from the initial stage, but there was a region where the velocity was almost constant after the initial stage. The molten metal temperature became lower from the root side to the tip side, and the solid fraction at the time of flow cessation was calculated from the measurement results, for the Al–7%Si–0.3%Mg alloy it was 0.35–0.4 near the tip, and for the Cu–8%Sn alloy it was 0.25. Computer simulations were performed by tuning the heat transfer coefficient so that the flow length and flow velocity would match the experimental results. Computer simulations were performed by tuning the heat transfer coefficients so that the flow length and flow velocity would match the experimental results and could simulate the changes in flow velocity obtained from the experiments. The solid fraction at the tip of the molten metal was almost the same as the experimental results. These results show that it is possible to estimate the solid fraction at the flow cessation from the flow velocity at the tip.
Design of Cost-Efficient SRAM Cell in Quantum Dot Cellular Automata Technology
Authors: Bhat Soha Maqbool , Ahmed Suhaib , Bahar Ali Newaz , Wahid Khan A. , Otsuki Akira , Singh Pooran
Published: January 2023

SRAM or Static Random-Access Memory is the most vital memory technology. SRAM is fast and robust but faces design challenges in nanoscale CMOS such as high leakage, power consumption, and reliability. Quantum-dot Cellular Automata (QCA) is the alternative technology that can be used to address the challenges of conventional SRAM. In this paper, a cost-efficient single layer SRAM cell has been proposed in QCA. The design has 39 cells with a latency of 1.5 clock cycles and achieves an overall improvement in cell count, area, latency, and QCA cost compared to the reported designs. It can therefore be used to design nanoscale memory structures of higher order.
Extractive Article Summarization Using Integrated TextRank and BM25+ Algorithm
Authors: Gulati Vaibhav , Kumar Deepika , Popescu Daniela Elena , Hemanth Jude D.
Published: January 2023

The quantity of textual data on the internet is growing exponentially, and it is very tough task to obtain important and relevant information from it. An efficient and effective method is required that provides a concise summary of an article. This can be achieved by the usage of automatic text summarization. In this research, the authors suggested an efficient approach for text summarization where an extractive summary is generated from an article. The methodology was modified by integrating a normalized similarity matrix of both BM25+ and conventional TextRank algorithm, which resulted in the improvised results. A graph is generated by taking the sentences in the article as nodes and edge weights as the similarity score between two sentences. The maximum rank nodes are selected, and the summary is extracted. Empirical evaluation of the proposed methodology was analyzed and compared with baseline methods viz. the conventional TextRank algorithm, term frequency–inverse document frequency (TF–IDF) cosine, longest common consequence (LCS), and BM25+ by taking precision, recall, and F1 score as evaluation criteria. ROUGE-1, ROUGE-2, and ROUGE-L scores were calculated for all the methods. The outcomes demonstrate that the proposed method can efficiently summarize any article irrespective of the category it belongs to.
Charging Behavior Analysis Based on Operation Data of Private BEV Customers in Beijing
Authors: Tian Hao , Sun Yujuan , Hu Fangfang , Du Jiuyu
Published: January 2023

Charging behavior is essential to understanding the real performance and evaluating the sustainability of battery electric vehicle (BEV) development and providing the basis for optimal infrastructure deployment. However, it is very hard to obtain the rules, due to lack of the data support, etc. In this research, analyzing the charging behavior of users with private charging piles (PCPs) is carried out based on the real vehicle data of 168 BEV users in Beijing, covering 8825 charging events for a one-year duration. In this study, the charging behaviors are defined by five indexes: the starting state of charge (SOC) of batteries, charging location selection, charging start time, driving distance, and duration between two charging events. To further find the influencing rules of the PCPs owning state, we setup a method to divide the data into two categories to process further analysis and comparison. Meanwhile, in order to better observe the impact of electric vehicle charging on the power grid, we use a Monte Carlo (MC) simulation to predict the charging load of different users based on the analysis. In addition, an agent-based trip chain model (ABTCM), a multinomial logistic regression (MLR), and a machine learning algorithm (MLA) approach are proposed to analyze the charging behavior. The results show that with 40% or lower charging start SOC, the proportion of users without PCPs (weekday: 55.9%; weekend: 59.9%) is larger than users with PCPs (weekday: 45.5%; weekend: 42.6%). Meanwhile, users without PCPs have a certain decrease in the range of 60–80% charging start SOC. The median charging time duration is 51.44 h for users with PCPs and is 17.25 h for users without PCPs. The charging peak effect is evident, and the two types of users have different power consumption distributions. Due to the existence of PCPs, users have lower mileage anxiety and more diverse charging time choices. The analysis results and method can provide a basis for optimal deployment and allocation of charging infrastructure, and to make suitable incentive policies for changing the charging behavior, targeting the carbon neutral objectives.
Fire Hazard: Undesirable Ecosystem Function of Orchard Vegetation
Authors: Winkler Jan , Ježová Markéta , Punčochář Radek , Hurajová Erika , Martínez Barroso Petra , Kopta Tomáš , Semerádová Daniela , Vaverková Magdalena Daria
Published: January 2023

