bluuebunny/crossref_metadata_2025 huggingface dataset:
The Synthesis and Optical Property of a Ternary Hybrid Composed of Aggregation-Induced Luminescent Polyfluorene, Polydimethylsiloxane, and Silica
Authors: Zainuddin Nurul Amira Shazwani , Suizu Yusuke , Uno Takahiro , Kubo Masataka
Published: November 2024

Tetraphenylethene (TPE) is known as a molecule that exhibits aggregation-induced emission (AIE). In this study, pendant hydroxyl groups were introduced onto polyfluorene with a TPE moiety. Sol-gel reactions of polydiethoxysiloxane (PDEOS) were carried out in the presence of hydroxyl-functionalized AIE polyfluorene (TPE-PF-OH) and polydimethylsiloxane carrying pendant hydroxyl groups (PDMS-OH) to immobilize AIE polyfluorene into a PDMS/SiO2 hybrid in an isolated dispersion state. The luminescence intensity from this three-component hybrid increased with the increase in silica content. The luminescence intensity decreased with increasing external temperature. For the control experiment, sol-gel reactions of PDEOS were carried out in the presence of hydroxyl group-free polyfluorene (TPE-PF) and PDMS to obtain ternary composites. We found that the luminescence from this composite was not significantly affected by the silica content or external temperature. We synthesized temperature-responsive AIE materials without changing the concentration or aggregation state of the AIE molecules.
Investigation of γ-Aminopropyltriethoxysilane (APTES)-Modified Halloysite Nanotubes on the Reinforcement of Halloysite/Polypropylene (PP) Nanocomposites
Authors: Bao Zuguo , Yan Yunxiang , Han Weijian
Published: November 2024

Halloysite was successfully grafted with silane APTES using both wet and dry modification methods. Among them, wet modification using aqueous solution possessed the highest modification efficiency and grafting ratio. Morphological observations demonstrated that APTES grafting on halloysite improved both the filler dispersion and interfacial compatibility in polymer composites. The rheology and crystallization behavior indicated that silane modification improved the halloysite dispersion in the polypropylene (PP) matrix and enhanced the interfacial bonding. Furthermore, the modified halloysite also improved the thermal stability of the PP composites, showing elevated decomposition temperatures of PP. The mechanical properties of halloysite/PP nanocomposites were apparently improved with APTES modification. The filler content of the nanocomposites was finally optimized to 2% by considering trade-offs of the tensile, flexural, and Izod impact properties.
Priority/Demand-Based Resource Management with Intelligent O-RAN for Energy-Aware Industrial Internet of Things
Authors: Ros Seyha , Kang Seungwoo , Song Inseok , Cha Geonho , Tam Prohim , Kim Seokhoon
Published: November 2024

The last decade has witnessed the explosive growth of the internet of things (IoT), demonstrating the utilization of ubiquitous sensing and computation services. Hence, the industrial IoT (IIoT) is integrated into IoT devices. IIoT is concerned with the limitation of computation and battery life. Therefore, mobile edge computing (MEC) is a paradigm that enables the proliferation of resource computing and reduces network communication latency to realize the IIoT perspective. Furthermore, an open radio access network (O-RAN) is a new architecture that adopts a MEC server to offer a provisioning framework to address energy efficiency and reduce the congestion window of IIoT. However, dynamic resource computation and continuity of task generation by IIoT lead to challenges in management and orchestration (MANO) and energy efficiency. In this article, we aim to investigate the dynamic and priority of resource management on demand. Additionally, to minimize the long-term average delay and computation resource-intensive tasks, the Markov decision problem (MDP) is conducted to solve this problem. Hence, deep reinforcement learning (DRL) is conducted to address the optimal handling policy for MEC-enabled O-RAN architectures. In this study, MDP-assisted deep q-network-based priority/demanding resource management, namely DQG-PD, has been investigated in optimizing resource management. The DQG-PD algorithm aims to solve resource management and energy efficiency in IIoT devices, which demonstrates that exploiting the deep Q-network (DQN) jointly optimizes computation and resource utilization of energy for each service request. Hence, DQN is divided into online and target networks to better adapt to a dynamic IIoT environment. Finally, our experiment shows that our work can outperform reference schemes in terms of resources, cost, energy, reliability, and average service completion ratio.
Microbial Adhesion to Poly Methyl Methacrylate (PMMA) Denture Base Resins Containing Zinc Oxide (ZnO) Nanostructures: A Systematic Review of In Vitro Studies
Authors: Majrashi Nawal M. , Al Qattan Mohammed S. , AlMubarak Noor S. , Alzahir Kawther Zahar , Gad Mohammed M.
Published: November 2024

