bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Characterization of Nylon Composites Functional Material Filled with Al2O3 Particle
Authors: Chen Jibing , Liu Bowen , Hu Maohui , Shi Qianyu , Chen Junsheng , Yang Junsheng , Wu Yiping
Published: May 2023

This study revolves around the issues raised by the current semiconductor device metal casings (mainly composed of aluminum and its alloys), such as resource and energy consumption, complexity of the production process, and environmental pollution. To address these issues, researchers have proposed an eco-friendly and high-performance alternative material—Al2O3 particle-filled nylon composite functional material. This research conducted detailed characterization and analysis of the composite material through scanning electron microscopy (SEM) and differential scanning calorimetry (DSC). The results show that the Al2O3 particle-filled nylon composite material has a significantly superior thermal conductivity, about twice as high as that of pure nylon material. Meanwhile, the composite material has good thermal stability, maintaining its performance in high-temperature environments above 240 °C. This performance is attributed to the tight bonding interface between the Al2O3 particles and the nylon matrix, which not only improves the heat transfer efficiency but also significantly enhances the material’s mechanical properties, with a strength of up to 53 MPa. This study is of great significance, aiming to provide a high-performance composite material that can alleviate resource consumption and environmental pollution issues, with excellent polishability, thermal conductivity, and moldability, which is expected to play a positive role in reducing resource consumption and environmental pollution problems. In terms of potential applications, Al2O3/PA6 composite material can be widely used in heat dissipation components for LED semiconductor lighting and other high-temperature heat dissipation components, thereby improving product performance and service life, reducing energy consumption and environmental burden, and laying a solid foundation for the development and application of future high-performance eco-friendly materials.
Polyvinylidene Fluoride/Aromatic Hyperbranched Polyester of Third-Generation-Based Electrospun Nanofiber as a Self-Powered Triboelectric Nanogenerator for Wearable Energy Harvesting and Health Monitoring Applications
Authors: Gunasekhar Ramadasu , Sathiyanathan Ponnan , Reza Mohammad Shamim , Prasad Gajula , Prabu Arun Anand , Kim Hongdoo
Published: May 2023

Flexible pressure sensors have played an increasingly important role in the Internet of Things and human–machine interaction systems. For a sensor device to be commercially viable, it is essential to fabricate a sensor with higher sensitivity and lower power consumption. Polyvinylidene fluoride (PVDF)-based triboelectric nanogenerators (TENGs) prepared by electrospinning are widely used in self-powered electronics owing to their exceptional voltage generation performance and flexible nature. In the present study, aromatic hyperbranched polyester of the third generation (Ar.HBP-3) was added into PVDF as a filler (0, 10, 20, 30 and 40 wt.% w.r.t. PVDF content) to prepare nanofibers by electrospinning. The triboelectric performances (open-circuit voltage and short-circuit current) of PVDF-Ar.HBP-3/polyurethane (PU)-based TENG shows better performance than a PVDF/PU pair. Among the various wt.% of Ar.HBP-3, a 10 wt.% sample shows maximum output performances of 107 V which is almost 10 times that of neat PVDF (12 V); whereas, the current slightly increases from 0.5 μA to 1.3 μA. The self-powered TENG is also effective in measuring human motion. Overall, we have reported a simpler technique for producing high-performance TENG using morphological alteration of PVDF, which has the potential for use as mechanical energy harvesters and as effective power sources for wearable and portable electronic devices.
On the Thermomechanical Behavior of 3D-Printed Specimens of Shape Memory R-PETG
Authors: Sava Ștefan-Dumitru , Lohan Nicoleta-Monica , Pricop Bogdan , Popa Mihai , Cimpoeșu Nicanor , Comăneci Radu-Ioachim , Bujoreanu Leandru-Gheorghe
Published: May 2023

From commercial pellets of recycled polyethylene terephthalate glycol (R-PETG), 1.75 mm diameter filaments for 3D printing were produced. By varying the filament’s deposition direction between 10° and 40° to the transversal axis, parallelepiped specimens were fabricated by additive manufacturing. When bent at room temperature (RT), both the filaments and the 3D-printed specimens recovered their shape during heating, either without any constraint or while lifting a load over a certain distance. In this way, free-recovery and work-generating shape memory effects (SMEs) were developed. The former could be repeated without any visible fatigue marks for as much as 20 heating (to 90 °C)-RT cooling–bending cycles, while the latter enabled the lifting of loads over 50 times heavier than the active specimens. Tensile static failure tests revealed the superiority of the specimens printed at larger angles over those printed at 10°, since the specimens printed at 40° had tensile failure stresses and strains over 35 MPa and 8.5%, respectively. Scanning electron microscopy (SEM) fractographs displayed the structure of the successively deposited layers and a shredding tendency enhanced by the increase in the deposition angle. Differential scanning calorimetry (DSC) analysis enabled the identification of the glass transition between 67.5 and 77.3 °C, which might explain the occurrence of SMEs in both the filament and 3D-printed specimens. Dynamic mechanical analysis (DMA) emphasized a local increase in storage modulus of 0.87–1.66 GPa that occurred during heating, which might explain the development of work-generating SME in both filament and 3D-printed specimens. These properties recommend 3D-printed parts made of R-PETG as active elements in low-price lightweight actuators operating between RT and 63 °C.
FDM 3D Printing and Soil-Burial-Degradation Behaviors of Residue of Astragalus Particles/Thermoplastic Starch/Poly(lactic acid) Biocomposites
Authors: Ni Zhibing , Shi Jianan , Li Mengya , Lei Wen , Yu Wangwang
Published: May 2023

