bluuebunny/crossref_metadata_2025 huggingface dataset:
A Mini-Review on Lanthanum–Nickel-Based Perovskite-Derived Catalysts for Hydrogen Production via the Dry Reforming of Methane (DRM)
Authors: Georgiadis Amvrosios G. , Charisiou Nikolaos D. , Goula Maria A.
Published: October 2023

Given that the attempts to head toward a hydrogen economy are gathering pace, the dry reforming of methane (DRM) to produce hydrogen-rich syngas is a reaction that is worthy of investigation. Nickel-based catalysts have been extensively examined as a cost-effective solution for DRM, though they suffer from fast deactivation caused by coke accumulation. However, a number of published studies report high catalytic performance in terms of both activity and stability for La–Ni-based perovskite-derived catalysts used in DRM in comparison to other corresponding materials. In the work presented herein, a thorough analysis regarding the application of La–Ni-based perovskite catalysts for DRM is carried out. LaNiO3 is known for its anti-coking ability owing to the strong interaction between CO2 and La2O3. A further modification to improve the catalytic performance can be achieved by the partial or complete substitution of A or/and B sites of the perovskite catalysts. The latest developments with respect to this topic are also discussed in this manuscript. Even though the low surface area of perovskite catalysts has always been an obstacle for their commercialization, new supported and porous perovskite materials have recently emerged to address, at least partly, the challenge. Finally, conclusions and future outlooks for developing novel perovskite catalysts that may potentially pioneer new technology are included.
Copy Number Variation That Influences the Ionizing Radiation Sensitivity of Oral Squamous Cell Carcinoma
Authors: Izumi Tadahide , Rychahou Piotr , Chen Li , Smith Molly H. , Valentino Joseph
Published: October 2023

Genome instability in cancer cells causes not only point mutations but also structural variations of the genome, including copy number variations (CNVs). It has recently been proposed that CNVs arise in cancer to adapt to a given microenvironment to survive. However, how CNV influences cellular resistance against ionizing radiation remains unknown. PRMT5 (protein arginine methyltransferase 5) and APE1 (apurinic/apyrimidinic endonuclease 1), which enhance repair of DNA double-strand breaks and oxidative DNA damage, are closely localized in the chromosome 14 of the human genome. In this study, the genomics data for the PRMT5 and APE1 genes, including their expression, CNVs, and clinical outcomes, were analyzed using TCGA’s data set for oral squamous cell carcinoma patients. The two genes were found to share almost identical CNV values among cancer tissues from oral squamous cell carcinoma (OSCC) patients. Levels of expression of PRMT5 and APE1 in OSCC tissues are highly correlated in cancer but not in normal tissues, suggesting that regulation of PRMT5 and APE1 were overridden by the extent of CNV in the PRMT5-APE1 genome region. High expression levels of PRMT5 and APE1 were both associated with poor survival outcomes after radiation therapy. Simultaneous down-regulation of PRMT5 and APE1 synergistically hampered DNA double-strand break repair and sensitized OSCC cell lines to X-ray irradiation in vitro and in vivo. These results suggest that the extent of CNV in a particular genome region significantly influence the radiation resistance of cancer cells. Profiling CNV in the PRMT5-APE1 genome region may help us to understand the mechanism of the acquired radioresistance of tumor cells, and raises the possibility that simultaneous inhibition of PRMT5 and APE1 may increase the efficacy of radiation therapy.
Impedance In Vitro Assessment for the Detection of Salmonella typhimurium Infection in Intestinal Human Cancer Cells
Authors: Marka Sofia , Zografaki Maria-Eleftheria , Papaioannou George-Marios , Mavrikou Sofia , Flemetakis Emmanouil , Kintzios Spyridon
Published: October 2023

A significant number of research papers regarding biosensor-related assays for key food safety pathogens based on the use of mammalian cells has been reported. In this study, the Salmonella typhimurium infection progression was monitored in the human colon cancer cell line Caco-2 and the mucus-secreting HT29-MTX-E12, after treatment with five different bacterial MOI for 30 min by comparing the alterations of frequencies recordings with impedance spectroscopy measurements. For this purpose, bacterial adhesion and invasion assays were initially performed. Then, the data obtained from impedance spectroscopy recordings were compared to cell viability data derived from the MTT uptake cell proliferation assay as well as from live cell analysis assays of mitochondrial membrane potential alterations. From our findings a concentration-dependent increase in bacterial colonies occurring from invaded cells was observed upon a higher multiplicity of infection (MOI) bacterial infection at both cell lines. On the contrary, the bacteria infection did not have any impact on the viability of the cells after 1 h of treatment. Differential results were obtained from the measurement of mitochondrial potential at both cell lines. Finally, the impedance values recorded from the 2D, and 3D cultures were concentration-dependent for both cell lines whereas a characteristic pattern specific to each cell line was revealed. Our results indicate that human cell-based bio-electric assays can be a valuable tool for obtaining a unique fingerprint for each bacterial infection in the near future.
Preparation and Innovative Design Applications of Paper-Based Aluminized Film
Authors: Zhou Yi , Zhou Wei , Xia Guobin
Published: October 2023

