bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Sodium Silicate and Sodium Citrated on the Properties and Structure of Alkali-Activated Foamed Concrete
Authors: Liu Hao , Zhang Gaoke , Li Jixin , Xuan Jiaqi , Wang Yongsheng , Wan Huiwen , Huang Yun
Published: September 2024

Alkali-activated slag cementitious (AASC) foamed concrete (FC) has presented challenges such as rapid setting time and poor working performance. The use of sodium citrate (Na3Cit) as a retarding agent can improve the workability and microstructure of AASC foamed concrete. The effects of the dosage, modulus of water glass (WG, the main component is Na2O·nSiO2), and retarding agent on the properties and structure of FC were studied in this paper. The results indicated that using a water binder ratio of 0.4, WG with a modulus of 1.2, and an additional amount of 15% and 0.5% of Na3Cit, the prepared FC had a flowability of 190 mm. Its initial and final setting times were 3.7 h and 35.3 h. Its 7 d and 28 d compressive strengths reached 1.1 MPa and 1.5 MPa, respectively. After hardening, the pore walls were dense and consistent in size, with few larger pores and nearly spherical shapes. The addition of Na3Cit resulted in the formation of calcium citrate, which adsorbed onto the slag surface. This hindered the initial dissolution of the slag, reduced the number of hydration products produced, and decreased the early strength. With increasing curing time, the slag in the FC mixture dissolved further. This led to the decomposition of a portion of calcium citrate and the release of Ca2+. The Ca2+ reacted with [Si(OH)4]4− and [Al(OH)4]−, creating more C-(A)-S-H gel. This gel filled the voids in the FC and repaired any defects on the pore walls. Ultimately, this process increased the compressive strength of the FC in the later stages.
Re-Calibrating the Mercury-Intrusion-Porosimetry-Measured Pore Size Distribution of Coals: A Novel Method for Calculating the Matrix Compression Coefficient
Authors: Ren Bin , Zheng Sijian , Ping Lihua , Wang Meng , Dai Xuguang , Liu Yanzhi , Xu Shen , Wu Xiuping
Published: September 2024

Accurate measurement of the pore size distribution (PSD) in coals is crucial for guiding subsequent coalbed methane (CBM) engineering practice. Currently, mercury intrusion porosimetry (MIP) measurement has been widely used as a PSD testing method due to its effectiveness and convenience. Nevertheless, it is worth noting that the elevated pressure during the MIP experiments can lead to matrix compressibility, potentially causing inaccurate estimations of PSD in coals. Therefore, correction methods are used to modify the PSD in the high-pressure segment to improve the accuracy of MIP data. This study proposed a novel method with higher accuracy and convenience for calculating the matrix compressibility coefficient compared to the traditional calculation methods. Firstly, the matrix compressibility coefficients of six coal samples were calculated by using low-temperature nitrogen adsorption (LTNA) data. Subsequently, by utilizing the mathematical correlation between Kc (the compressibility coefficient of the coal matrix) and Ro,max (the maximum vitrinite reflectance) from prior research, a novel statistical method was designed to determine the matrix compressibility coefficient of the samples. Finally, the statistical matrix compressibility coefficient determination method was used to examine the fractal characteristics of the actual PSD. The results indicate that when the pressure exceeds 24 MPa, the volume obtained from mercury intrusion exceeds the pore volume measurement. The Kc calculated using the traditional correction method is in the range of 0.876–1.184 × 10−10 m2/N, while the Kc values of our proposed statistical correction method range from 0.898 × 10−10 to 1.233 × 10−10 m2/N, with a comparison error rate of ~0.11–5.25%. The MIP data greater than 24 MPa were effectively corrected using the statistical correction method, thus reducing the mercury intrusion volume error by 91.75–96.40%. Additionally, the corrected pore fractal dimension (D2) values fall within the range of 2.792 to 2.975, which are closer to the actual values than the pore fractal dimension range of 3.186 to 3.339.
Modified Deng’s Grey Relational Analysis Model for Panel Data and Its Applications in Assessing the Water Environment of Poyang Lake
Authors: Jian Fanghong , Li Jiangfeng , Liu Xiaomei , Wu Qiong , Zhong Dan
Published: September 2024

