bluuebunny/crossref_metadata_2025 huggingface dataset:
Recent Progress in Polyion Complex Nanoparticles with Enhanced Stability for Drug Delivery
Authors: Ma Xinlin , Zhao Tianyi , Ren Xiaoyue , Lin Hui , He Pan
Published: July 2024

Polyion complex (PIC) nanoparticles, including PIC micelles and PICsomes, are typically composed of poly(ethylene glycol) block copolymers coupled with oppositely charged polyelectrolytes or therapeutic agents via electrostatic interaction. Due to a simple and rapid preparation process with high drug-loading efficiency, PIC nanoparticles are beneficial to maintaining the chemical integrity and high biological activity of the loaded drugs. However, the stability of PIC nanoparticles can be disrupted in high-ionic-strength solutions because electrostatic interaction is the DRIVING force; these disruptions can thus impair drug delivery. Herein, we summarize the advances in the use of PIC nanoparticles for delivery of charged drugs, focusing on the different chemical and physical strategies employed to enhance their stability, including enhancing the charge density, crosslinking, increasing hydrophobic interactions, forming hydrogen bonds, and the development of PIC-based gels. In particular, we describe the use of PIC nanoparticles to load peptide antibiotics targeting antibiotic-resistant and biofilm-related diseases and the use of nanoparticles that load chemotherapeutics and gaseous donors for cancer treatment. Furthermore, the application of PIC nanoparticles as magnetic resonance imaging contrast agents is summarized for the first time. Therefore, this review is of great significance for advances in the use of polymeric nanoparticles for functional drug delivery.
Enhancement of Thermal Management Performance of Copper Foil Using Additive–Free Graphene Coating
Authors: Hu Bing , Yuan Huilin , Chen Guohua
Published: July 2024

Advanced thermal interface materials with high thermal conductivity are crucial for addressing the heat dissipation issue in high-power, highly integrated electronic devices. One great potential way in this field is to take advantage of cooling copper foil (Cu) materials based on graphene (G). However, the current manufacturing of these cooling copper foil materials is accompanied by high cost, process complexity, and environmental problems, which limit their development and application. In this work, a simple, low-cost, environmentally friendly graphene-copper foil composite film (rGO/G-Cu) with high thermal conductivity was successfully prepared using graphene oxide directly as a dispersant and binder of graphene coating. The microstructure characterization, thermal conductivity and thermal management performance tests were carried out on the composite films. The results demonstrate that compared to pure copper foil (342.47 W·m−1·K−1) and 10% PVA/G-Cu (367.98 W·m−1·K−1) with polyvinyl alcohol as a binder, 10% rGO/G-Cu exhibits better thermal conductivity (414.56 W·m−1·K−1). The introduction of two-dimensional graphene oxide effectively enhances the adhesion between the coating and the copper foil while greatly improving its thermal conductivity. Furthermore, experimental results indicate that rGO/G-Cu exhibits excellent heat transfer performance and flexibility. This work is highly relevant to the development of economical and environmentally friendly materials with high thermal conductivity to meet the increasing demand for heat dissipation.
Nanoscopic Characterization of Starch-Based Biofilms Extracted from Ecuadorian Potato (Solanum tuberosum) Varieties
Authors: Ilvis Pablo , Acosta José , Arancibia Mirari , Casado Santiago
Published: July 2024

Synthetic plastic polymers are causing considerable emerging ecological hazards. Starch-based biofilms are a potential alternative. However, depending on the natural source and extraction method, the properties of starch can vary, affecting the physicochemical characteristics of the corresponding casted films generated from it. These differences might entail morphological changes at the nanoscale, which can be explored by inspecting their surfaces. Potato (Solanum tuberosum) is a well-known tuber containing a high amount of starch, but the properties of the biofilms extracted from it are dependent on the specific variety. In this research, four Ecuadorian potato varieties (Leona Blanca, Única, Chola, and Santa Rosa) were analyzed and blended with different glycerol concentrations. The amylose content of each extracted starch was estimated, and biofilms obtained were characterized at both macroscopic and nanoscopic levels. Macroscopic tests were conducted to evaluate their elastic properties, visible optical absorption, water vapor permeability, moisture content, and solubility. It was observed that as the glycerol percentage increased, both moisture content and soluble matter increased, while tensile strength decreased, especially in the case of the Chola variety. These results were correlated to a surface analysis using atomic force microscopy, providing a possible explanation based on the topography and phase contrast observations made at the nanoscale.
Transparent Superhydrophobic and Self-Cleaning Coating
Authors: Zhang Binbin , Xue Xiaochen , Zhao Lixia , Hou Baorong
Published: July 2024

