bluuebunny/crossref_metadata_2025 huggingface dataset:
Kraft (Nano)Lignin as Reactive Additive in Epoxy Polymer Bio-Composites
Authors: Pappa Christina P. , Cailotto Simone , Gigli Matteo , Crestini Claudia , Triantafyllidis Konstantinos S.
Published: February 2024

The demand for high-performance bio-based materials towards achieving more sustainable manufacturing and circular economy models is growing significantly. Kraft lignin (KL) is an abundant and highly functional aromatic/phenolic biopolymer, being the main side product of the pulp and paper industry, as well as of the more recent 2nd generation biorefineries. In this study, KL was incorporated into a glassy epoxy system based on the diglycidyl ether of bisphenol A (DGEBA) and an amine curing agent (Jeffamine D-230), being utilized as partial replacement of the curing agent and the DGEBA prepolymer or as a reactive additive. A D-230 replacement by pristine (unmodified) KL of up to 14 wt.% was achieved while KL–epoxy composites with up to 30 wt.% KL exhibited similar thermo-mechanical properties and substantially enhanced antioxidant properties compared to the neat epoxy polymer. Additionally, the effect of the KL particle size was investigated. Ball-milled kraft lignin (BMKL, 10 μm) and nano-lignin (NLH, 220 nm) were, respectively, obtained after ball milling and ultrasonication and were studied as additives in the same epoxy system. Significantly improved dispersion and thermo-mechanical properties were obtained, mainly with nano-lignin, which exhibited fully transparent lignin–epoxy composites with higher tensile strength, storage modulus and glass transition temperature, even at 30 wt.% loadings. Lastly, KL lignin was glycidylized (GKL) and utilized as a bio-based epoxy prepolymer, achieving up to 38 wt.% replacement of fossil-based DGEBA. The GKL composites exhibited improved thermo-mechanical properties and transparency. All lignins were extensively characterized using NMR, TGA, GPC, and DLS techniques to correlate and justify the epoxy polymer characterization results.
Effect of Heat Treatment under Different Atmospheres on the Bonding Properties and Mechanism of Ceramiziable Heat-Resistant Adhesive
Authors: Wang Qingke , Tao Jiadong , Shan Huawei , Cui Tangyin , Ding Jie , Wang Jianghang
Published: February 2024

In this study, a heat-resistant adhesive was prepared using molybdenum-phenolic (Mo-PF) resin as the matrix and TiB2 particle as the ceramizable filler for bonding Al2O3 ceramic substrates. Firstly, Fourier transform infrared (FTIR) was used to characterize the chemical structure of the Mo-PF. Subsequently, thermo gravimetric analysis (TGA) and shear strength testing were employed to investigate the effects of heat treatment in different atmospheres on the thermal stability and residual bonding properties of the adhesive. To further explore the bonding mechanism of the adhesive after heat treatment in different atmospheres, scanning electron microscopy (SEM), compressive strength testing, and X-ray diffraction (XRD) were utilized to analyze the microstructure, mechanical strength, and composition evolution of the adhesive at different temperatures. The bonding strength of Al2O3 joints showed a trend of initially decreasing and then increasing after different temperature heat treatment in air, with the shear strength reaching a maximum value of 25.68 MPa after treatment at 1200 °C. And the bonding strength of Al2O3 joints decreased slowly with the increase of temperature in nitrogen. In air, the ceramicization reaction at a high temperature enabled the mechanical strength of the adhesive to rise despite the continuous pyrolysis of the resin. However, the TiB2 filler in nitrogen did not react, and the properties of the adhesive showed a decreasing tendency with the pyrolysis of the resin.
Preparation and Mechanical Properties of Flexible Prepreg Resin with High Strength and Low Creep
Authors: Sun Zhaoyi , Mei Zhiyuan , Huang Zheng , Wang Guorong
Published: February 2024

In this study, aiming at the problem of low strength and high creep caused by medium–low modulus flexible resin based on the formulation design idea of high-molecular-weight epoxy resin (E12)-reinforced flexible epoxy-terminated urethane resin (EUR), a flexible epoxy prepreg resin with high strength and low bending creep was prepared to be suitable for hot melt processing technology. Flexible EUR was synthesized by grafting flexible polyurethane segments onto the epoxy side chain by urethane bonding. By adjusting the ratio of E12 and EUR, the effects of different ratios of the two components on the mechanical properties and viscoelasticity of the resin were systematically studied with dicyandiamide as the latent curing system. Research has found that when the E12 content is between 20%wt and 40%wt, the resin system has the best coating viscosity at 65 °C to 85 °C. The molecular weight and the content of aromatic heterocyclic groups of the resin determine the strength and creep behavior of the resin. When the content of E12 in the system is less than 50%wt, modulus and strength increase linearly, but after more than 50%wt E12 content, the modulus is almost unchanged and the strength begins to decrease. By increasing the content of E12 in the resin, the creep behavior of the resin is greatly reduced. When the content of E12 increases to 50%wt, the bending creep is the lowest.
Pretreating Recycled Carbon Fiber Nonwoven with a Sizing Formulation to Improve the Performance of Thermoplastic Recycled Fiber-Reinforced Composites
Authors: Goethals Frederik , Demeyer Elke , De Schrijver Isabel , Vanneste Myriam
Published: February 2024

