bluuebunny/crossref_metadata_2025 huggingface dataset:
Environmental Evaluation of Chemical Plastic Waste Recycling: A Life Cycle Assessment Approach
Authors: Vinci Giuliana , Gobbi Laura , Porcaro Daniela , Pinzi Sara , Carmona-Cabello Miguel , Ruggeri Marco
Published: December 2024

Due to the high environmental burden of plastics, this study aimed to evaluate the environmental performance of chemical recycling of plastic waste through Life Cycle Assessment (LCA), focusing on pyrolysis oil production as the primary output. A pyrolysis plant in Almería, Spain, was chosen as a case study. The results indicate that the production of 1 L of pyrolysis oil from plastic waste generates about 0.032 kg CO2 eq and a water consumption of 0.031 m3, with other impact categories registering values of less than 0.1 kg/L or 0.01 m2a crop eq/L, reducing impacts in 17 out of 18 categories compared to fossil diesel. In addition, its chemical and physical properties, close to those of fossil diesel, suggest its suitability for internal combustion engines, although as a blend rather than a complete substitute. Chemical recycling also appears to be more environmentally favorable than incineration and landfilling in all 18 impact categories, achieving significant benefits, including a reduction in global warming of −3849 kg CO2 eq/ton, ionizing radiation of −22.4 kBq Co-60 eq/ton, and fossil resource consumption of −1807.5 kg oil eq/ton. These results, thus, highlight the potential dual role of chemical recycling of plastic waste, both in mitigating environmental impacts and in supporting circular economy goals by reducing demand for virgin plastics. However, although it appears to be a promising technology, challenges associated with high energy requirements, raw material variability, and scale infrastructure still need to be addressed to ensure industrial competitiveness and significant environmental benefits.
Temporal and Spatial Dynamics of Summer Crop Residue Burning Practices in North China: Exploring the Influence of Climate Change and Anthropogenic Factors
Authors: Yin Shuai , Yi Kunpeng , Zhang Xiu , Nie Tangzhe , Meng Lingqi , Sun Zhongyi , Chu Qingnan , Ai Zhipin , Zhao Xin , Wu Lan , Guo Meng , Liu Xinlu
Published: December 2024

Better understanding the complex mechanisms underlying the variations in crop residue burning (CRB) intensity and patterns is crucial for evaluating control strategies and developing sustainable policies aimed at the efficient recycling of crop residues. However, the intricate interplay between the CRB practices, climate variability, and human activities poses a significant challenge in this endeavor. Here, we utilize the high spatiotemporal resolution of satellite observations to characterize and explore the dynamics of summer CRB in North China at multiple scales. Between 2003 and 2012, there was a significant intensification of summer CRB in North China, with the annual number of burning spots increasing by an average of 499 (95% confidence interval, 252–1426) spots/year. However, in 2013, China promulgated the stringent Air Pollution Prevention and Control Action Plan, which led to a rapid decrease in the intensity of summer CRB. Local farmers also adjusted their burning practices, shifting from concentrated and intense burning to a more dispersed and uniformly intense approach. Between 2003 and 2020, the onset of summer CRB shifted earlier in North China by 0.75 (0.5–1.1) days/year, which is attributed to the combined effects of climate change and anthropogenic controls. Specifically, the onset time is found to be significantly and negatively correlated with spring temperature anomalies and positively correlated with anomalies in the number of spring frost days. Climate change has led to a shortened crop growing season, resulting in an earlier start to summer CRB. Moreover, the enhanced anthropogenic controls on CRB expedited this process, making the trend of an earlier start time even more pronounced from 2013 to 2020. Contrary to the earlier onset of summer CRB, the termination of local wheat residue burning experienced a notable delay by 1.0 (0.8–1.4) days/year, transitioning from mid-June to early July.
A Multi-Level SAR-Guided Contextual Attention Network for Satellite Images Cloud Removal
Authors: Liu Ganchao , Qiu Jiawei , Yuan Yuan
Published: December 2024

In the field of remote sensing, cloud cover severely reduces the quality of satellite observations of the earth. Due to the complete absence of information in cloud-covered regions, cloud removal with a single optical image is an ill-posed problem. Since the synthetic aperture radar (SAR) can effectively penetrate clouds, fusing SAR and optical remote sensing images will effectively alleviate this problem. However, existing SAR-based optical cloud removal methods fail to effectively leverage the global information provided by the SAR image, resulting in limited performance gains. In this paper, we introduce a novel cloud removal method named the Multi-Level SAR-Guided Contextual Attention Network (MSGCA-Net). MSGCA-Net is designed with a multi-level architecture that integrates a SAR-Guided Contextual Attention (SGCA) module to fuse the dependable global contextual information from SAR images with the local features of optical images effectively. In the module of SGCA, the SAR image provides reliable global contextual information and genuine structure of cloud-covered regions, while the optical image provides the local feature information. The proposed model can efficiently extract and fuse global and local contextual information in SAR and optical images. We trained and evaluated the performance of the model on both simulated and real-world datasets. Both qualitative and quantitative experimental evaluation demonstrated that the proposed method can yield high quality cloud-free images and outperform state-of-the-art cloud removal methods.
Land Subsidence Velocity and High-Speed Railway Risks in the Coastal Cities of Beijing–Tianjin–Hebei, China, with 2015–2021 ALOS PALSAR-2 Multi-Temporal InSAR Analysis
Authors: Luo Qingli , Li Mengli , Yin Zhiyuan , Ma Peifeng , Perissin Daniele , Zhang Yuanzhi
Published: December 2024