Surface roughness and low surface energy are key elements for the artificial preparation of biomimetic superhydrophobic materials. However, the presence of micro-/nanostructures and the corresponding increase in roughness can increase light scattering, thereby reducing the surface transparency. Therefore, designing and constructing superhydrophobic surfaces that combine superhydrophobicity with high transparency has been a continuous research focus for researchers and engineers. In this study, a transparent superhydrophobic coating was constructed on glass substrates using hydrophobic fumed silica (HF-SiO2) and waterborne polyurethane (WPU) as raw materials, combined with a simple spray-coating technique, resulting in a water contact angle (WCA) of 158.7 ± 1.5° and a sliding angle (SA) of 6.2 ± 1.8°. Characterization tests including SEM, EDS, LSCM, FTIR, and XPS revealed the presence of micron-scale protrusions and a nano-scale porous network composite structure on the surface. The presence of HF-SiO2 not only provided a certain roughness but also effectively reduced surface energy. More importantly, the coating exhibited excellent water-repellent properties, extremely low interfacial adhesion, self-cleaning ability, and high transparency, with the light transmittance of the coated glass substrate reaching 96.1% of that of the bare glass substrate. The series of functional characteristics demonstrated by the transparent superhydrophobic HF-SiO2@WPU coating designed and constructed in this study will play an important role in various applications such as underwater observation windows, building glass facades, automotive glass, and goggles.
Novel Reactive Polyhedral Oligomeric Silsesquioxane-Reinforced and Toughened Epoxy Resins for Advanced Composites
Authors: Liu Weibo , Wang Caiyun , Feng Yu , Chen Yongfeng , Wan Liqiang , Huang Farong , Liu Zuozhen , Qian Jianhua , Liu Weiping
Published: July 2024

Most toughening methods for epoxy resins are usually used at the expense of other properties. Some polyhedral oligomeric silsesquioxanes (POSSs) with both a rigid Si-O-Si structure and flexible organic chain segments could be expected to be effective toughening agents. In this study, three reactive polyhedral oligomeric silsesquioxanes with a thiol group (OMPPS), a carboxyl group (OCOPS), and an epoxy group (OGCPS) were synthesized and characterized. They were utilized as modifiers to toughen 3-(oxiran-2-ylmethoxy)-N,N-bis(oxiran-2-ylmethyl)aniline (AFG-90MH)/4,4′-methylenebis(2-ethylaniline) (MOEA) (epoxy resin) with different molar ratios to obtain hybrid resins named OMPPS-EP-i, OCOPS-EP-j, and OGCPS-EP-k. The effects of the amount of modifier added and the length of the organic chain on the cage structure on various properties of the hybrid resins were investigated. The results show that all three modifiers show good compatibility with the epoxy resin. The hybrid resins have a low viscosity at 45~85 °C and can be cured at a low temperature (110 °C). The cured hybrid resins display improved toughness. Typically, the critical stress intensity factor (KIC) and impact strength of OGCPS-EP-0.6-C are 2.54 MPa∙m−1/2 and 19.33 kJ∙m−2, respectively, which increased by 58.75% and 22.48% compared with the pristine epoxy resin, respectively. In addition, the glass transition temperature and flexural strength of the hybrid resins are basically unchanged.
Self-Cleaning Antibacterial Composite Coating of Fluorinated Acrylic Resin and Ag/SiO2 Nanoparticles with Quaternary Ammonium
Authors: Gu Jiangdong , An Qiufeng , Huang Meng-chen , Ge Ping , Xue Chao-hua
Published: July 2024

With improvements in living standards, the demand for antibacterial self-cleaning coatings has significantly increased. In this work, self-cleaning coatings with antibacterial properties were fabricated by spray-coating a composite of fluorinated acrylic resin and Ag/SiO2 nanoparticles with quaternary ammonium salts. The synergistic action of the quaternary ammonium salts and silver nanostructures caused the coating to show a dual antibacterial effect. The Ag/SiO2 nanoparticles roughened the coating’s surface and, in combination with the fluorinated chains, provided the surface a superhydrophobic self-cleaning property with a contact angle of 156° and a sliding angle of less than 2°. Notably, the composite coating withstood 100 abrasion cycles without losing its superhydrophobicity and the contact angle is still exceeded 150° after 60 h of immersion solutions with different pH values, demonstrating outstanding wear resistance and acid/alkali stability. The incorporation of nanostructured antibacterial agents was effective in improving the roughness and antibacterial properties of the low-surface-energy resin, resulting in a self-cleaning antibacterial composite coating. This method may pave a new route for the design of functional coating materials with excellent overall performance.
Eco-Friendly Straws: A Fusion of Soy Protein Isolate and Cassava Starch Coated with Beeswax and Shellac Wax
Authors: Choeybundit Wissuta , Karbowiak Thomas , Lagorce Aurélie , Ngiwngam Kittaporn , Auras Rafael , Rachtanapun Pornchai , Noiwan Duangjai , Tongdeesoontorn Wirongrong
Published: July 2024

This research aimed to produce eco-friendly straws using soy protein isolate (SPI) and cassava starch (CS) at different ratios by the extrusion technique and by coating with beeswax and shellac wax. Three straw formulations (F) (F1: 24.39% SPI–24.39% CS; F2: 19.51% SPI–29.37% CS; and F3: 14.63% SPI–34.15% CS) were prepared, incorporating glycerol (14.6% w/w) and water (36.6% w/w). After extrusion and drying at 80 °C for 20 h, visual assessment favored F2 straws due to smoother surfaces, the absence of particles, and enhanced straightness. For the physical property test, the straws were softened in pH buffer solutions for 5 min. To simulate practical application, mechanical bending strength was studied under different relative humidity (RH) settings. Water absorption reduced the strength as RH increased. F2 straws outperformed other formulations in bending strength at 54% RH. For hydrophobic coatings, F2 was chosen. Beeswax- and shellac wax-coated straws displayed negligible water absorption and sustained their integrity for over 6 h compared to uncoated straws. This study shows that extrusion and natural coatings may make sustainable straws from SPI and CS. These efforts help meet the growing demand for eco-friendly plastic alternatives, opening up new options for single-use straws.
Mattel’s ©Barbie: Preventing Plasticizers Leakage in PVC Artworks and Design Objects through Film-Forming Solutions
Authors: Macchia Andrea , Marinelli Livia , Barbaccia Francesca Irene , de Caro Tilde , Hansen Alice , Schuberthan Lisa Maria , Izzo Francesca Caterina , Pintus Valentina , Testa Chiari Katiuscia , La Russa Mauro Francesco
Published: July 2024