Astragalus residue powder (ARP)/thermoplastic starch (TPS)/poly(lactic acid) (PLA) biocomposites were prepared by fused-deposition modeling (FDM) 3D-printing technology for the first time in this paper, and certain physico-mechanical properties and soil-burial-biodegradation behaviors of the biocomposites were investigated. The results showed that after raising the dosage of ARP, the tensile and flexural strengths, the elongation at break and the thermal stability of the sample decreased, while the tensile and flexural moduli increased; after raising the dosage of TPS, the tensile and flexural strengths, the elongation at break and the thermal stability all decreased. Among all of the samples, sample C—which was composed of 11 wt.% ARP, 10 wt.% TPS and 79 wt.% PLA—was the cheapest and also the most easily degraded in water. The soil-degradation-behavior analysis of sample C showed that, after being buried in soil, the surfaces of the samples became grey at first, then darkened, after which the smooth surfaces became rough and certain components were found to detach from the samples. After soil burial for 180 days, there was weight loss of 21.40%, and the flexural strength and modulus, as well as the storage modulus, reduced from 82.1 MPa, 11,922.16 MPa and 2395.3 MPa to 47.6 MPa, 6653.92 MPa and 1476.5 MPa, respectively. Soil burial had little effect on the glass transition, cold crystallization or melting temperatures, while it reduced the crystallinity of the samples. It is concluded that the FDM 3D-printed ARP/TPS/PLA biocomposites are easy to degrade in soil conditions. This study developed a new kind of thoroughly degradable biocomposite for FDM 3D printing.
Poly(Lactic Acid) Composites with Lignin and Nanolignin Synthesized by In Situ Reactive Processing
Authors: Makri Sofia P. , Xanthopoulou Eleftheria , Valera Miguel Angel , Mangas Ana , Marra Giacomo , Ruiz Víctor , Koltsakidis Savvas , Tzetzis Dimitrios , Zoikis Karathanasis Alexandros , Deligkiozi Ioanna , Nikolaidis Nikolaos , Bikiaris Dimitrios , Terzopoulou Zoi
Published: May 2023

Poly(lactic acid) (PLA) composites with 0.5 wt% lignin or nanolignin were prepared with two different techniques: (a) conventional melt-mixing and (b) in situ Ring Opening Polymerization (ROP) by reactive processing. The ROP process was monitored by measuring the torque. The composites were synthesized rapidly using reactive processing that took under 20 min. When the catalyst amount was doubled, the reaction time was reduced to under 15 min. The dispersion, thermal transitions, mechanical properties, antioxidant activity, and optical properties of the resulting PLA-based composites were evaluated with SEM, DSC, nanoindentation, DPPH assay, and DRS spectroscopy. All reactive processing-prepared composites were characterized by means of SEM, GPC, and NMR to assess their morphology, molecular weight, and free lactide content. The benefits of the size reduction of lignin and the use of in situ ROP by reactive processing were demonstrated, as the reactive processing-produced nanolignin-containing composites had superior crystallization, mechanical, and antioxidant properties. These improvements were attributed to the participation of nanolignin in the ROP of lactide as a macroinitiator, resulting in PLA-grafted nanolignin particles that improved its dispersion.
Toward a Circular Bioeconomy: Development of Pineapple Stem Starch Composite as a Plastic-Sheet Substitute for Single-Use Applications
Authors: Thongphang Chanaporn , Namphonsane Atitiya , Thanawan Sombat , Chia Chin Hua , Wongsagonsup Rungtiwa , Smith Siwaporn Meejoo , Amornsakchai Taweechai
Published: May 2023

Plastic waste poses a significant challenge for the environment, particularly smaller plastic products that are often difficult to recycle or collect. In this study, we developed a fully biodegradable composite material from pineapple field waste that is suitable for small-sized plastic products that are difficult to recycle, such as bread clips. We utilized starch from waste pineapple stems, which is high in amylose content, as the matrix, and added glycerol and calcium carbonate as the plasticizer and filler, respectively, to improve the material’s moldability and hardness. We varied the amounts of glycerol (20–50% by weight) and calcium carbonate (0–30 wt.%) to produce composite samples with a wide range of mechanical properties. The tensile moduli were in the range of 45–1100 MPa, with tensile strengths of 2–17 MPa and an elongation at break of 10–50%. The resulting materials exhibited good water resistance and had lower water absorption (~30–60%) than other types of starch-based materials. Soil burial tests showed that the material completely disintegrated into particles smaller than 1 mm within 14 days. We also created a bread clip prototype to test the material’s ability to hold a filled bag tightly. The obtained results demonstrate the potential of using pineapple stem starch as a sustainable alternative to petroleum-based and biobased synthetic materials in small-sized plastic products while promoting a circular bioeconomy.
Task Containerization and Container Placement Optimization for MEC: A Joint Communication and Computing Perspective
Authors: Liu Ao , Yang Shaoshi , Tan Jingsheng , Liang Zongze , Sun Jiasen , Wen Tao , Yan Hongyan
Published: May 2023