The growing demand for sustainable and innovative materials in product design has spurred interest in unconventional resources. Despite this, a gap persists in the effective utilization of paper-based materials, particularly with metallic coatings, for creative applications. This study aims to address this by exploring the technical methods for applying Aluminum (Al) coatings to paper substrates. We developed paper-based aluminum coatings and combined them with corrugated cardboard to create a novel material for product development. Utilizing high-strength specialty paper as the substrate, an orthogonal experiment was conducted to identify key process parameters. Factors such as target–substrate distance, working pressure, current intensity, and coating duration were evaluated for their impact on the properties of the Al film. Our research culminated in the production of high-quality Al-plated corrugated cardboard. Capitalizing on its unique attributes, we employed a design approach that led to the creation of innovative furniture featuring structural forms like folding and insertion. This study not only introduces a new range of Al-plated corrugated cardboard products but also expands the potential applications of paper-based aluminized film in material-based product design.
Comparing Three Profoundly Influential Prognostic Scores in Cirrhotic Patients with Acute-on-Chronic-Liver Failure Admitted to the ICU: Prediction of One-Month Mortality—A Retrospective Cohort Study
Authors: Lin Shih-Hua , Chen Wei-Ting , Tsai Ming-Hung , Kuo Wei-Liang , Wang Sheng-Fu , Liu Yu , Chiu Yu-Ting , Chen Bo-Huan , Huang Chien-Hao , Chien Rong-Nan
Published: October 2023

Background: Acute-on-chronic-liver failure (ACLF) demonstrates high short-term mortality rates and usually requires intensive care unit (ICU) admission. Accurate prognostication of these patients is pivotal for timely referral for liver transplantation. The superiority of CLIF-C ACLF, CLIF-C ACLF lactate, and NACSELD-ACLF scores in Asian patients with ACLF admitted to an ICU remains inconclusive. Aims: To compare the predictive performance of CLIF-C ACLF, CLIF-C ACLF lactate, and NACSELD-ACLF scores for one-month mortality. Methods: 276 consecutive cirrhotic patients with ACLF admitted to ICU were enrolled. The prognostic values for one-month mortality were assessed by AUROC analysis. Results: The primary cause of cirrhosis in this cohort was alcohol abuse (56.5%). AUROC analysis (95% confidence intervals) demonstrated that CLIF-C ACLF lactate [0.802 (0.747–0.856)] outperformed both CLIF-C ACLF [0.791 (0.733–0.848)] and NACSELD-ACLF [0.673 (0.606–0.740)] in predicting one-month mortality. However, no statistically significant difference was observed between the predictive abilities of CLIF-C ACLF and CLIF-C ACLF lactate. Conclusions: In critically ill cirrhotic patients with ACLF admitted to the hepatology ICU, CLIF ACLF-lactate outperformed CLIF-C ACLF and NACSELD-ACLF in predicting one-month mortality. Nevertheless, no statistically significant difference was observed between CLIF-C ACLF and CLIF-C ACLF lactate. Larger-scale multi-center prospective studies are warranted to validate these results.
Integrating Molecular Diagnostics and GIS Mapping: A Multidisciplinary Approach to Understanding Tuberculosis Disease Dynamics in South Africa Using Xpert MTB/RIF
Authors: Scott Lesley Erica , Shapiro Anne Nicole , Da Silva Manuel Pedro , Tsoka Jonathan , Jacobson Karen Rita , Emch Michael , Moultrie Harry , Jenkins Helen Elizabeth , Moore David , Van Rie Annelies , Stevens Wendy Susan
Published: October 2023

An investigation was carried out to examine the use of national Xpert MTB/RIF data (2013–2017) and GIS technology for MTB/RIF surveillance in South Africa. The aim was to exhibit the potential of using molecular diagnostics for TB surveillance across the country. The variables analysed include Mycobacterium tuberculosis (Mtb) positivity, the mycobacterial proportion of rifampicin-resistant Mtb (RIF), and probe frequency. The summary statistics of these variables were generated and aggregated at the facility and municipal level. The spatial distribution patterns of the indicators across municipalities were determined using the Moran’s I and Getis Ord (Gi) statistics. A case-control study was conducted to investigate factors associated with a high mycobacterial load. Logistic regression was used to analyse this study’s results. There was striking spatial heterogeneity in the distribution of Mtb and RIF across South Africa. The median patient age, urban setting classification, and number of health care workers were found to be associated with the mycobacterial load. This study illustrates the potential of using data generated from molecular diagnostics in combination with GIS technology for Mtb surveillance in South Africa. Spatially targeted interventions can be implemented in areas where high-burden Mtb persists.
FedEHR: A Federated Learning Approach towards the Prediction of Heart Diseases in IoT-Based Electronic Health Records
Authors: Bebortta Sujit , Tripathy Subhranshu Sekhar , Basheer Shakila , Chowdhary Chiranji Lal
Published: October 2023