The main conservation problem of p-PVC artworks is phthalate-based plasticizer migration. Phthalate migration from the bulk to the surface of the materials leads to the formation of a glossy and oily film on the outer layers, ultimately reducing the flexibility of the material. This study aimed to develop a removable coating for the preservation of contemporary artworks and design objects made of plasticized polyvinyl chloride (p-PVC). Several coatings incorporating chitosan, collagen, and cellulose ethers were assessed as potential barriers to inhibiting plasticizer migration. Analytical techniques including optical microscopy (OM), ultraviolet/visible/near-infrared spectroscopy (UV/Vis/NIR), Fourier transform infrared spectroscopy with attenuated total reflection (FTIR-ATR), and scanning electron microscopy (SEM) were utilized to evaluate the optical and chemical stability of selected coating formulations applied to laboratory p-PVC sheet specimens. Subsequently, formulations were tested on a real tangible example of a design object, ©Barbie doll, characterized by the prevalent issue of plasticizer migration. Furthermore, the results obtained with the tested formulations were evaluated by a group of conservators using a tailored survey. Finally, a suitable coating formulation capable of safeguarding plastic substrates was suggested.
Disasters and Archaeology: A Remote Sensing Approach for Determination of Archaeology At-Risk to Desertification in Sistan
Authors: Smith Rachel
Published: July 2024

Desertification in semi-arid environments poses a significant risk to the archaeology within arid and semi-arid regions. Due to multiple political and physical barriers, accessing desertification-prone areas is complex, complicating pathways towards generating a hands-on understanding of the time–depth and distribution of archaeology throughout these regions. This research developed a remote sensing methodology to determine the areas of Sistan experiencing the highest levels of desertification and the threat of that desertification to known and potential archaeology. As desertification processes are occurring rapidly, this work’s methodology is straightforward and efficient. In a region of vast archaeological value, desertification threatens to prevent archaeologists from potential insight and discovery. This work showcases the opportunity for remote sensing to work as a tool for accessing archaeology in physically inaccessible desertification-prone regions.
Dust Events over the Urmia Lake Basin, NW Iran, in 2009–2022 and Their Potential Sources
Authors: Abadi Abbas Ranjbar Saadat , Shukurov Karim Abdukhakimovich , Hamzeh Nasim Hossein , Kaskaoutis Dimitris G. , Opp Christian , Shukurova Lyudmila Mihailovna , Ghasabi Zahra
Published: July 2024

Nowadays, dried lake beds constitute the largest source of saline dust storms, with serious environmental and health issues in the surrounding areas. In this study, we examined the spatial–temporal distribution of monthly and annual dust events of varying intensity (dust in suspension, blowing dust, dust storms) in the vicinity of the desiccated Urmia Lake in northwestern (NW) Iran, based on horizontal visibility data during 2009–2022. Dust in suspension, blowing dust and dust storm events exhibited different monthly patterns, with higher frequencies between March and October, especially in the southern and eastern parts of the Urmia Basin. Furthermore, the intra-annual variations in aerosol optical depth at 500 nm (AOD550) and Ångström exponent at 412/470 nm (AE) were investigated using Terra/Aqua MODIS (Moderate Resolution Imaging Spectroradiometer) data over the Urmia Lake Basin (36–39°N, 44–47°E). Monthly distributions of potential coarse aerosol (AE < 1) sources affecting the lower troposphere over the Urmia Basin were reconstructed, synergizing Terra/Aqua MODIS AOD550 for AE < 1 values and HYSPLIT_4 backward trajectories. The reconstructed monthly patterns of the potential sources were compared with the monthly spatial distribution of Terra MODIS AOD550 in the Middle East and Central Asia (20–70°E, 20–50°N). The results showed that deserts in the Middle East and the Aral–Caspian arid region (ACAR) mostly contribute to dust aerosol load over the Urmia Lake region, exhibiting higher frequency in spring and early summer. Local dust sources from dried lake beds further contribute to the dust AOD, especially in the western part of the Urmia Basin during March and April. The modeling (DREAM8-NMME-MACC) results revealed high concentrations of near-surface dust concentrations, which may have health effects on the local population, while distant sources from the Middle East are the main controlling factors to aerosol loading over the Urmia Basin.
Application of Remote Sensing for Identifying Soil Erosion Processes on a Regional Scale: An Innovative Approach to Enhance the Erosion Potential Model
Authors: Polovina Siniša , Radić Boris , Ristić Ratko , Milčanović Vukašin
Published: July 2024