Deng’s grey relational analysis (GRA) model is widely used in clustering because of its simple mathematical mechanisms. For sample data of different dimensions, people have put forward different Deng’s GRA models, including time series data, panel data, and panel time series data. The purpose of this paper is to improve the clustering accuracy of the existing Deng’s GRA model for panel data in order to overcome some of its shortcomings. Firstly, the existing Deng’s GRA model for panel data was tested based on the dataset LP1 of Robot Execution Failures. Then, according to the test results, the existing Deng’s GRA model for panel data is modified by means of Taylor’s formula, and the modified model is successfully validated by the dataset LP1 of Robot Execution Failures. Finally, as a practical application, the modified Deng’s GRA model for panel data is applied to assess the water environment of Poyang Lake over the past five years. Compared with other cluster methods, the results of the case study show that the modified Deng’s GRA model for panel data is applicable and also confirm the remarkable effectiveness of the Chinese government’s water quality regulation in Poyang Lake. Therefore, the modified Deng’s GRA model presented in this paper improves the clustering accuracy compared to the original model and can be applied well to the classification of data with a large dimension.
Energy Evaluation and Mathematical Modeling of Pellet Production from Metal-Bearing Waste with a Focus on Alternative Applications of Reducing Agents
Authors: Varga Augustin , Kizek Jan , Rimar Miroslav , Fedak Marcel , Jablonský Gustáv , Oravec Peter , Bialik Wojciech
Published: September 2024

The authors of this study focused on the energy and material assessment of processes for processing pellets from metal-bearing waste, specifically Fe concentrate. A mathematical model was created for process evaluation, with which thermotechnical calculations of parameters in the processing of metallized pellets were carried out. Thermodynamic calculations were performed to determine the enthalpy of the charge in individual devices (drying chamber, rotary kiln, cooler). For the reduction of Fe oxides, carbon from coke (with Fe oxide reductions of 50%, 61%, and 92%) and lignite (with Fe oxide reductions of 69% and 92%) were considered as part of the pellets. The degree of reduction of iron oxides was a determining parameter, and the consumption of the reducing agent corresponded to the direct reduction of Fe oxides by carbon with a coefficient of 1.5. Another determining parameter was the input and output temperature in individual devices. For a more precise description of the processes in individual devices, calculations were carried out zonally. The results of the calculations are analyses and recommendations for feasible alternatives for the reducing agent and associated processes.
ISO Standards in Healthcare Organizations: Research Evolution and Trends from a Bibliometric Analysis
Authors: Villa-Gallón Jazmín Eliana , Valencia-Bernal Jorge Alberto , Garcés-Gómez Yeison Alberto
Published: September 2024

This study provides an overview of trends and evolution in International Organization for Standardization (ISO) implementation in healthcare over the past three decades, useful for researchers, practitioners, and policymakers in the sector. As an additional contribution, we propose the NU-index, which allows the evaluation of authors’ scientific output in a comprehensive way that will be valuable for researchers, institutions, and funding agencies seeking to assess researcher performance more accurately and understandably. A bibliometric analysis of 476 scientific articles from the Scopus Database was conducted, examining the scientific output, key authors, high-impact journals, and frequent keywords using VOSviewer, Bibliometrix library, and statistical analysis. Results reveal a significant increase in publications on ISO standards in healthcare since 2009, particularly in areas such as telemedicine, artificial intelligence, and information security. The emergence of ISO 11073 (health informatics) and ISO 13606 (electronic health records) highlights a growing trend towards information and communication technologies. Despite reported implementation barriers, such as lack of top management commitment and associated costs, adoption of these standards is increasing due to the demand for high-quality healthcare services and the need to comply with regulatory requirements.
A Control System Design and Implementation for Autonomous Quadrotors with Real-Time Re-Planning Capability
Authors: Kovryzhenko Yevhenii , Li Nan , Taheri Ehsan
Published: September 2024