Background: Denture stomatitis is an inflammatory condition involving swelling and redness of the oral mucosa beneath a denture. Among various available treatments, zinc oxide nanoparticles (ZnONPs) and nano-wire nanostructures have been suggested as potential future therapies. However, there is a lack of information in the literature about the effectiveness of ZnONPs regarding microbial adhesion to different denture base resins. Here, we review studies on the effect of ZnONP use on microbial adhesion to denture base resins to answer the following study question: “Does incorporating ZnONPs into denture base resins reduce microbial adhesion?” Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, an electronic and manual search ranging from Jan 2000 to May 2024 was performed using PubMed, Web of Science, and Scopus databases to answer the study question. All full-length English-language articles investigating the effects of ZnO nanostructures on Candida albicans adhesion to polymethyl methacrylate (PMMA) denture base resins were included. The extracted data were tabulated for qualitative and quantitative analysis of the included studies. Results: Of the 479 studies reviewed, 7 studies successfully met the eligibility criteria. All included studies utilized PMMA as the denture base material with different polymerization methods. C. albicans was the most extensively studied microbial species, with various count methods used. Six studies concluded a statistically significant impact of ZnONPs on decreasing C. albicans adhesion to the denture base. However, one study reported the opposite. Conclusions: Incorporating ZnONPs into PMMA denture base resin has a positive impact on reducing C. albicans adherence and could be recommended for denture stomatitis treatment. However, further studies are needed to cover the notable gap in data regarding the safety and effectiveness of ZnO nanostructures.
Salmonella Brain Abscess in Sickle Cell Disease Patient: Case Report
Authors: Monteiro Felipe M. R. , O’Boyle Ryan P. , Taylor Ruby R. , John Danny L. , Piedade Guilherme S. , Cordeiro Joacir G.
Published: November 2024

Background and Clinical Significance: A brain abscess, defined as a localized intracranial infection that evolves into a purulent collection encased by a vascularized capsule, has higher prevalence among immunocompromised populations. Patients with sickle cell disease (SCD) are particularly vulnerable to bacterial infections due to their compromised immune systems, increasing their susceptibility to pathogens like Salmonella. While Salmonella is typically associated with gastroenteritis, osteomyelitis, and septicemia, its involvement in brain abscesses is exceedingly rare. There are few documented cases of Salmonella brain abscesses in the general population, and among patients with SCD, only one such case has been reported to date. In this report, we describe the second known case of a brain abscess caused by Salmonella infection in a patient with sickle cell disease, contributing to the limited literature on this rare and life-threatening condition. Case Presentation: A 32-year-old African American woman with sickle cell disease presented to the ER after a generalized seizure, reporting two weeks of worsening headaches, fevers, and left upper extremity weakness. Imaging revealed a right frontoparietal brain abscess, which was surgically drained, and cultures identified Salmonella enterica. After antibiotic treatment and a 23-day hospital stay, she was discharged. Four months later, she returned with another seizure during a sickle cell crisis, but follow-up MRI showed only minor scarring, and she was discharged on anticonvulsant therapy. Conclusions: This case emphasizes that Salmonella infections, though typically linked to osteomyelitis and sepsis, can also cause brain abscesses in immunocompromised patients like those with sickle cell disease. It highlights the need to consider infections alongside vascular causes in acute neurological cases and underscores the value of a multidisciplinary approach in managing such complex conditions.
The Influence of Short-Term Water Level Fluctuations on the Habitat Response and Ecological Fragility of Siberian Cranes in Poyang Lake, China
Authors: Li Xin , Hu Bisong , Qi Shuhua , Luo Jin
Published: November 2024

The landscape of the Poyang Lake wetland is significantly influenced by changes in water levels, impacting the distribution of habitats for migratory birds. While long-term effects of water level variations have been extensively studied, short-term impacts on Siberian crane habitats and their ecological vulnerability remain poorly understood. This study utilized 35 years (1987–2022) of Landsat remote sensing data and daily water level records from Poyang Lake to examine the effects of short-term water level fluctuations on the spatial distribution and ecological vulnerability of Siberian crane habitats. The geographic detector method was employed to quantify the explanatory power and interaction effects of factors, including short-term water level fluctuations, on ecological vulnerability. The findings reveal significant differences in the habitats of wintering Siberian cranes across various water level intervals and short-term fluctuation patterns. Short-term water level fluctuations can result in the largest suitable wintering habitat area for Siberian cranes, reaching 1856.41 km2 in this study. These habitats are highly sensitive to short-term water level changes, with rising and falling trends potentially leading to habitat loss. Oscillating water levels in the short term create broader and more concentrated habitats. Notably, fluctuations at low water levels support the sustainability and stability of crane habitats. Furthermore, short-term water level trends and nature reserves play a critical role in maintaining habitat ecological vulnerability; well-managed and protected nature reserves exhibit significant explanatory power, both in single-factor analysis and in their interaction with other environmental factors. Specifically, these protected areas show explanatory power exceeding the 20% threshold for both water level fluctuations and ranges, highlighting the crucial role of anthropogenic management in mitigating ecological vulnerability. This study emphasizes the necessity of scientifically informed regulation of short-term water level fluctuations to protect Siberian crane habitats and provides a strong scientific basis for decision-making support.
Pulsed Orthogonal Time Frequency Space: A Fast Acquisition and High-Precision Measurement Signal for Low Earth Orbit Position, Navigation, and Timing
Authors: Fu Dong , Lin Honglei , Ma Ming , Yuan Muzi , Ou Gang
Published: November 2024