Soil erosion represents a complex ecological issue that is present on a global level, with negative consequences for environmental quality, the conservation and availability of natural resources, population safety, and material security, both in rural and urban areas. To mitigate the harmful effects of soil erosion, a soil erosion map can be created. Broadly applied in the Balkan Peninsula region (Serbia, Bosnia and Herzegovina, Croatia, Slovenia, Montenegro, North Macedonia, Romania, Bulgaria, and Greece), the Erosion Potential Method (EPM) is an empirical erosion model that is widely applied in the process of creating soil erosion maps. In this study, an innovation in the process of the identification and mapping of erosion processes was made, creating a coefficient of the types and extent of erosion and slumps (φ), representing one of the most sensitive parameters in the EPM. The process of creating the coefficient (φ) consisted of applying remote sensing methods and satellite images from a Landsat mission. The research area for which the satellite images were obtained and thematic maps of erosion processes (coefficient φ) were created is the area of the Federation of Bosnia and Herzegovina and the Brčko District (situated in Bosnia and Herzegovina). The Google Earth Engine (GEE) platform was employed to process and retrieve Landsat 7 Enhanced Thematic Mapper plus (ETM+) and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) satellite imagery over a period of ten years (from 1 January 2010 to 31 December 2020). The mapping and identification of erosion processes were performed based on the Bare Soil Index (BSI) and by applying the equation for fractional bare soil cover. The spatial–temporal distribution of fractional bare soil cover enabled the definition of coefficient (φ) values in the field. An accuracy assessment was conducted based on 190 reference samples from the field using a confusion matrix, overall accuracy (OA), user accuracy (UA), producer accuracy (PA), and the Kappa statistic. Using the confusion matrix, an OA of 85.79% was obtained, while UA ranged from 33% to 100%, and PA ranged from 50% to 100%. Applying the Kappa statistic, an accuracy of 0.82 was obtained, indicating a high level of accuracy. The availability of a time series of multispectral satellite images for each month is a crucial element in monitoring the occurrence of erosion processes of various types (surface, mixed, and deep) in the field. Additionally, it contributes significantly to decision-making, strategies, and plans in the domain of erosion control work, the development of plans for identifying erosion-prone areas, plans for defense against torrential floods, and the creation of soil erosion maps at local, regional, and national levels.
Snowmelt Onset and Caribou (Rangifer tarandus) Spring Migration
Authors: Matias Mariah T. , Ramage Joan M. , Gurarie Eliezer , Brodzik Mary J.
Published: July 2024

Caribou (Rangifer tarandus) undergo exceptionally large, annual synchronized migrations of thousands of kilometers, triggered by their shared environmental stimuli. The proximate triggers of those migrations remain mysterious, though snow characteristics play an important role due to their influence on the mechanics of locomotion. We investigate whether the snow melt–refreeze status relates to caribou movement, using previously collected Global Positioning System (GPS) caribou collar data. We analyzed 117 individual female caribou with >30,000 observations between 2007 and 2016 from the Bathurst herd in Northern Canada. We used a hierarchical model to estimate the beginning, duration, and end of spring migration and compared these statistics against snow pack melt characteristics derived from 37 GHz vertically polarized (37V GHz) Calibrated Enhanced-Resolution Brightness Temperatures (CETB) at 3.125 km resolution. The timing of migration for Bathurst caribou generally tracked the snowmelt onset. The start of migration was closely linked to the main melt onset in the wintering areas, occurring on average 2.6 days later (range −1.9 to 8.4, se 0.28, n = 10). The weighted linear regression was also highly significant (p-value = 0.002, R2=0.717). The relationship between migration arrival times and the main melt onset on the calving grounds (R2 = 0.688, p-value = 0.003), however, had a considerably more variable lag (mean 13.3 d, se 0.67, range 3.1–20.4). No migrations ended before the main melt onset at the calving grounds. Thawing conditions may provide a trigger for migration or favorable conditions that increase animal mobility, and suggest that the snow properties are more important than snow presence. Further work is needed to understand how widespread this is and why there is such a relationship.
Uncertainty in Sea State Observations from Satellite Altimeters and Buoys during the Jason-3/Sentinel-6 MF Tandem Experiment
Authors: Timmermans Ben W. , Gommenginger Christine P. , Donlon Craig J.
Published: July 2024

The Copernicus Sentinel-6 Michael Freilich (S6-MF) and Jason-3 (J3) Tandem Experiment (S6-JTEX) provided over 12 months of closely collocated altimeter sea state measurements, acquired in “low-resolution” (LR) and synthetic aperture radar “high-resolution” (HR) modes onboard S6-MF. The consistency and uncertainties associated with these measurements of sea state are examined in a region of the eastern North Pacific. Discrepancies in mean significant wave height (Hs, 0.01 m) and root-mean-square deviation (0.06 m) between J3 and S6-MF LR are found to be small compared to differences with buoy data (0.04, 0.29 m). S6-MF HR data are found to be highly correlated with LR data (0.999) but affected by a nonlinear sea state-dependent bias. However, the bias can be explained robustly through regression modelling based on Hs. Subsequent triple collocation analysis (TCA) shows very little difference in measurement error (0.18 ± 0.03 m) for the three altimetry datasets, when analysed with buoy data (0.22 ± 0.02 m) and ERA5 reanalysis (0.27 ± 0.02 m), although statistical precision, limited by total collocations (N = 535), both obscures interpretation and motivates the use of a larger dataset. However, we identify uncertainties in the collocation methodology, with important consequences for methods such as TCA. Firstly, data from some commonly used buoys are found to be statistically questionable, possibly linked to erroneous buoy operation. Secondly, we develop a methodology based on altimetry data to show how statistically outlying data also arise due to sampling over local sea state gradients. This methodology paves the way for accurate collocation closer to the coast, bringing larger collocation sample sizes and greater statistical robustness.
Integrating Knowledge Graph and Machine Learning Methods for Landslide Susceptibility Assessment
Authors: Wu Qirui , Xie Zhong , Tian Miao , Qiu Qinjun , Chen Jianguo , Tao Liufeng , Zhao Yifan
Published: July 2024

