bluuebunny/crossref_metadata_2025 huggingface dataset:
Calcium-Alginate-Chitosan Nanoparticle as a Potential Solution for Pesticide Removal, a Computational Approach
Authors: Yáñez Osvaldo , Alegría-Arcos Melissa , Suardiaz Reynier , Morales-Quintana Luis , Castro Ricardo I. , Palma-Olate Jonathan , Galarza Christian , Catagua-González Ángel , Rojas-Pérez Víctor , Urra Gabriela , Hernández-Rodríguez Erix W. , Bustos Daniel
Published: July 2023

Pesticides have a significant negative impact on the environment, non-target organisms, and human health. To address these issues, sustainable pest management practices and government regulations are necessary. However, biotechnology can provide additional solutions, such as the use of polyelectrolyte complexes to encapsulate and remove pesticides from water sources. We introduce a computational methodology to evaluate the capture capabilities of Calcium-Alginate-Chitosan (CAC) nanoparticles for a broad range of pesticides. By employing ensemble-docking and molecular dynamics simulations, we investigate the intermolecular interactions and absorption/adsorption characteristics between the CAC nanoparticles and selected pesticides. Our findings reveal that charged pesticide molecules exhibit more than double capture rates compared to neutral counterparts, owing to their stronger affinity for the CAC nanoparticles. Non-covalent interactions, such as van der Waals forces, π-π stacking, and hydrogen bonds, are identified as key factors which stabilized the capture and physisorption of pesticides. Density profile analysis confirms the localization of pesticides adsorbed onto the surface or absorbed into the polymer matrix, depending on their chemical nature. The mobility and diffusion behavior of captured compounds within the nanoparticle matrix is assessed using mean square displacement and diffusion coefficients. Compounds with high capture levels exhibit limited mobility, indicative of effective absorption and adsorption. Intermolecular interaction analysis highlights the significance of hydrogen bonds and electrostatic interactions in the pesticide-polymer association. Notably, two promising candidates, an antibiotic derived from tetracycline and a rodenticide, demonstrate a strong affinity for CAC nanoparticles. This computational methodology offers a reliable and efficient screening approach for identifying effective pesticide capture agents, contributing to the development of eco-friendly strategies for pesticide removal.
Advances in Material Modification with Smart Functional Polymers for Combating Biofilms in Biomedical Applications
Authors: Mejía-Manzano Luis Alberto , Vázquez-Villegas Patricia , Prado-Cervantes Luis Vicente , Franco-Gómez Kristeel Ximena , Carbajal-Ocaña Susana , Sotelo-Cortés Daniela Lizeth , Atehortúa-Benítez Valeria , Delgado-Rodríguez Miguel , Membrillo-Hernández Jorge
Published: July 2023

Biofilms as living microorganism communities are found anywhere, and for the healthcare sector, these constitute a threat and allied mechanism for health-associated or nosocomial infections. This review states the basis of biofilms and their formation. It focuses on their relevance for the biomedical sector, generalities, and the major advances in modified or new synthesized materials to prevent or control biofilm formation in biomedicine. Biofilm is conceptualized as an aggregate of cells highly communicated in an extracellular matrix, which the formation obeys to molecular and genetic basis. The biofilm offers protection to microorganisms from unfavorable environmental conditions. The most frequent genera of microorganisms forming biofilms and reported in infections are Staphylococcus spp., Escherichia spp., and Candida spp. in implants, heart valves, catheters, medical devices, and prostheses. During the last decade, biofilms have been most commonly related to health-associated infections and deaths in Europe, the United States, and Mexico. Smart, functional polymers are materials capable of responding to diverse stimuli. These represent a strategy to fight against biofilms through the modification or synthesis of new materials. Polypropylene and poly-N-isopropyl acrylamide were used enough in the literature analysis performed. Even smart polymers serve as delivery systems for other substances, such as antibiotics, for biofilm control.
Novel PEG6000–Silica-MWCNTs Shape-Stabilized Composite Phase-Change Materials (ssCPCMs) for Thermal-Energy Storage
Authors: Nistor Cristina Lavinia , Gifu Ioana Catalina , Anghel Elena Maria , Ianchis Raluca , Cirstea Cristiana-Diana , Nicolae Cristian Andi , Gabor Augusta Raluca , Atkinson Irina , Petcu Cristian
Published: July 2023