Sea-level rise has important implications for the economic and infrastructure security of coastal cities. Land subsidence further exacerbates relative sea-level rise. The Beijing–Tianjin–Hebei region (BTHR) along the Bohai Bay is one of the areas most severely affected by ground subsidence in the world. This study applies the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS InSAR) method to analyze 47 ALOS PALSAR-2 images with five frames, mapping subsidence across 21,677.7 km2 and revealing spatial patterns and trends over time from 2015 to 2021. This is one of the few published research studies for large-scale and long-term analysis of its kind using ALOS-2 data in this region. The results reveal the existence of six major areas affected by severe subsidence in the study area, with the most pronounced in Jinzhan Town, Beijing, with the maximum subsiding velocity of −94.42 mm/y. Except for the two subsidence areas located in Chaoyang District of Beijing and Guangyang District of Langfang City, the other areas with serious subsidence detected are all located in suburban areas; this means that the strict regulations of controlling urban subsidence for downtown areas in the BTHR have worked. The accumulated subsidence is highly correlated with the time in the time series. Moreover, the subsidence of 161.4 km of the Beijing–Tianjin Inter-City High-Speed Railway (HSR) and 194.5 km of the Beijing–Shanghai HSR (out of a total length of 1318 km) were analyzed. It is the first time that PALSAR-2 data have been used to simultaneously investigate the subsidence along two important HSR lines in China and to analyze relatively long sections of the routes. The above two railways intersect five and seven subsiding areas, respectively. Within the range of the monitored railway line, the percentage of the section with subsidence velocity below −10 mm/y in the monitoring length range is 11.2% and 27.9%; this indicates that the Beijing–Shanghai HSR has suffered more serious subsidence than the Beijing–Tianjin Inter-City HSR within the monitoring period. This research is also beneficial for assessing the subsidence risk associated with different railways. In addition, this study further analyzed the potential reasons for the serious land subsidence of the identified areas. The results of the geological interpretation still indicate that the main cause of subsidence in the area is due to hydrogeological characteristics and underground water withdrawal.
Exploring Trends and Variability of Water Quality over Lake Titicaca Using Global Remote Sensing Products
Authors: Maligaya Vann Harvey , Baltodano Analy , Agramont Afnan , van Griensven Ann
Published: December 2024

Understanding the current water quality dynamics is necessary to ensure that ecological and sociocultural services are provided to the population and the natural environment. Water quality monitoring of lakes is usually performed with in situ measurements; however, these are costly, time consuming, laborious, and can have limited spatial coverage. Nowadays, remote sensing offers an alternative source of data to be used in water quality monitoring; by applying appropriate algorithms to satellite imagery, it is possible to retrieve water quality parameters. The use of global remote sensing water quality products increased in the last decade, and there are a multitude of products available from various databases. However, in Latin America, studies on the inter-comparison of the applicability of these products for water quality monitoring is rather scarce. Therefore, in this study, global remote sensing products estimating various water quality parameters were explored on Lake Titicaca and compared with each other and sources of data. Two products, the Copernicus Global Land Service (CGLS) and the European Space Agency Lakes Climate Change Initiative (ESA-CCI), were evaluated through a comparison with in situ measurements and with each other for analysis of the spatiotemporal variability of lake surface water temperature (LSWT), turbidity, and chlorophyll-a. The results of this study showed that the two products had limited accuracy when compared to in situ data; however, remarkable performance was observed in terms of exhibiting spatiotemporal variability of the WQ parameters. The ESA-CCI LSWT product performed better than the CGLS product in estimating LSWT, while the two products were on par with each other in terms of demonstrating the spatiotemporal patterns of the WQ parameters. Overall, these two global remote sensing water quality products can be used to monitor Lake Titicaca, currently with limited accuracy, but they can be improved with precise pixel identification, accurate optical water type definition, and better algorithms for atmospheric correction and retrieval. This highlights the need for the improvement of global WQ products to fit local conditions and make the products more useful for decision-making at the appropriate scale.
Classification of Karst Rocky Desertification Levels in Jinsha County Using a Feature Space Method Based on SDGSAT-1 Multispectral Data
Authors: Chen Qi , Fu Han , Li Xiaoming , Qin Xiaochuan , Yan Lin
Published: December 2024