The suddenness of landslide disasters often causes significant loss of life and property. Accurate assessment of landslide disaster susceptibility is of great significance in enhancing the ability of accurate disaster prevention. To address the problems of strong subjectivity in the selection of assessment indicators and low efficiency of the assessment process caused by the insufficient application of a priori knowledge in landslide susceptibility assessment, in this paper, we propose a novel landslide susceptibility assessment framework by combing domain knowledge graph and machine learning algorithms. Firstly, we combine unstructured data, extract priori knowledge based on the Unified Structure Generation for Universal Information Extraction Pre-trained model (UIE) fine-tuned with a small amount of labeled data to construct a landslide susceptibility knowledge graph. We use Paired Relation Vectors (PairRE) to characterize the knowledge graph, then construct a target area characterization factor recommendation model by calculating spatial correlation, attribute similarity, Term Frequency–Inverse Document Frequency (TF-IDF) metrics. We select the optimal model and optimal feature combination among six typical machine learning (ML) models to construct interpretable landslide disaster susceptibility assessment mapping. Experimental validation and analysis are carried out on the three gorges area (TGA), and the results show the effectiveness of the feature factors recommended by the knowledge graph characterization learning, with the overall accuracy of the model after adding associated disaster factors reaching 87.2%. The methodology proposed in this research is a better contribution to the knowledge and data-driven assessment of landslide disaster susceptibility.
Ensemble One-Class Support Vector Machine for Sea Surface Target Detection Based on k-Means Clustering
Authors: Chen Shichao , Ouyang Xin , Luo Feng
Published: July 2024

Sea surface target detection is a key stage in a typical target detection system and directly influences the performance of the whole system. As an effective discriminator, the one-class support vector machine (OCSVM) has been widely used in target detection. In OCSCM, training samples are first mapped to the hypersphere in the kernel space with the Gaussian kernel function, and then, a linear classification hyperplane is constructed in each cluster to separate target samples from other classes of samples. However, when the distribution of the original data is complex, the transformed data in the kernel space may be nonlinearly separable. In this situation, OCSVM cannot classify the data correctly, because only a linear hyperplane is constructed in the kernel space. To solve this problem, a novel one-class classification algorithm, referred to as ensemble one-class support vector machine (En-OCSVM), is proposed in this paper. En-OCSVM is a hybrid model based on k-means clustering and OCSVM. In En-OCSVM, training samples are clustered in the kernel space with the k-means clustering algorithm, while a linear decision hyperplane is constructed in each cluster. With the combination of multiple linear classification hyperplanes, a complex nonlinear classification boundary can be achieved in the kernel space. Moreover, the joint optimization of the k-means clustering model and OCSVM model is realized in the proposed method, which ensures the linear separability of each cluster. The experimental results based on the synthetic dataset, benchmark datasets, IPIX datasets, and SAR real data demonstrate the better performance of our method over other related methods.
Precise Orbit Determination for Maneuvering HY2D Using Onboard GNSS Data
Authors: Xu Kexin , Zhou Xuhua , Li Kai , Wang Xiaomei , Peng Hailong , Gao Feng
Published: July 2024

The Haiyang-2D (HY2D) satellite is the fourth ocean dynamics environment monitoring satellite launched by China. The satellite operates on a re-entry frozen orbit, which necessitates orbital maneuvers to maintain its designated path once the satellite’s sub-satellite point deviates beyond a certain threshold. However, the execution of orbit maneuvers presents a significant challenge to the field of Precise Orbit Determination (POD). The thesis selects the on-board GPS data of HY2D satellite in December 2023 and five maneuvering days of that year. Employing a multifaceted approach that includes the assessment of observational data quality, orbit overlap, external orbit validation, and SLR (Satellite Laser Ranging) verification, the research delves into precise orbit determination during both maneuver and non-maneuver periods. The results indicate that: (1) The average number of satellites tracked by the receiver is 6.4; (2) During the non-maneuver periods, the average RMS (Root Mean Square) value of the radial difference in the 6-h overlapping arc segment is 0.66 cm, and the three-dimensional position difference is about 1.16 cm; (3) When compared with the precision science orbits (PSO) provided by CNES (Centre National d’Études Spatiales), the average values of the RMS values of the differences in the radial (R), transverse (T), and normal (N) directions during the non-maneuver and maneuver periods are respectively 1.32 cm, 2.31 cm, 1.92 cm and 3.04 cm, 8.78 cm, 2.72 cm. (4) The SLR verification of the orbit revealed a residual RMS of 2.24 cm. This suggests that by incorporating the modeling of maneuver forces during the maneuver periods, the impact of orbital maneuvers on orbit determination can be mitigated.
Interactions between MSTIDs and Ionospheric Irregularities in the Equatorial Region Observed on 13–14 May 2013
Authors: Wu Kun , Qian Liying
Published: July 2024