Pyrolysis is already an established recycling method to recover the carbon fibers of end-of-life composites. However, the pyrolysis process removes the fiber sizing. Fiber sizing is a critical step in composite material production, influencing adhesion, protection and overall performance. In this study, recycled carbon nonwoven reinforcements made from pyrolyzed carbon fibers were pretreated to improve the mechanical properties of polyamide and polypropylene composites. The pretreatment involved applying specific coatings (sizings) on the nonwoven by spraying. Pretreated and non-pretreated composites were prepared by compression molding to investigate the impact of the fiber pretreatment on the tensile properties and interlaminar shear strength. The tests were performed in the 0° and 90° directions of the composite plate. The results revealed that pretreatment had little effect on the polyamide composites. However, significant improvements were obtained for the polypropylene composites, as an increase of more than 50% in tensile strength was achieved in the 0° direction and more than 35% in the 90° direction. In addition, the interlaminar shear strength increased from 11.9 MPa to 14.3 MPa in the 0° direction and from 14.9 MPa to 17.8 MPa in the 90° direction.
Agro-Waste Sweet Pepper Extract-Magnetic Iron Oxide Nanoparticles for Antioxidant Enrichment and Sustainable Nanopackaging
Authors: López-Alcántara Elisia María , Colindres-Vásquez Grecia Marcela , Fodil Nouzha , Sánchez-Barahona Marlon , Rivera-Flores Octavio , Romero Alberto , Abdullah Johar Amin Ahmed
Published: February 2024

This study synthesizes magnetic iron oxide nanoparticles from agro-waste sweet pepper extract, exploring their potential as antioxidant additives and in food preservation. Iron (III) chloride hexahydrate is the precursor, with sweet pepper extract as both a reducing and capping agent at pH 7.5. Characterization techniques, including microscopy and spectroscopy, analyze the sweet pepper extract-magnetic iron oxide nanoparticles. Antioxidant capacities against 2,2-diphenyl-1-picrylhydrazyl are assessed, incorporating nanoparticles into banana-based bioplastic for grape preservation. Microscopy reveals cubic and quasi-spherical structures, and spectroscopy confirms functional groups, including Fe–O bonds. X-ray diffraction identifies cubic and monoclinic magnetite with a monoclinic hematite presence. Sweet pepper extract exhibits 100% inhibitory activity in 20 min, while sweet pepper extract-magnetic iron oxide nanoparticles show an IC50 of 128.1 µg/mL. Furthermore, these nanoparticles, stabilized with banana-based bioplastic, effectively preserve grapes, resulting in a 27.4% lower weight loss rate after 144 h compared to the control group (34.6%). This pioneering study encourages institutional research into the natural antioxidant properties of agro-waste sweet pepper combined with magnetic iron and other metal oxide nanoparticles, offering sustainable solutions for nanopackaging and food preservation. Current research focuses on refining experimental parameters and investigating diverse applications for sweet pepper extract-magnetic iron oxide nanoparticles in varied contexts.
The Electrical Conductivity, EMI Absorption Shielding Performance, Curing Process, and Mechanical Properties of Rubber Composites
Authors: Kruželák Ján , Kvasničáková Andrea , Džuganová Michaela , Dosoudil Rastislav , Hudec Ivan , Krump Henrich
Published: February 2024

Three types of composites were tested for electromagnetic interference (EMI) absorption shielding effectiveness, the curing process, and their physical–mechanical properties. For the first type of composites, nickel–zinc ferrite, manganese–zinc ferrite, and both fillers in their mutual combinations were incorporated into acrylonitrile–butadiene rubber. The overall content of the filler, or fillers, was kept at 200 phr. Then, carbon black or carbon fibers were incorporated into each rubber formulation at a constant loading of—25 phr, while the content of magnetic fillers was unchanged, at —200 phr. This work focused on the understanding of correlations between the electromagnetic shielding parameters and electrical conductivity of composites in relation to their EMI absorption shielding effectiveness. The absorption shielding abilities of materials were evaluated within a frequency bandwidth from 1 MHz to 6 GHz. This study revealed good correlation among permittivity, conductivity, and EMI absorption effectiveness. Although the absorption shielding efficiency of composites filled only with ferrites seems to be the highest, the absorption maxima of those composites reached over 6 GHz. The application of carbon-based fillers resulted in the higher electrical conductivity and higher permittivity of composites, which was reflected in their lower absorption shielding performance. However, the composites filled with ferrites and carbon-based fillers absorbed electromagnetic radiation within the desired frequency range. The presence of carbon-based fillers caused improvement in the tensile behavior of composites. This study also demonstrated that the higher the ratio of nickel–zinc ferrite in combined magnetic fillers, the better the absorption shielding efficiency.
Preparation and Properties of Mechanically Robust, Colorless, and Transparent Aramid Films
Authors: Kim Heesang , Noh Jin-Hee , Kim Young-Rae , Kim Hyojin , Kwak Giseop
Published: February 2024