Fires will become an increasingly frequent perturbation even under the conditions of the mild climate zone and will interfere with the agricultural landscape. Fire is a natural phenomenon, and depending on ecosystems, vegetation may develop and contribute to the occurrence and spread of fire. Vegetation of the sour cherry orchard located in the climatically dry conditions of the South Moravian Region, Czech Republic (CR), was evaluated. Vegetation assessment was performed using phytocenological relevé. In each variant, 10 relevé were recorded. Coverage of the found species was estimated directly in percentages. Moreover, the maximum height in the stand was measured for each type of plant. Biomass of individual plant species was calculated, using the biomass index (IB) equation. The IB values of individual plant species in the treatments were processed by employing a multidimensional analysis of the ecological data. Different vegetation management practices in an orchard change the species diversity of the vegetation and thus the fire hazards in the orchard conditions. Grassy interrow has the most grass biomass during the entire vegetation season, and therefore represents the greatest hazard and spread of fire. The most important grasses include Arrhenatherum elatius, Dactylis glomerata, Festuca pratensis, Lolium perenne, and Poa pratensis. On the contrary, bare soil conditions in the interrow are most suitable for annual species, and this is the place with the highest changes in the number of species during the growing season. Biomass of the orchard vegetation combined with dry and warm weather increases the fire hazard. Annual and perennial grasses have very good potential for the production of biomass, which increases the hazard of fire. The nature of the vegetation in the orchards has the potential for the actual start of a fire and its subsequent spread, however, under other environmental conditions. During hot and dry weather, dead biomass may accumulate resulting in increasing the hazard of large wildfires. Varied orchard management practices lead to a higher diversity of vegetation and make orchards, islands of biodiversity in the agricultural landscape.
Identification of Distinctive Primary Metabolites Influencing Broccoli (Brassica oleracea, var. Italica) Taste
Authors: Chevilly Sergio , Dolz-Edo Laura , Blanca José , Yenush Lynne , Mulet José M.
Published: January 2023

Broccoli (Brassica oleracea L. var. Italica Plenck) is a cruciferous crop that is considered to be a good source of micronutrients. Better taste is a main objective for breeding, as consumers are demanding novel cultivars suited for a healthy diet, but ones that are more palatable. This study aimed to identify primary metabolites related to cultivars with better taste according to a consumer panel. For this purpose, we performed a complete primary metabolomic profile of 20 different broccoli cultivars grown in the field and contrasted the obtained data with the results of a consumer panel which evaluated the taste of the same raw buds. A statistical analysis was conducted to find primary metabolites correlating with better score in the taste panels. According to our results, sugar content is not a distinctive factor for taste in broccoli. The accumulation of the amino acids leucine, lysine and alanine, together with Myo-inositol, negatively affected taste, while a high content of γ-aminobutyric acid (GABA) is a distinctive trait for cultivars scoring high in the consumer panels. A Principal Component Analysis (PCA) allowed us to define three different groups according to the metabolomic profile of the 20 broccoli cultivars studied. Our results suggest molecular traits that could be useful as distinctive markers to predict better taste in broccoli or to design novel biotechnological or classical breeding strategies for improving broccoli taste.
Predicting the Textural Properties of Plant-Based Meat Analogs with Machine Learning
Authors: Kircali Ata Sezin , Shi Jing K. , Yao Xuesi , Hua Xin Yi , Haldar Sumanto , Chiang Jie Hong , Wu Min
Published: January 2023