We investigate the interactions between medium-scale traveling ionospheric disturbances (MSTIDs) and the equatorial ionization anomaly (EIA) as well as between MSTIDs and equatorial plasma bubbles (EPBs) on the night of 13–14 May 2013, based on observations from multiple instruments (an all-sky imager, digisonde, and global positioning system (GPS)). Two dark bands (the low plasma density region) for the MSTIDs were observed moving toward each other, encountering and interacting with the EIA, and subsequently interacting again with the EIA before eventually dissipating. Then, a new dark band of MSTIDs moved in the southwest direction, drifted into the all-sky imager’s field of view (FOV), and interacted with the EIA. Following this interaction, a new dark band split off from the original dark band, slowly moved in the northeast direction, and eventually faded away in a short time. Subsequently, the original southwestward-propagating dark band of the MSTIDs encountered eastward-moving EPBs, leading to an interaction between the MSTIDs and the EPBs. Then, the dark band of the MSTIDs faded away, while the EPBs grew larger with a pronounced westward tilt. The results from various observational instruments indicate the pivotal role played by the high-density region of the EIA in the occurrence of various interaction processes. In addition, this study also revealed that MSTIDs propagating into the equatorial region can significantly impact the morphology and evolution characteristics of EPBs.
Study on Morphometrical Urban Aerodynamic Roughness Multi-Scale Exploration Using LiDAR Remote Sensing
Authors: An Seung Man , Kim Byungsoo , Yi Chaeyeon , Eum Jeong-Hee , Woo Jung-Hun , Wende Wolfgang
Published: July 2024

This study proposes the use of light detection and ranging (LiDAR) remote sensing (RS) to support morphometric research for estimating the aerodynamic roughness length (z0 ) of building placement on various scales. A LiDAR three-dimensional point cloud (3DPC) data processing graphical user interface (GUI) was developed to explore the z0 and related urban canopy parameters (UCPs) in the Incheon metropolitan area in South Korea. The results show that multi-scale urban aerodynamic roughness exploration is viable and can address differences in urban building data at various spatial resolutions. Although validating morphological multi-scale UCPs using dense tall towers is challenging, emerging low-cost and efficient methods can serve as substitutes. However, further efforts are required to link the measured z0 to building form regulations, such as floor area ratio, and expand RS research to obtain more quantitative and qualitative knowledge.
A Framework Analyzing Climate Change, Air Quality and Greenery to Unveil Environmental Stress Risk Hotspots
Authors: Rao Priyanka , Tassinari Patrizia , Torreggiani Daniele
Published: July 2024

Rapid urbanization has resulted in increased environmental challenges, compounding worries about deteriorating air quality and rising temperatures. As cities become hubs of human activity, understanding the complex interplay of numerous environmental elements is critical for developing effective mitigation solutions. Recognizing this urgency, a framework to highlight the hotspots with critical environmental issues emerges as a comprehensive approach that incorporates key criteria such as the surface urban heat island intensity (SUHII), heat index (HI) and air quality index (AQI) to assess and address the complex web of environmental stressors that grip urban landscapes. Employing the multicriteria decision analysis approach, the proposed framework, named the environmental risk hotspot mapping framework (ERHMF), innovatively applies the analytic hierarchy process at a sub-criteria level, considering long-term heat island trends with recent fluctuations in the HI and AQI. Climate change impact has been symbolized through rising temperatures, as reflected by surface urban heat island intensity trends over two decades. The robustness and correctness of the weights have been assessed by computing the consistency ratio, which came out as 0.046, 0.065 and 0.044 for the sub-criteria of the SUHII, AQI and HI, respectively. Furthermore, the framework delves into the nexus between environmental stressors and vegetation cover, elucidating the role of green spaces in mitigating urban environmental risks. Augmented by spatial and demographic data, the ERHMF adeptly discerns high-risk areas where environmental stress converges with urban development, vulnerable population concentrations and critical vegetation status, thereby facilitating targeted risk management interventions. The framework’s effectiveness has been demonstrated in a regional case study in Italy, underscoring its ability to pinpoint risk hotspots and inform specific policy interventions. The quantitative study undertaken at the sub-administrative level revealed that approximately 6,000,000 m2 of land in Bologna are classified as being under high to extremely high environmental stress, with over 4,000,000 m2 lying only within the extremely high stress group (90–100). Similarly, 1,000,000 m2 of land in Piacenza and Modena have high levels of environmental stress (80–90). In conclusion, the ERHMF presents a holistic methodology for delineating high-risk urban hotspots, providing essential insights for policymakers, urban planners and stakeholders, with the potential to enhance overall urban resilience and foster sustainable development efforts.
Convformer: A Model for Reconstructing Ocean Subsurface Temperature and Salinity Fields Based on Multi-Source Remote Sensing Observations
Authors: Song Tao , Xu Guangxu , Yang Kunlin , Li Xin , Peng Shiqiu
Published: July 2024