Real-time (re-)planning is crucial for autonomous quadrotors to navigate in uncertain environments where obstacles may be detected and trajectory plans must be adjusted on-the-fly to avoid collision. In this paper, we present a control system design for autonomous quadrotors that has real-time re-planning capability, including the hardware pipeline for the hardware–software integration to realize the proposed real-time re-planning algorithm. The framework is based on a modified version of the PX4 Autopilot and a Raspberry Pi 5 companion computer. The planning algorithm utilizes minimum-snap trajectory generation, taking advantage of the differential flatness property of quadrotors, to realize computationally light, real-time re-planning using an onboard computer. We first verify the control system and the planning algorithm through simulation experiments, followed by implementing and demonstrating the system on hardware using a quadcopter.
A Potential Link between Space Weather and Atmospheric Parameters Variations: A Case Study of November 2021 Geomagnetic Storm
Authors: Regi Mauro , Piscini Alessandro , Francia Patrizia , De Lauretis Marcello , Redaelli Gianluca , Carnevale Giuseppina
Published: September 2024

On 4 November 2021, during the rising phase of solar cycle 25, an intense geomagnetic storm (Kp = 8−) occurred. The effects of this storm on the outer magnetospheric region up to the ionospheric heights have already been examined in previous investigations. This work is focused on the analysis of the solar wind conditions before and during the geomagnetic storm, the high-latitude electrodynamics conditions, estimated through empirical models, and the response of the atmosphere in both hemispheres, based on parameters from the ECMWF ERA5 atmospheric reanalysis dataset. Our investigations are also supported by counter-test analysis and Monte Carlo tests. We find, for both hemispheres, a significant correspondence, within 1–2 days, between high-latitude electrodynamics variations and changes in the temperature, specific humidity, and meridional and zonal winds, in both the troposphere and stratosphere. The results indicate that, in the complex solar wind–atmosphere relationship, a significant role might be played by the intensification of the polar cap potential. We also study the reciprocal relation between the ionospheric Joule heating, calculated from a model, and two adiabatic invariants used in the analysis of solar wind turbulence.
Enhancing Surface Water Monitoring through Multi-Satellite Data-Fusion of Landsat-8/9, Sentinel-2, and Sentinel-1 SAR
Authors: Declaro Alexis , Kanae Shinjiro
Published: September 2024

Long revisit intervals and cloud susceptibility have restricted the applicability of earth observation satellites in surface water studies. Integrating multiple satellites offers potential for more frequent observations, yet combining different satellite sources, particularly optical and SAR satellites, presents complexities. This research explores the data-fusion potential and limitations of Landsat-8/9 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture (SAR) satellites to enhance surface water monitoring. By focusing on segmented surface water images, we demonstrate that combining optical and SAR data is generally effective and straightforward using a simple statistical thresholding algorithm. Kappa coefficients(κ) ranging from 0.80 to 0.95 indicate very strong harmony for integration across reservoirs, lakes, and river environments. In vegetative environments, integration with S1SAR shows weak harmony, with κ values ranging from 0.27 to 0.45, indicating the need for further studies. Global revisit interval maps reveal significant improvement in median revisit intervals from 15.87 to 22.81 days using L8/9 alone, to 4.51 to 7.77 days after incorporating S2, and further to 3.48 to 4.62 days after adding S1SAR. Even during wet season months, multi-satellite fusion maintained the median revisit intervals to less than a week. Maximizing all available open-source earth observation satellites is integral for advancing studies requiring more frequent surface water observations, such as flood, inundation, and hydrological modeling.
Development of a Simple Observation System to Monitor Regional Wind Erosion
Authors: Kimura Reiji , Liu Jiaqi , Ganzorig Ulgiichimg , Moriyama Masao
Published: September 2024

Dryland occupies about 46% of the global land surface area (except Antarctica) and is the most vulnerable area to climate change. From the conditions of vegetation and land surface wetness and blown sand phenomena, a simple observation system was developed to monitor regional wind erosion and applied to Khuld of Mongolia, which is sensitive to drought and desertification. The system was composed of instruments that observed blown sand, vegetation amount, land surface wetness, and landscape features related to regional wind erosion. Sixteen blown sand and eight sandstorm events were evaluated from 5 March to 5 June 2023 (i.e., during the Asian dust season in northeast Asia). The normalized difference vegetation index and visible images showed that the vegetation amount was considerably less, and the developed moisture index related to land surface wetness indicated dry conditions. Combining the results of blown sand, these indices, and visible images, land surface conditions during the analysis period were likely to occur with blown sand events.
Improve the Performance of SAR Ship Detectors by Small Object Detection Strategies
Authors: Li Jianwei , Yu Zhentao , Chen Jie , Chi Cheng , Yu Lu , Cheng Pu
Published: September 2024