Plant-based meat analogs are food products that mimic the appearance, texture, and taste of real meat. The development process requires laborious experimental iterations and expert knowledge to meet consumer expectations. To address these problems, we propose a machine learning (ML)-based framework to predict the textural properties of meat analogs. We introduce the proximate compositions of the raw materials, namely protein, fat, carbohydrate, fibre, ash, and moisture, in percentages and the “targeted moisture contents” of the meat analogs as input features of the ML models, such as Ridge, XGBoost, and MLP, adopting a build-in feature selection mechanism for predicting “Hardness” and “Chewiness”. We achieved a mean absolute percentage error (MAPE) of 22.9%, root mean square error (RMSE) of 10.101 for Hardness, MAPE of 14.5%, and RMSE of 6.035 for Chewiness. In addition, carbohydrates, fat and targeted moisture content are found to be the most important factors in determining textural properties. We also investigate multicollinearity among the features, linearity of the designed model, and inconsistent food compositions for validation of the experimental design. Our results have shown that ML is an effective aid in formulating plant-based meat analogs, laying out the groundwork to expediently optimize product development cycles to reduce costs.
A Review on Fractional-Order Modelling and Control of Robotic Manipulators
Authors: Bingi Kishore , Rajanarayan Prusty B , Pal Singh Abhaya
Published: January 2023

Robot manipulators are widely used in many fields and play a vital role in the assembly, maintenance, and servicing of future complex in-orbit infrastructures. They are also helpful in areas where it is undesirable for humans to go, for instance, during undersea exploration, in radioactive surroundings, and other hazardous places. Robotic manipulators are highly coupled and non-linear multivariable mechanical systems designed to perform one of these specific tasks. Further, the time-varying constraints and uncertainties of robotic manipulators will adversely affect the characteristics and response of these systems. Therefore, these systems require effective modelling and robust controllers to handle such complexities, which is challenging for control engineers. To solve this problem, many researchers have used the fractional-order concept in the modelling and control of robotic manipulators; yet it remains a challenge. This review paper presents comprehensive and significant research on state-of-the-art fractional-order modelling and control strategies for robotic manipulators. It also aims to provide a control engineering community for better understanding and up-to-date knowledge of fractional-order modelling, control trends, and future directions. The main table summarises around 95 works closely related to the mentioned issue. Key areas focused on include modelling, fractional-order modelling type, model order, fractional-order control, controller parameters, comparison controllers, tuning techniques, objective function, fractional-order definitions and approximation techniques, simulation tools and validation type. Trends for existing research have been broadly studied and depicted graphically. Further, future perspective and research gaps have also been discussed comprehensively.
Theoretical Analysis and Simulation of a Fractional-Order Compartmental Model with Time Delay for the Propagation of Leprosy
Authors: Iqbal Zafar , Ahmed Nauman , Macías-Díaz Jorge E.
Published: January 2023

This article investigates the propagation of a deadly human disease, namely leprosy. At the outset, the mathematical model is transformed into a fractional-order model by introducing the Caputo differential operator of arbitrary order. A result is established, which ensures the positivity of the fractional-order epidemic model. The stability of the continuous model at different points of equilibria is investigated. The basic reproduction number, R0, is obtained for the leprosy model. It is observed that the leprosy system is locally asymptotically stable at both steady states when R0<1. On the other hand, the fractional-order system is globally asymptotically stable when R0>1. To find the approximate solutions for the continuous epidemic model, a non-standard numerical scheme is constructed. The main features of the non-standard scheme (such as positivity and boundedness of the numerical method) are also confirmed by applying some benchmark results. Simulations and a feasible test example are presented to discern the properties of the numerical method. Our computational results confirm both the analytical and the numerical properties of the finite-difference scheme.
Asymptotic Behavior of Delayed Reaction-Diffusion Neural Networks Modeled by Generalized Proportional Caputo Fractional Partial Differential Equations
Authors: Agarwal Ravi P. , Hristova Snezhana , O’Regan Donal
Published: January 2023

In this paper, a delayed reaction-diffusion neural network model of fractional order and with several constant delays is considered. Generalized proportional Caputo fractional derivatives with respect to the time variable are applied, and this type of derivative generalizes several known types in the literature for fractional derivatives such as the Caputo fractional derivative. Thus, the obtained results additionally generalize some known models in the literature. The long term behavior of the solution of the model when the time is increasing without a bound is studied and sufficient conditions for approaching zero are obtained. Lyapunov functions defined as a sum of squares with their generalized proportional Caputo fractional derivatives are applied and a comparison result for a scalar linear generalized proportional Caputo fractional differential equation with several constant delays is presented. Lyapunov functions and the comparison principle are then combined to establish our main results.
Multistability and Phase Synchronization of Rulkov Neurons Coupled with a Locally Active Discrete Memristor
Authors: Ma Minglin , Lu Yaping , Li Zhijun , Sun Yichuang , Wang Chunhua
Published: January 2023