The recent rapid development of low Earth orbit (LEO) constellation-based navigation techniques has enhanced the ability of position, navigation, and timing (PNT) services in deep attenuation and interference environments. However, existing navigation modulations face the challenges of high acquisition complexity and do not improve measurement precision at the same signal strength. We propose a pulsed orthogonal time frequency space (Pulse-OTFS) signal, which naturally converts continuous signals into pulses through a special delay-Doppler domain pseudorandom noise (PRN) code sequence arrangement. The performance evaluation indicates that the proposed signal reduces at least 89.4% of the acquisition complexity. The delay measurement accuracy is about 8 dB better than that of the traditional binary phase shift keying (BPSK) signals with the same bandwidth. It also provides superior compatibility and anti-multipath performance. The advantages of fast acquisition and high-precision measurement are verified by processing the real signal in the developed software receiver. As Pulse-OTFS occupies only one time slot of a signal period, it can be easily integrated with OTFS-modulated communication signals and used as a navigation signal from broadband LEO satellites as an effective complement to the global navigation satellite system (GNSS).
BDS-3/GNSS Undifferenced Pseudorange and Phase Time-Variant Mixed OSB Considering the Receiver Time-Variant Biases and Its Benefit on Multi-Frequency PPP
Authors: Jiao Guoqiang , Su Ke , Fan Min , Yang Yuze , Hu Huaquan
Published: November 2024

The legacy Global Navigation Satellite System (GNSS) satellite clock offsets obtained by the dual-frequency undifferenced (UD) ionospheric-free (IF) model absorb the code and phase time-variant hardware delays, which leads to the inconsistency of the precise satellite clock estimated by different frequencies. The dissimilarity of the satellite clock offsets generated by different frequencies is called the inter-frequency clock bias (IFCB). Estimates of the IFCB typically employ epoch-differenced (ED) geometry-free ionosphere-free (GFIF) observations from global networks. However, this method has certain theoretical flaws by ignoring the receiver time-variant biases. We proposed a new undifferenced model coupled with satellite clock offsets, and further converted the IFCB into the code and phase time-variant mixed observable-specific signal bias (OSB) to overcome the defects of the traditional model and simplify the bias correction process of multi-frequency precise point positioning (PPP). The new model not only improves the mixed OSB performance, but also avoids the negative impact of the receiver time-variant biases on the satellite mixed OSB estimation. The STD and RMS of the original OSB can be improved by 7.5–60.9% and 9.4–66.1%, and that of ED OSB (it can reflect noise levels) can be improved by 50.0–87.5% and 60.0–88.9%, respectively. Similarly, the corresponding PPP performance for using new mixed OSB is better than that of using the traditional IFCB products. Thus, the proposed pseudorange and phase time-variant mixed OSB concept and the new undifferenced model coupled with satellite clock offsets are reliable, applicable, and effective in multi-frequency PPP.
Remote Sensing in Bridge Digitalization: A Review
Authors: Casas Joan R. , Chacón Rolando , Catbas Necati , Riveiro Belén , Tonelli Daniel
Published: November 2024

A review of the application of remote sensing technologies in the SHM and management of existing bridges is presented, showing their capabilities and advantages, as well as the main drawbacks when specifically applied to bridge assets. The main sensing technologies used as corresponding platforms are discussed. This is complemented by the presentation of five case studies emphasizing the wide field of application in several bridge typologies and the justification for the selection of the optimal techniques depending on the objectives of the monitoring and assessment of a particular bridge. The review shows the potentiality of remote sensing technologies in the decision-making process regarding optimal interventions in bridge management. The data gathered by them are the mandatory precursors for determining the relevant performance indicators needed for the quality control of these important infrastructure assets.
Ecological Systems Classification: Integrating Machine Learning, Ancillary Modeling, and Sentinel-2 Satellite Imagery
Authors: Sunde Michael , Diamond David , Elliott Lee
Published: November 2024

Spatial land cover depictions are essential for ecological and environmental management. The thematic resolution of land cover and vegetation maps is also a significant factor affecting the ability to effectively develop policy and land management decisions based on spatial data. Natural resource and conservation planners often seek to develop strategies at broad scales; however, high-quality spatial data depicting current vegetation and ecosystem types over large areas are often unavailable. Since widely available land cover and vegetation datasets are generally lacking in either thematic resolution or spatial coverage, there is a need to integrate modeling approaches and ancillary data with traditional satellite image classifications to produce more detailed ecosystem maps for large areas. In this study, we present a comprehensive approach using satellite imagery, machine learning, and ancillary modeling approaches to develop high-resolution ecological system type maps statewide for Arkansas, USA. A RandomForest land cover classification of Sentinel-2 imagery was generated and further articulated into ecological types using a comprehensive set of secondary modeling approaches. A total of 123 types were mapped in Arkansas, including common cultural and ruderal land cover and vegetation such as pine plantations and developed types. Ozark–Ouachita Dry–Mesic Forest covered the most area, 17.51% of the state. Row Crops covered 17.16%. Twenty-five pine or pine plantation types covered 19.73% of the state, with Ozark–Ouachita pine woodland or mature pine plantation covering 6.15%. Field survey points were used to assess the quality of the mapped ecological systems. The approaches presented here provide a framework for finer resolution mapping of ecological systems at broad scales in other regions.
Locating Strong Electromagnetic Pulses Recorded by a Single Satellite with Cluster Analysis and Worldwide Lightning Location Network Observations
Authors: Li Zongxiang , Cao Baofeng , Zhang Wenjuan , Li Xiaoqiang , Zhang Xiong , Wei Yongli , Li Xiao , Duan Changjiao , Li Peng
Published: November 2024