Containers are used by an increasing number of Internet service providers to deploy their applications in multi-access edge computing (MEC) systems. Although container-based virtualization technologies significantly increase application availability, they may suffer expensive communication overhead and resource use imbalances. However, so far there has been a scarcity of studies to conquer these difficulties. In this paper, we design a workflow-based mathematical model for applications built upon interdependent multitasking composition, formulate a multi-objective combinatorial optimization problem composed of two subproblems—graph partitioning and multi-choice vector bin packing, and propose several joint task-containerization-and -container-placement methods to reduce communication overhead and balance multi-type computing resource utilization. The performance superiority of the proposed algorithms is demonstrated by comparison with the state-of-the-art task and container scheduling schemes.
This Is Your Miḥrāb: Sacred Spaces and Power in Early Islamic North Africa—Al-Qayrawān as a Case Study
Authors: Albarrán Javier
Published: May 2023

Al-Qayrawān has long been figured, especially in the culture of the Islamic West, as the Islamic city par excellence, as the fourth sacred place after Mecca, Medina, and Jerusalem. The prominence of this garrison city—supposedly founded by ‘Uqba b. Nāfi‘ in the year 50/670–671—is undeniable in the traditional account of the Islamic conquest of Ifrīqiyya. Through a case study of al-Qayrawān and an analysis of the sources recounting its miraculous foundation as well as the construction of its mosque, this article aims to study the process of sacralisation of space, how this is inserted into a given context and related to power and its consolidation, particularly in times of political, cultural, and religious transition, and how it uses, appropriates, or eliminates the previous reality. To this end, the article provides a context for the creation of al-Qayrawān as a sacred space, which relates directly to the region’s Christian past and the construction of a new Islamic identity.
The Interplay of Rites and Customs: The Evolution and Regional Propagation of the Religion of Crown Prince Zhaoming
Authors: Sun Tinglin
Published: May 2023

Previous studies on the religion (xinyang 信仰) of Crown Prince Zhaoming 昭明太子, focused on the welcome ceremony of the Nuo deities 傩神 (the deities driving away the plague) and the historical figure of Crown Prince Zhaoming but on the other hand, overlooked the evolution from the folk or heterodox deity Jiulang Shen 九郎神 (Jiulang God) to the state-recognized or orthodox deity Crown Prince Zhaoming and the role of Song-era national policy of conferring titles and inscriptions upon deities in this process. This paper aims to illuminate the following five points: Firstly, the original deity upon which the religion of Crown Prince Zhaoming in Chizhou 池州 is based is Jiulang God, one of many deities in the Nuo religion imbued with rich elements of Wuism (wuxi 巫觋). The religion of Jiulang ascended to its peak during the Tang dynasty (618–907). Secondly, driven by the discourses of scholars, government officials and national rites during the Song dynasty (960–1276), Jiulang was transformed into Crown Prince Zhaoming through the conferment of titles and inscriptions, becoming an orthodox deity. Thirdly, Crown Prince Zhaoming and Jiulang God coexisted for a prolonged period, and this suggests that the rites–customs dichotomy was universally found in folk religions in traditional China. Fourthly, the proliferation of the religion of Crown Prince Zhaoming in western Anhui, Jiangxi, Jiangsu, Zhejiang and other regions of China reveals a mix of factors that led to the widespread and lasting prevalence of the religion. These factors include the deity’s role as a guardian of maritime voyages and merchants; a stable, enduring organizational structure for sacrificial rituals; and the dichotomous coexistence of rites and customs. This article reveals that from the Song Dynasty, the national system of rites permeated and impacted folk religions through official and academic discourses, propelling the latter’s continuing transformation into an orthodox form. Nevertheless, there remained spaces between the national system of rites and folk religions where “rites” and “customs” interacted, integrated and coexisted well. The interplay, fusion and peaceful coexistence between “rites” and “customs” is the normative state of folk religions in traditional society in China, as well as one of the key reasons why many folk religions continue to flourish and play a societal role.
“I’ll Bring You More Than a Song”: Toward a Reassessment of Methodology in the Study of Contemporary Praise and Worship
Authors: Ottaway Jonathan M.
Published: May 2023

In the recent study of Contemporary Praise and Worship (CPW), many studies have focused on musical repertory, including its text, music, and performance, as the foundational text(s) for theoretical analysis. In particular, scholars have relied on lists of the most popular songs that have been reported to Christian Copyright Licensing International (CCLI). This essay points out several critical weaknesses in the current overreliance on this methodology and instead contends for two underutilized methodologies—liturgical ethnography and liturgical history—that need to be developed in the scholarship. The essay argues that such a cultivation of methodology will enable the burgeoning scholarship on CPW to gain richer insight into the range of theological meaning expressed in CPW contexts.
Bankruptcy Prediction for Micro and Small Enterprises Using Financial, Non-Financial, Business Sector and Macroeconomic Variables: The Case of the Lithuanian Construction Sector
Authors: Kanapickienė Rasa , Kanapickas Tomas , Nečiūnas Audrius
Published: May 2023