In contemporary healthcare, the prediction and identification of cardiac diseases is crucial. By leveraging the capabilities of Internet of Things (IoT)-enabled devices and Electronic Health Records (EHRs), the healthcare sector can largely benefit to improve patient outcomes by increasing the accuracy of disease prediction. However, protecting data privacy is essential to promote participation and adhere to rules. The suggested methodology combines EHRs with IoT-generated health data to predict heart disease. For its capacity to manage high-dimensional data and choose pertinent features, a soft-margin L1-regularised Support Vector Machine (sSVM) classifier is used. The large-scale sSVM problem is successfully solved using the cluster primal–dual splitting algorithm, which improves computational complexity and scalability. The integration of federated learning provides a cooperative predictive analytics methodology that upholds data privacy. The use of a federated learning framework in this study, with a focus on peer-to-peer applications, is crucial for enabling collaborative predictive modeling while protecting the confidentiality of each participant’s private medical information.
S100 Proteins in the Pathogenesis of Psoriasis and Atopic Dermatitis
Authors: Saito-Sasaki Natsuko , Sawada Yu
Published: October 2023

The skin, the outermost layer of the human body, is exposed to various external stimuli that cause inflammatory skin reactions. These external stimulants trigger external epithelial cell damage and the release of intracellular substances. Following cellular damage or death, intracellular molecules are released that enhance tissue inflammation. As an important substance released from damaged cells, the S100 protein is a low-molecular-weight acidic protein with two calcium-binding sites and EF-hand motif domains. S100 proteins are widely present in systemic organs and interact with other proteins. Recent studies revealed the involvement of S100 in cutaneous inflammatory disorders, psoriasis, and atopic dermatitis. This review provides detailed information on the interactions among various S100 proteins in inflammatory diseases.
Cultural Awareness in Pre-Service Early Childhood Teacher Training: A Catalogue of British Cultural Elements in Peppa Pig
Authors: Estrada-Chichón José Luis , Sánchez-Cabrero Roberto
Published: October 2023

Foreign language teaching should integrate the culture embodied in the target language. However, raising cultural awareness does not systematically produce the intended effects when considered an integral component in the teaching context. This quantitative research study focuses on creating a catalogue featuring elements representative of British culture in the animated television series Peppa Pig as part of pre-service early childhood education teacher training in English as a Foreign Language (EFL). This prompts the examination of the potential of Peppa Pig to not exclusively enhance EFL proficiency but to foster a comprehensive understanding of British culture for non-native speakers. Eleven pre-service teachers at the University of Cádiz, Spain, analysed the 52 episodes of Peppa Pig’s season 1 and classified all elements into 13 categories, according to the Qualitative Text Analysis approach. To minimise differences between evaluators, each element of each episode was only checked if at least three evaluators agreed; therefore, 1050 elements were identified, with 501 elements verified in 48 of the 52 episodes. The resulting catalogue contributes to selecting the most significant Peppa Pig’s season 1 episodes concerning British culture elements. The major limitation of the investigation may be the fatigue experienced by the evaluators.
Teaching Complex Introductory Concepts in a Sophomore Circuits Course: A Descriptive Case Study
Authors: Pitterson Nicole
Published: October 2023

This descriptive case study explores the teaching and learning of complex introductory circuit concepts in a compulsory sophomore circuits’ course. The study investigates the instructional strategies employed by the instructor to facilitate students’ understanding of intricate circuit phenomena. Data were collected through classroom observations, interviews with the instructor, and an analysis of the course documents. The findings shed light on the challenges encountered by students when grappling with introductory circuit concepts, the effectiveness of different instructional methods, and implications for curriculum design and pedagogical approaches in electrical engineering education. Specifically, the instructors reported students’ prior knowledge, the nature of the content, and the structure of the course itself as some of the main features that impact students’ overall learning of the content. The study highlights the importance of providing targeted support and scaffolding to students, promoting active learning strategies, and incorporating practical applications to enhance the comprehension of introductory circuit concepts in sophomore-level electrical engineering courses.
Mathematics, Learning Disabilities, and Learning Styles: A Review of Perspectives Published by the National Council of Teachers of Mathematics
Authors: Joswick Candace , Skultety Lisa , Olsen Amanda A.
Published: October 2023

Learning styles is the idea that there are unique ways in which individuals approach learning and process information. Though refuted, the idea of learning styles has not declined in peer-reviewed reports of empirical studies or teacher/practitioner resources. Some reports have also used learning styles as a tool for improving the mathematics education of students with learning disabilities—an area of interest for mathematics education and special education communities alike. In this paper, we review articles published by the National Council of Teachers of Mathematics to investigate the perspectives of learning styles at the intersection of mathematics education and learning disabilities. Analyses highlight the relationship between mathematics education, learning disabilities, and learning styles, and the varied meanings and perspectives of the articles’ authors. Of note is both the perpetuation of unfounded concepts and the lackluster response to explicit contests of the idea of learning styles.
Research on a Permanent Magnet Synchronous Motor Sensorless Anti-Disturbance Control Strategy Based on an Improved Sliding Mode Observer
Authors: Du Shenhui , Liu Yang , Wang Yao , Li Ying , Yan Zhibang
Published: October 2023