This paper describes the preparation of new PEG6000–silica-MWCNTs composites as shape-stabilized phase change materials (ssPCMs) for application in latent heat storage. An innovative method was employed to obtain the new organic–inorganic hybrid materials, in which both a part of the PEG chains, used as the phase change material, and a part of the hydroxyl functionalized multiwall carbon nanotubes (MWCNTs-OH), used as thermo-conductive fillers, were covalently connected by newly formed urethane bonds to the in-situ-generated silica matrix. The study’s main aim was to investigate the optimal amount of PEG6000 that can be added to the fixed sol–gel reaction mixture so that no leakage of PEG occurs after repeated heating–cooling cycles. The findings show that the optimum PEG6000/NCOTEOS molar ratio was 2/1 (~91.5% PEG6000), because both the connected and free PEG chains interacted strongly with the in-situ-generated silica matrix to form a shape-stabilized material while preserving high phase-transition enthalpies (~153 J/G). Morphological and structural findings obtained by SEM, X-ray and Raman techniques indicated a distribution of the silica component in the amorphous phase (~27% for the optimum composition) located among the crystalline lamellae built by the folded chains of the PEG component. This composite maintained good chemical stability after a 450-cycle thermal test and had a good storage efficiency (~84%).
Tuning of Morphological and Antibacterial Properties of Poly(3,4-ethylenedioxythiophene):Peroxodisulfate by Methyl Violet
Authors: Gupta Sonal , Acharya Udit , Thottappali Muhammed Arshad , Pištěková Hana , Morávková Zuzana , Hromádková Jiřina , Taboubi Oumayma , Pfleger Jiří , Humpolíček Petr , Bober Patrycja
Published: July 2023

This study demonstrates a one-step synthesis of poly(3,4-ethylenedioxythiophene) (PEDOT) in the presence of the methyl violet (MV) dye. The structural properties of PEDOT:peroxodisulfate were studied using Raman and MALDI-TOF spectroscopies. The use of the MV dye in the polymerization process resulted in a change in the typical irregular morphology of PEDOT:peroxodisulfate, leading to the formation of spherical patterns. SEM and TEM analyses revealed that increasing the dye concentration can produce larger spherical aggregates probably due to the hydrophobic and π–π interactions. These larger aggregates hindered the charge transport and reduced the electrical conductivity. Interestingly, at higher dye concentrations (0.05 and 0.075 M), the PEDOT:peroxodisulfate/MV films exhibited significantly improved antibacterial activity against Staphylococcus aureus and Escherichia coli. Furthermore, the PEDOT:peroxodisulfate films with the incorporated MV dye exhibited a well-defined and repeatable redox behavior. The remarkable amalgamation of their optical, electrochemical and antibacterial properties provides the PEDOT:peroxodisulfate/MV materials with an immensely diverse spectrum of applications, including in optical sensors and medical devices.
Polyhydroxybutyrate Metabolism in Azospirillum brasilense and Its Applications, a Review
Authors: Martínez María de los Ángeles Martínez , Urzúa Lucía Soto , Carrillo Yovani Aguilar , Ramírez Mirian Becerril , Morales Luis Javier Martínez
Published: July 2023

Gram-negative Azospirillum brasilense accumulates approximately 80% of polyhydroxybutyrate (PHB) as dry cell weight. For this reason, this bacterium has been characterized as one of the main microorganisms that produce PHB. PHB is synthesized inside bacteria by the polymerization of 3-hydroxybutyrate monomers. In this review, we are focusing on the analysis of the PHB production by A. brasilense in order to understand the metabolism during PHB accumulation. First, the carbon and nitrogen sources used to improve PHB accumulation are discussed. A. brasilense accumulates more PHB when it is grown on a minimal medium containing a high C/N ratio, mainly from malate and ammonia chloride, respectively. The metabolic pathways to accumulate and mobilize PHB in A. brasilense are mentioned and compared with those of other microorganisms. Next, we summarize the available information to understand the role of the genes involved in the regulation of PHB metabolism as well as the role of PHB in the physiology of Azospirillum. Finally, we made a comparison between the properties of PHB and polypropylene, and we discussed some applications of PHB in biomedical and commercial areas.
Effect of Different Standard Geometry Shapes on the Tensile Properties of 3D-Printed Polymer
Authors: Faidallah Rawabe Fatima , Hanon Muammel M. , Vashist Varun , Habib Ahmad , Szakál Zoltán , Oldal István
Published: July 2023

This study presents a comparative analysis of the tensile properties of 3D-printed polymer specimens with different standard geometry shapes. The objective is to assess the influence of printing orientation and geometry on the mechanical performance. Rectangular-shaped ASTM D3039 specimens with angles of 0°, 15°, and 90° are compared to various tensile test specimens based on ASTM and ISO standards. All specimens are fabricated using polyethylene terephthalate glycol (PETG) material through fused deposition modeling (FDM). Two printing orientations, flat and on-edge, are investigated, and tensile strength, elastic modulus, strain, and elongation at break are measured. The study examines the weak spot commonly found at the neck of the specimens and evaluates the broken areas. Additionally, a numerical analysis using the finite element method (FEM) is performed to identify stress risers’ locations in each specimen type. Experimental results show that the ASTM D3039-0° specimen printed in the on-edge orientation exhibits the highest tensile properties, while the flat orientation yields the best results in terms of the broken area. The ISO 527-2 specimens consistently display lower tensile properties, irrespective of the printing orientation. The study highlights the enhanced tensile properties achieved with the rectangular shape. Specifically, the tensile strength of ASTM D3039-0° was 17.87% and 21% higher than that of the ISO 527 geometry shape for the flat and on-edge orientations, respectively. The numerical analysis indicated that the ISO 527-2 specimen had either no or minimal stress raisers, and the higher stresses observed in the narrow section were isolated from the gripping location. The findings contribute to understanding the relationship between standard geometry shapes, printing orientation, and the resulting tensile properties of 3D-printed polymer specimens.
Aqueous-Cellulose-Solvent-Derived Changes in Cellulose Nanocrystal Structure and Reinforcing Effects
Authors: Tong Yuqi , Huang Shuting , Meng Xianjun , Wang Yixiang
Published: July 2023