Credit-risk models that are designed for general application across sectors may not be suitable for the construction industry, which has unique characteristics and financial risks that require specialised modelling approaches. Moreover, advanced bankruptcy-prediction models are often used to achieve the highest accuracy in large modern datasets. Therefore, the aim of this research is the creation of enterprise-bankruptcy prediction (EBP) models for Lithuanian micro and small enterprises (MiSEs) in the construction sector. This issue is analysed based on classification models and the specific types of variable used. Firstly, four types of variable are proposed. In EBP models, financial variables substantially explain an enterprise’s financial statements and performance from different perspectives. Including enterprises’ non-financial, construction-sector and macroeconomic variables improves the characteristics of EBP models. The inclusion of macroeconomic variables in the model has a particularly significant impact. These findings can be of great significance to investors, creditors, policymakers and practitioners in assessing financial risks and making informed decisions. The second question is related to the classification models used. To develop the EBP models, logistic regression (LR), artificial neural networks (ANNs) and multivariate adaptive regression splines (MARS) were used. In addition, this study developed two-stage hybrid models, i.e., the LR is combined with ANNs. The findings show that two-stage hybrid models do not improve bankruptcy prediction. It cannot be argued that ANN models are more accurate in predicting bankruptcy. The MARS model demonstrates the best bankruptcy prediction, i.e., this model could be a valuable tool for stakeholders to evaluate enterprises’ financial risk.
Watch the Next Step: A Comprehensive Survey of Stair-Climbing Vehicles
Authors: Pappalettera Antonio , Bottiglione Francesco , Mantriota Giacomo , Reina Giulio
Published: May 2023

Stair climbing is one of the most challenging tasks for vehicles, especially when transporting people and heavy loads. Although many solutions have been proposed and demonstrated in practice, it is necessary to further improve their climbing ability and safety. This paper presents a systematic review of the scientific and engineering stair climbing literature, providing brief descriptions of the mechanism and method of operation and highlighting the advantages and disadvantages of different types of climbing platform. To quantitatively evaluate the system performance, various metrics are presented that consider allowable payload, maximum climbing speed, maximum crossable slope, transport ability and their combinations. Using these metrics, it is possible to compare vehicles with different locomotion modes and properties, allowing researchers and practitioners to gain in-depth knowledge of stair-climbing vehicles and choose the best category for transporting people and heavy loads up a flight of stairs.
Enhancing Streamflow Modeling by Integrating GRACE Data and Shared Socio-Economic Pathways (SSPs) with SWAT in Hongshui River Basin, China
Authors: Touseef Muhammad , Chen Lihua , Chen Hang , Gabriel Hamza Farooq , Yang Wenzhe , Mubeen Ammara
Published: May 2023

Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. This research studied how changing climate influences the hydro-climatic parameters based on the earth system models that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). GRACE evapotranspiration data were forced into the Soil and Water Assessment Tool (SWAT) to project hydrologic responses to future climatic conditions in the Hongshui River basin (HRB) model. A novel approach based on climate elasticity was utilized to determine the extent to which climate variability affects stream flow. CMIP6 SSPs (shared socio-economic pathways) for the second half of the 20th century (1960–2020) and 21st century (2021–2100) projected precipitation (5–16%) for the whole Hongshui River basin (HRB). The ensemble of GCMs projected an increase of 2 °C in mean temperature. The stream flow is projected to increase by 4.2% under SSP-1.26, 6.2% under SSP-2.45, 8.45% under SSP-3.70, and 9.5% under SSP-5.85, based on the average changes throughout the various long-term future scenarios. We used the climate elasticity method and found that climate change contributes 11% to streamflow variability in the Hongshui River basin (HRB). Despite the uncertainty in projected hydrological variables, most members of the modeling ensemble present encouraging findings for future methods of water resource management.
Large Area High-Resolution 3D Mapping of the Von Kármán Crater: Landing Site for the Chang’E-4 Lander and Yutu-2 Rover
Authors: Tao Yu , Muller Jan-Peter , Conway Susan J. , Xiong Siting , Walter Sebastian H. G. , Liu Bin
Published: May 2023

We demonstrate the creation of a large area of high-resolution (260 × 209 km2 at 1 m/pixel) DTM mosaic from the Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images over the Chang’E-4 landing site at Von Kármán crater using an in-house deep learning-based 3D modelling system developed at University College London, called MADNet, trained with lunar orthorectified images and digital terrain models (DTMs). The resultant 1 m DTM mosaic is co-aligned with the Chang’E-2 (CE-2) and the Lunar Orbiter Laser Altimeter (LOLA)—SELenological and Engineering Explorer (SELENE) blended DTM product (SLDEM), providing high spatial and vertical congruence. In this paper, technical details are briefly discussed, along with visual and quantitative assessments of the resultant DTM mosaic product. The LROC NAC MADNet DTM mosaic was compared with three independent DTM datasets, and the mean differences and standard deviations are as follows: PDS photogrammetric DTM at 5 m grid-spacing had a mean difference of −0.019 ± 1.09 m, CE-2 DTM at 20 m had a mean difference of −0.048 ± 1.791 m, and SLDEM at 69 m had a mean difference of 0.577 ± 94.940 m. The resultant LROC NAC MADNet DTM mosaic, alongside a blended LROC NAC and CE-2 MADNet DTM mosaic and a separate LROC NAC, orthorectified image mosaic, are made publicly available via the ESA planetary science archive’s guest storage facility.
Study on Single-Tree Extraction Method for Complex RGB Point Cloud Scenes
Authors: Xia Kai , Li Cheng , Yang Yinhui , Deng Susu , Feng Hailin
Published: May 2023