Karst rocky desertification (KRD) is a significant issue that affects the ecological and economic sustainability of southwest China. Obtaining the accurate distribution of different levels of KRD can provide decision-making support for the effective management of KRD. The Sustainable Development Goals Science Satellite 1 (SDGSAT-1) is the world’s first scientific satellite serving the 2030 Agenda for Sustainable Development of the United Nations, and is dedicated to developing high-resolution, multi-scale, global public datasets to support policy and decision-making support systems for sustainable development. SDGSAT-1 multispectral data provide detailed ground information with a spatial resolution of 10 m and a rich spectral resolution. In this study, we combined the red-modified carbonate rock index (RCRI, an index that characterizes the degree of carbonate rock exposure) and the normalized difference red edge index (NDRE, an index that characterizes the degree of vegetation coverage) to propose a novel feature space method based on SDGSAT-1 multispectral data to classify the different levels of KRD in the Jinsha County of Guizhou Province, a representative region with significant KRD in southwest China. This method effectively identified different levels of KRD with an overall classification accuracy of 87%. This was 20% higher than that of the grading index method, indicating that SDGSAT-1 multispectral data have promising potential for KRD classification. In this study, we offer a new insight into the classification of KRD and a greater quantity of remote-sensing data to monitor KRD over a wider area and for a longer period of time, contributing to the economic development and environmental protection of KRD areas.
Prelaunch Reflective Solar Band Radiometric Performance of JPSS-3 and -4 VIIRS
Authors: Angal Amit , Moyer David , Xiong Xiaoxiong , Ji Qiang , Link Daniel
Published: December 2024

The Joint Polar Satellite System 3 (JPSS-3) and -4 (JPSS-4) Visible Infrared Imaging Radiometer Suite (VIIRS) instruments are the last in the series (S-NPP VIIRS launched in October 2011, JPSS-1 VIIRS launched in November 2017, and JPSS-2 VIIRS launched in November 2022) of highly advanced polar-orbiting environmental satellites. Both instruments underwent a comprehensive sensor-level thermal vacuum (TVAC) testing at the Raytheon Technologies El Segundo facility to characterize the spatial, spectral, and radiometric aspects of the VIIRS sensor performance. This paper focuses on the radiometric performance of the 14 reflective solar bands (RSBs) that cover the wavelength range from 0.41 to 2.3 µm. Key instrument calibration parameters such as instrument gain, signal-to-noise ratio (SNR), dynamic range, and radiometric calibration uncertainty were derived from the TVAC measurements for both the primary and redundant electronics at three instrument temperature plateaus: cold, nominal, and hot. This paper shows that all the JPSS-3 and -4 VIIRS RSB detectors have been well characterized, with key performance metrics comparable to the previous VIIRS instruments on-orbit. The radiometric calibration uncertainty of the RSBs is within the 2% requirement, except in the case of band M1 of JPSS-4. Comparison of the radiometric performance to sensor requirements, as well as a summary of key instrument testing and performance issues, is also presented.
Research on the Heavy Rainstorm–Flash Flood–Debris Flow Disaster Chain: A Case Study of the “Haihe River ‘23·7’ Regional Flood”
Authors: Li Renzhi , Qi Shuwen , Wang Zhonggen , Fu Xiaoran , Gao Huiran , Ma Junxue , Zhao Liang
Published: December 2024

Over the past decades, China has experienced severe compound natural disasters, such as extreme rainfalls, which have led to significant losses. In response to the challenges posed by the lack of a clear investigation process and inadequate comprehensiveness in evaluating the natural disaster chains, this study proposes a comprehensive retrospective simulation strategy for emergency investigation and simulation of heavy rainstorm–flash flood–debris flow chain disasters at the county–town level. The primary aim is to avert potential new chain disasters and alleviate subsequent disasters. This study combines emergency investigation efforts with hydrodynamic models to digitally simulate and analyze compound chain disasters triggered by an extreme rainfall event in the Haihe River regional area, specifically Gaoyakou Valley, Liucun Town, Changping District, Beijing, in July 2023, along with potential new disasters in adjacent regions. The findings indicate that the heavy rainstorm chain disaster on “7.29” resulted from a complex interplay of interrelated natural phenomena, including flash floods, debris flows, urban floodings, and river overflows. Hantai Village has experienced flash flood and debris flow events at different times in this area. Should the rainfall volume experienced in Liucun Town be replicated in the Ming Tombs Town area, approximately 6.2 km2 of land would be inundated, leading to damages to 458 residences and impacting around 240 ha of agricultural land. The anticipated release of floodwater from the reservoir would lead to significant impacts on downstream residents and roads. Our research can improve the efficacy of emergency investigations and assessments, which in turn can help with the management and reduction of disaster risks at the grassroots level.
Optimization of Grassland Carrying Capacity with Grass Quality Indicators Through GF5B Hyperspectral Images
Authors: Cheng Xuejun , Liao Maoxin , Zhang Shuangyin , Wang Siying , Chen Yiyun , Fei Teng
Published: December 2024