Cellulose nanocrystals as reinforcing agents have received considerable interest, and their dimension mainly depends on the original sources of cellulose. We intend to manually modulate the morphology of cellulose nanocrystals by treating them with cellulose solvents so that we can explore their reinforcing capacity. In this work, waste cotton fabric was processed in two aqueous solvents (a sulfuric acid aqueous solution and a NaOH/urea aqueous solution), and the regenerated cellulose was used to produce cellulose nanocrystals using acid hydrolysis. The results revealed that the nanocrystals (RCNC-H) obtained after the treatment in sulfuric acid had a hybrid crystalline structure and a needle-like shape with an aspect ratio of about 15.2, while cotton fabric was completely dissolved in the NaOH/urea aqueous solution, and the regenerated nanocrystals (RCNC-N) displayed a typical crystalline form of cellulose II with a higher crystallinity and a shorter rod-like shape with an aspect ratio of about 6.3. The reinforcing effects of RCNC-H and RCNC-N were evaluated using polyvinyl alcohol (PVA) films as a model, where the addition of RCNC-H resulted in a relatively better tensile strength and oxygen barrier property, and the PVA/RCNC-N films had a slightly lower water vapor permeability. Therefore, this work suggests a new possibility for altering the naturally formed nanostructure of cellulose for different applications.
Experimental Study on Migration and Intrusion Characteristics of Pulverized Coal in Propped Fractures
Authors: Zhu Qingao , Yin Liming , Huang Qiming , Wang Enmao , Hou Zhiguo
Published: July 2023

Aiming at the problem of pulverized migration and plugging propped fractures during coal seam fracturing, we experimentally studied the pressure changes and pulverized coal blocking characteristics with deionized water and solutions of three surfactants including 1227 (C21H38ClN), SDS (C12H25SO4Na) and TX-100 (C34H62O11). A device capable of visualizing propped fractures was established, and simulation experiments were conducted with solutions of different surfactants at different injection flow rates. The obtained images were binarized and analyzed to quantify the pulverized coal blockage degrees of facture under different conditions. The experimental results show that: (1) The higher the injection flow rate, the higher the inlet pressure. (2) All three surfactants can lower the injection pressure, as compared with water alone. SDS decreases the injection pressure more obviously at low injection flow rates, and the other two perform better at high injection flow rates. (3) Similar to their effects on inlet pressure, the ratio of pulverized coal in SDS solution is lower at low injection flow rates, while TX-100 and 1227 solutions show lower ratios of pulverized coal at high injection flow rates. Our work has provided a theoretical support for coal blockage removal and pressure reduction in propped fractures during coal seam fracturing to improve coal seam permeability and further improves the dust prevention effect of coal seam water injection.
Numerical Investigation on Solidification Behavior of Slab Ingot during Electroslag Remelting Process
Authors: Geng Xin , Jiang Zhou-Hua , Liu Fu-Bin
Published: July 2023

In the process of electroslag remelting (ESR) for large-sized slab ingots, controlling the surface quality of the slab ingot is challenging due to its relatively high width-to-thickness ratio. In this study, a three-dimensional dynamic mathematical model for single-electrode ESR slab ingots was developed using dynamic mesh technology, with the aid of the commercial software FLUENT. The model is based on the electromagnetic field equation, flow field equation, and energy equation. A detailed analysis of various physical fields and the distribution law of the metal pool shape was conducted. According to the calculation results, the maximum flow velocity of the molten slag was found below the consumable electrode, with the range of maximum velocity at different time points varying between 4.35 × 10−2 and 4.88 × 10−2 m/s. The range of the maximum temperature for the slag bath at different time points was between 2118 and 2122 K. As the remelting continued, the impact of the forced cooling of the bottom plate on the temperature of the metal pool weakened. Consequently, the temperature gradient of the electroslag ingot gradually decreased, the depth of the metal pool increased, and the height of the metal liquid head in the metal pool rose. The effects of different voltages, filling ratios, and mold chamfers on the shape of the metal pool were investigated using the established mathematical model. Based on the research findings from the mathematical model, the technical processes for ESR J80 large-sized slab ingots were improved, providing solutions to improve the surface quality of the ESR large-sized slab ingots.
The Emergence of Regressive Heroism in Current Far-Right Populism
Authors: Pérez-Agote José M. , Aleman Eliana
Published: July 2023

The purpose of this paper is to analyze the ways in which heroic leadership is manifested in current right-wing populism. Based on the distinction between heroic modernity and postheroic modernity, a genealogy of the heroic populist leader is proposed. This figure is analyzed by following the hero’s life process in three moments: recognition of his charismatic exceptionality, the struggle to carry out his mission of salvation and the inevitable consequences of the struggle, which cannot be anything other than victory or defeat. Throughout these three phases of heroic action, the way in which the populist hero manages his charisma and intervenes in the culture wars will be shown. Finally, after accompanying him on this ritual journey, it will be understood why populist heroism adopts a regressive model of heroism. It is concluded that extreme right-wing populist heroism is regressive in character, both in its personal and institutional deployment. As a regressive force, it is a source of instability and conflict in postheroic modernity.
Inverse Kinematics of an Anthropomorphic 6R Robot Manipulator Based on a Simple Geometric Approach for Embedded Systems
Authors: Anschober Michael , Edlinger Raimund , Froschauer Roman , Nüchter Andreas
Published: July 2023