In this study, various diamine monomers were used to synthesize aramid polymer films via a low-temperature solution condensation reaction with diacid chloride. For diamines with relatively high basicity, the reaction system became opaque because amine salt formation inhibited polymer synthesis. Meanwhile, low-basicity diamines with strong electron-withdrawing groups, such as CF3 and sulfone, were smoothly polymerized without amine salt formation to provide highly viscous solutions. The acid byproduct HCl generated during polymerization was removed by adding propylene oxide to the reaction vessel and converting the acid into highly volatile inert substances. The resulting solutions were used as varnishes without any additional purification, and polymer films with an excellent appearance were easily obtained through a conventional casting and convection drying process. The films neither tore nor broke when pulled or bent by hand; furthermore, even when heated up to 400 °C, they did not decompose or melt. Moreover, polymers prepared from 2,2-bis(trifluoromethyl)benzidine (TFMB) and bis(4-aminophenyl)sulfone (pAPS) did not exhibit glass transition until decomposition. The prepared polymer films showed a high elastic modulus of more than 4.1 GPa and a high tensile strength of more than 52 MPa. In particular, TFMB-, pAPS-, and 2,2-bis(4-aminophenyl)hexafluoropropane-based polymer films were colorless and transparent, with very high light transmittances of 95%, 96%, and 91%, respectively, at 420 nm and low yellow indexes of 2.4, 1.9, and 4.3, respectively.
Evaluation of the Thermal Diffusivity of Carbon/Phenolic Composites (CPCs) through Oxy-Acetylene Torch (OAT) Test—Part 1: Experimental Characterization and Preliminary Validation
Authors: Natali Maurizio , Torre Luigi , Rallini Marco
Published: February 2024

Carbon/Phenolic Composites (CPCs) are essential to manufacture many portions of the nozzle assembly of Solid Rocket Motors (SRMs) which are essential both to preserve the independent access to space as well as for the homeland security. In our research, a feasible approach aimed at preliminary retrieving the in-plane and out-plane thermal diffusivity of CPCs through the Oxy-Acetylene Torch (OAT) tests was validated. The proposed approach showed to be effective and able to bypass some limitations of common protocols, especially in terms of capability to determine the thermal diffusivity of CPCs at high heating rates. A comprehensive work of comparison of the obtained data with state-of-the-art CPCs such as MX-4926 and FM-5014 has also been carried out, evidencing the effectiveness of the proposed method.
The Entrepreneur’s Prayer and the Scholastic Inspirations of Free-Market Economics
Authors: Bednarz Jacek , Błasiak Zdzisław Adam
Published: February 2024

The paper explores the historical and philosophical roots of economic thought, drawing connections between the entrepreneurial mindset and the scholastic traditions that have shaped the conceptual landscape of free markets. Through a multidisciplinary approach, the paper examines how religious and scholastic influences have contributed to the development of economic ideas, providing a nuanced understanding of the ethical dimensions inherent in entrepreneurial endeavors. By unraveling the threads that connect entrepreneurship, prayer, and scholasticism, this paper also seeks to illuminate the symbiotic relationship between faith, intellectual heritage, and the principles that underpin free-market economies.
Introduction of Spiritual Psychotherapy for Inpatient, Residential, and Intensive Treatment (SPIRIT) in The Netherlands: Translation and Adaptation of a Psychotherapy Protocol for Mental Health Care
Authors: van Nieuw Amerongen Joke C. , Ouwehand Eva , Graaf Nienke de , van Parijs Linda , Schaap-Jonker Hanneke , Braam Arjan W. , Verhagen Peter J. , Rosmarin David H. , van den Brink Bart
Published: February 2024

The perceived value of the integration of spirituality and religion (SR) in mental health care is growing. This study aimed to adapt an SR intervention developed in the USA (SPIRIT) for use in the Netherlands and to explore its applicability. Employing a participatory practice-based action research design, professionals, clients, and an advisory board collaborated in iterative cycles of translation, adaptation, discussion, and testing. The ongoing interfaith dialog during the adaptation process broadened the perspectives incorporated into the existing handouts. We added the term “meaning” (M) alongside SR to accommodate patients who do not identify with religion or spirituality. Additionally, several handouts were added to the original protocol: autonomy, responsibility, and liberty; loneliness and belonging; inspiring persons in the past and present; and grief and loss. Moreover, the existing handout on sacred verses was expanded to encompass versions from various outlooks on life: philosophical/humanistic, Judeo-Christian, Buddhist, Islamic, and Hindu. Finally, layout modifications and diverse exercise formats were introduced. A qualitative examination revealed that the adapted SPIRIT protocol was well received by professionals and patients, and quantitative studies on its applicability and usefulness are recommended.
Narrative Integration: An In-Depth Exploration of the “Buddha Story Stele” in the Maiji Mountain Grottoes
Authors: Lin Zejie , Li Zhijun , Xie Meizi
Published: February 2024