The integration of satellite-borne and ground-based global lightning location networks offers a better perspective to study lightning processes and their evolutionary characteristics within thunderstorm clouds, thereby bolstering the predictive capabilities for severe weather phenomena. Currently, the satellite-borne network is in the preliminary testing phase with a single satellite. The geographic locations of single-satellite detection events primarily rely on synchronous information from coincident ground-based network events; this method is called synchronous locating (SCL). However, variations in detection-frequency bands and system capabilities prevent this method from accurately locating more than a mere 10% of events. To address this limitation, this paper introduces a cluster-analysis-based strategy, utilizing the observations from the Worldwide Lightning Location Network (WWLLN), termed the cluster analysis locating (CAL) method. The CAL method’s performance, influenced by the density-based spatial clustering of applications with noise (DBSCAN), the K-means, and the mean shift algorithms, is examined. Subsequently, an advanced version, mean shift denoised (MSDN)-CAL, is proposed, demonstrating marked improvements in location accuracy and reliability over the other CAL methods. The satellite-borne wideband electromagnetic pulse detector (WEMPD), orbiting at an altitude of approximately 500 km with a 97.5° inclination, captured 1061 strong electromagnetic pulses (EMPs). Among these, trans-ionospheric single pulses (TISPs) and trans-ionospheric pulse pairs (TIPPs) constituted 21.30% and 78.70%, respectively. Using the MSDN-CAL method successfully determines the geographic locations for 81.15% (861 out of 1061) of the events. This success rate represents an approximate eightfold enhancement over the SCL method. The arithmetic mean, geometric mean, and standard deviation of the two-dimensional range deviation of the locating results between the MSDN-CAL method versus the WWLLN-SCL (or the Guangdong-Hong Kong-Macao Lightning Location System (GHMLLS)-SCL) method are 51.06 (176.26) km, 16.17 (92.53) km, and 100.95 (174.79) km, respectively. Furthermore, it has been possible to estimate the occurrence altitudes for 81.92% (684 out of 835) of the TIPP events. The altitude deviations, as determined by comparing them with the GHMLLS-SCL method’s locating results, exhibit an arithmetic mean of 2.08 km, a geometric mean of 1.30 km, and a standard deviation of 2.26 km. The outcomes of this research establish a foundation for deeper investigation into the origins of various event types, their seasonal variations, and their geographical distribution patterns. Moreover, they pave the way for utilizing a single satellite to measure global surface reflectance, thus contributing valuable data for meteorological and atmospheric studies.
Ecological Restoration Projects Adapt Response of Net Primary Productivity of Alpine Grasslands to Climate Change across the Tibetan Plateau
Authors: Liang Yuling , Zhao Hui , Yuan Zhengrong , Wei Da , Wang Xiaodan
Published: November 2024

Alpine grassland is sensitive to climate change, and many studies have explored the trends in alpine vegetation. Most research focuses on the effects of climate warming and increased humidity on vegetation greening. However, less attention has been given to the positive impacts of human activities, particularly ecological restoration projects (ERPs). Our study utilized the CASA (Carnegie Ames Stanford Approach) model to simulate the net primary productivity (NPP) of alpine grasslands on the Tibetan Plateau (TP) from 2000 to 2020. Additionally, a moving window approach was employed to comparatively analyze the changes in the response characteristics of NPP to climate change before and after the implementation of ERPs. Our results indicated: (1) The NPP exhibited a fluctuating upward trend. The NPP growth rates of alpine meadow, alpine grassland, and desert grassland were found to be 2.38, 1.5, and 0.8 g C·m−2·a−1, respectively. (2) The annual average NPP and annual growth rate of alpine grasslands after the implementation of ERPs were both higher than before, indicating that ERPs have intensified the growth trend of NPP in alpine grasslands. (3) ERPs have reduced the responsiveness of alpine grassland NPP to temperature variations and enhanced its responsiveness to changes in precipitation. In detail, ERPs enhanced the responsiveness of NPP in alpine meadow to both temperature and precipitation, reduced the responsiveness of NPP in alpine steppe to temperature while enhancing its responsiveness to precipitation, and mitigated the changes in the response of NPP in desert steppe to temperature and significantly enhanced its responsiveness to precipitation.
A Resolution-Improving Method for Multiband Imaging Based on an Extrapolated RELAX Algorithm
Authors: Huang Jiajie , Jiang Wen , Liu Jianwei , Xie Qinyu , Li Wangzhe
Published: November 2024