Although advanced deep learning techniques have significantly improved SAR ship detection, accurately detecting small ships remains challenging due to their limited size and the few appearance and geometric clues available. In order to solve this problem, we propose several small object detection strategies. The backbone network uses space-to-depth convolution to replace stride and pooling. It reduces information loss during down-sampling. The neck integrates multiple layers of features globally and injects global and local information into different levels. It avoids the inherent information loss of traditional feature pyramid networks and strengthens the information fusion ability without significantly increasing latency. The proposed intersection-of-union considers the center distance and scale of small ships specifically. It reduces the sensitivity of intersection-of-union to positional deviations of small ships, which is helpful for training toward small ships. During training, the smaller the localization loss of small ships, the greater their localization loss gains are. By this, the supervision of small ships is strengthened in the loss function, which can make the losses more biased toward small ships. A series of experiments are conducted on two commonly used datasets, SSDD and SAR-Ship-Dataset. The experimental results show that the proposed method can detect small ships successfully and thus improve the overall performance of detectors.
Orthophoto-Based Vegetation Patch Analyses—A New Approach to Assess Segmentation Quality
Authors: Maćków Witold , Bondarewicz Malwina , Łysko Andrzej , Terefenko Paweł
Published: September 2024

The following paper focuses on evaluating the quality of image prediction in the context of searching for plants of a single species, using the example of Heracleum sosnowskyi Manden, in a given area. This process involves a simplified classification that ends with a segmentation step. Because of the particular characteristics of environmental data, such as large areas of plant occurrence, significant partitioning of the population, or characteristics of a single individual, the use of standard statistical measures such as Accuracy, the Jaccard Index, or Dice Coefficient does not produce reliable results, as shown later in this study. This issue demonstrates the need for a new method for assessing the betted prediction quality adapted to the unique characteristics of vegetation patch detection. The main aim of this study is to provide such a metric and demonstrate its usefulness in the cases discussed. Our proposed metric introduces two new coefficients, M+ and M−, which, respectively, reward true positive regions and penalise false positive regions, thus providing a more nuanced assessment of segmentation quality. The effectiveness of this metric has been demonstrated in different scenarios focusing on variations in spatial distribution and fragmentation of theoretical vegetation patches, comparing the proposed new method with traditional metrics. The results indicate that our metric offers a more flexible and accurate assessment of segmentation quality, especially in cases involving complex environmental data. This study aims to demonstrate the usefulness and applicability of the metric in real-world vegetation patch detection tasks.
Development and Application of Unmanned Aerial High-Resolution Convex Grating Dispersion Hyperspectral Imager
Authors: Xue Qingsheng , Gao Xinyu , Lu Fengqin , Ma Jun , Song Junhong , Xu Jinfeng
Published: September 2024

This study presents the design and development of a high-resolution convex grating dispersion hyperspectral imaging system tailored for unmanned aerial vehicle (UAV) remote sensing applications. The system operates within a spectral range of 400 to 1000 nm, encompassing over 150 channels, and achieves an average spectral resolution of less than 4 nm. It features a field of view of 30°, a focal length of 20 mm, a compact volume of only 200 mm × 167 mm × 78 mm, and a total weight of less than 1.5 kg. Based on the design specifications, the system was meticulously adjusted, calibrated, and tested. Additionally, custom software for the hyperspectral system was independently developed to facilitate functions such as control parameter adjustments, real-time display, and data preprocessing of the hyperspectral camera. Subsequently, the prototype was integrated onto a drone for remote sensing observations of Spartina alterniflora at Yangkou Beach in Shouguang City, Shandong Province. Various algorithms were employed for data classification and comparison, with support vector machine (SVM) and neural network algorithms demonstrating superior classification accuracy. The experimental results indicate that the UAV-based hyperspectral imaging system exhibits high imaging quality, minimal distortion, excellent resolution, an expansive camera field of view, a broad detection range, high experimental efficiency, and remarkable capabilities for remote sensing detection.
Data-Aided Maximum Likelihood Joint Angle and Delay Estimator Over Orthogonal Frequency Division Multiplex Single-Input Multiple-Output Channels Based on New Gray Wolf Optimization Embedding Importance Sampling
Authors: Abdelkhalek Maha , Ben Amor Souheib , Affes Sofiène
Published: September 2024