This research delves into the intricacies of the “Buddha Story Stele” in Cave 133 of the Maiji Mountain Grottoes, China, examining the sculptural combinations and conceptual nuances rooted in Buddhist culture from the 5th to the 6th centuries CE. The research focuses on discerning the identities of the “Two Adjacent-Seated Buddhas” and the Cross-Legged Bodhisattva carved on the stele, concurrently delving into the embedded symbolic significance within its structural composition. Our investigation posits that the upper, middle, and lower segments of the “Buddha Story Stele” respectively symbolize the post-Nirvana Dharmakāya Shakyamuni, the Bodhisattva Shakyamuni, and the Buddha Shakyamuni of Sumedha. Advancing scholarly discourse, it reevaluates the Cross-Legged Bodhisattva’s identity and the configuration of the “Two Adjacent-Seated Buddhas”, elucidating the interplay of imagery and conceptual themes. This study provides pivotal insights into the sculptural arrangement and religious thought transmission in the Maiji Mountain Grottoes, contributing significant academic and cultural value to preserve this unique heritage.
The Cult of Our Lady of Fátima, Portuguese Colonialism, and Migration, c. 1930–c. 1980
Authors: von Klimo Arpad
Published: February 2024

Emerging in 1917 amidst the anxieties of World War I, the Cult of Our Lady of Fátima began with a vision witnessed by three shepherd children in rural Portugal. News of the apparition quickly spread, drawing hundreds, then thousands of pilgrims to the Cova da Iria. This potent symbol of faith soon transcended its origin, migrating in the form of venerated statues and dedicated shrines that sprouted across the globe. Particularly intertwined with Portuguese emigration, the cult’s reach extended to former colonies in Africa and Asia (“Ultramar”) and distant communities like Brazil. Statues of Our Lady became beacons of familiarity and solace, offering “homes away from home” for displaced populations. This essay focuses on the discourses surrounding the cult between the early 1930s and 1950s, exploring how Fátima served as a focal point for navigating the social, political, and cultural conflicts inherent in the emigration experience.
Estimation of Forest Residual Biomass for Bioelectricity Utilization towards Carbon Neutrality Based on Sentinel-2A Multi-Temporal Images: A Case Study of Aizu Region of Fukushima, Japan
Authors: Qian Tana , Ooba Makoto , Fujii Minoru , Matsui Takanori , Haga Chihiro , Namba Akiko , Nakamura Shogo
Published: February 2024

Forest biomass is expected to remain a key part of the national energy portfolio mix, yet residual forest biomass is currently underused. This study aimed to estimate the potential availability of waste woody biomass in the Aizu region and its energy potential for local bioelectricity generation as a sustainable strategy. The results showed that the available quantity of forest residual biomass for energy production was 191,065 tons, with an average of 1.385 t/ha in 2018, of which 72% (146,976 tons) was from logging residue for commercial purposes, and 28% (44,089 tons) was from thinning operations for forest management purposes. Forests within the biomass–collection radius of a local woody power plant can provide 45,925 tons of residual biomass, supplying bioelectricity at 1.6 times the plant’s capacity, which could avoid the amount of 65,246 tons of CO2 emission per year by replacing coal-fired power generation. The results highlight the bioelectricity potential and carbon-neutral capacity of residual biomass. This encourages government initiatives or policy inclinations to sustainably boost the production of bioenergy derived from residual biomass.
CoastalWQL: An Open-Source Tool for Drone-Based Mapping of Coastal Turbidity Using Push Broom Hyperspectral Imagery
Authors: Pak Hui Ying , Kieu Hieu Trung , Lin Weisi , Khoo Eugene , Law Adrian Wing-Keung
Published: February 2024

Uncrewed-Aerial Vehicles (UAVs) and hyperspectral sensors are emerging as effective alternatives for monitoring water quality on-demand. However, image mosaicking for largely featureless coastal water surfaces or open seas has shown to be challenging. Another pertinent issue observed is the systematic image misalignment between adjacent flight lines due to the time delay between the UAV-borne sensor and the GNSS system. To overcome these challenges, this study introduces a workflow that entails a GPS-based image mosaicking method for push-broom hyperspectral images, together with a correction method to address the aforementioned systematic image misalignment. An open-source toolkit, CoastalWQL, was developed to facilitate the workflow, which includes essential pre-processing procedures for improving the image mosaic’s quality, such as radiometric correction, de-striping, sun glint correction, and object masking classification. For validation, UAV-based push-broom hyperspectral imaging surveys were conducted to monitor coastal turbidity in Singapore, and the implementation of CoastalWQL’s pre-processing workflow was evaluated at each step via turbidity retrieval. Overall, the results confirm that the image mosaicking of the push-broom hyperspectral imagery over featureless water surface using CoastalWQL with time delay correction enabled better localisation of the turbidity plume. Radiometric correction and de-striping were also found to be the most important pre-processing procedures, which improved turbidity prediction by 46.5%.
Annual Daily Irradiance Analysis of Clusters in Mexico by Machine Learning Algorithms
Authors: Salinas-González Jared D. , García-Hernández Alejandra , Riveros-Rosas David , González-Cabrera Adriana E. , Mauricio-González Alejandro , Galván-Tejada Carlos E. , Vázquez-Reyes Sodel , Gamboa-Rosales Hamurabi
Published: February 2024