A resolution-improving method for multiband imaging based on an extrapolated RELAX algorithm (ERA) is proposed. The proposed method improves image resolution by reconstructing a wideband signal through nonadjacent narrow subbands. The key points of this method are the coherent compensation of the subbands and the accurate extraction of target point scatters’ parameters from each subband. For coherent compensation, a two-step phase compensation (TSPC) is used to precisely compensate for the phase incoherence terms between the subbands. In order to accurately extract the parameters of point scatters (PSs), the ERA is proposed, which establishes a cost function between the extrapolated subbands and the PSs’ parameters. Furthermore, to enhance the robustness of PSs’ parameters extraction, a local band purification (LBP) process is proposed to resist the non-Gaussian clutter in the subbands. To validate the performance of the proposed method, Monte Carlo experiments using simulated data are carried out, whose results show that the proposed method can successfully improve the image resolution through the subbands under low signal-to-clutter ratio (SCR). Moreover, experiments with real measured data are conducted, using two 0.75 GHz subbands to reconstruct a 5 GHz signal, whose 2D image result is approximated to that based on the real 5 GHz signal. Image parameters are also compared, whose results demonstrate that the proposed method has satisfactory accuracy and robustness on improving image resolution.
Spectral Response Function Retrieval of Spaceborne Fourier Transform Spectrometers: Application to Metop-IASI
Authors: Dussarrat Pierre , Deschamps Guillaume , Coppens Dorothee
Published: November 2024

In the past decades, satellite hyperspectral remote sensing instruments have been providing key measurements for environmental monitoring, such as the analysis of water and air quality, soil usage, weather forecasting, or climate change. The success of this technology, however, relies on an accurate knowledge of the instrument’s spectral response functions (SRFs). Usually, the SRFs are assessed on-ground and then monitored on-flight using tedious analysis of the acquired radiances coupled with instrumental models; nonetheless, the complete retrieval of the SRFs is generally out of reach. In this context, EUMETSAT has developed a novel SRF retrieval methodology, with the intention of applying it routinely to the current Metop IASI instruments and soon to Metop-SG IASI-NG, and MTG-S IRS. By making use of spatiotemporal colocations of different detectors within a single instrument or between different platforms, relative SRFs may be retrieved on-flight without any a priori knowledge. The presented methodology is suited for instruments acquiring radiances with contiguous sampling over large spectral bands as the SRFs are retrieved by analyzing the neighboring channels’ correlations. This article focuses on Fourier transform spectrometers (FTS) in the far infrared as they possess these characteristics per design, but it is believed that the method could be extended to other technology and spectral bands. The SRFs are further processed to evaluate the relative self-apodization functions (SAFs), as they represent the discrepancies between the detectors at the interferograms level, the primary measurements of FTS. The following article presents both simulations and applications of the SRF retrieval for the three IASI instruments aboard the Metop platforms of the EPS program. We analyze both IASI sensors aboard Metop-B and C as well as the evolution of Metop-A IASI over 13 years of operation.
Spatial and Temporal Dynamics of Transportation Accessibility in China: Insights from Sustainable Development Goal Indicators from 2015 to 2022
Authors: Yang Minshu , Sun Zhongchang , Ouyang Xiaoying , Li Hongwei , Han Youmei , Gunasekera Dinoo
Published: November 2024

SDG 9.1.1 and SDG 11.2.1 are significant evaluation indicators of the United Nations Sustainable Development Goals related to transportation accessibility and are used to measure the proportion of the population facilitating the use of road services in rural areas and the proportion of the population facilitating the use of public transportation services in urban areas, respectively. However, there are currently challenges related to incomplete data and the inadequate interpretation of the indicators. In this study, we therefore evaluate the spatiotemporal patterns of the indicators and the number of disadvantaged groups in 337 Chinese cities from 2015 to 2022 based on multi-source data, and explore the spatial aggregation of the indicators and the driving factors. The results demonstrate that the indicator values of SDG 9.1.1 and SDG 11.2.1 reached 99.36% and 90.00%, respectively, in 2022, and the number of vulnerable groups decreased to approximately 1.89 million and 2.82 million. The indicator values of SDG 9.1.1 are high in the eastern part of China and low in the western part of the country, whereas the indicator values of SDG 11.2.1 exhibit spatial agglomeration in regions such as the Pearl River Delta. The average rural elevation and the density of urban public transportation stops are the most influential factors for these two indicators, respectively. The insights and data from this study provide support for improving transportation infrastructure and inequality in China, contributing to the achievement of the 2030 Sustainable Development Goals.
A Parameter Estimation-Based Anti-Deception Jamming Method for RIS-Aided Single-Station Radar
Authors: Zhao Shanshan , An Jirui , Xie Biao , Liu Ziwei
Published: November 2024

Multi-station radar can provide better performance against deception jamming, but the harsh detection requirements and risk of network destruction undermine the practicability of the multi-station radar. Therefore, it is necessary to further explore the anti-deception jamming performance of a single-station radar. This paper introduces a novel method, based on parameter estimation with a virtual multi-station system, to discriminate range deceptive jamming. The system consists of a single-station radar assisted by the reconfigurable intelligent surfaces (RIS). A unified parameter estimation model for true and false targets is established, and the convex optimization method is applied to estimate the target location and deception range. The Cramer–Rao lower bound (CRLB) of the target localization and the measured deception range is then derived. By using the measured deception range and its CRLB, an optimal discrimination algorithm in accordance with the Neyman–Pearson lemma is designed. Simulation results demonstrate the feasibility of the proposed method and analyze the effects of factors such as signal-to-noise ratio (SNR), deception range, jammer location, and the RISs station arrangement on the discrimination performance.
Investigating Synoptic Influences on Tropospheric Volcanic Ash Dispersion from the 2015 Calbuco Eruption Using WRF-Chem Simulations and Satellite Data
Authors: de Bem Douglas Lima , Anabor Vagner , Puhales Franciano Scremin , Pinheiro Damaris Kirsch , Grasso Fabio , Steffenel Luiz Angelo , Brenner Leonardo , Rizza Umberto
Published: November 2024