In order to enrich the dynamic behaviors of discrete neuron models and more effectively mimic biological neural networks, this paper proposes a bistable locally active discrete memristor (LADM) model to mimic synapses. We explored the dynamic behaviors of neural networks by introducing the LADM into two identical Rulkov neurons. Based on numerical simulation, the neural network manifested multistability and new firing behaviors under different system parameters and initial values. In addition, the phase synchronization between the neurons was explored. Additionally, it is worth mentioning that the Rulkov neurons showed synchronization transition behavior; that is, anti-phase synchronization changed to in-phase synchronization with the change in the coupling strength. In particular, the anti-phase synchronization of different firing patterns in the neural network was investigated. This can characterize the different firing behaviors of coupled homogeneous neurons in the different functional areas of the brain, which is helpful to understand the formation of functional areas. This paper has a potential research value and lays the foundation for biological neuron experiments and neuron-based engineering applications.
Comparative Analysis of Long-Term Care in OECD Countries: Focusing on Long-Term Care Financing Type
Authors: Lee Seok-Hwan , Chon Yongho , Kim Yun-Young
Published: January 2023

This study aims to examine the characteristics of long-term care (LTC) financing in Organization for Economic Cooperation Development (OECD) countries. To this end, the 26 OECD countries that have introduced LTC systems were classified into three types of models: tax-based, health insurance, and LTC insurance (LTCI) systems. Thereafter, these systems were analyzed using Gilbert and Terrell’s policy analysis framework. The results indicated differences in the characteristics of each type of financing in terms of allocation, benefit provision, service delivery, and finance. It is likely that while the LTC insurance model was mainly based on universalism and showed the highest level of coverage, the tax-based and health insurance models adopted selectivism with lower level of benefits per capita. In terms of service delivery, local authorities tended to have the responsibility to decide LTC service users and provide services in many countries, regardless of the type of model. In terms of finance, LTC insurance-based countries had the highest LTC expenditure as a percentage of GDP, followed by countries with tax-based and health insurance systems.
A History of Heat Health Management Policies in the Singapore Military
Authors: Sim Joshua Dao Wei , Lee Jason Kai Wei
Published: January 2023

Our paper, which is the first historical study about heat injuries in Singapore, seeks to situate the Singapore Armed Forces’ (SAF) history of heat stress management policies within the national context. Firstly, we observe that since the late 1970s, a research-driven approach has been adopted by the SAF’s military medical leaders to formulate a range of policies to address the Forces’ high incidence of heat injuries. This has resulted in the introduction of SAF-wide training measures, and the assembling of local scientific research expertise, which has led to a sharp reduction in heat injury incidence from the 1980s to 2000s. Through this, the SAF sought to demonstrate that its heat stress mitigation measures made the Singapore military ‘heat proof’. Secondly, the state shaped a soldier safety agenda in the late 2000s on the back of an increasing emphasis on safety and the transformation of the SAF into a highly-educated and technologically-sophisticated force. This meant a shift towards concern about the welfare of every soldier, particularly through the state’s drive to eradicate all training-related deaths. Accordingly, the SAF medical military leaders responded to the state’s safety agenda by introducing heat stress management research and policies that were oriented towards the target of eradicating deaths due to heat stress. This policy and research direction, as such, has been strongly guided by the state’s safety agenda and utilised to demonstrate to the public that all efforts have been taken to comprehensively mitigate the risks of heat.
Will the Construction of Sports Facilities Nudge People to Participate in Physical Exercises in China? The Moderating Role of Mental Health
Authors: Xue Xiaojing , Li Yong
Published: January 2023

This study aims to examine the nudging effect of the sports facility construction on physical exercise (PE) participation with consideration of the moderating role of mental health in China. Multiple linear regression models are used in this study. The subjects are 4634 from the 2014 China Family Panel Studies (CFPS) data, which is a nationally representative longitudinal survey of Chinese individuals. We find that the construction of sports facilities nudges people to participate in PE, and gender, age, and education significantly influence people’s participation in PE. Young, female, and better-educated people compose the “neo-vulnerable” population, who participate less in PE in China and need more interventions. Mental health status has no significant effect on people’s PE participation, while it negatively moderates the nudging effect of the construction of sports facilities on PE. The results of this study suggest that only building sporting facilities is insufficient to encourage PE participation. Policies and interventions should be given to mentally disturbed individuals to guarantee and magnify the nudging effect of sports facilities on PE.