The accurate estimation of grassland carrying capacity (GCC) in the alpine grasslands of the Changjiang River source region is crucial for managing livestock loads and ensuring ecological security on the Qinghai-Tibetan Plateau. Previous remote sensing methods have predominantly focused on yield indicators, often neglecting quality indicators, which hampers precise GCC estimation. Here, we collected 25 samples from the Dangqu basin, analyzing various grass parameters including yield, crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF). Then, we developed models to optimize GCC using quality indicators derived from GF5B images, assessing performance through Pearson correlation coefficient (R2), root mean square error (RMSE), and relative root mean square error (rRMSE). Results were found to show an average yield of 61.26 g/m2, with CP, ADF, and NDF ranging from 5.81% to 18.75%, 45.47% to 58.80%, and 27.50% to 31.81%, respectively. Spectra in the near-infrared range, such as 1918 nm, and spectral indices improved the accuracy of the hyperspectral inversion of grass parameters. The GCC increased from 0.51 SU·hm−2 to 0.63 SU·hm−2 post-optimization, showing an increasing trend from northwest to southeast. This study enhances GCC estimation accuracy, aiding in reasonable livestock management and effective ecological preservation.
Multi-Scale Mapping and Analysis of Broadleaf Species Distribution Using Remotely Piloted Aircraft and Satellite Imagery
Authors: Chandrasekaran Aishwarya , Hupy Joseph P. , Shao Guofan
Published: December 2024

Tree species mapping from the individual crown to landscape scales provides crucial information on the diversity and richness of forest ecosystems, supporting major conservation decisions under ongoing climate change. With the emergence of Remote Piloted Aircraft (RPA), high spatial resolution datasets can be obtained and analyzed to inherently improve the current understanding of broadleaf tree species distribution. The utility of RPA for mapping broadleaf species at broader scales using satellite data needs to be explored. This study investigates the use of RPA RGB imagery captured during peak fall foliage to leverage coloration commonly exhibited by different broadleaf tree species during phenology transition to delineate individual tree crowns and map species distribution. Initially, a two-step hybrid segmentation procedure was designed to delineate tree crowns for two broadleaf forests using RPA imagery collected during the fall season. With the tree crowns, a subsequent Object-based Random Forest (ORF) model was tested for classifying common and economically important broadleaf tree species groups. The classified map was further utilized to improve ground reference data for mapping species distribution at the stand and landscape scales using multispectral satellite imagery (1.4 m to 10 m). The results indicated an improvement in the overall accuracy of 0.13 (from 0.68 to 0.81) and a MICE metric of 0.14 (from 0.61 to 0.75) using reference samples derived from RPA data. The results of this preliminary study are promising in utilizing RPA for multi-scale mapping of broadleaf tree species effectively.
A Review: Developments in Hardware Systems of Active Ankle Orthoses
Authors: Gunaratne Praveen Nuwantha , Tamura Hiroki
Published: December 2024

Active ankle orthoses which have been designed over the past few years by diverse sources were critically reviewed in this paper. It begins by providing an overview of the anatomy of the ankle joint complex, establishing a basis for understanding the subsequent discussion on the research challenges and design difficulties associated with developing active ankle orthosis devices. The review systematically examined the mechanisms, actuation methods, and control strategies utilized in these orthosis devices. This covers various control strategies, including Electromyography (EMG)-based, adaptive, and modular control systems, emphasizing their importance in achieving precise and user-intended movements. By integrating insights from recent studies and technological innovations, this paper provides a holistic view of the progress in active ankle orthoses. The paper concludes with design recommendations aimed at overcoming existing limitations and promoting further development of advanced active ankle orthosis devices for future research.
Lightweight Siamese Network with Global Correlation for Single-Object Tracking
Authors: Ding Yuxuan , Miao Kehua
Published: December 2024

Recent advancements in the field of object tracking have been notably influenced by Siamese-based trackers, which have demonstrated considerable progress in their performance and application. Researchers frequently emphasize the precision of trackers, yet they tend to neglect the associated complexity. This oversight can restrict real-time performance, rendering these trackers inadequate for specific applications. This study presents a novel lightweight Siamese network tracker, termed SiamGCN, which incorporates global feature fusion alongside a lightweight network architecture to improve tracking performance on devices with limited resources. MobileNet-V3 was chosen as the backbone network for feature extraction, with modifications made to the stride of its final layer to enhance extraction efficiency. A global correlation module, which was founded on the Transformer architecture, was developed utilizing a multi-head cross-attention mechanism. This design enhances the integration of template and search region features, thereby facilitating more precise and resilient tracking capabilities. The model underwent evaluation across four prominent tracking benchmarks: VOT2018, VOT2019, LaSOT, and TrackingNet. The results indicate that SiamGCN achieves high tracking performance while simultaneously decreasing the number of parameters and computational costs. This results in significant benefits regarding processing speed and resource utilization.
Optimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation
Authors: Tai Chi-en Amy , Wong Alexander
Published: December 2024