This paper designs an improved sliding mode observer (ISMO) compound control scheme combined with a disturbance observer to solve the chattering and anti-disturbance problems of the traditional sliding mode observer (SMO) for permanent magnet synchronous motor (PMSM) in a sensorless control system. First, the sign function is replaced by an exponential type input function, and the fuzzy control rules are developed to automatically regulate the boundary layer control coefficient of the exponential input function, thereby changing the convergence characteristics of the exponential input function and improving the system observation accuracy. Then, the integral sliding mode surface and the quadratic radical term function of the square of the state variable are introduced to reduce system chattering. The proposed ISMO is proved using Lyapunov’s law to guarantee the whole system is stable. Based on the exponential input function and the integral sliding surface, an improved sliding mode disturbance observer (ISMDO) is constructed as a feed-forward compensator, which can optimize the dynamic performance of the improved observation system and ensure the strong robustness of the system by compensating the q-axis current. Finally, MATLAB/Simulink simulation and experimental platform verification have been carried out, which confirms the feasibility of the proposed composite control scheme.
Digital Restoration and 3D Virtual Space Display of Hakka Cardigan Based on Optimization of Numerical Algorithm
Authors: Yu Qianqian , Zhu Guangzhou
Published: October 2023

The Hakka cardigan stands as a quintessential representation of traditional Hakka attire, embodying not only the rich cultural heritage of a nation but also serving as a global cultural treasure. In this academic paper, we focus on a representative model to showcase the development of an autonomous 3D scanning system founded on an offline point cloud generation algorithm. Through a meticulous process involving the emulation of clothing pattern restoration, we employ a diverse array of software tools including Photoshop, Autodesk Maya, and CORELDRAW, harnessing graphic and image processing techniques to seamlessly transition from two-dimensional pattern restoration to a three-dimensional realm. This study revolves around the establishment of an autonomous 3D scanning system centered on a representative model, leveraging an offline point cloud generation algorithm. We incorporate the La-place mesh deformation algorithm to execute conformal transformations on neighboring vertices of motion vertices, while delving into the fundamental methodologies behind digital restoration and the three-dimensional virtual presentation of Hakka cardigans. Our experiments culminate in the measurement of six three-dimensional clothing pieces, revealing absolute deviation between the model and the actual clothing. Furthermore, when we compare the automatic measurements from 200 3D scanned human bodies with their manually obtained counterparts, the displayed measurement error hovers at approximately 0.5 cm. This research endeavor charts an expedited pathway to achieve digital restoration and three-dimensional virtual representation of Hakka cardigans. It not only offers a novel perspective for the digital revitalization of traditional clothing but also serves as a valuable augmentation to contemporary methods of preserving traditional clothing.
SoC-VRP: A Deep-Reinforcement-Learning-Based Vehicle Route Planning Mechanism for Service-Oriented Cooperative ITS
Authors: Hou Boyuan , Zhang Kailong , Gong Zu , Li Qiugang , Zhou Junle , Zhang Jiahao , de La Fortelle Arnaud
Published: October 2023

With the rapid development of emerging information technology and its increasing integration with transportation systems, the Intelligent Transportation System (ITS) is entering a new phase, called Cooperative ITS (C-ITS). It offers promising solutions to numerous challenges in traditional transportation systems, among which the Vehicle Routing Problem (VRP) is a significant concern addressed in this work. Considering the varying urgency levels of different vehicles and their different traveling constraints in the Service-oriented Cooperative ITS (SoC-ITS) framework studied in our previous research, the Service-oriented Cooperative Vehicle Routing Problem (SoC-VRP) is firstly analyzed, in which cooperative planning and vehicle urgency degrees are two vital factors. After examining the characteristics of both VRP and SoC-VRP, a Deep Reinforcement Learning (DRL)-based prioritized route planning mechanism is proposed. Specifically, we establish a deep reinforcement learning model with Rainbow DQN and devise a prioritized successive decision-making route planning method for SoC-ITS, where vehicle urgency degrees are mapped to three priorities: High for emergency vehicles, Medium for shuttle buses, and Low for the rest. All proposed models and methods are implemented, trained using various scenarios on typical road networks, and verified with SUMO-based scenes. Experimental results demonstrate the effectiveness of this hybrid prioritized route planning mechanism.
Personal Identification Using Long Short-Term Memory with Efficient Features of Electromyogram Biomedical Signals
Authors: Byeon Yeong-Hyeon , Kwak Keun-Chang
Published: October 2023

This study focuses on personal identification using bidirectional long short-term memory (LSTM) with efficient features from electromyogram (EMG) biomedical signals. Personal identification is performed by comparing and analyzing features that can be stably identified and are not significantly affected by noise. For this purpose, 13 efficient features, such as enhanced wavelength, zero crossing, and mean absolute value, were obtained from EMG signals. These features were extracted from segmented signals of a specific length. Then, the bidirectional LSTM was trained on the selected features as sequential data. The features were ranked based on their classification performance. Finally, the most effective features were selected, and the selected features were connected to achieve an improved classification rate. Two public EMG datasets were used to evaluate the proposed model. The first database was acquired from eight-channel Myo bands and was composed of EMG signals from 10 varying motions of 50 individuals. The total numbers of segments for the training and test sets were 30,000 and 20,000, respectively. The second dataset consisted of ten arm motions acquired from 40 individuals. A performance comparison of the dataset revealed that the proposed method exhibited good performance and efficiency compared to other well-known methods.
Investigation of Spindt Cold Cathode Electron Guns for Terahertz Traveling Wave Tubes
Authors: Li Yongtao , Li Hanyan , Feng Jinjun
Published: October 2023