This manuscript presents an efficient algorithm for solving the inverse kinematics problem of a 6R robot manipulator to be deployed on embedded control hardware. The proposed method utilizes the geometric relationship between the end-effector and the base of the manipulator, resulting in a computationally efficient solution. The approach aims to minimize computational complexity and memory consumption while maintaining the accuracy and real-time performance demonstrated by simulations and verified by experimental results on an embedded system. Furthermore, the manipulator is analyzed in terms of singularities, limits, the workspace, and general solvability. Due to the simplicity of the algorithm, a platform-independent implementation is possible. As a result, the average calculation time is reduced by a factor of five to eight and the average error is decreased by a factor of fifty compared to a powerful analytical solver.
Automatic Early Warning to Derive Eruption Source Parameters of Paroxysmal Activity at Mt. Etna (Italy)
Authors: Mereu Luigi , Marzano Frank Silvio , Bonadonna Costanza , Lacanna Giorgio , Ripepe Maurizio , Scollo Simona
Published: July 2023

Tephra dispersal and fallout resulting from explosive activity of Mt. Etna (Italy) represent a significant threat to the surrounding inhabited areas as well as to aviation operations. An early-warning system aimed at foreseeing the onset of paroxysmal activity has been developed, combining a thermal infrared camera, infrasonic network, and a weather radar. In this way, it is possible to identify the onset of a lava fountain as well as to determine the associated mass eruption rate (MER) and top plume height (HTP). The new methodology, defined as the paroxysmal early-warning (PEW) alert system, is based on the analysis of some explosive eruptions that occurred between 2011 and 2021 at Etna, simultaneously observed by the thermal camera and infrasound systems dislocated around the summit eruptive craters, and by the weather radar, located at about 32 km from the summit craters. This work represents an important step towards the mitigation of the potential impact associated with the tephra dispersal and fallout during paroxysms at Etna, which can be applied to other volcanoes with similar activity and monitoring strategies.
Soil Moisture Retrieval in Bare Agricultural Areas Using Sentinel-1 Images
Authors: Ettalbi Mouad , Baghdadi Nicolas , Garambois Pierre-André , Bazzi Hassan , Ferreira Emmanuel , Zribi Mehrez
Published: July 2023

Soil moisture maps are essential for hydrological, agricultural and risk assessment applications. To best meet these requirements, it is essential to develop soil moisture products at high spatial resolution, which is now made possible using the free Sentinel-1 (S1) SAR (Synthetic Aperture Radar) data. Some soil moisture retrieval techniques using S1 data relied on the use of a priori weather information in order to increase the precision of soil moisture estimates, which required access to a weather-forecasting framework. This paper presents an improved and fully autonomous solution for high-resolution soil moisture mapping in bare agricultural areas. The proposed solution derives a priori weather information directly from the original Sentinel images, thus bypassing the need for a weather forecasting framework. For soil moisture estimation, the neural network technique was implemented to ensure the optimum integration of radar information. The neural networks were trained using synthetic data generated by the modified Integral Equation Model (IEM) model and validated on real data from two study sites in France and Tunisia. The main findings showed that the use of a radar signal averaged over grids of a few km2 in addition to radar signal at plot scale instead of a priori weather information provides good soil moisture estimations. The accuracy is even slightly better compared to the accuracy obtained using a priori weather information.
Development of a Google Earth Engine-Based Application for the Management of Shallow Coral Reefs Using Drone Imagery
Authors: Zapata-Ramírez Paula A. , Hernández-Hamón Hernando , Fitzsimmons Clare , Cano Marcela , García Julián , Zuluaga Carlos A. , Vásquez Rafael E.
Published: July 2023

The Caribbean is one of the world’s most vulnerable regions to the projected impacts of climate change, and changes in coral reef ecosystems have been studied over the last two decades. Lately, new technology-based methods using satellites and unmanned vehicles, among others have emerged as tools to aid the governance of these ecosystems by providing managers with high-quality data for decision-making processes. This paper addresses the development of a Google Earth Engine (GEE)-based application for use in the management processes of shallow coral reef ecosystems, using images acquired with Remotely Piloted Aircraft Systems (RPAS) known as drones, at the Old Providence McBean Lagoon National Natural Park; a Marine Protected Area (MPA) located northwest of Old Providence Island, Colombia. Image acquisition and processing, known as drone imagery, is first described for flights performed using an RTK multispectral drone at five different monitoring stations within the MPA. Then, the use of the GEE app is described and illustrated. The user executes four simple steps starting with the selection of the orthomosaics uploaded to GEE and obtaining the reef habitat classification for four categories: coral, macroalgae, sand, and rubble, at any of the five monitoring stations. Results show that these classes can be effectively mapped using different machine-learning (ML) algorithms available inside GEE, helping the manager obtain high-quality information about the reef. This remote-sensing application represents an easy-to-use tool for managers that can be integrated into modern ecosystem monitoring protocols, supporting effective reef governance within a digitized society with more demanding stakeholders.
Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference
Authors: Mukhopadhyay Ritwika , Næsset Erik , Gobakken Terje , Mienna Ida Marielle , Bielza Jaime Candelas , Austrheim Gunnar , Persson Henrik Jan , Ørka Hans Ole , Roald Bjørn-Eirik , Bollandsås Ole Martin
Published: July 2023