Breast cancer is a significant cause of death from cancer in women globally, highlighting the need for improved diagnostic imaging to enhance patient outcomes. Accurate tumor identification is essential for diagnosis, treatment, and monitoring, emphasizing the importance of advanced imaging technologies that provide detailed views of tumor characteristics and disease. Recently, a new imaging modality named synthetic correlated diffusion imaging (CDIs) has been showing promise for enhanced prostate cancer delineation when compared to existing MRI imaging modalities. In this study, we explore the efficacy of optimizing the correlated diffusion imaging (CDI) protocol to tailor it for breast cancer tumor delineation. More specifically, we optimize the coefficients of the calibrated signal mixing function in the CDIs protocol that controls the contribution of different gradient pulse strengths and timings by maximizing the area under the receiver operating characteristic curve (AUC) across a breast cancer patient cohort. Experiments showed that the optimized CDIs can noticeably increase the delineation of breast cancer tumors by over 0.03 compared to the unoptimized form, as well as providing the highest AUC when compared with gold-standard modalities. These experimental results demonstrate the importance of optimizing the CDIs imaging protocol for specific cancer applications to yield the best diagnostic imaging performance.
DSiam-CnK: A CBAM- and KCF-Enabled Deep Siamese Region Proposal Network for Human Tracking in Dynamic and Occluded Scenes
Authors: Liu Xiangpeng , Han Jianjiao , Peng Yulin , Liang Qiao , An Kang , He Fengqin , Cheng Yuhua
Published: December 2024

Despite the accuracy and robustness attained in the field of object tracking, algorithms based on Siamese neural networks often over-rely on information from the initial frame, neglecting necessary updates to the template; furthermore, in prolonged tracking situations, such methodologies encounter challenges in efficiently addressing issues such as complete occlusion or instances where the target exits the frame. To tackle these issues, this study enhances the SiamRPN algorithm by integrating the convolutional block attention module (CBAM), which enhances spatial channel attention. Additionally, it integrates the kernelized correlation filters (KCFs) for enhanced feature template representation. Building on this, we present DSiam-CnK, a Siamese neural network with dynamic template updating capabilities, facilitating adaptive adjustments in tracking strategy. The proposed algorithm is tailored to elevate the Siamese neural network’s accuracy and robustness for prolonged tracking, all the while preserving its tracking velocity. In our research, we assessed the performance on the OTB2015, VOT2018, and LaSOT datasets. Our method, when benchmarked against established trackers, including SiamRPN on OTB2015, achieved a success rate of 92.1% and a precision rate of 90.9%. On the VOT2018 dataset, it excelled, with a VOT-A (accuracy) of 46.7%, a VOT-R (robustness) of 135.3%, and a VOT-EAO (expected average overlap) of 26.4%, leading in all categories. On the LaSOT dataset, it achieved a precision of 35.3%, a normalized precision of 34.4%, and a success rate of 39%. The findings demonstrate enhanced precision in tracking performance and a notable increase in robustness with our method.
Binary Transformer Based on the Alignment and Correction of Distribution
Authors: Wang Kaili , Wang Mingtao , Wan Zixin , Shen Tao
Published: December 2024

Transformer is a powerful model widely used in artificial intelligence applications. It contains complex structures and has extremely high computational requirements that are not suitable for embedded intelligent sensors with limited computational resources. The binary quantization technology takes up less memory space and has a faster calculation speed; however, it is seldom studied for the lightweight transformer. Compared with full-precision networks, the key bottleneck lies in the distribution shift problem caused by the existing binary quantization methods. To tackle this problem, the feature distribution alignment operation in binarization is investigated. The median shift and mean restore is designed to ensure consistency between the binary feature distribution and the full-precision transformer. Then, a knowledge distillation architecture for distribution correction is developed, which has a teacher–student structure comprising a full-precision and binary transformer, to further rectify the feature distribution of the binary student network to ensure the completeness and accuracy of the data. Experimental results on the CIFAR10, CIFAR100, ImageNet-1k, and TinyImageNet datasets show the effectiveness of the proposed binary optimization model, which outperforms the previous state-of-the-art binarization mechanisms while maintaining the same computational complexity.
Endpoint Distribution Modeling-Based Capture Algorithm for Interfering Multi-Target
Authors: Zhang Xiangliang , Li Junlin , Li Pengjie , Si Fang , Liu Xiangzhi , Gu Yu , Meng Shuguang , Yin Jibin , Liu Tao
Published: December 2024