The assessment of solar resources involves the utilization of physical or satellite models for the determination of solar radiation on the Earth’s surface. However, a critical aspect of model validation necessitates comparisons against ground-truth measurements obtained from surface radiometers. Given the inherent challenges associated with establishing and maintaining solar radiation measurement networks—characterized by their expense, logistical complexities, limited station availability and the imperative consideration of climatic criteria for siting—countries endowed with substantial climatic diversity face difficulties in station placement. In this investigation, the measurements of annual solar irradiation, from meteorological stations of the National Weather Service in Mexico, were compared in different regions clustered by similarities in altitude, TL Linke, albedo and cloudiness index derived from satellite images; the main objective is to find the best ratio of annual solar irradiation in a set of clusters. Employing machine learning algorithms, this research endeavors to identify the most suitable model for predicting the ratio of annual solar irradiation and to determine the optimal number of clusters. The findings underscore the efficacy of the L-method as a robust technique for regionalization. Notably, the cloudiness index emerges as a pivotal feature, with the Random Forest algorithm yielding superior performance with a R2 score of 0.94, clustering Mexico into 17 regions.
Deep Learning Approach to Improve Spatial Resolution of GOES-17 Wildfire Boundaries Using VIIRS Satellite Data
Authors: Badhan Mukul , Shamsaei Kasra , Ebrahimian Hamed , Bebis George , Lareau Neil P. , Rowell Eric
Published: February 2024

The rising severity and frequency of wildfires in recent years in the United States have raised numerous concerns regarding the improvement in wildfire emergency response management and decision-making systems, which require operational high temporal and spatial resolution monitoring capabilities. Satellites are one of the tools that can be used for wildfire monitoring. However, none of the currently available satellite systems provide both high temporal and spatial resolution. For example, GOES-17 geostationary satellite fire products have high temporal (1–5 min) but low spatial resolution (≥2 km), and VIIRS polar orbiter satellite fire products have low temporal (~12 h) but high spatial resolution (375 m). This work aims to leverage currently available satellite data sources, such as GOES and VIIRS, along with deep learning (DL) advances to achieve an operational high-resolution, both spatially and temporarily, wildfire monitoring tool. Specifically, this study considers the problem of increasing the spatial resolution of high temporal but low spatial resolution GOES-17 data products using low temporal but high spatial resolution VIIRS data products. The main idea is using an Autoencoder DL model to learn how to map GOES-17 geostationary low spatial resolution satellite images to VIIRS polar orbiter high spatial resolution satellite images. In this context, several loss functions and DL architectures are implemented and tested to predict both the fire area and the corresponding brightness temperature. These models are trained and tested on wildfire sites from 2019 to 2021 in the western U.S. The results indicate that DL models can improve the spatial resolution of GOES-17 images, leading to images that mimic the spatial resolution of VIIRS images. Combined with GOES-17 higher temporal resolution, the DL model can provide high-resolution near-real-time wildfire monitoring capability as well as semi-continuous wildfire progression maps.
An Approach to Large-Scale Cement Plant Detection Using Multisource Remote Sensing Imagery
Authors: Li Tianzhu , Ma Caihong , Lv Yongze , Liao Ruilin , Yang Jin , Liu Jianbo
Published: February 2024

The cement industry, as one of the primary contributors to global greenhouse gas emissions, accounts for 7% of the world’s carbon dioxide emissions. There is an urgent need to establish a rapid method for detecting cement plants to facilitate effective monitoring. In this study, a comprehensive method based on YOLOv5-IEG and the Thermal Signature Detection module using Google Earth optical imagery and SDGSAT-1 thermal infrared imagery was proposed to detect large-scale cement plant information, including geographic location and operational status. The improved algorithm demonstrated an increase of 4.8% in accuracy and a 7.7% improvement in MAP@.5:95. In a specific empirical investigation in China, we successfully detected 781 large-scale cement plants with an accuracy of 90.8%. Specifically, of the 55 cement plants in Shandong Province, we identified 46 as operational and nine as non-operational. The successful application of advanced models and remote sensing technology in efficiently and accurately tracking the operational status of cement plants provides crucial support for environmental protection and sustainable development.
OII: An Orientation Information Integrating Network for Oriented Object Detection in Remote Sensing Images
Authors: Liu Yangfeixiao , Jiang Wanshou
Published: February 2024

Oriented object detection for remote sensing images poses formidable challenges due to arbitrary orientation, diverse scales, and densely distributed targets (e.g., across terrain). Current investigations in remote sensing object detection have primarily focused on improving the representation of oriented bounding boxes yet have neglected the significant orientation information of targets in remote sensing contexts. Recent investigations point out that the inclusion and fusion of orientation information yields substantial benefits in training an accurate oriented object system. In this paper, we propose a simple but effective orientation information integrating (OII) network comprising two main parts: the orientation information highlighting (OIH) module and orientation feature fusion (OFF) module. The OIH module extracts orientation features from those produced by the backbone by modeling the frequency information of spatial features. Given that low-frequency components in an image capture its primary content, and high-frequency components contribute to its intricate details and edges, the transformation from the spatial domain to the frequency domain can effectively emphasize the orientation information of images. Subsequently, our OFF module employs a combination of a CNN attention mechanism and self-attention to derive weights for orientation features and original features. These derived weights are adopted to adaptively enhance the original features, resulting in integrated features that contain enriched orientation information. Given the inherent limitation of the original spatial attention weights in explicitly capturing orientation nuances, the incorporation of the introduced orientation weights serves as a pivotal tool to accentuate and delineate orientation information related to targets. Without unnecessary embellishments, our OII network achieves competitive detection accuracy on two prevalent remote sensing-oriented object detection datasets: DOTA (80.82 mAP) and HRSC2016 (98.32 mAP).
LiDAR-Based Morphometry of Dolines in Aggtelek Karst (Hungary) and Slovak Karst (Slovakia)
Authors: Telbisz Tamás , Mari László , Székely Balázs
Published: February 2024