With the development of sensor technology and point cloud generation techniques, there has been an increasing amount of high-quality forest RGB point cloud data. However, popular clustering-based point cloud segmentation methods are usually only suitable for pure forest scenes and not ideal for scenes with multiple ground features or complex terrain. Therefore, this study proposes a single-tree point cloud extraction method that combines deep semantic segmentation and clustering. This method first uses a deep semantic segmentation network, Improved-RandLA-Net, which is developed based on RandLA-Net, to extract point clouds of specified tree species by adding an attention chain to improve the model’s ability to extract channel and spatial features. Subsequently, clustering is employed to extract single-tree point clouds from the segmented point clouds. The feasibility of the proposed method was verified in the Gingko site, the Lin’an Pecan site, and a Fraxinus excelsior site in a conference center. Finally, semantic segmentation was performed on three sample areas using pre- and postimproved RandLA-Net. The experiments demonstrate that Improved-RandLA-Net had significant improvements in Accuracy, Precision, Recall, and F1 score. At the same time, based on the semantic segmentation results of Improved-RandLA-Net, single-tree point clouds of three sample areas were extracted, and the final single-tree recognition rates for each sample area were 89.80%, 75.00%, and 95.39%, respectively. The results demonstrate that our proposed method can effectively extract single-tree point clouds in complex scenes.
Parameterization and Remote Sensing Retrieval of Land Surface Processes in the Gurbantunggut Desert, China
Authors: Li Wei , Gao Jiacheng , Mamtimin Ali , Liu Yongqiang , Wang Yu , Song Meiqi , Wen Cong , Aihaiti Ailiyaer , Yang Fan , Huo Wen , Zhou Chenglong , Wang Wenbiao , Cui Zhengnan
Published: May 2023

The exchange of energy between the land surface and atmosphere is dependent upon crucial parameters, including surface roughness, emissivity, bulk transfer coefficients for momentum (CD) and heat (CH). These parameters are calculated through site observation data and remote sensing data. The following conclusions are drawn: (1) the aerodynamic roughness of the Gurbantunggut Desert measures 1.1 × 10−2 m, which is influenced by the varying conditions of the underlying surface. The roughness decreases as wind speed increases and is seen to be directly proportional to the growth of vegetation. From April to June, the aerodynamic roughness increases with increasing vegetation cover, but begins to gradually decrease after July. Spatially, the middle regions show higher roughness values than the eastern and western areas. In the central part of the desert, the roughness is between 2.37 × 10−2 m and 2.46 × 10−2 m from April to November. The northwest and northeast regions measure 1.41 × 10−2 m–2.04 × 10−2 m and 1.53 × 10−2 m–2.39 × 10−2 m, respectively. (2) The surface emissivity is 0.93, and it varies depending on the snow and vegetation present in the underlying area. (3) CD and CH exhibit an inverse relationship with wind speed. When wind speed falls below 6 m/s, the CD declines rapidly as wind speed increases. In contrast, once wind speed surpasses 6 m/s, the propensity for the CD to decrease with increasing wind speed slows down and approaches stability.
Video-Monitoring Tools for Assessing Beach Morphodynamics in Tidal Beaches
Authors: Montes Juan , del Río Laura , Plomaritis Theocharis A. , Benavente Javier , Puig María , Simarro Gonzalo
Published: May 2023

Beach behaviour and evolution are controlled by a large number of factors, being susceptible to human-derived pressures and the impacts of climate change. In order to understand beach behaviour at different scales, systematic monitoring programs that assess shoreline and volumetric changes are required. Video-monitoring systems are widely used in this regard, as they are cost-effective and acquire data automatically and continuously, even in bad weather conditions. This work presents a methodology to use the basic products of low-cost IP video cameras to identify both the cross-shore and long-shore variability of tidal beaches. Shorelines were automatically obtained, digital elevation models (DEMs) were generated and validated with real data, and the outputs were combined to analyse beach behaviour from a morphodynamic perspective. The proposed methodology was applied to La Victoria Beach (SW Spain) for the analysis of beach variations over a 5-year period. The combination of shoreline position analysis and data from DEMs facilitates understanding and provides a complete overview of beach behaviour, revealing alongshore differences in an apparently homogeneous beach. Furthermore, the methods used allowed us to inter-relate the different processes occurring on the beach, which is difficult to achieve with other types of techniques.
Research on the Characteristics of Thermosyphon Embankment Damage and Permafrost Distribution Based on Ground-Penetrating Radar: A Case Study of the Qinghai–Tibet Highway
Authors: Qi Shunshun , Li Guoyu , Chen Dun , Niu Fujun , Sun Zhizhong , Wu Gang , Du Qingsong , Chai Mingtang , Cao Yapeng , Yue Jianwei
Published: May 2023