In physical spaces, pointing interactions cannot rely on cursors, rays, or virtual hands for feedback as in virtual environments; users must rely solely on their perception and experience to capture targets. Currently, research on modeling target distribution for pointing interactions in physical space is relatively sparse. Area division is typically simplistic, and theoretical models are lacking. To address this issue, we propose two models for target distribution in physical space-pointing interactions: the single-target pointing endpoint distribution model (ST-PEDM) and the multi-target pointing endpoint distribution model (MT-PEDM). Based on these models, we have developed a basic region partitioning algorithm (BRPA) and an enhanced region partitioning algorithm (ERPA). We conducted experiments with 15 participants (11 males, and four females) to validate the proposed distribution models and region partitioning algorithm. The results indicate that these target distribution models accurately describe the distribution areas of targets, and the region partitioning algorithm demonstrates high precision and efficiency in determining user intentions during pointing interactions. At target distances of 200 cm and 300 cm, the accuracy without any algorithm is 60.54% and 42.39%, respectively. Using the BRPA algorithm, the accuracy is 72.94% and 68.57%, while, with the ERPA algorithm, the accuracy reaches 84.11% and 82.74%, respectively. This technology can be utilized in interaction scenarios involving handheld pointing devices, such as handheld remote controls. Additionally, it can be applied to the rapid capture control and trajectory planning of drone swarms. Users can quickly and accurately capture and control target drones using pointing interaction technology, issue commands, and transmit data through smart glasses, thereby achieving effective drone control and trajectory planning.
Correction: Almadhor et al. AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery. Sensors 2021, 21, 3830
Authors: Almadhor Ahmad , Rauf Hafiz Tayyab , Lali Muhammad Ikram Ullah , Damaševičius Robertas , Alouffi Bader , Alharbi Abdullah
Published: December 2024

Affiliation Correction [...]
Unveiling the Floral Scent Dynamics of Calamondin (Citrus × microcarpa) Across Developmental Stages
Authors: Chen Yiwei , Liang Zhiqing , Chen Shiyu , Yan Fulong , He Jingjuan , Zhou Yiwei , Gao Ting
Published: December 2024

The calamondin (Citrus × microcarpa) is highly valued for its ornamental appeal and rich aromatic compounds, making it suitable for therapeutic gardens and widely applicable in the cosmetics, food, pharmaceutical, and perfume industries. Despite its importance, there is a lack of research on its floral volatiles. This study utilized headspace solid-phase microextraction gas chromatography–mass spectrometry (HS–SPME–GC–MS) to detect the volatile organic compounds (VOCs) of calamondin at different floral developmental stages: bud (BS), half-open (HS), full bloom (FS), and senescence (SS). Multivariate statistical analysis was employed to elucidate the aromatic characteristics. The results identified 67 VOCs across the four stages, including forty-eight terpenoids, six esters, five aromatics, four aldehydes, one olefin, one alcohol, and two others. Thirty-three VOCs were common across all stages, while BS, HS, FS, and SS had three, three, four, and nine unique VOCs, respectively. The total VOC content increased initially and then decreased as the flowers developed, with terpenoids being the predominant compounds, accounting for over 90% of the total emissions at all stages. Principal component analysis and hierarchical cluster analysis confirmed significant differences in VOC profiles at different stages. Partial least squares discriminant analysis identified five VOCs with variable importance in projection (VIP) values greater than one, including limonene, linalool, β-pinene, germacrene D, and β-ocimene, indicating their varying emission levels across stages. These findings enhance our understanding of the VOC characteristics of calamondin flowers and provide a scientific basis for further ornamental and industrial applications.
Ion Activity Coefficient of Sodium Halides in Anion-Exchange Polymers: Empirical Model Based on Manning’s Counterion Condensation Theory
Authors: Liu Guiming , Gao Dandan
Published: December 2024

The theory of electrolyte solution provides a precise description of the thermodynamic state and non-ideality of electrolyte solutions, allowing for the accurate prediction of the crystallization separation process of Salt Lake brine. Analogously, we attempt to describe the non-ideality of ions in ion-exchange polymers based on Manning’s Counterion Condensation Theory, which was originally used to describe the thermodynamics of polyelectrolyte solutions, has amply proven the potential to extend to ion-exchange polymers. In this article, equilibrium solvent and solute concentrations in aminated cross-linked polystyrene AEM were determined experimentally as a function of external NaCl concentration, and ion activity coefficients in the membranes were obtained via a thermodynamic treatment. With the recombination and empirical parameters added to Manning’s model, the ion activity coefficient of NaCl and NaBr in the aminated cross-linked polystyrene AEM can be accurately described in concentration ranges of 0.01 mol·kg−1~3 mol·kg−1. Compared with the original model, the Coefficient of Determination between the improved model and the experimental data was increased from 0.65 to 0.95. The Residual Sum of Squares is reduced by about one order of magnitude, significantly improving the Manning model’s adaptability when applied to AEM.
Modified Biochar Adsorption Combined with Alkaline Solution Absorption for Sulfur-Containing Odor Gases Removal from Domestic Waste Transfer Stations
Authors: Wei Wei , Wang Ningjie , Zhang Xiaolei
Published: December 2024