Observational data on ocean subsurface temperature and salinity are patently insufficient because in situ observations are complex and costly, while satellite remote-sensed measurements are abundant but mainly focus on sea surface data. To make up for the ocean interior data shortage and entirely use the abundant satellite data, we developed a data-driven deep learning model named Convformer to reconstruct ocean subsurface temperature and salinity fields from satellite-observed sea surface data. Convformer is designed by deeply optimizing Vision Transformer and ConvLSTM, consisting of alternating residual connections between multiple temporal and spatial attention blocks. The input variables consist of sea surface temperature (SST), sea surface salinity (SSS), sea surface height (SSH), and sea surface wind (SSW). Our results demonstrate that Convformer exhibits superior performance in estimating the temperature-salinity structure of the tropical Pacific Ocean. The all-depth average root mean square error (RMSE) of the reconstructed subsurface temperature (ST)/subsurface salinity (SS) is 0.353 °C/0.0695 PSU, with correlation coefficients (R²) of 0.98663/0.99971. In the critical thermocline, although the root mean square errors of ST and SS reach 0.85 °C and 0.121 PSU, respectively, they remain smaller compared to other models. Furthermore, we assessed Convformer’s performance from various perspectives. Notably, we also delved into the potential of Convformer to extract physical and dynamic information from a model mechanism perspective. Our study offers a practical approach to reconstructing the subsurface temperature and salinity fields from satellite-observed sea surface data.
Data Quality Assessment of Gravity Recovery and Climate Experiment Follow-On Accelerometer
Authors: Pan Zongpeng , Xiao Yun
Published: July 2024

Accelerometers are mainly used to measure the non-conservative forces at the center of mass of gravity satellites and are the core payloads of gravity satellites. All kinds of disturbances in the satellite platform and the environment will affect the quality of the accelerometer data. This paper focuses on the quality assessment of accelerometer data from the GRACE-FO satellites. Based on the ACC1A data, we focus on the analysis of accelerometer data anomalies caused by various types of disturbances in the satellite platform and environment, including thruster spikes, peaks, twangs, and magnetic torque disturbances. The data characteristics and data accuracy of the accelerometer in different operational states and satellite observation modes are analyzed using accelerometer observation data from different time periods. Finally, the data consistency of the accelerometer is analyzed using the accelerometer transplantation method. The results show that the amplitude spectral density of three-axis linear acceleration is better than the specified accuracy (above 10−1 Hz) in the accelerometer’s nominal status. The results are helpful for understanding the characteristics and data accuracy of GRACE-FO accelerometer observations.
Research on the Influencing Factors of Cultural and Tourism Service Quality in Huizhou Area
Authors: Wang Xin , Yang Zimeng , Guo Yanlong
Published: July 2024

This study investigates the elements that influence the quality of cultural and tourism services in the Huizhou region, seeking to improve the region’s tourism competitiveness and revive the growth of the local rural tourism industry based on the background of cultural and tourism integration. This article builds an evaluation index system for the influencing variables of culture and tourism service quality by choosing 20 indicators from three categories: public service quality, cultural service quality, and tourism industry performance. The entropy weight Topsis method is employed to assess the service quality of three districts and five counties in the Huizhou area, which serves as the research object. Research has shown that (1) the number of five-star hotels, the number of A-level scenic spots, and the number of overseas tourists received have a significant weight, and these have become important factors affecting the effective supply of high-quality rural tourism; (2) there is a significant difference in the quality of cultural and tourism services in different areas across the Huizhou region, with Tunxi District and Yi County having the highest level of service quality, while Qimen County and Jixi County have the lowest level; (3) The overall quality of cultural and tourism services in Huizhou region is relatively high, with six districts and counties rated medium or above, accounting for about 75% of the total. Therefore, it is necessary to improve the infrastructure construction, improve the quality of public services, maintain the local and regional culture, accelerate the integration of culture and tourism, and enhance the high-quality development of regional tourism in Huizhou.
Light Enables Partial Nitrification and Algal-Bacterial Consortium in Rotating Biological Contactors: Performance and Microbial Community
Authors: Yan Zichun , Pei Zhibin
Published: July 2024

Partial nitrification–anaerobic ammonia oxidation represents an innovative nitrogen removal technique, distinguished by its shortened nitrogen removal pathway and reduced energy demands. Currently, partial nitrification is mostly studied in sequential batch reactors, and some of the methods to realize partial nitrification in continuous flow reactors have problems such as complicated operation and management, and can be easily destabilized. This study introduces a novel system utilizing light to establish an algal-bacterial consortium within a partial nitrification framework, where oxygen is supplied by algae and a novel rotating biological contactor (RBC). This approach aims to simplify the control strategy and decrease the energy required for aeration. The results demonstrated that light at an intensity of 200 μmol/(m2·s) effectively inhibited nitrite-oxidizing bacteria (NOB), swiftly stabilizing partial nitrification. In the absence of light, free ammonia (FA) and free nitric acid (FNA) inhibited NOB, with ammonium removal efficiency (ARE) and nitrite accumulation ratio (NAR) at 68.35% and 34.00%, respectively. By day 88, under light exposure, effluent NO2−-N concentrations surged, with ARE and NAR at 64.21% and 69.45%, respectively. By day 98, NAR peaked at 80.28%. The specific oxygen uptake rate (SOUR) of ammonia-oxidizing bacteria (AOB) and NOB outside the disc was 3.24 mg O2/(g MLSS·h) and 0.75 mg O2/(g MLSS·h), respectively. Extracellular polymeric substance (EPS) content initially decreased, then increased, ultimately exceeding pre-light exposure levels. Microbial abundance significantly declined due to light exposure, with Nitrosomonas related-AOB decreasing by 91.88% from 1.6% to 0.13%, and Nitrospira related-NOB decreasing by 99.23% from 5.19% to 0.04%, respectively. The results indicated that both AOB and NOB were inhibited by light, especially NOB. It is a feasible strategy to achieve partial nitrification and algal-bacterial consortia by using light in a rotating biological contactor.
Sustainability in Educational Research: Mapping the Field with a Bibliometric Analysis
Authors: Dönmez İsmail
Published: July 2024