In order to research the special embankment (thermosyphon embankment) damages and the distribution of permafrost under the Qinghai–Tibet Highway (QTH) embankment. The section K2952–K2953, which is a typical representative of the QTH, was chosen for the detection and research of the permafrost and embankment damages in order to determine the sources of the damages. In this study, the performance characteristics of the embankment, the active layer, and the permafrost table found in ground-penetrating radar (GPR) images were researched, combined with multi-source. According to the research findings, the construction of the embankment in this section has stabilized the effect on the permafrost table. Under the embankment of the unemployed thermosyphon section, the permafrost distribution has good structural integrity and continuity, with the permafrost table at a depth of around 5 m. The continuity of the permafrost distribution under the embankment in the thermosyphon section was poor, and there was localized degradation, with the permafrost table being approximately 6 m deep. The main cause of the irregular settlement and other damage in this section is the presence of a loose area at the base of the embankment. Although the thermosyphon on both sides of the embankment also plays a role in lifting the permafrost table, it is not ideal for managing the damage to high embankments where the type of permafrost under the embankment is high-temperature permafrost with a high ice content and where the sunny–shady slope effect is obvious. The research results described in this article can therefore provide a crucial foundation for the detection of highway damage and permafrost under embankments in permafrost regions in the future.
Three-Dimensional Deformation of the 2023 Turkey Mw 7.8 and Mw 7.7 Earthquake Sequence Obtained by Fusing Optical and SAR Images
Authors: An Qi , Feng Guangcai , He Lijia , Xiong Zhiqiang , Lu Hao , Wang Xiuhua , Wei Jianchao
Published: May 2023

In February 2023, Mw 7.8 and Mw 7.7 earthquakes struck southeastern Turkey. Generating a coseismic 3D deformation field that can directly reflect the characteristics of surface deformation is important for revealing the movement mode of a seismogenic fault and analyzing the focal mechanism. Optical image sub-pixel correlation (SPC) only captures deformation in the horizontal direction, and SAR image pixel offset tracking (POT) obtains range deformation that is not sensitive to north–south deformation signals. Thus, neither of them can capture the complete 3D deformation alone. Combining them may be able to allow the monitoring of 3D deformation. In this study, we used Sentinel-2 optical images to obtain the horizontal deformation (east–west and north–south) and Sentinel-1 and ALOS-2 data to extract the range and azimuth offsets. The least-squares method was used to fuse the optical and SAR offsets to obtain the 3D deformation field of the 2023 Turkey earthquake sequence, which indicates that the two events were both left-lateral strike-slip earthquakes. The surface deformation caused by the two large earthquakes is mainly in the east–west direction. In the vertical direction, the two earthquakes caused a small-magnitude uplift and subsidence. The findings in this paper can be used as a reference for the study of coseismic 3D deformation.
Precipitation Microphysics of Locally-Originated Typhoons in the South China Sea Based on GPM Satellite Observations
Authors: Huang Xingtao , Wu Zuhang , Xie Yanqiong , Zhang Yun , Zhang Lifeng , Zheng Hepeng , Xiao Wupeng
Published: May 2023

Locally-originated typhoons in the South China Sea (SCS) are characterized by long duration, complex track, and high probability of landfall, which tend to cause severe wind, rainstorm, and flood disasters in coastal regions. Therefore, it is of great significance to conduct research on typhoon precipitation microphysics in the SCS. Using GPM satellite observations, the precipitation microphysics of typhoons in the SCS are analyzed by combining case and statistical studies. The precipitation of Typhoon Ewiniar (2018) in the SCS is found to be highly asymmetric. In the eyewall, the updraft is strong, the coalescence process of particles is distinct, and the precipitation is mainly concentrated in large raindrops. In the outer rainbands, the “bright-band” of melting layer is distinct, the melting of ice particles and the evaporation of raindrops are distinct, and there exist a few large raindrops in the precipitation. Overall, the heavy precipitation of typhoons in the SCS is composed of higher concentration of smaller raindrops than that in the western Pacific (WP), leading to a more “oceanic deep convective” feature of typhoons in the SCS. While the heavy precipitation of typhoons in the SCS is both larger in drop size and number concentration than that in the North Indian Ocean (NIO), leading to more abundant rainwater of typhoons in the SCS. For the relatively weak precipitation (R < 10 mm h−1), the liquid water path (LWP) of typhoons in the SCS is higher than that of the NIO, while the ice water path (IWP) of the locally-originated typhoons in the SCS is lower than that of the WP. For the heavy precipitation (R ≥ 10 mm h−1), the LWP and IWP of typhoons in the SCS are significantly higher than those in the WP and NIO.
On the Retrieval of Surface-Layer Parameters from Lidar Wind-Profile Measurements
Authors: Araújo da Silva Marcos Paulo , Salcedo-Bosch Andreu , Rocadenbosch Francesc , Peña Alfredo
Published: May 2023