In this paper, we propose a new data-aided (DA) joint angle and delay (JADE) maximum likelihood (ML) estimator. The latter consists of a substantially modified and, hence, significantly improved gray wolf optimization (GWO) technique by fully integrating and embedding within it the powerful importance sampling (IS) concept. This new approach, referred to hereafter as GWOEIS (for “GWO embedding IS”), guarantees global optimality, and offers higher resolution capabilities over orthogonal frequency division multiplex (OFDM) (i.e., multi-carrier and multi-path) single-input multiple-output (SIMO) channels. The traditional GWO randomly initializes the wolfs’ positions (angles and delays) and, hence, requires larger packs and longer hunting (iterations) to catch the prey, i.e., find the correct angles of arrival (AoAs) and time delays (TDs), thereby affecting its search efficiency, whereas GWOEIS ensures faster convergence by providing reliable initial estimates based on a simplified importance function. More importantly, and beyond simple initialization of GWO with IS (coined as IS-GWO hereafter), we modify and dynamically update the conventional simple expression for the convergence factor of the GWO algorithm that entirely drives its hunting and tracking mechanisms by accounting for new cumulative distribution functions (CDFs) derived from the IS technique. Simulations unequivocally confirm these significant benefits in terms of increased accuracy and speed Moreover, GWOEIS reaches the Cramér–Rao lower bound (CRLB), even at low SNR levels.
Use of the SNOWED Dataset for Sentinel-2 Remote Sensing of Water Bodies: The Case of the Po River
Authors: Scarpetta Marco , Spadavecchia Maurizio , Affuso Paolo , D’Alessandro Vito Ivano , Giaquinto Nicola
Published: September 2024

The paper demonstrates the effectiveness of the SNOWED dataset, specifically designed for identifying water bodies in Sentinel-2 images, in developing a remote sensing system based on deep neural networks. For this purpose, a system is implemented for monitoring the Po River, Italy’s most important watercourse. By leveraging the SNOWED dataset, a simple U-Net neural model is trained to segment satellite images and distinguish, in general, water and land regions. After verifying its performance in segmenting the SNOWED validation set, the trained neural network is employed to measure the area of water regions along the Po River, a task that involves segmenting a large number of images that are quite different from those in SNOWED. It is clearly shown that SNOWED-based water area measurements describe the river status, in terms of flood or drought periods, with a surprisingly good accordance with water level measurements provided by 23 in situ gauge stations (official measurements managed by the Interregional Agency for the Po). Consequently, the sensing system is used to take measurements at 100 “virtual” gauge stations along the Po River, over the 10-year period (2015–2024) covered by the Sentinel-2 satellites of the Copernicus Programme. In this way, an overall space-time monitoring of the Po River is obtained, with a spatial resolution unattainable, in a cost-effective way, by local physical sensors. Altogether, the obtained results demonstrate not only the usefulness of the SNOWED dataset for deep learning-based satellite sensing, but also the ability of such sensing systems to effectively complement traditional in situ sensing stations, providing precious tools for environmental monitoring, especially of locations difficult to reach, and permitting the reconstruction of historical data related to floods and draughts. Although physical monitoring stations are designed for rapid monitoring and prevention of flood or other disasters, the developed tool for remote sensing of water bodies could help decision makers to define long-term policies to reduce specific risks in areas not covered by physical monitoring or to define medium- to long-term strategies such as dam construction or infrastructure design.
Optoelectronics Interfaces for a VLC System for UHD Audio-Visual Content Transmission in a Passenger Van: HW Design
Authors: del Valle Morales Carlos Iván , Betancourt Perlaza Juan Sebastián , Torres Zafra Juan Carlos , Martinez-Sarriegui Iñaki , Sánchez-Pena José Manuel
Published: September 2024