LiDAR-based digital terrain models (DTMs) represent an advance in the investigation of small-scale geomorphological features, including dolines of karst terrains. Important issues in doline morphometry are (i) which statistical distributions best model the size distribution of doline morphometric parameters and (ii) how to characterize the volume of dolines based on high-resolution DTMs. For backward compatibility, how previous datasets obtained predominantly from topographic maps relate to doline data derived from LiDAR is also examined. Our study area includes the karst plateaus of Aggtelek Karst and Slovak Karst national parks, whose caves are part of the UNESCO World Heritage. To characterize the study area, the relationships between doline parameters and topography were studied, as well as their geological characteristics. Our analysis revealed that the LiDAR-based doline density is 25% higher than the value calculated from topographic maps. Furthermore, LiDAR-based doline delineations are slightly larger and less rounded than in the case of topographic maps. The plateaus of the study area are characterized by low (5–10 km−2), moderate (10–30 km−2), and medium (30–35 km−2) doline densities. In terms of topography, the slope trend is decisive since the doline density is negligible in areas where the general slope is steeper than 12°. As for the lithology, 75% of the dolines can be linked to Wetterstein Limestone. The statistical distribution of the doline area can be well modeled by the lognormal distribution. To describe the DTM-based volume of dolines, a new parameter (k) is introduced to characterize their 3D shape: it is equal to the product of the area and the depth divided by the volume. This parameter indicates whether the idealized shape of the doline is closer to a cylinder, a bowl (calotte), a cone, or a funnel shape. The results show that most sinkholes in the study area have a transitional shape between a bowl (calotte) and a cone.
An Instrument Error Correlation Model for Global Navigation Satellite System Reflectometry
Authors: Powell C. E. , Ruf Christopher S. , McKague Darren S. , Wang Tianlin , Russel Anthony
Published: February 2024

All sensing systems have some inherent error. Often, these errors are systematic, and observations taken within a similar region of space and time can have correlated error structure. However, the data from these systems are frequently assumed to have completely independent and uncorrelated error. This work introduces a correlated error model for GNSS reflectometry (GNSS-R) using observations from NASA’s Cyclone Global Navigation Satellite System (CYGNSS). We validate our model against near-simultaneous observations between two CYGNSS satellites and double-difference our results with modeled observables to extract the correlated error structure due to the observing system itself. Our results are useful to catalog for future GNSS-R missions and can be applied to construct an error covariance matrix for weather data assimilation.
Efficient Model-Based Anthropometry under Clothing Using Low-Cost Depth Sensors
Authors: Park Byoung-Keon D. , Jung Hayoung , Ebert Sheila M. , Corner Brian D. , Reed Matthew P.
Published: February 2024

Measuring human body dimensions is critical for many engineering and product design domains. Nonetheless, acquiring body dimension data for populations using typical anthropometric methods poses challenges due to the time-consuming nature of manual methods. The measurement process for three-dimensional (3D) whole-body scanning can be much faster, but 3D scanning typically requires subjects to change into tight-fitting clothing, which increases time and cost and introduces privacy concerns. To address these and other issues in current anthropometry techniques, a measurement system was developed based on portable, low-cost depth cameras. Point-cloud data from the sensors are fit using a model-based method, Inscribed Fitting, which finds the most likely body shape in the statistical body shape space and providing accurate estimates of body characteristics. To evaluate the system, 144 young adults were measured manually and with two levels of military ensembles using the system. The results showed that the prediction accuracy for the clothed scans remained at a similar level to the accuracy for the minimally clad scans. This approach will enable rapid measurement of clothed populations with reduced time compared to manual and typical scan-based methods.
Wind-Speed-Adaptive Resonant Piezoelectric Energy Harvester for Offshore Wind Energy Collection
Authors: Wu Weijian , Pan Zhen , Zhou Jiangtao , Wang Yingting , Ma Jijie , Li Jianping , Hu Yili , Wen Jianming , Wang Xiaolin
Published: February 2024

This paper proposes a wind-speed-adaptive resonant piezoelectric energy harvester for offshore wind energy collection (A-PEH). The device incorporates a coil spring structure, which sets the maximum threshold of the output rotational frequency, allowing the A-PEH to maintain a stable output rotational frequency over a broader range of wind speeds. When the maximum output excitation frequency of the A-PEH falls within the sub-resonant range of the piezoelectric beam, the device becomes wind-speed-adaptive, enabling it to operate in a sub-resonant state over a wider range of wind speeds. Offshore winds exhibit an annual average speed exceeding 5.5 m/s with significant variability. Drawing from the characteristics of offshore winds, a prototype of the A-PEH was fabricated. The experimental findings reveal that in wind speed environments, the device has a startup wind speed of 4 m/s, and operates in a sub-resonant state when the wind speed exceeds 6 m/s. At this point, the A-PEH achieves a maximum open-circuit voltage of 40 V and an average power of 0.64 mW. The wind-speed-adaptive capability of the A-PEH enhances its ability to harness offshore wind energy, showcasing its potential applications in offshore wind environments.
Reptile Identification for Endemic and Invasive Alien Species Using Transfer Learning Approaches
Authors: Hernández-López Ruymán , Travieso-González Carlos M.
Published: February 2024