Due to climate change, treelines are moving to higher elevations and latitudes. The estimation of biomass of trees and shrubs advancing into alpine areas is necessary for carbon reporting. Remotely sensed (RS) data have previously been utilised extensively for the estimation of forest variables such as tree height, volume, basal area, and aboveground biomass (AGB) in various forest types. Model-based inference is found to be efficient for the estimation of forest attributes using auxiliary RS data, and this study focused on testing model-based estimations of AGB in the treeline ecotone using an area-based approach. Shrubs (Salix spp., Betula nana) and trees (Betula pubescens ssp. czerepanovii, Sorbus aucuparia, Populus tremula, Pinus sylvestris, Picea abies) with heights up to about five meters constituted the AGB components. The study was carried out in a treeline ecotone in Hol, southern Norway, using field plots and point cloud data obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP). The field data were acquired for two different strata: tall and short vegetation. Two separate models for predicting the AGB were constructed for each stratum based on metrics calculated from ALS and DAP point clouds, respectively. From the stratified predictions, mean AGB was estimated for the entire study area. Despite the prediction models showing a weak fit, as indicated by their R2-values, the 95% CIs were relatively narrow, indicating adequate precision of the AGB estimates. No significant difference was found between the mean AGB estimates for the ALS and DAP models for either of the strata. Our results imply that RS data from ALS and DAP can be used for the estimation of AGB in treeline ecotones.
Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis
Authors: Anderson Connor J. , Heins Daniel , Pelletier Keith C. , Knight Joseph F.
Published: July 2023

Machine learning is frequently combined with imagery acquired from uncrewed aircraft systems (UASs) to detect invasive plants. Having prior knowledge of which machine learning algorithm will produce the most accurate results is difficult. This study examines the efficacy of a voting-based ensemble classifier to identify invasive Phragmites australis from three-band (red, green, blue; RGB) and five-band (red, green, blue, red edge, near-infrared; multispectral; MS) UAS imagery acquired over multiple Minnesota wetlands. A Random Forest, histogram-based gradient-boosting classification tree, and two artificial neural networks were used within the voting-based ensemble classifier. Classifications from the RGB and multispectral imagery were compared across validation sites both with and without post-processing from an object-based image analysis (OBIA) workflow (post-machine learning OBIA rule set; post-ML OBIA rule set). Results from this study suggest that a voting-based ensemble classifier can accurately identify invasive Phragmites australis from RGB and multispectral imagery. Accuracies greater than 80% were attained by the voting-based ensemble classifier for both the RGB and multispectral imagery. The highest accuracy, 91%, was achieved when using the multispectral imagery, a canopy height model, and a post-ML OBIA rule set. The study emphasizes the need for further research regarding the accurate identification of Phragmites australis at low stem densities.
Infrared Dim Small Target Detection Based on Nonconvex Constraint with L1–L2 Norm and Total Variation
Authors: Shao Yu , Kang Xu , Ma Mingyang , Chen Cheng , He Sun , Wang Dejiang
Published: July 2023

Infrared dim small target detection has received a lot of attention, because it is a crucial component of the IR search and track systems (IRST). The robust principal component analysis (RPCA) is a common detection framework, which works with poor performance with complex background edges and sparse clutters due to the inappropriate approximation of sparse items. A nonconvex constraint detection method based on the difference between the L1 and L2 (L1–L2) norm and total variation (TV) is presented. The L1–L2 norm is a more accurate sparse item approximation of L0 norm, which can achieve a better description of the sparse item to separate the target from the complex backgrounds. Then, the total variation norm is conducted on the target image to suppress the sparse clutters. The new model is solved using the alternating direction method of multipliers (ADMM) method. Then, the subproblems in the model are tackled by the difference of convex algorithm (DCA) and the Newton conjugate gradient (Newton-CG) solving L1–L2 norm and TV norm, respectively. In the experiment, we conducted experiments on multiple and single target datasets, and the proposed model outperforms the state-of-the-art (SOTA) methods in terms of background suppression and robustness to accurately detect the target. It can achieve a higher true position rate (TPR) with a low false position rate (FPR).
High-Resolution Remote Sensing Image Change Detection Method Based on Improved Siamese U-Net
Authors: Wang Qing , Li Mengqi , Li Gongquan , Zhang Jiling , Yan Shuoyue , Chen Zhuoran , Zhang Xiaodong , Chen Guanzhou
Published: July 2023