We revisit two recent methodologies based on Monin–Obukhov Similarity Theory (MOST), the 2D method and Hybrid-Wind (HW), which are aimed at estimation of the Obukhov length, friction velocity and kinematic heat flux within the surface layer. Both methods use wind-speed profile measurements only and their comparative performance requires assessment. Synthetic and observational data are used for their quantitative assessment. We also present a procedure to generate synthetic noise-corrupted wind profiles based on estimation of the probability density functions for MOST-related variables (e.g., friction velocity) and the statistics of the noise-corrupting perturbational amplitude found during an 82-day IJmuiden observational campaign. In the observational part of the study, 2D and HW parameter retrievals from floating Doppler wind lidar measurements are compared against those from a reference mast. Overall, the 2D algorithm outperformed the HW in the estimation of all the three parameters above. For instance, when assessing the friction-velocity retrieval performance with reference to sonic anemometers, determination coefficients of ρ2D2=0.77 and ρHW2=0.33 were found under unstable atmospheric stability conditions, and ρ2D2=0.81 and ρHW2=0.07 under stable conditions, which suggests the 2D algorithm as a prominent method for estimating the above-mentioned surface-layer parameters.
The Identification of Ice Floes and Calculation of Sea Ice Concentration Based on a Deep Learning Method
Authors: Zhou Li , Cai Jinyan , Ding Shifeng
Published: May 2023

When navigating ships in cold regions, sea ice concentration plays a crucial role in determining a ship’s navigability. However, automatically extracting the sea ice concentration and floe size distribution remains challenging, due to the difficulty in detecting all the ice floes from the images captured in complex polar environments, particularly those that include both ships and sea ice. In this paper, we propose using the YOLACT network to address this issue. Cameras installed on the ship collect images during transit and an image dataset is constructed to train a model that can intelligently identify all the targets in the image and remove any noisy targets. To overcome the challenge of identifying seemingly connected ice floes, the non-maximum suppression (NMS) in YOLACT is improved. Binarization is then applied to process the detection results, with the aim of obtaining an accurate sea ice concentration. We present a color map and histogram of the associated floe size distribution based on the ice size. The speed of calculating the sea ice density of each image reaches 21 FPS and the results show that sea ice concentration and floe size distribution can be accurately measured. We provide a case study to demonstrate the effectiveness of the proposed approach.
A Flexible Design Strategy for Three-Element Non-Uniform Linear Arrays
Authors: Quirini Andrea , Filippini Francesca , Bongioanni Carlo , Colone Fabiola , Lombardo Pierfrancesco
Published: May 2023

This paper illustrates a flexible design strategy for a three-element non-uniform linear array (NULA) aimed at estimating the direction of arrival (DoA) of a source of interest. Thanks to the spatial diversity resulting from non-uniform sensor spacings, satisfactory DoA estimation accuracies can be achieved by employing a very limited number of receiving elements. This makes NULA configurations particularly attractive for low-cost passive location applications. To estimate the DoA of the source of interest, we resort to the maximum likelihood estimator, and the proposed design strategy is obtained by constraining the maximum pairwise error probability to control the errors occurring due to outliers. In fact, it is well known that the accuracy of the maximum likelihood estimator is often degraded by outliers, especially when the signal-to-noise power ratio does not belong to the so-called asymptotic region. The imposed constraint allows for the defining of an admissible region in which the array should be selected. This region can be further modified to incorporate practical design constraints concerning the antenna element size and the positioning accuracy. The best admissible array is then compared to the one obtained with a conventional NULA design approach, where only antenna spacings multiple of λ/2 are considered, showing improved performance, which is also confirmed by the experimental results.
User QoS-Based Optimized Handover Algorithm for Wireless Networks
Authors: Chu Hung-Chi , Wong Chia-En , Cheng Wei-Min , Lai Hong-Cheng
Published: May 2023

Due to the development of wireless network technology, various applications relying on good network quality are widely used on mobile devices. Taking the commonly used video streaming service as an example, a network with high throughput and low packet loss rate can meet the service requirements. When the moving distance of the mobile device is greater than the signal coverage of the AP, it will trigger the handover process to connect to another AP, and cause the network to disconnect and reconnect instantaneously. However, frequently triggering the handover procedure will cause a significant drop in network performance and affect the operation of application services. In order to solve this problem, this paper proposes the OHA and OHAQR. The OHA considers whether the signal quality is good or bad, and uses the corresponding HM method to solve the problem of frequent handover procedures. The OHAQR integrates the QoS requirements of the throughput and packet loss rate into the OHA with the Q-handover score, to provide high-performance handover services with QoS. Our experimental results show that the OHA and OHAQR have 13 and 15 handovers in a high-density scenario, respectively, and are better than the other two methods. The actual throughput and packet loss rate of the OHAQR are 123 Mbps and 5%, respectively, and the network performance is better than that of other methods. The proposed method shows excellent performance in ensuring the network QoS requirements and reducing the number of handover procedures.
An IoT-Enabled E-Nose for Remote Detection and Monitoring of Airborne Pollution Hazards Using LoRa Network Protocol
Authors: Kumar Kanak , Chaudhri Shiv Nath , Rajput Navin Singh , Shvetsov Alexey V. , Sahal Radhya , Alsamhi Saeed Hamood
Published: May 2023