In this work, a Spindt cold cathode electron gun with a PPM (periodic permanent magnet) focusing system for a terahertz TWT (traveling wave tube) was designed and simulated based on the Pierce electron gun structure. More specifically, a new 3D (three dimensional) emission model was used, where the cathode radius of the electron gun was 1 mm and the cathode current was 30 mA, with an emitting half angle of about 28°. It was demonstrated that the electron beam was well focused with an electron beam radius of 0.3 mm and a filling ratio of 0.5 when the maximum value of the PPM field along with the axis was 0.122T. According to the simulation results, a planar cold cathode electron gun was developed. Measurements demonstrated that the I/V characteristics of the cold cathode gun were consistent with that of a cold cathode, revealing that the electrons emitted from the cathode are not intercepted when passing through the electron gun.
Point-of-Interest Recommendations Based on Immediate User Preferences and Contextual Influences
Authors: Li Jingwen , Yang Yi , Gong Xu , Jiang Jianwu , Lu Yanling , Lu Jinjin , Xie Shaoshao
Published: October 2023

With the development of various location-based social networks (LSBNs), personalized point-of-interest (POI) recommendations have become a recent research hotspot. Current recommendation methods tend to mine user preferences from their historical check-in records but overlook interest deviations caused by real-time geographic environments and immediate interests present in the records, failing to meet users’ real-time and accurate needs. Therefore, this paper proposes a composite preference-based recommendation model (CPRM) for personalized POI recommendation. This method first extracts multi-factor contextual features, constructs a dual-layer attention network (DLAN) to capture long and short-term preferences, combines real-time geographic scenarios to uncover user immediate preferences, and then weights and fuses these three types of preferences to generate user composite preferences. Finally, a prediction function is employed to obtain the Top-N recommendation list. The experiments on two classic datasets, Foursquare and Gowalla, affirm the effectiveness of the model presented in this paper and offer a novel approach for providing personalized POI recommendations to users.
An Efficient Path Planning Method for the Unmanned Aerial Vehicle in Highway Inspection Scenarios
Authors: Li Yuanlong , Gao Shang , Liu Xuewen , Zuo Peiliang , Li Haoliang
Published: October 2023

Unmanned aerial vehicles (UAVs) have received widespread attention due to their flexible deployment characteristics. Automated airports equipped with UAVs are expected to become important equipment for improving quality and reducing costs in many inspection scenarios. This paper focuses on the automated inspection business of UAVs dispatched by automated airports in highway scenarios. On the basis of considering the shape of highway curves, inspection targets, and the energy consumption characteristics of UAVs, planning the flight parameters of UAVs is of great significance for ensuring the effectiveness of the inspection process. This paper first sets the inspection path points for the UAV based on highway curves, and then proposes an efficient heuristic method for the nonlinear non-convex parameter optimization problem, through which the parameters of the UAV’s inspection altitude, hovering altitude, and flight speed are planned. Simulation and analysis show that the proposed method possesses good parameter planning efficiency. By combining several existing trajectory planning methods, e.g., the traversal method, the deep Q-network based method, and the genetic method, it can be concluded that the proposed method in this paper has better overall planning performance including planning efficiency and inspection effectiveness.
Feature-Based Gait Pattern Modeling on a Treadmill
Authors: Shin Woo-Chul , Kim Min-Jung , Han Ji-Hun , Cho Hyun-Sang , Hong Youn-Sik
Published: October 2023

In this paper, we present a method of gait analysis on a treadmill based on pressure distribution. We aimed to model the gait patterns of a subject walking at a constant speed on a treadmill based on differences in current consumption. The changes in current consumption were converted into pressure distribution curves, and then specific features were extracted. The extracted features were used to model the walking pattern on a treadmill. To verify the validity of our proposed feature-based gait pattern modeling, we conducted experiments by gender, age, BMI (body mass index), and step-to-step symmetry. The experimental results showed that the heavier the subject, the higher the value of each feature. In particular, our feature point-based gait modeling provides an index that can help determine whether a subject’s gait is abnormal, depending on the difference between the features.
Accuracy Analysis of Visual Odometer for Unmanned Rollers in Tunnels
Authors: Huang Hao , Wang Xuebin , Hu Yongbiao , Tan Peng
Published: October 2023

Rollers, integral to road construction, are undergoing rapid advancements in unmanned functionality. To address the specific challenge of unmanned compaction within tunnels, we propose a vision-based odometry system for unmanned rollers. This system solves the problem of tunnel localization under conditions of low texture and high noise. We evaluate and compare the performance of various feature extraction and matching methods, followed by the application of random sample consensus (RANSAC) to eliminate false matches. Subsequently, Perspective-n-Points (PnP) was employed to establish a minimal-error analysis for pose estimation and trajectory analysis. The findings reveal that binary robust invariant scalable key points (BRISK) exhibits larger errors due to fewer correctly matched feature points, while scale invariant feature transform (SIFT) falls short of real-time requirements. Compared to Oriented FAST and Rotated BRIEF (ORB) and the direct method, the maximum relative error and the median error between the compaction trajectory estimated by speed-up robust features (SURF) and the actual trajectory were the smallest. Consequently, the unmanned rollers employing SURF + PnP improved the accuracy and robustness. This research contributes valuable insights to the development of autonomous road construction equipment, particularly in challenging tunnels.
Research on Automatic Vertical Parking Path-Planning Algorithms for Narrow Parking Spaces
Authors: Wu Yanfeng , Li Xuan , Gao Jianping , Yang Xinling
Published: October 2023