This work aims to provide the hardware (HW) design of the optoelectronics interfaces for a visible-light communication (VLC) system that can be employed for several use cases. Potential applications include the transmission of ultra-high-definition (UHD) streaming video through existing reading lamps installed in passenger vans. In this use case, visible light is employed for the downlink, while infrared light is used for the uplink channel, acting as a remote controller. Two primary components -a Light Fidelity (LiFi) router and a USB dongle—were designed and implemented. The ‘LiFi Router’, handling the downlink channel, comprises components such as a visible Light-Emitting Diode (LED) and an infrared receiver. Operating at a supply voltage of 12 V and consuming current at 920 mA, it is compatible with standard voltage buses found in transport vehicles. The ‘USB dongle’, responsible for the uplink, incorporates an infrared LED and a receiver optimized for visible light. The USB dongle works at a supply voltage of 5 V and shows a current consumption of 1.12 A, making it well suited for direct connection to a universal serial bus (USB) port. The bandwidth achieved for the downlink is 11.66 MHz, while the uplink’s bandwidth is 12.27 MHz. A system competent at streaming UHD video with the feature of being single-input multiple-output (SIMO) was successfully implemented via the custom hardware design of the optical transceivers and optoelectronics interfaces. To ensure the system’s correct performance at a distance of 110 cm, the minimum signal-to-noise ratio (SNRmin) for both optical links was maintained at 10.74 dB. We conducted a proof-of-concept test of the VLC system in a passenger van and verified its optimal operation, effectively illustrating its performance in a real operating environment. Exemplifying potential implementations possible with the hardware system designed in this work, a bit rate of 15.2 Mbps was reached with On–Off Keying (OOK), and 11.25 Mbps was obtained with Quadrature Phase Shift Keying (QPSK) using Orthogonal Frequency-Division Multiplexing (OFDM) obtaining a bit-error rate (BER) of 3.3259 × 10−5 in a passenger van at a distance of 72.5 cm between the LiFi router and the USB dongle. As a final addition, a solar panel was installed on the passenger van’s roof to power the user’s laptop and the USB dongle via a power bank battery. It took 13.4 h to charge the battery, yielding a battery life of 22.3 h. This characteristic renders the user’s side of the system entirely self-powered.
High-Accuracy Calibration Method of a Thermal Camera Using Two Reference Blackbodies
Authors: Sosnowski Tomasz , Kastek Mariusz , Sawicki Krzysztof , Ligienza Andrzej , Gogler Sławomir , Więcek Bogusław
Published: September 2024

Body temperature is one of the most important physiological parameters of a human being used to assess his basic vital functions. In medical practice, various types of measuring instruments are used to measure temperature, such as liquid thermometers, electronic thermometers, non-contact ear thermometers, and non-contact forehead thermometers. Such body temperature measurement techniques require the connection of appropriate sensors to a person, and non-contact thermometers operate over short distances and force a specific position of the person during the measurement. As a result, using the above methods, it is practically impossible to perform body temperature measurements of a moving human being. A thermal imaging camera can be used effectively for the purpose of the temperature measurement of moving objects, but the remote measurement of a human body temperature using a thermal imaging camera is affected by many factors that are difficult to control. Accurate remote measurement of human body temperature requires a measurement system that implements a specialized temperature determination algorithm. This article presents a model of a measurement system that facilitates the development of a highly accurate temperature measurement method. For the model, its parameters were determined on the calibration stand. The correct operation of the developed method and the effectiveness of temperature measurement have been confirmed by tests on a test stand using reference radiation sources.
Impact of Land Use and Land Cover (LULC) Changes on Carbon Stocks and Economic Implications in Calabria Using Google Earth Engine (GEE)
Authors: Khachoo Yasir Hassan , Cutugno Matteo , Robustelli Umberto , Pugliano Giovanni
Published: September 2024