We used WRF-Chem to simulate ash transport from eruptions of Chile’s Calbuco volcano on 22–23 April 2015. Massive ash and SO2 ejections reached the upper troposphere, and particulates transported over South America were observed over Argentina, Uruguay, and Brazil via satellite and surface data. Numerical simulations with the coupled Weather Research and Forecasting–Chemistry (WRF-Chem) model from 22 to 27 April covered eruptions and particle propagation. Chemical and aerosol parameters utilized the GOCART (Goddard Chemistry Aerosol Radiation and Transport) model, while the meteorological conditions came from NCEP-FNL reanalysis. In WRF-Chem, we implemented a more efficient methodology to determine the Eruption Source Parameters (ESP). This permitted each simulation to consider a sequence of eruptions and a time varying ESP, such as the eruption height and mass and the SO2 eruption rate. We used two simulations (GCTS1 and GCTS2) differing in the ash mass fraction in the finest bins (0–15.6 µm) by 2.4% and 16.5%, respectively, to assess model efficiency in representing plume intensity and propagation. Analysis of the active synoptic components revealed their impact on particle transport and the Andes’ role as a natural barrier. We evaluated and compared the simulated Aerosol Optical Depth (AOD) with VIIRS Deep Blue Level 3 data and SO2 data from Ozone Mapper and Profiler Suite (OMPS) Limb Profiler (LP), both of which are sensors onboard the Suomi National Polar Partnership (NPP) spacecraft. The model successfully reproduced ash and SO2 transport, effectively representing influencing synoptic systems. Both simulations showed similar propagation patterns, with GCTS1 yielding better results when compared with AOD retrievals. These results indicate the necessity of specifying lower mass fraction in the finest bins. Comparison with VIIRS Brightness Temperature Difference data confirmed the model’s efficiency in representing particle transport. Overestimation of SO2 may stem from emission inputs. This study demonstrates the feasibility of our implementation of the WRF-Chem model to reproduce ash and SO2 patterns after a multi-eruption event. This enables further studies into aerosol–radiation and aerosol–cloud interactions and atmospheric behavior following volcanic eruptions.
Automated Shoreline Segmentation in Satellite Imagery Using USV Measurements
Authors: Jaszcz Antoni , Włodarczyk-Sielicka Marta , Stateczny Andrzej , Połap Dawid , Garczyńska Ilona
Published: November 2024

Generating aerial shoreline segmentation masks can be a daunting task, often requiring manual labeling or correction. This is further problematic because neural segmentation models require decent and abundant data for training, requiring even more manpower to automate the process. In this paper, we propose utilizing Unmanned Surface Vehicles (USVs) in an automated shoreline segmentation system on satellite imagery. The remotely controlled vessel first collects above- and underwater shoreline information using light detection and ranging (LiDAR) and multibeam echosounder (MBES) measuring instruments, resulting in a geo-referenced 3D point cloud. After cleaning and processing these data, the system integrates the projected map with an aerial image of the region. Based on the height values of the mapped points, the image is segmented. Finally, post-processing methods and the k-NN algorithm are introduced, resulting in a complete binary shoreline segmentation mask. The obtained data were used for training U-Net-type segmentation models with pre-trained backbones. The InceptionV3-based model achieved an accuracy of 96% and a dice coefficient score of 93%, demonstrating the effectiveness of the proposed system as a source of data acquisition for training deep neural networks.
A Composite Pulse Excitation Technique for Air-Coupled Ultrasonic Detection of Defects in Wood
Authors: Wang Jun , Zhang Changsen , Zhao Maocheng , Zou Hongyan , Qi Liang , Wang Zheng
Published: November 2024

To overcome the problems of the low signal-to-noise ratio and poor performance of wood ultrasonic images caused by ring-down vibrations during the ultrasonic quality detection of wood, a composite pulse excitation technique using a wood air-coupled ultrasonic detection system is proposed. Through a mathematical analysis of the output of the ultrasonic transducer, the conditions necessary for implementing composite pulse excitation were analyzed and established, and its feasibility was verified through COMSOL simulations. Firstly, wood samples with knot and pit defects were used as experimental samples. We refined the parameters for the composite pulse excitation technique by conducting A-scan measurements on both defective and non-defective areas of the samples. Moreover, two stepper motors were employed to control the path for C-scan imaging to detect wood defects. The experiment results showed that the composite pulse excitation technique significantly enhanced the precision of nondestructive ultrasonic testing for wood defects compared to the traditional single-pulse excitation method. This technique successfully achieved precise detection and location of pit defects, with a detection accuracy rate of 90% for knot defects.
Measuring Entrepreneurial Intentions of Students in Northwestern Croatia
Authors: Bujan Katanec Ivana , Pisker Barbara , Magdalenić Danijela
Published: November 2024