Narrow parking spaces pose difficulties in path planning and spot turning caused by sudden changes and discontinuities in path curvature. To address these problems, this paper investigates the performance of three path-planning algorithms and proposes a path-optimization algorithm. First, a narrow parking space is defined based on single-step parking using the arc-line combination parking algorithm. Second, to compare the arc-line combination algorithm, Hybrid A* algorithm, and particle swarm optimization parking algorithm with respect to different narrow parking spaces, a multi-objective evaluation function is proposed, including three evaluation indicators, namely, the path length, the number of positive and negative conversions of vehicle speed, and the smoothness of the path. Their performance is compared using a simulation conducted in MATLAB. With the same starting point and different parking space widths, the three algorithms are simulated to generate different planned paths. Then, the evaluation indices are obtained to compare the performance of the algorithms based on the multi-objective function, the values of which indicate the fitness of the algorithm in a narrow parking environment. The results show that the Hybrid A* algorithm is better than the others for narrow parking spaces. Third, to smooth the planning path, a path optimization algorithm based on the cubic B-spline curve and gradient descent is proposed. Finally, the results of a simulation conducted on the proposed algorithm and the Hybrid A* algorithm are provided: the average minimum curvature of the path was reduced by 0.005 m−1, and the path meets the requirements of the minimum turning radius constraint of the analyzed vehicle. The results show that the proposed algorithm can effectively eliminate the curvature mutation point and constrain the path curvature to meet the requirements of a smooth path.
Hybrid Heat Pump Performance Evaluation in Different Operation Modes for Single-Family House
Authors: Tihana Jelena , Ali Hesham , Apse Jekaterina , Jekabsons Janis , Ivancovs Dmitrijs , Gaujena Baiba , Dedov Andrei
Published: October 2023

Hybrid heat pump (HHP) represents a heating system (HS) that simultaneously utilises two or more energy sources. The key novelty is the integration of an optimised control strategy, effectively maximising the efficiency of both the heat pump and gas boiler segments. In this study, a HHP system that consists of an air-source heat pump (ASHP) and a condensing-type gas boiler (GB) for a two-story single-family house was calculated and validated. The results from three different calculation methods were obtained: the heat pump manufacturer’s calculator, the simulator programme, and the calculations based on real measured data. Two operation modes were tested: economic mode, where the cheapest energy resource becomes the priority, and ecological mode, where the system operates using the energy resource with lowest CO2 emissions. When comparing consumed energy, there was a 15.36% variance between the manufacturer’s program and the actual measured data, while for produced energy, the difference amounted to 25.81%. It was found that the balance point temperature is −7 °C, where the heat pump unit of the HHP system can cover necessary heat losses until that point, while the gas boiler operates at lower temperatures. Changes in electricity price can significantly influence the point of the system switch, but the possibility to cover heat loads of the heat pump unit always has to be taken into account.
Higher Electrical Conductivity of Functionalized Graphene Oxide Doped with Silver and Copper (II) Ions
Authors: Pereira Nelson Gustavo Alves , Gonzaléz Maria Elena Leyva , Queiroz Alvaro Antonio Alencar de , Oliveira Adhimar Flávio , Tavares Wanderley Neto Estácio
Published: October 2023

This study presents a new methodology for graphene oxide (GO) synthesis through electrochemical exfoliation of graphite, followed by phthalic anhydride functionalization (PhA-GO) and doping with Cu2+ and Ag+ ions. The synthesis of GO involved the use of an electrochemical cell with H2SO4 as the electrolyte, with a gradual increase in potential from 2.3 V to 10 V. Extensive characterization techniques confirmed the successful incorporation of oxygen-containing functional groups, verifying the oxidation of graphite. PhA-GO functionalization was confirmed by thermogravimetric analysis, Differential Scanning Calorimetry, Fourier-transform infrared spectroscopy (FTIR), UV-Vis spectroscopy, X-ray diffraction, scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDX), which confirmed the presence of Cu2+ and Ag+ ions. The Scherrer equation determined a grain size of 75.85 nm for GO. The electrical properties exhibited semiconductor and semimetal behavior, particularly in PhA-GO/Ag+ composites, making them suitable for electronic devices over a wide temperature range, presenting a promising pathway for advanced materials in electronic applications.
Numerical Investigation of Aerodynamic Performance and Structural Analysis of a 3D J-Shaped Based Small-Scale Vertical Axis Wind Turbine
Authors: Bel Laveda Oriol , Roche Marie-Alix , Phadtare Mohit , Sauge Louise , Xavier Keerthana Jonnafer , Bhat Grishma , Saxena Divya , Saini Jagmeet Singh , Verdin Patrick G.
Published: October 2023