This research uncovers contemporary patterns by employing the bibliometric analysis approach to analyze sustainability research in the education domain. Consequently, we map the academic outputs and observe a tendency of increased publications, which proves the growing interest in global sustainability imperatives with the help of WoS data. Regarding the publications, the United Kingdom, Germany, and the United States were the most productive, stressing an international focus and interdisciplinarity. The analysis showed that there was a shift in the topic focus from environmental education to sustainable education as a result of integrating SDGs into every level of education. As such, the results highlight the role of education in sustainability and necessitate more research for better evaluation and implementation of educational efforts. This study not only presents a history of the field but also sets a future agenda for the discipline, which is the significance of education for sustainability. In this way, our work enhances the knowledge of sustainability in education, and the results of our work lay a theoretical and methodological basis for further research and activities in the field.
Exploring Green Inventory Management through Periodic Review Inventory Systems—A Comprehensive Literature Review and Directions for Future Research
Authors: Žic Jasmina , Žic Samir , Đukić Goran , Dabić-Miletić Svetlana
Published: July 2024

With the increasing environmental concerns and legislative pressures, the focus on incorporating ecologically sustainable practices into inventory management systems has grown, leading to the emergence of green inventory management. However, this field is not without its challenges, with numerous conflicting real-world constraints and goals. A comprehensive literature review targeting green inventory management operating under a periodic review inventory system was conducted to identify research gaps and potential directions for future research. Despite the growing interest in the field, this review highlighted the scarcity of relevant studies. Out of the 1272 papers reviewed, only 16 studies, or 1.3%, met the criteria for exploring periodic review inventory systems while simultaneously considering environmental and economic aspects. These studies were further analyzed in detail and categorized according to key classification criteria. The future research directions highlighted the need for additional studies on periodic review inventory systems operating under stochastic market demand in the context of green supply chain management. The standardization of emission calculation methodologies was also emphasized as a crucial step towards aligning inventory management practices with the aim of increasing inventory management efficiency and the related improvement in the environmental performance of supply chains.
Climate Change: Relationship between Knowledge and Perception in Students of an Agricultural-Based University in Ecuador
Authors: Cornejo Gloria Anabel , Lamiño Pablo , Trejos Bernardo
Published: July 2024

The Intergovernmental Panel on Climate Change has confirmed that climate change is an unequivocal fact, presenting significant challenges due to its adverse impacts. Understanding climate change is crucial for agricultural students, as climate variability and extreme weather events directly affect agriculture. This study examined agronomy students’ perceptions and knowledge of climate change at a technical university in Cotopaxi, Ecuador. An online structured questionnaire was used to gather data on students’ perceptions and knowledge. The questionnaire had two sections, i.e., perception and knowledge. The perception section employed a Likert scale covering the following six components: skepticism, perceived benefit, economy, environmentalism, perceived risk, and negative effects. The knowledge section included true/false questions across four dimensions, i.e., causes, effects, concepts, and human relationships. The results indicated that most students had a medium level of perception (55.85%) and knowledge (54.25%) regarding climate change. A low but significant correlation was found between perception and knowledge (rs = 0.12, p = 0.02). Based on these findings, the researchers recommend incorporating specific climate change courses to better prepare students for sustainable agricultural development in a changing climate.
A Study on the Daylighting, Energy Consumption, and Climate Adaptability of Curved Mesh Shading Based on the Parametric Performance Design Method
Authors: Jiang Yan , Qi Zongxin , Ran Shenglin , Ma Qingsong , Dewancker Bart Julien , Gao Weijun
Published: July 2024

Building shading forms are becoming increasingly diversified, driven by both building performance requirements and architectural aesthetics. The application of computer technology in shading design and performance evaluation is becoming increasingly popular. This study adopted a parametric performance design method and created a one-click workflow for parametric curved mesh shading design and performance evaluation based on the Grasshopper platform and Ladybugtools. Applying this workflow, this paper takes five typical cities in different climate zones in China as examples to analyze the impact rules of curved mesh shading parameters (blade width, number of horizontal grids, and number of vertical grids) on building daylighting and energy consumption and explore the application potential of curved mesh shading. This study found that curved mesh shading has the best potential to improve daylighting in Harbin and can increase the annual average UDIa (300~3000 lux) by 7.42%. In Guangzhou, curved mesh shading has the highest potential for energy saving, which can reduce annual energy consumption by 14.8%. This study can provide theoretical, methodological, and data support for the optimal design of curved mesh shading.