This study explores the factors influencing entrepreneurial intentions among students in northwestern Croatia, with a focus on educational background, family entrepreneurial environment, studying experiences, and perceived self-efficacy. Empirical research was conducted between March and June 2024 on a sample of 160 students from northwestern Croatia, and a multiple regression analysis was performed to identify key predictors of entrepreneurial intentions. The results revealed that entrepreneurial self-efficacy significantly impacted students’ intentions to start and run successful businesses, aligning with prior research on entrepreneurial behavior. However, other factors, such as family background and entrepreneurial education, showed no significant influence in this specific regional context. The findings suggest that educational programs should emphasize developing entrepreneurial self-efficacy to foster future entrepreneurs. This study highlights the importance of integrating entrepreneurial activities, such as business plan competitions and start-up incubators, into the curriculum. Limitations related to sample size and cross-sectional design are acknowledged, and future research is encouraged to explore additional factors and larger samples. This research provides valuable insights for educators and policymakers seeking to enhance students’ entrepreneurial capacities and support regional economic development.
Long-Term Monitoring and Early Warning of Coal Mine Underground Reservoirs—A Case Study in Shigetai Coal Mine
Authors: Zha Ersheng , Li Peng , Wu Yang , Wu Baoyang , Zhang Yong , Li Zhengdai , Zhang Zetian
Published: November 2024

Coal mining is often associated with groundwater pollution and loss, and coal–water conflicts are becoming increasingly prominent in Western China. As a new way to protect mine water, coal mine underground reservoirs (CMURs) have effectively alleviated the water shortage problem in Western China. The CMURs have been in existence for 25 years, but field-monitoring studies on their long-term stability are rare. In this paper, we take the Shigetai coal mine in the Shendong mining area as the research background. Long-term observation of stress, deformation, seepage pressure, and other parameters of 22 dams in five goaves (31201–31205) of the Shigetai coal mine for the whole year of 2022 has been pioneeringly carried out. A novel early-warning model, which incorporates expert evaluations and real-time indicator fluctuations, is proposed to assess the stability of CMURs. The stability characteristics of coal pillar dams (CPDs) and artificial dams (ADs) of CMURs are evaluated by this model, proving the validity and applicability of this model. This model provides theoretical and methodological guidance for long-term monitoring and early-warning systems for CMURs in the Shendong mining area.
Sustainable Characteristics of Traditional Villages: A Systematic Literature Review Based on the Four-Pillar Theory of Sustainable Development
Authors: Zheng Xiaoli , Herman Siti Sarah Binti , Salih Sarah Abdulkareem , Ismail Sumarni Binti
Published: November 2024

The definition of sustainable characteristics of traditional villages can assist in determining the direction of development and evaluating the development results. Nevertheless, a clearly defined concept of the sustainable performance of traditional villages is required. (1) This paper addresses the phenomenon of traditional villages and their decline due to urbanization, industrialization, and the movement of people from rural settlements. The development of traditional villages causes several concerns. This study aims to present a more precise definition of the sustainability of traditional villages. (2) the Preferred Reporting Items for Systematic Evaluation and Meta-Analysis (PRISMA) guidelines conducted a systematic literature review. The data were searched using the Web of Science database, with consideration given to the values of relevance, authority, and impact. (3) The sustainability of traditional villages is explained based on the four-pillar theory of sustainable development, focusing on the economic, environmental, social, and cultural dimensions. (4) The findings provide a scientific framework for understanding the sustainability of traditional villages. These results will provide insights to the future preservation and development of traditional villages.
The Integrated Development and Regional Disparities of Urban Agglomerations in the Yellow River Basin, China
Authors: Jin Zhenxing , Teng Chao , Jiao Xumin , Miao Yi , Wang Chengxin
Published: November 2024

This study develops an evaluation system to assess the integration levels of the seven urban agglomerations in the Yellow River Basin. Based on the weighted comprehensive indicator-based evaluation and Dagum’s Gini decompositions, it evaluates the integration of these urban agglomerations as well as their regional disparities from 2010 to 2022. The results show the following: (1) During the study period, the overall integration level of these urban agglomerations exhibited a general upward trend, although significant gaps still exist, with a spatial pattern of “lower reaches > middle reaches > upper reaches”. Moreover, after 2019, the integration accelerated markedly, indicating that the Yellow River Strategy has positively influenced the integration of these urban agglomerations. (2) Significant differences exist between the urban agglomerations in different dimensions of integration, although the gap has shown a fluctuating but narrowing trend. In addition, the degree of integration across different dimensions has been increasing annually for all urban agglomerations, except for the Shandong Peninsula Urban Agglomeration. The focus of integration varies among these urban agglomerations due to their differing stages of development. (3) In terms of regional disparities, the overall Gini coefficient displayed a “reverse U-shaped” decline, suggesting that while the gap in integration between the urban agglomerations has been narrowing over time, imbalances persist. Inter-group differences are the primary source contributing to the overall disparities in the integration levels of the urban agglomerations in the Yellow River Basin.
An ML-Based Ensemble Approach for the Precision Classification of Mangroves, Trend Analysis, and Priority Reforestation Areas in Asir, Saudi Arabia
Authors: Al-Huqail Asma A. , Islam Zubairul , Al-Harbi Hanan F.
Published: November 2024