Small vertical axis wind turbines (VAWTs) are often considered suitable for use in urban areas due to their compact design. However, they are also well known to offer poor performance at low wind speeds, which is a common situation in such environments. An optimised 3D J-shaped VAWT was designed from standard NACA 0015 blades and analysed numerically through computational fluid dynamics (CFD). A finite element analysis (FEA) was also carried out to ensure the model’s structural integrity. Optimal results were obtained with aluminium alloy hollow blades and stainless-steel struts with X-shaped beams, with internal ribs. Numerical results showed that the J-shaped VAWT achieved an 18.34% higher moment coefficient compared to a NACA 0015-based VAWT, indicating better self-starting abilities.
Utilization of Biowaste for Sustainable Production of Coal Briquettes
Authors: Khan Amad Ullah , Jan Qazi Muhammad Usman , Abas Muhammad , Muhammad Khan , Ali Qazi Muhammad , Zimon Dominik
Published: October 2023

In energy scarcity, particularly in Agri-based developing economies, bio-coal briquetting is the most suitable means of meeting sustainable energy needs utilizing agricultural waste. In this study, briquettes were made from an indigenously designed briquetting machine for investigating coal–biomass proportion blend using coal from Dara Adam Khel, Khyber Pakhtunkhwa in Pakistan, and pomegranate/olive waste to analyze their resulting calorific value, strength, and geochemical properties. A central composite design (CCD) and response surface methodology (RSM) were employed to design the experiments and analyze the data. Regression models were developed for each biomass type, demonstrating their adequacy and reliability for further analysis and prediction. Energy Dispersive X-ray Spectroscopy (EDX) analysis provided insights into the elemental composition of the coal briquettes. Mechanical analysis was performed to assess the strength of the briquettes, with varying compositions showing different levels of strength. Optimization using a composite desirability function yielded an optimal calorific value of 6728 kJ/kg. In summary, this study underscores the viability of bio-coal briquetting as a transformative solution to alleviate energy scarcity. Repurposing agricultural waste curtails resource depletion while mitigating waste disposal challenges. The optimized calorific value aligns with eco-friendly energy initiatives, advancing a greener path toward energy security.
Computational Study of Deflagration-to-Detonation Transition in a Semi-Confined Slit Combustor
Authors: Ivanov Vladislav S. , Shamshin Igor O. , Frolov Sergey M.
Published: October 2023

Systematic three-dimensional numerical simulations of flame acceleration and deflagration-to-detonation transition (DDT) in a semi-confined flat slit combustor are performed. The combustor is assumed to be partly filled with the stoichiometric ethylene–oxygen mixture at normal pressure and temperature conditions. The objective of the study is to reveal the conditions for DDT in terms of the minimum height of the combustible mixture layer in the slit, the maximum dilution of the mixture with nitrogen and the maximum slit width. The results of the calculations are compared with the available experimental data. The calculation results are shown to agree satisfactorily with the experimental data on the slit-filling dynamics, flame structure, the occurrence of the preflame self-ignition center, DDT, and detonation propagation. DDT occurs in the layer at a time instant when the flame accelerates to a velocity close to 750 m/s. DDT occurs near the slit bottom due to the formation of the self-ignition center ahead of the leading edge of the flame as a result of shock wave reflections from the walls of injector holes at the slit bottom and from the corners of the conjugation of the slit bottom and side walls. The decrease in the height of the mixture layer, the dilution of the mixture with nitrogen, and the increase in the slit width are shown to slow down flame acceleration in the slit and increase the DDT run-up distance and time until DDT failure. The obtained results are important for determining the conditions for mild initiation of detonation via DDT in semi-confined annular RDE combustors.
Improving Directional Overcurrent Relay Coordination in Distribution Networks for Optimal Operation Using Hybrid Genetic Algorithm with Sequential Quadratic Programming
Authors: Al-Bhadely Faraj , İnan Aslan
Published: October 2023

In recent years, with the growing popularity of smart microgrids in distribution networks, the effective coordination of directional overcurrent relays (DOCRs) has presented a significant challenge for power system operators due to the intricate and nonlinear nature of their optimization model. Hence, this study proposes a hybrid GA-SQP algorithm to enhance the coordination of directional overcurrent relays (DOCRs) in radial and non-radial interconnected distributed power networks. The proposed approach combines the advantages of both the genetic algorithm (GA) and sequential quadratic programming (SQP) methods to optimize the objective function of relay coordination in the best manner. Thus, the proposed hybrid techniques improved the convergence of the problem and increased the likelihood of obtaining a globally optimal solution. Finally, to validate the effectiveness of the proposed algorithm, it was tested through three case studies involving the IEEE 3-Bus, 8-Bus, and modified 30-Bus distribution networks. In addition, the results were compared to those obtained using previous methods. The results obtained from the comparison of the proposed method and recent advanced research indicate that the proposed optimization approach is preeminent in terms of accuracy and total operating time as well as the continuity of the minimum margin time requirements between the primary/backup relay pairs.
Beat the Heat: Signaling Pathway-Mediated Strategies for Plant Thermotolerance
Authors: Cao Zidan , Wang Enbo , Xu Xinyi , Tong Chenheng , Zhao Xia , Song Xiqiang , Wang Jian , Wang Hou-ling , Xia Xinli , Zhao Ying
Published: October 2023