Terrestrial ecosystems play a crucial role in global carbon cycling by sequestering carbon from the atmosphere and storing it primarily in living biomass and soil. Monitoring terrestrial carbon stocks is essential for understanding the impacts of changes in land use on carbon sequestration. This study investigates the potential of remote sensing techniques and the Google Earth Engine to map and monitor changes in the forests of Calabria (Italy) over the past two decades. Using satellite-sourced Corine land cover datasets and the InVEST model, changes in Land Use Land Cover (LULC), and carbon concentrations are analyzed, providing insights into the carbon dynamics of the region. Furthermore, cellular automata and Markov chain techniques are used to simulate the future spatial and temporal dynamics of LULC. The results reveal notable fluctuations in LULC; specifically, settlement and bare land have expanded at the expense of forested and grassland areas. These land use and land cover changes significantly declined the overall carbon stocks in Calabria between 2000 and 2024, resulting in notable economic impacts. The region experienced periods of both decline and growth in carbon concentration, with overall losses resulting in economic impacts up to EUR 357.57 million and carbon losses equivalent to 6,558,069.68 Mg of CO 2 emissions during periods of decline. Conversely, during periods of carbon gain, the economic benefit reached EUR 41.26 million, with sequestered carbon equivalent to 756,919.47 Mg of CO 2 emissions. This research aims to highlight the critical role of satellite data in enhancing our understanding and development of comprehensive strategies for managing carbon stocks in terrestrial ecosystems.
Self-Supervised Dam Deformation Anomaly Detection Based on Temporal–Spatial Contrast Learning
Authors: Wang Yu , Liu Guohua
Published: September 2024

The detection of anomalies in dam deformation is paramount for evaluating structural integrity and facilitating early warnings, representing a critical aspect of dam health monitoring (DHM). Conventional data-driven methods for dam anomaly detection depend extensively on historical data; however, obtaining annotated data is both expensive and labor-intensive. Consequently, methodologies that leverage unlabeled or semi-labeled data are increasingly gaining popularity. This paper introduces a spatiotemporal contrastive learning pretraining (STCLP) strategy designed to extract discriminative features from unlabeled datasets of dam deformation. STCLP innovatively combines spatial contrastive learning based on temporal contrastive learning to capture representations embodying both spatial and temporal characteristics. Building upon this, a novel anomaly detection method for dam deformation utilizing STCLP is proposed. This method transfers pretrained parameters to targeted downstream classification tasks and leverages prior knowledge for enhanced fine-tuning. For validation, an arch dam serves as the case study. The results reveal that the proposed method demonstrates excellent performance, surpassing other benchmark models.
Leveraging Crowdsourcing for Mapping Mobility Restrictions in Data-Limited Regions
Authors: Aburas Hala , Shahrour Isam , Sadek Marwan
Published: September 2024

This paper introduces a novel methodology for the real-time mapping of mobility restrictions, utilizing spatial crowdsourcing and Telegram as a traffic event data source. This approach is efficient in regions suffering from limitations in traditional data-capturing devices. The methodology employs ArcGIS Online (AGOL) for data collection, storage, and analysis, and develops a 3W (what, where, when) model for analyzing mined Arabic text from Telegram. Data quality validation methods, including spatial clustering, cross-referencing, and ground-truth methods, support the reliability of this approach. Applied to the Palestinian territory, the proposed methodology ensures the accurate, timely, and comprehensive mapping of traffic events, including checkpoints, road gates, settler violence, and traffic congestion. The validation results indicate that using spatial crowdsourcing to report restrictions yields promising validation rates ranging from 67% to 100%. Additionally, the developed methodology utilizing Telegram achieves a precision value of 73%. These results demonstrate that this methodology constitutes a promising solution, enhancing traffic management and informed decision-making, and providing a scalable model for regions with limited traditional data collection infrastructure.
The Roma Population: Migration, Settlement, and Resilience
Authors: Ullah A. K. M. Ahsan , Azizuddin Muhammad , Ferdous Jannatul
Published: September 2024

The Roma population—with a unique history marked by migration, settlement issues, and ongoing resilience—has always faced significant social marginalization and has often been subjected to forced migration. Despite being one of the largest and most diverse ethnic groups in Europe, Roma continue to face systemic discrimination and social exclusion, leading to poor outcomes in education, employment, health, and housing. This article analyses the migration pathways, settlement experiences, and persistent obstacles faced by Roma. We argue that removing historical and systemic barriers to create a more equitable and welcoming environment for the Roma community is their right. The resilience of the Roma community in the face of adversity is a testament to their cultural strength and adaptability. This research aims to document these aspects and thus provide a basis for policies that promote social inclusion, equality, and respect for cultural diversity.
Australian Non-Resident Fathers’ Relationship and Ongoing Engagement with Their Children: A Critical Focus on Power
Authors: Violi Dominic , Lewis Peter , Kwok Cannas , Wilson Nathan J.
Published: September 2024