In the recent past, mangrove ecosystems have undergone significant transformation, necessitating precise classification, the assessment of ecological changes, and the identification of suitable sites for urgent replantation. Therefore, this study aims to address three key objectives: first, to map the current extent of mangroves; second, to assess the ecological changes within these ecosystems; and third, to identify suitable areas for replantation, ensuring their sustainability across coastal Asir. The mangrove classification was conducted using an ensemble of machine learning models, utilizing the key spectral indices from Landsat 8 data for 2023. To analyze the ecological trends and to assess the changes over time, Landsat 5–8 data from 1991 to 2023 were used. Finally, a generalized additive model (GAM) identified the areas suitable for reforestation. The EC identified the mangrove area as 14.69 sq. km, with a 95.6% F1 score, 91.3% OA, and a KC of 0.83. The trends in the NDVI and LST increased (p = 0.029, 0.049), whereas the NDWI showed no significant change (p = 0.186). The GAM model demonstrated a strong fit (with an adjusted R2 of 0.89) and high predictive accuracy (R2 = 0.91) for mangrove priority reforestation suitability, confirmed by a 10-fold cross-validation and minimal bias in the residual diagnostics. The suitability varied across groups, with Group (e) showing the highest suitability at 77%. Moran’s I analysis revealed significant spatial clustering. This study provides actionable insights for mangrove reforestation, supporting the for sustainable development through targeted efforts that enhance ecological resilience in coastal regions.
Logistics Industry Agglomeration Affects New-Type Urbanization—An Empirical Test Based on Spatial Panel Models
Authors: Li Fanghu , Xie Naiming , He Yinnan
Published: November 2024

The rapid development of the logistics industry and its cooperation with other production factors have an impact on the promotion of new-type urbanization (NTU), a more sustainable and inclusive model of urban growth. This article analyzes in-depth the impact mechanism of logistics industry agglomeration, a new way to promote innovation and improve industrial efficiency, on NTU from various dimensions, including population, economy, society, space, ecology, and urban-rural coordination. Using panel data from 31 provinces in China between 2002 and 2021, the level of NTU was calculated using the entropy weight method, and a spatial econometric model was employed to examine the impact of logistics industry agglomeration on NTU and its spatial spillover effects. The research findings are as follows. The study reveals a spatial correlation between logistics industry agglomeration and NTU across Chinese regions. Logistics industry agglomeration significantly enhances NTU levels and generates spatial spillover effects, facilitating urban development in surrounding areas. The influence of regional logistics industry agglomeration on NTU demonstrates notable spatial heterogeneity, with the central region exerting a greater impact than the eastern and western regions. It can help in the understanding of regional differences and help policy makers optimize resource allocation. The impact of logistics industry agglomeration on NTU is nonlinear, primarily characterized by a substantial improvement in NTU at the medium and low levels due to logistics industry agglomeration. It helps identify regional differences and supports personalized decision making. The level of human capital, the degree of government intervention, the degree of marketization, the level of technological industrialization, the ratio of elderly dependency, and the level of innovation have direct effects and spillover effects on NTU. This paper elaborates on the mechanism of logistics industry agglomeration on NTU in China and proposes targeted proposals for promoting the development of NTU, which is highly important for promoting urbanization in other regions of the world from the perspective of industry.
Cause–Effect Modelling of Soil Liming in Poland
Authors: Zadrożny Paweł , Nicia Paweł , Wojewodzic Tomasz , Dacko Mariusz , Paluch Łukasz , Płonka Aleksandra , Janus Jarosław , Pijanowski Jacek , Bejger Romualda , Ukalska-Jaruga Aleksandra , Smreczak Bożena , Parzych Piotr
Published: November 2024

This research aimed to use the cause-and-effect diagram (model) as a method to describe the 15 main factors (for example, awareness, knowledge and motivation of farmers, farmers income, institutional and financial support, condition of the natural environment, healthiness of the population, etc.) leading to soil acidification, their impact on soil health and ecosystem functions, and how soil liming serves as a remedial measure. The cause-and-effect model was developed based on questionnaire studies as a part of the project ‘Opportunities and Barriers to the Use of Soil Liming for Improving the Economic Efficiency of Agricultural Production and Reducing Eutrophication of Surface Waters’ in 2022–2023. The results showed that the effects of soil acidification and liming as well as their interrelationships are multifaceted and affect agricultural production economics, agricultural land and crop prices, environmental health and biodiversity, as well as soil productivity and food security. The causes of this situation can be attributed to social, technological–logistical–technical, and economic factors. To change the existing situation, it is necessary to take effective steps to motivate farmers to lime their soils. The most effective would be (1) offering training courses for farmers to discuss the benefits that a farmer can achieve by maintaining optimum soil pH levels while growing a specific crop species; (2) implementing liming payment programs that will be more attractive and motivating from the farmers’ perspective; and (3) linking agri-environmental payments to the necessity of systematic testing of soil pH levels and maintaining optimal pH levels under specific crops species.