The Canary Islands are considered a hotspot of biodiversity and have high levels of endemicity, including endemic reptile species. Nowadays, some invasive alien species of reptiles are proliferating with no control in different parts of the territory, creating a dangerous situation for the ecosystems of this archipelago. Despite the fact that the regional authorities have initiated actions to try to control the proliferation of invasive species, the problem has not been solved as it depends on sporadic sightings, and it is impossible to determine when these species appear. Since no studies for automatically identifying certain species of reptiles endemic to the Canary Islands have been found in the current state-of-the-art, from the Signals and Communications Department of the Las Palmas de Gran Canaria University (ULPGC), we consider the possibility of developing a detection system based on automatic species recognition using deep learning (DL) techniques. So this research conducts an initial identification study of some species of interest by implementing different neural network models based on transfer learning approaches. This study concludes with a comparison in which the best performance is achieved by integrating the EfficientNetV2B3 base model, which has a mean Accuracy of 98.75%.
GY-SLAM: A Dense Semantic SLAM System for Plant Factory Transport Robots
Authors: Xie Xiaolin , Qin Yibo , Zhang Zhihong , Yan Zixiang , Jin Hang , Xu Man , Zhang Cheng
Published: February 2024

Simultaneous Localization and Mapping (SLAM), as one of the core technologies in intelligent robotics, has gained substantial attention in recent years. Addressing the limitations of SLAM systems in dynamic environments, this research proposes a system specifically designed for plant factory transportation environments, named GY-SLAM. GY-SLAM incorporates a lightweight target detection network, GY, based on YOLOv5, which utilizes GhostNet as the backbone network. This integration is further enhanced with CoordConv coordinate convolution, CARAFE up-sampling operators, and the SE attention mechanism, leading to simultaneous improvements in detection accuracy and model complexity reduction. While mAP@0.5 increased by 0.514% to 95.364, the model simultaneously reduced the number of parameters by 43.976%, computational cost by 46.488%, and model size by 41.752%. Additionally, the system constructs pure static octree maps and grid maps. Tests conducted on the TUM dataset and a proprietary dataset demonstrate that GY-SLAM significantly outperforms ORB-SLAM3 in dynamic scenarios in terms of system localization accuracy and robustness. It shows a remarkable 92.59% improvement in RMSE for Absolute Trajectory Error (ATE), along with a 93.11% improvement in RMSE for the translational drift of Relative Pose Error (RPE) and a 92.89% improvement in RMSE for the rotational drift of RPE. Compared to YOLOv5s, the GY model brings a 41.5944% improvement in detection speed and a 17.7975% increase in SLAM operation speed to the system, indicating strong competitiveness and real-time capabilities. These results validate the effectiveness of GY-SLAM in dynamic environments and provide substantial support for the automation of logistics tasks by robots in specific contexts.
Sustainable Management Strategies for Fruit Processing Byproducts for Biorefineries: A Review
Authors: Błaszczyk Alfred , Sady Sylwia , Pachołek Bogdan , Jakubowska Dominika , Grzybowska-Brzezińska Mariola , Krzywonos Małgorzata , Popek Stanisław
Published: February 2024

The fruit processing industry generates enormous amounts of byproducts, which are primarily removed through landfill or incineration. However, these processes cause carbon dioxide and methane emissions and release dioxin into the environment. The management of fruit processing byproducts is important for reducing the amount of food waste that is sent to landfills and for developing strategies through the reuse of these products for valorization and economic added value. Fruit processing byproducts are rich sources of bioactive compounds and fermentable and nonfermentable sugars. Therefore, these materials are very attractive feedstocks for developing integrated multifeed biorefineries that coproduce a wide range of natural products and bioenergy. The studies presented here have shown sustainable strategies for managing fruit processing byproducts via a biorefinery approach to achieve full valorization via a circular economy. The full valorization project proposed five main phases, namely, pretreatment, extraction, dark or aerobic fermentation, anaerobic digestion, and post-treatment, as well as two additional pathways to generate additional bioelectricity. When choosing the appropriate directions for the presented concept, a technoeconomic analysis should be carried out, considering the type of biomass and its availability at the site of the biorefinery and throughout the year of production. Applying the proposed concept of biorefineries in closed-loop technology is a promising way to enhance economic efficiency and decrease environmental influence in accordance with sustainable development.
Sustainable Supply Chain Practices in the Oil and Gas Industry: A Case Study
Authors: Hasan Jasim , Thomas Andrew , Tomos Owain
Published: February 2024