Focusing on problems of blurred detection boundary, small target miss detection, and more pseudo changes in high-resolution remote sensing image change detection, a change detection algorithm based on Siamese neural networks is proposed. Siam-FAUnet can implement end-to-end change detection tasks. Firstly, the improved VGG16 is utilized as an encoder to extract the image features. Secondly, the atrous spatial pyramid pooling module is used to increase the receptive field of the model to make full use of the global information of the image and obtain the multi-scale contextual information of the image. The flow alignment module is used to fuse the low-level features in the encoder to the decoder and solve the problem of semantic misalignment caused by the direct concatenation of features when the features are fused, so as to obtain the change region of the image. The experiments are trained and tested using publicly available CDD and SZTAKI datasets. The results show that the evaluation metrics of the Siam-FAUnet model are improved compared to the baseline model, in which the F1-score is improved by 4.00% on the CDD and by 7.32% and 2.62% on the sub-datasets of SZTAKI (SZADA and TISZADOB), respectively; compared to other state-of-the-art methods, the Siam-FAUnet model has improved in both evaluation metrics, indicating that the model has a good detection performance.
Influences of Ecological Restoration Programs on Ecosystem Services in Sandy Areas, Northern China
Authors: Xu Shixian , Su Yuan , Yan Wei , Liu Yuan , Wang Yonghui , Li Jiaxin , Qian Kaixuan , Yang Xiuyun , Ma Xiaofei
Published: July 2023

Ecosystem services (ESs) are important for supporting human development. However, a changing climate and anthropogenic impacts are resulting in the degradation of dryland ecosystems to varying degrees. While there has been the global implementation of Ecological Restoration Programs (ERPs) to restore degraded ecosystems, there remains limited comprehensive assessment of their impacts on ESs of drylands. In this study, the sandy areas of northern China were used as the study area. The RUSLE, RWEQ, CASA, and InVEST models were used to simulate four major ESs: soil conservation (SC), sand fixation (SF), carbon sequestration (CS), and water yield (WY). The study aimed to evaluate the influences of various ERPs on major ESs. The dominant factors affecting the overall benefits provided by ESs were also identified. Since ERPs were implemented, forest areas have increased by 2.8 × 104 km2, whereas the areas of cropland, shrubland, and grassland have decreased. There were generally increasing trends in SF, SC, and CS, whereas there was a decreasing trend in WY. We then used a scenario-based simulation approach to eliminate the influence of climate variability on ESs. The results showed increasing trends in SF, SC, and CS, whereas there were minimal changes in WY. The results suggested that although ERPs can significantly increase regional ESs, unregulated expansion in vegetation can result in a water crisis and affect regional water security.
TranSDet: Toward Effective Transfer Learning for Small-Object Detection
Authors: Xu Xinkai , Zhang Hailan , Ma Yan , Liu Kang , Bao Hong , Qian Xu
Published: July 2023

Small-object detection is a challenging task in computer vision due to the limited training samples and low-quality images. Transfer learning, which transfers the knowledge learned from a large dataset to a small dataset, is a popular method for improving performance on limited data. However, we empirically find that due to the dataset discrepancy, directly transferring the model trained on a general object dataset to small-object datasets obtains inferior performance. In this paper, we propose TranSDet, a novel approach for effective transfer learning for small-object detection. Our method adapts a model trained on a general dataset to a small-object-friendly model by augmenting the training images with diverse smaller resolutions. A dynamic resolution adaptation scheme is employed to ensure consistent performance on various sizes of objects using meta-learning. Additionally, the proposed method introduces two network components, an FPN with shifted feature aggregation and an anchor relation module, which are compatible with transfer learning and effectively improve small-object detection performance. Extensive experiments on the TT100K, BUUISE-MO-Lite, and COCO datasets demonstrate that TranSDet achieves significant improvements compared to existing methods. For example, on the TT100K dataset, TranSDet outperforms the state-of-the-art method by 8.0% in terms of the mean average precision (mAP) for small-object detection. On the BUUISE-MO-Lite dataset, TranSDet improves the detection accuracy of RetinaNet and YOLOv3 by 32.2% and 12.8%, respectively.
Minimal Information Data-Modelling (MID) and an Easily Implementable Low-Cost SHM System for Use on a Short-Span Bridge
Authors: O’Higgins Connor , Hester David , McGetrick Patrick , Cross Elizabeth J. , Ao Wai Kei , Brownjohn James
Published: July 2023

Structural Health Monitoring (SHM) is a technique that involves gathering information to ensure that a structure is safe and behaving as expected. Within SHM, vibration-based monitoring is generally seen as one of the more cost-effective types of monitoring. However, vibration-based monitoring has mostly been undertaken on long-span bridges using data collected with a dense network of sensors. Historically, the logistical difficulty of collecting data on short- and medium-span bridges has meant that the usefulness of vibration-based methods on these bridges is largely unknown. Therefore, this study proposes Minimal Information Data-modelling (MID). MID is an approach that utilises low-cost, easily implementable sensors that are potentially feasible for operators to purchase and operate across a network. This approach will be investigated to determine whether MID is a feasible approach for monitoring short- and medium- span bridges. The results from MID were assessed to determine whether they could detect a suitably small shift in frequency, which is indicative of damage. It was determined that the data models could reliably detect frequency shifts as low as 0.01 Hz. This magnitude of frequency shift is similar to the level of frequency shift reported for a range of bridge damage cases found by others and validated with FE models. The accuracy achieved by the data models indicates that MID could potentially be used as a damage detection method. The cost of the equipment used to collect the data was approximately £370, demonstrating that it is feasible to use MID to monitor bridges across an entire network.
The Unknown Abnormal Condition Monitoring Method for Pumped-Storage Hydroelectricity
Authors: Lee Jun , Kim Kiyoung , Sohn Hoon
Published: July 2023