Detection and monitoring of airborne hazards using e-noses has been lifesaving and prevented accidents in real-world scenarios. E-noses generate unique signature patterns for various volatile organic compounds (VOCs) and, by leveraging artificial intelligence, detect the presence of various VOCs, gases, and smokes onsite. Widespread monitoring of airborne hazards across many remote locations is possible by creating a network of gas sensors using Internet connectivity, which consumes significant power. Long-range (LoRa)-based wireless networks do not require Internet connectivity while operating independently. Therefore, we propose a networked intelligent gas sensor system (N-IGSS) which uses a LoRa low-power wide-area networking protocol for real-time airborne pollution hazard detection and monitoring. We developed a gas sensor node by using an array of seven cross-selective tin-oxide-based metal-oxide semiconductor (MOX) gas sensor elements interfaced with a low-power microcontroller and a LoRa module. Experimentally, we exposed the sensor node to six classes i.e., five VOCs plus ambient air and as released by burning samples of tobacco, paints, carpets, alcohol, and incense sticks. Using the proposed two-stage analysis space transformation approach, the captured dataset was first preprocessed using the standardized linear discriminant analysis (SLDA) method. Four different classifiers, namely AdaBoost, XGBoost, Random Forest (RF), and Multi-Layer Perceptron (MLP), were then trained and tested in the SLDA transformation space. The proposed N-IGSS achieved “all correct” identification of 30 unknown test samples with a low mean squared error (MSE) of 1.42 × 10−4 over a distance of 590 m.
Discovery and Characterisation of Forward Line Formations at Centre Bounces in the Australian Football League
Authors: Seakins Daylon , Gastin Paul B. , Jackson Karl , Gloster Matthew , Brougham Aaron , Carey David L.
Published: May 2023

The extent of player formation usage and the characteristics of player arrangements are not well understood in Australian football, unlike other team-based invasion sports. Using player location data from all centre bounces in the 2021 Australian Football League season; this study described the spatial characteristics and roles of players in the forward line. Summary metrics indicated that teams differed in how spread out their forward players were (deviation away from the goal-to-goal axis and convex hull area) but were similar with regard to the centroid of player locations. Cluster analysis, along with visual inspection of player densities, clearly showed the presence of different repeated structures or formations used by teams. Teams also differed in their choice of player role combinations in forward lines at centre bounces. New terminology was proposed to describe the characteristics of forward line formations used in professional Australian Football.
Swarm Metaverse for Multi-Level Autonomy Using Digital Twins
Authors: Nguyen Hung , Hussein Aya , Garratt Matthew A. , Abbass Hussein A.
Published: May 2023

Robot swarms are becoming popular in domains that require spatial coordination. Effective human control over swarm members is pivotal for ensuring swarm behaviours align with the dynamic needs of the system. Several techniques have been proposed for scalable human–swarm interaction. However, these techniques were mostly developed in simple simulation environments without guidance on how to scale them up to the real world. This paper addresses this research gap by proposing a metaverse for scalable control of robot swarms and an adaptive framework for different levels of autonomy. In the metaverse, the physical/real world of a swarm symbiotically blends with a virtual world formed from digital twins representing each swarm member and logical control agents. The proposed metaverse drastically decreases swarm control complexity due to human reliance on only a few virtual agents, with each agent dynamically actuating on a sub-swarm. The utility of the metaverse is demonstrated by a case study where humans controlled a swarm of uncrewed ground vehicles (UGVs) using gestural communication, and via a single virtual uncrewed aerial vehicle (UAV). The results show that humans could successfully control the swarm under two different levels of autonomy, while task performance increases as autonomy increases.
Comparative Analysis of Power Consumption between MQTT and HTTP Protocols in an IoT Platform Designed and Implemented for Remote Real-Time Monitoring of Long-Term Cold Chain Transport Operations
Authors: Jara Ochoa Heriberto J. , Peña Raul , Ledo Mezquita Yoel , Gonzalez Enrique , Camacho-Leon Sergio
Published: May 2023

IoT platforms for the transportation industry are portable with limited battery life and need real-time and long-term monitoring operations. Since MQTT and HTTP are widely used as the main communication protocols in the IoT, it is imperative to analyze their power consumption to provide quantitative results that help maximize battery life in IoT transportation systems. Although is well known that MQTT consumes less power than HTTP, a comparative analysis of their power consumption with long-time tests and different conditions has not yet been conducted. In this sense, a design and validation of an electronic cost-efficient platform system for remote real-time monitoring is proposed using a NodeMCU module, in which experimentation is carried out for HTTP and MQTT with different QoS levels to make a comparison and demonstrate the differences in power consumption. Furthermore, we characterize the behavior of the batteries in the systems and compare the theoretical analysis with real long-time test results. The experimentation using the MQTT protocol with QoS 0 and 1 was successful, resulting in power savings of 6.03% and 8.33%, respectively, compared with HTTP, demonstrating many more hours in the duration of the batteries, which could be very useful in technological solutions for the transport industry.