Sustainability reporting within the oil and gas (O&G) industry started back in the 1990s and has improved longitudinally since then. However, when reporting their sustainability-related practices and initiatives, O&G companies seldomly mention the term green supply chain management (GSCM). The study aims to investigate the development of GSCM practices in the O&G sector and to categorize how they are integrated with the sustainability practices reported by the industry. A multi-phase research approach was adopted consisting of a comprehensive literature review, followed by a single case study employed in an international oil and gas company. Primary data were collected by conducting 12 semi-structured interviews with senior members of an O&G company. Thematic analysis was employed to analyze the primary data from the interviews and to synthesize this work with the secondary data in order to answer the research question. The research identifies that the adoption of green purchasing practices is still in its infancy, whereas green production practices are more advanced compared to the current academic literature on the O&G industry. Additionally, new insights are obtained on how O&G companies are diversifying their business models and investing in the renewable energy business. The results of this work will enable O&G businesses to understand the latest developments in GSCM practices and how they are impacting the O&G sector. Practitioners will also be able to benchmark their current GSCM practices with the research findings and develop and formulate strategies to maximize the implementation of GSCM practices.
Experimental Study on the Influence of Real-Time Temperature Cycling on Physical and Mechanical Properties of Granite
Authors: Li Chun , Zhang Chunwang , Hu Yaoqing , Feng Gan
Published: February 2024

In this paper, a self-developed multi-functional high-temperature rock triaxial servo control testing machine was used to carry out uniaxial compression tests on the granite after the cooling and heating cycles under real-time temperature. The physical and mechanical properties of two types of granite damaged by hot and cold cycling under real-time temperature were discussed, and the changes in apparent color, longitudinal wave velocity, elastic modulus, uniaxial compressive strength, and damage characteristics of the specimen were revealed. The research results show the following: (1) With the increase in temperature or the increase in number of cycles, the uniaxial compressive strength, longitudinal wave velocity, and elastic modulus of the samples under the two cooling methods all show a decreasing trend, but the decrease in the range is different. The change range of the sample with temperature is greater than that with the number of cycles. (2) Under the dual action of real-time temperature and cold heat cycle damage, the failure form of granite is very random, but it is mainly shear failure, longitudinal splitting failure, and conical failure, and it is accompanied by a high temperature with the increase in the number of cycles, and the degree of crushing of the test piece gradually increases. For example, the sample under 600 °C water cooling for 25 cycles is crushed and destroyed. (3) As the temperature and the number of cycles increase, the surface of the water-cooled sample becomes rougher with the increase in the temperature and the number of cycles and the higher temperature, along with more cracks and debris; the increase in the temperature cycle, no obvious cracks appeared on the surface. The test results in this paper can provide relevant theoretical guidance for the stability and safety of rock in geothermal mining.
An Integrated Multi-Criteria Decision Analysis and Structural Equation Modeling Application for the Attributes Influencing the Customer’s Satisfaction and Trust in E-Commerce Applications
Authors: Jou Yung-Tsan , Saflor Charmine Sheena , Mariñas Klint Allen , Manzano Hannah Maureen , Uminga John Mark , Verde Nicole Angela , Dela Fuente Ginber
Published: February 2024

Since the COVID-19 pandemic has forced most industries to embrace an online platform utilizing technological breakthroughs, it has significantly impacted our daily lives. Businesses that use marketplaces to sell and trade products to customers while increasing their participation through online shopping or e-commerce are among the sectors that take advantage of these situations. The current study set out to evaluate the level of customer satisfaction, trust, and service quality of the e-commerce application to enhance the system and provide a better shopping experience. Facebook, Shopee, Lazada, Shein, and TikTok were the five e-commerce platforms evaluated. The Philippines was the location of this study, and at least 200 people answered the survey, which was conducted in-person and online and consisted of 72 questionnaires. The researchers assessed twelve latent variables: perceived security, customer satisfaction, application interface, brand equity, tangibility, reliability, responsiveness, assurance, empathy, and information credibility. Structural equation modeling and multi-criteria decision analysis were used to analyze the data. The findings demonstrated that assurance, application interface, information credibility, and brand equity directly impacted service quality. Moreover, a direct and significant correlation exists between customer satisfaction and service quality. Customers’ trust is significantly impacted by their level of satisfaction and perception of security. The e-commerce apps were ranked using a multi-criteria decision analysis technique, which is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on tangibility, responsiveness, assurance, reliability, and empathy. Facebook received a low rating, whereas Shopee was ranked highest. To further enhance the services offered, the lowest rated application may use the results from the combination of the TOPSIS and SEM results. Additionally, application providers, managers, and researchers examining the user–software interaction of relevant e-commerce applications might utilize the study’s results to enhance their services regarding the purchasing experience and provide a sustainable service. Finally, this study is among the first to use the structural modeling approach to evaluate customer trust and satisfaction while integrating service quality and TOPSIS.
Energy and Circular Economy: Nexus beyond Concepts
Authors: Martins Florinda F. , Castro Hélio , Smitková Miroslava , Felgueiras Carlos , Caetano Nídia
Published: February 2024

Energy and materials are increasingly important in industrialized countries, and they impact the economy, sustainability, and people’s future. The purpose of this work was to study the relationship between energy and the circular economy using methods such as Pearson’s correlation and a principal component analysis. Thus, 12 strong correlations were found, with 5 of them between the following relevant variables from two different subjects: the correlations of the raw material consumption, the domestic material consumption, and the material import dependency with the final energy consumption in transport (0.81, 0.92, and 0.81); the correlation of the circular material use rate with the final energy consumption in households (0.70); and the correlation of the material import dependency with the final energy consumption in industry (0.89). The time series forecast was only conclusive for the waste generated, showing that it will increase in the next 10 years.