Pumped-storage hydroelectricity (PSH) is a facility that stores energy in the form of the gravitational potential energy of water by pumping water from a lower to a higher elevation reservoir in a hydroelectric power plant. The operation of PSH can be divided into two states: the turbine state, during which electric energy is generated, and the pump state, during which this generated electric energy is stored as potential energy. Additionally, the condition monitoring of PSH is generally challenging because the hydropower turbine, which is one of the primary components of PSH, is immersed in water and continuously rotates. This study presents a method that automatically detects new abnormal conditions in target structures without the intervention of experts. The proposed method automatically updates and optimizes existing abnormal condition classification models to accommodate new abnormal conditions. The performance of the proposed method was evaluated with sensor data obtained from on-site PSH. The test results show that the proposed method detects new abnormal PSH conditions with an 85.89% accuracy using fewer than three datapoints and classifies each condition with a 99.73% accuracy on average.
Performance of a Double RIS Communication System Aided by Partially Active Elements
Authors: Yoo Seung-Geun , Kim Min-A , Kim Jin-Woo , Park Sang-Wook , You Young-Hwan , Song Hyoung-Kyu
Published: July 2023

Reconfigurable intelligent surface (RIS) has emerged as a promising technology to enhance the spectral efficiency of wireless communication systems. However, if there are many obstacles between the RIS and users, a single RIS may not provide sufficient performance. For this reason, a double RIS-aided communication system is proposed in this paper. However, this system also has a problem: the signal is attenuated three times due to the three channels created by the double RIS. To overcome these attenuations, an active RIS is proposed in this paper. An active RIS is almost the same as a conventional RIS, except for the included amplifier. Comprehensively, the proposed system overcomes various obstacles and attenuations. In this paper, an active RIS is applied to the second RIS. To reduce the power consumption of active elements, a partially active RIS is applied. To optimize the RIS elements, the sum of the covariance matrix is found by using channels related to each RIS, and the right singular vector is exploited using singular value decomposition for the sum of the covariance matrix. Then, the singular value of the sum of the covariance value is checked to determine which element is the active element. Simulation results show that the proposed system has better sum rate performance compared to a single RIS system. Although it has a lower sum rate performance compared to a double RIS with fully active elements, the proposed system will be more attractive in the future because it has much better energy efficiency.
Next-Generation Pedal: Integration of Sensors in a Braking Pedal for a Full Brake-by-Wire System
Authors: Gumiel Jose Ángel , Mabe Jon , Burguera Fernando , Jiménez Jaime , Barruetabeña Jon
Published: July 2023

This article presents a novel approach to designing and validating a fully electronic braking pedal, addressing the growing integration of electronics in vehicles. With the imminent rise of brake-by-wire (BBW) technology, the brake pedal requires electronification to keep pace with industry advancements. This research explores technologies and features for the next-generation pedal, including low-power consumption electronics, cost-effective sensors, active adjustable pedals, and a retractable pedal for autonomous vehicles. Furthermore, this research brings the benefits of the water injection technique (WIT) as the base for manufacturing plastic pedal brakes towards reducing cost and weight while enhancing torsional stiffness. Communication with original equipment manufacturers (OEMs) has provided valuable insights and feedback, facilitating a productive exchange of ideas. The findings include two sensor prototypes utilizing inductive technology and printed-ink gauges. Significantly, reduced power consumption was achieved in a Hall-effect sensor already in production. Additionally, a functional BBW prototype was developed and validated. This research presents an innovative approach to pedal design that aligns with current electrification trends and autonomous vehicles. It positions the braking pedal as an advanced component that has the potential to redefine industry standards. In summary, this research significantly contributes to the electronic braking pedal technology presenting the critical industry needs that have driven technical studies and progress in the field of sensors, electronics, and materials, highlighting the challenges that component manufacturers will inevitably face in the forthcoming years.
Target Detection for Synthetic Aperture Radiometer Based on Satellite Formation Flight
Authors: Li Rui , Deng Li , Wang Yuan , Dai Haoming , Duan Ran
Published: July 2023