Odor emission has become a major issue in waste transfer stations. Hydrogen sulfide, methyl mercaptan (MM), and dimethyl disulfide (DMDS) are the main odorous gases. They have a low odor threshold and are difficult to remove. In this study, pine bark biochar was produced and modified with metal ions, including Ni2+, Ti2+, Mn2+, Zn2+, Mg2+, and Cu2+. It was then used for the removal of hydrogen sulfide, methyl mercaptan, and dimethyl disulfide. Among all modifications, the Cu2+ modified biochar showed the best sorption capacity, and the maximum sorption amounts were 20.50 mg/g for H2S, 36.50 mg/g for MM, and 57.98 mg/g for DMDS. To understand the adsorption, BET, SEM, and XPS of the original and modified biochar were performed. This illustrated that modification with Cu2+ increased the surface area and porosity, thus enhancing the adsorption capacity. In the alkaline absorption study, it was found that the removal of the three odor gases increased with the pH increase. Based on the results, a combined process called absorption–adsorption was established to treat the odor gas generated in a local waste transfer station. Thirty-one gas components were detected in the odor gas of the waste transfer station. The process proceeded for 30 days, and these gas components were not found in the effluent during treatment. Regarding H2S, MM, and DMDS, they were not detected even after 90 days. This indicates the high adsorption capacity of the modified biochar toward the three odor gases. In addition, the process is simple and easy to operate. This suggests that it is suitable for treating odor in places where there is no technician, and the odor needs efficient treatment. The study provides a feasible alternative for domestic waste transfer stations to control the odor problem.
An Applied Approach to Transformational Leadership for Whole School Communities: Perspectives of Primary School and System Leaders
Authors: Heenan Inez Wilson , Lafferty Niamh , McNamara Patricia Mannix
Published: December 2024

This paper examines the vision, strategy and leadership support structures for Irish primary schools where leadership is specifically referenced, with focus on links to transformational and distributed school leadership. Of particular interest is how transformational and distributed leadership models could aid effective and sustainable leadership enactment in times of exceptional change. This article offers new insights into primary school and system leaders’ perceptions of transformational school leadership and the factors that facilitate and/or inhibit transformational school leadership for the whole school community with a qualitative study. The overarching research question comprised: what are the perceptions of primary school and system leaders relating to the facilitating and inhibiting factors affecting the implementation of transformational school leadership, and is this model perceived to build relations with parents and the wider school community? The data highlight several factors that transcend both transformational and distributed leadership and, with previous research by these authors, inform the construction of a synthesised model of transformational and distributed school leadership for the whole school community aligned with the most recent Irish primary school policy document—‘Looking at Our School 2022: A Quality Framework for Primary Schools and Special Schools (LAOS)’. The authors also accompany this model with a roadmap that may support approaches to school leadership practice for the whole school community, at the primary and post-primary levels, in Ireland.
‘They Were Surprised That Such Jobs Even Exist…’ Supporting Students’ Career Awareness During Learning Activities at Museums and Environmental Education Centres
Authors: Uppin Helene , Timoštšuk Inge
Published: December 2024

Many factors influence students’ career awareness and future career choices. Curricula-related learning activities that entail boundary-crossing between formal and nonformal contexts, such as museums and environmental education centres, can also broaden perspectives. Out-of-school learning can unveil career trajectories, introduce professions, spark interest in new topics, and support lifelong learning. Nevertheless, it is unclear how on-site educators of museums and environmental education centres perceive or address supporting students’ career awareness. We aimed to explore how Estonian on-site educators perceive the connection between curricula-related learning at their institutions and students’ career awareness (namely, work-related knowledge and self-awareness). The qualitative data are drawn from two datasets: (1) 27 out-of-school educators chosen by purposeful sampling participated in focus-group interviews about their practice; (2) 43 out-of-school educators filled out open-ended online surveys on career awareness education. Qualitative content analysis was used to find meaningful patterns from the dataset. Various specific examples of work-related learning activities emerged. However, career awareness was often understood narrowly or had not been previously conceptualised: students’ self-awareness was seldom explicitly perceived as part of career awareness. Moreover, supporting students’ lifelong learning or the development of sustainability competencies was explicitly emphasised only by more experienced or outstanding on-site educators.
Nature at the Heart of Ecological Transition: Five Ideas to Allow a Plural, Reflexive, Intercultural, Transnational, Ecological, and Dynamic Citizenship
Authors: Alves Fátima , Vidal Diogo Guedes , Allegretti Giovanni , Gallo Edmundo , de Castro Hermano Albuquerque , Freitas Helena
Published: December 2024

To change the course of traditional citizen participation towards ecological transition (ET) and to promote a sustainable transformation of social systems, it is necessary to implement a transformative policy that is based on a deep understanding of the territories in their biophysical, socioeconomic, and cultural dimensions. This policy should incorporate and articulate a plurality of knowledge, technologies, powers, and local positions. In this paper, we propose five ideas inspired by initiatives and examples from around the world to promote plural, reflexive, intercultural, transnational, ecological, and dynamic citizenship, which may foster a fair and inclusive ET. This scenario aims to envision alternative modes of social organization to anticipate ecologically and globally equitable futures.
Authoritarian States and Global Sport: The Contested Cases of Qatar, the UAE and Saudi Arabia
Authors: Grix Jonathan , Brannagan Paul Michael
Published: December 2024