The frequent high temperatures caused by climate change have a very adverse impact on the growth and development of plants at different growth stages. Almost all cellular processes in plants are highly sensitive to high temperatures, but plants have their unique heat-resistant strategies. The plasma membrane usually senses temperature changes through changes in membrane fluidity. The accumulation of damaged proteins and reactive oxygen species in biofilms also helps calcium ions and thermal sensors cascade signals to transcription factors, thereby resisting high temperatures. There are also misfolded proteins in the endoplasmic reticulum and cytoplasm due to heat stress, which act as heat conduction signals. Carbohydrates commonly found in organisms can also serve as signaling molecules and participate in heat stress response. Heat shock transcription factor can effectively regulate the expression of heat-induced genes, producing heat shock proteins to maintain intracellular homeostasis.
Dynamic Changes and Correlation Analysis of Polysaccharide Content and Color Parameters in Glycyrrhiza Stems and Leaves during Fermentation
Authors: Du Juan , Song Yifeng , Li Xia , Liu Na , An Xiaoping , Qi Jingwei
Published: October 2023

Fermentation can increase the concentration of active ingredients and improve the effectiveness of Chinese herbal medicine. The purpose of this study was to investigate the effect of solid-state fermentation (SSF) on the polysaccharide content and color of Glycyrrhiza stems and leaves, as well as to explore the potential of computer vision-based analytical chemistry for the rapid, non-destructive, and accurate quality identification of fermented herbs. The effects of different inoculation rates on the polysaccharide content and color of fermented Glycyrrhiza stems and leaves were evaluated. Subsequently, dynamic changes in the viable counts of the probiotic strains, pH values, polysaccharide content, and color of Glycyrrhiza stems and leaves were explored during the entire fermentation process. The correlations of color variables that were extracted from the images with key quality indicators of the Glycyrrhiza stem and leaf samples were verified. The results showed that with an increase in inoculation amount, the polysaccharide content demonstrated a trend of first increasing and then decreasing, which was consistent with the color parameter behavior, and the optimal inoculation amount was 0.2%. During fermentation, R, G, B, S, V, L, a*, and B* were significantly correlated with the polysaccharide content (p < 0.01), while the correlation of H was weak. Principal component analysis (PCA) based on color variables can effectively distinguish between different stages of fermentation. This study provides a reference for the rapid and nondestructive analysis of fermented Glycyrrhiza stems and leaves, offering a new approach to process monitoring and quality control of fermented herbs.
Data-Driven Safe Deliveries: The Synergy of IoT and Machine Learning in Shared Mobility
Authors: Elwy Fatema , Aburukba Raafat , Al-Ali A. R. , Nabulsi Ahmad Al , Tarek Alaa , Ayub Ameen , Elsayeh Mariam
Published: October 2023

Shared mobility is one of the smart city applications in which traditional individually owned vehicles are transformed into shared and distributed ownership. Ensuring the safety of both drivers and riders is a fundamental requirement in shared mobility. This work aims to design and implement an adequate framework for shared mobility within the context of a smart city. The characteristics of shared mobility are identified, leading to the proposal of an effective solution for real-time data collection, tracking, and automated decisions focusing on safety. Driver and rider safety is considered by identifying dangerous driving behaviors and the prompt response to accidents. Furthermore, a trip log is recorded to identify the reasons behind the accident. A prototype implementation is presented to validate the proposed framework for a delivery service using motorbikes. The results demonstrate the scalability of the proposed design and the integration of the overall system to enhance the rider’s safety using machine learning techniques. The machine learning approach identifies dangerous driving behaviors with an accuracy of 91.59% using the decision tree approach when compared against the support vector machine and K-nearest neighbor approaches.
The Development of Highly pH-Sensitive Bacterial Cellulose Nanofibers/Gelatin-Based Intelligent Films Loaded with Anthocyanin/Curcumin for the Fresh-Keeping and Freshness Detection of Fresh Pork
Authors: Zhou Siyu , Li Nan , Peng Haonan , Yang Xingbin , Lin Dehui
Published: October 2023

The aim of this study was to develop highly pH-sensitive bacterial cellulose nanofibers/gelatin-based intelligent films, where the intelligent films were loaded with different ratios (10:0, 0:10 2:8, 5:5 and 8:2, w/w) of curcumin:anthocyanin (Cur/ATH), and the characterization of intelligent films was investigated. The results showed that the microstructures of intelligent films were much rougher as the proportion of curcumin increased. FTIR results showed that anthocyanin and curcumin were fixed in gelatin matrix by hydrogen bonds. Moreover, XRD results showed that curcumin had a significant effect on the crystal structure of the films. Interestingly, films loaded with a Cur/ATH ratio of 5:5 had the best mechanical and antioxidant properties and a high pH-sensitivity property. Consequently, the bacterial cellulose nanofibers/gelatin-based intelligent films loaded with a Cur/ATH ratio of 5:5 were used for the packaging of fresh pork, displaying good fresh-keeping and freshness detection effects. Therefore, this study suggested that bacterial cellulose nanofibers/gelatin-based intelligent films have great potential in the fresh-keeping and freshness detection of meat.