Synthetic aperture interferometers formed by satellite formations have been adopted to improve spatial resolution. Due to the limited number of satellites and limited integrated time, the use of sparse baselines can result in distorted reconstructed images, which will generate false targets or miss true targets. When detecting a target on the Earth from a geostationary orbit, the target usually occupies only one pixel, and it is almost submerged by noise. Considering the slow-varying characteristics of the observation area, combined with historical observation data and the motion characteristics of the target itself, a target detection method based on multi-frame snapshot images is proposed. Firstly, the observation background is estimated using multi-frame historical data, and background elimination is used to suppress the background noise. Then, potential targets are selected using the local brightness temperature characteristics of the targets. Lastly, the target motion tracks are applied to erase false targets and correct the positions of missed targets. Simulation experiments have been conducted, and the false alarm rate and the missing alarm rate are counted for randomly distributed targets.
Factors Affecting Attendance of and Attitudes towards Artistic Events among Primary School Children
Authors: Váradi Judit , Józsa Gabriella
Published: July 2023

In this study, the aim is twofold; on the one hand, we investigate extracurricular artistic activities, and on the other hand, regularity of visits to ten different artistic and cultural events, such as theatres, puppet theatres, dance and folk-dance performances, exhibitions, and musical performances for children, among 9–10 year old primary school children (N = 974). We are looking for an answer to the question of whether there is a connection between active artistic activity and the attitude towards cultural and artistic events. Additionally, we plan to identify differences in the family backgrounds of individuals who participate in artistic activities compared to those who do not. Furthermore, we will examine the influence of social, cultural, and economic capital on children’s cultural consumption and related attitudes. We tested our hypotheses using SPSS; the methods included logistic regression and factor analysis. In addition to highlighting the role of school in equalising cultural capital, the results confirm the powerful effect of generational transfer. When parents have actively engaged in artistic activities, they tend to offer enhanced support for their children’s artistic pursuits. Those who engage in certain types of extracurricular artistic activities during their childhood are more likely to exhibit more positive attitudes towards cultural events as adult consumers. However, parents’ high educational attainment and favourable financial circumstances are not the sole determinants of openness to art.
The Impact of Environmental Regulations on Enterprises’ Green Innovation: The Mediating Effect of Managers’ Environmental Awareness
Authors: Lin Deqin , Zhao Yuetong
Published: July 2023

It is of great significance to clarify the impact and mechanism of environmental regulations on enterprises’ green innovation. This paper empirically studies the impact of command-and-control environmental regulation (CCER) and market-incentive-based environmental regulation (MBER) on enterprises’ green innovation and tests the mediating effect of managers’ environmental awareness by using the data of Chinese A-share companies listed in the Shanghai and Shenzhen stock exchange from 2011 to 2020. The results show the following: 1. the CCER has a significant promoting effect on both the quantity and quality of green innovation, but the impact of the MBER is significantly negative; 2. managers’ environmental awareness has a mediating effect on the impact of the CCER, but there is no such mediating effect on the impact of the MBER; 3. The CCER has a strong promoting effect on the quantity and quality of the green innovation of heavily polluting state-owned enterprises with a high innovation capacity in central cities, while the MBER has a significant negative impact on the green innovation capacity of heavily polluting non-state-owned enterprises but can significantly promote the quantity and quality of enterprises’ green innovation with a high innovation capacity located in central cities. Finally, this paper gives some suggestions to promote the green innovation capacity of enterprises by optimizing the design of environmental regulation tools, improving managers’ environmental awareness and enhancing the degree of marketization.
Sector-Scale Proliferation of CSR Quality Label Programs via Mimicry: The Rotkäppchen Effect
Authors: Buckley Ralf
Published: July 2023

Proliferation of CSR quality certification programs can be analysed within theories of mimicry. Some firms use third-party quality certificates to signal their CSR practices to consumers accurately. These firms and consumers benefit from few, simple, recognized, reliable labels. Other firms use competing or own-brand labels to signal deceptively, gaining competitive advantage without compliance costs. Unreliable labels act as mimics to dupe consumers. If consumers cannot determine which labels are misleading, they ignore them all. Within ecological theories of mimicry, this is known as aggressive reverse Brouwerian automimicry. CSR-label research has a different naming tradition, and this sector-scale effect could be called a rotkäppchen effect, analogous to program-scale groucho and firm-scale goldilocks effects. It is testable by analysing mimicry mechanisms or predicted patterns.
Smart Tourism Technologies, Revisit Intention, and Word-of-Mouth in Emerging and Smart Rural Destinations
Authors: Torabi Zabih-Allah , Pourtaheri Mehdi , Hall Colin Michael , Sharifi Ayyoob , Javidi Fazlollah
Published: July 2023

This study examines the influence of the various attributes of smart tourism technologies (STTs) on tourists’ intentions to revisit locations and engage in word-of-mouth (WOM) activities regarding emerging and smart rural tourist destinations in Iran. A sample of 590 tourists who visited these destinations following the COVID-19 pandemic participated in the study. The findings reveal that three attributes of STTs, namely, informativeness, accessibility, and interactivity, positively contribute to tourists’ memorable experiences (ME). Furthermore, ME, satisfaction, and the willingness to engage in WOM recommendations are identified as predictors of tourists’ intention to revisit rural destinations. The study also reveals that user competence serves as a mediator between the attributes of STTs (informativeness, accessibility, and interactivity) and the tourists’ ME. Specifically, tourists with greater skills and knowledge of using STTs tend to have more memorable experiences in these emerging and smart rural destinations. The study discusses both the theoretical and practical implications of these findings.