Sport and authoritarianism have long been bedfellows, especially during the Cold War era. ‘Traditional’ authoritarian regimes—most notably the Soviet Union and its satellite states—learnt the art of instrumentalizing sport for political ends from each other. Motives for this included garnering international prestige via excellence in elite sport and showcasing communism as a viable alternative to capitalism. This paper shows how the ‘new’ authoritarian states are now beginning to impact global elite sport through similar sports investment strategies in an array of sports teams, sports sponsorship and sports leagues. Whereas ‘traditional’ authoritarian states sought sporting excellence on the playing field and the recognition this brought with it, the ‘new’ authoritarian states seek to buy into the cultural power and prestige of global elite sport for economic gain, to improve the health of their citizens and for global recognition. We draw on recent examples from Qatar, the UAE and Saudi Arabia to understand why and how ‘new’ authoritarian states pursue sport policies and why this is contested.
Advanced Footwear Technology in Non-Elite Runners: A Survey of Training Practices and Reported Outcomes
Authors: Bonato Matteo , Marmondi Federica , Faelli Emanuela , Pedrinelli Chiara , Ferraris Luigi , Filipas Luca
Published: December 2024

Background: Advanced footwear technology (AFT) has gained popularity among non-elite runners due to its potential benefits in training and competition. This study investigated the training practices and reported outcomes in non-elite runners using AFT. Methods: A cross-sectional observational study was conducted with 61 non-elite runners competing in distances ranging from 5 km to marathons. The survey collected data on demographics, training parameters, footwear usage, perceived changes in running mechanics, and self-reported injuries. Results: The results revealed a significant positive correlation (R = 0.6, p < 0.0001) between years of AFT use and weekly training volume, indicating that more experienced runners are likely to incorporate AFT consistently into their routines. Conversely, a significant negative correlation (R = −0.5, p < 0.0001) was found between training volume and the number of weekly sessions using AFT, suggesting a selective approach to footwear use. Participants reported biomechanical changes, such as increased forefoot support (49%) and higher calf muscle activation (44%), alongside a 16% self-reported injury rate, predominantly affecting the calves. Conclusions: These findings highlight the importance of proper guidance and gradual adaptation to maximize the benefits of AFT while minimizing injury risks. Future research should explore the long-term impact of AFT on performance and injury prevention through longitudinal studies.
Potential Importance of Maximal Upper Body Strength-Generating Qualities and Upper Body Strength Training for Performance of High-Intensity Running and Jumping Actions: A Scoping Review
Authors: Curovic Ivan , Grecic David , Rhodes David , Alexander Jill , Harper Damian J.
Published: December 2024

Purpose: To investigate the influence of upper body (UB) strength qualities and UB strength training on the performance of high-intensity running and jumping actions and to identify gaps and recommendations for future research. Methods: A systematic search using the PRISMA Scoping Review protocol was conducted in February 2024 using PubMed, Scopus, and ICTRP. Studies eligible for inclusion were those that reported associations between UB or trunk maximal strength qualities (e.g., absolute strength, forces, power) and high-intensity running or jumping actions or investigated the influence of an isolated UB strength training intervention on high-intensity running or jumping performances. Results: Of the 4730 articles, 7 studies met the inclusion criteria, reporting correlations for 16 high-intensity running or jumping tests. No intervention studies were identified. Preliminary findings of the limited number of studies highlight that greater UB maximal strength-generating capacity may positively influence repeated sprint ability. While a significant moderate correlation between greater absolute UB strength and faster “flying” sprint was also reported, mixed results were found for sprint acceleration. There is also evidence that change-of-direction performance may greatly benefit from high maximal isometric strength of all trunk muscles and that strong trunk extensors may enhance drop jumps. Conclusions: This review identifies the potential of UB strength to contribute to high-intensity running and jumping actions. Future research is warranted to investigate this link via various UB strength tests and UB strength training protocols aimed at maximising neuromuscular adaptations.
Cooperation-Oriented Multi-Modal Shared Mobility for Sustainable Transport: Developments and Challenges
Authors: Chen Xingguang , Deng Hepu , Guan Shuqi , Han Faxing , Zhu Zihuan
Published: December 2024

There is an increasing adoption of shared mobility for improving transport systems performance, reducing excessive private vehicle use, and making full utilization of existing infrastructure in urban traveling. Despite numerous studies in exploring the use of shared mobility for sustainable transport from different perspectives, how it has improved the sustainability of existing transport and what impact it has on various stakeholders are unclear. Therefore, a systematic literature review was carried out in this study on developing and adopting shared mobility for pursuing sustainable transport in urban traveling. Four emerging themes were identified, including attitude and intention, cooperation behaviors, operations and decisions, and performance evaluation, and some research gaps and challenges are discussed. An integrated framework for developing cooperation-oriented multi-modal shared mobility is proposed. This leads to better understanding of shared mobility and its use for sustainable transport in urban traveling.