Non-resident fathers are rarely researched from a critical perspective. Becoming a non-resident father often results in major dislocation, presenting challenges and hindrances to a meaningful relationship with children. Dislocation is increased by the involvement of the family court, legal issues, false abuse allegations, and ex-partners. Changing family configurations may marginalize non-resident fathers, with their own perspectives, voices, and lack of power remaining largely unmapped. This paper identifies what hinders non-resident fathers’ relationships with their children from a critical and Australian perspective. In-depth interviews using open-ended questions with 19 non-resident fathers were used to collect data, followed by a five-step critical thematic analysis to focus on the locus of power. Non-resident fathers’ perceptions included a lack of agency and decision-making power; the mother, legal obstacles, and agencies hindered their desired relationships with children. Hindrances were magnified by descriptions of false allegations and IPV from the ex-partner and/or her agents, resulting in a sense of marginalization, silencing, and disempowerment. Australian non-resident fathers in this study identified that desired relationships with their children were hindered by the roles of legal and welfare services, policing, and their ex-partners. The highlighting of these issues points to ways that non-resident fathers with similar experiences of a lack of agency and decision-making power might be better supported by more streamlined and balanced legal processes.
Establishment of Nitrogen-Fixing Frankia, Arbuscular Mycorrhizal Fungi, and Their Effects on Alder (Alnus glutinosa L.) Growth in Post-Mining Heap Soils
Authors: Buchbauerová Lucie , Ardestani Masoud M. , Rydlová Jana , Veselá Hana , Frouz Jan
Published: September 2024

Planting nitrogen-fixing plants in post-mining sites and similar degraded areas is a common approach to speed up soil development and buildup of the nitrogen pool in soil organic matter. The aim of this study was to explore if slower growth of alder seedlings in initial post-mining sites results from adverse soil conditions or lack of microbial symbionts. To address this question, we sampled young soil (age 15 years) and more developed soil (age 70 years) from heaps after coal mining near Sokolov (Czech Republic). Soil samples were sterilized and not inoculated or inoculated with arbuscular mycorrhizal fungi (AMF) or AMF + Frankia, followed by planting with alder (Alnus glutinosa) seedlings germinated and precultured under sterile conditions. The effect of soil age on alder growth appeared to be non-significant. The only significant growth effect was seen with Frankia inoculation, implicating this inoculum as a key factor in later succession in post-mining soils. When the soil was fully inoculated, alder biomass was higher in developed soil supplied with iron (Fe) and phosphorus (P), indicating that iron and phosphorus availability may affect alder growth. In young soil, alder growth was highest with a combination of iron, phosphorus, and sulfur (S), and a positive effect of sulfur in young soil may correspond with a reduced, alkaline soil pH and increased phosphorus and iron availability.
The Neighborhood Effects of National Climate Legislation: Learning or Competition?
Authors: Liu Ying , Murthy Uma , Feng Chao
Published: September 2024

This study aims to explore the spatial spillover effects of national climate legislation on carbon emission reduction by using cross-country panel data from 2002 to 2021. The results show the following: First, the estimation outcomes confirm the presence of spatial correlations between carbon dioxide emissions and climate legislation across countries. Second, the study shows that the spillover effect of climate legislation on CO2 emissions is significantly negative. Hence, the outcomes indicate that being surrounded by nations with more climate laws positively impacts environmental quality. Third, regarding direct impact and spillover effects, the carbon reduction impact of parliamentary legislative acts is stronger than that of governmental executive orders. Finally, even with the spillover effect, we uncover robust evidence supporting an inverted-U-shaped EKC linkage between carbon emissions and GDP per capita, even under the spatial spillover effect.
Re-Examination of the Relationship between Industrial Agglomeration and Haze Pollution: From the Perspective of the Spatial Moderating Effect of Environmental Regulation
Authors: Wang Xiaolin , Li Zhenyang
Published: September 2024

This paper uses panel data from 284 Chinese cities from 2004 to 2020 and employs a dynamic spatial panel Durbin model to re-examine the relationship between industrial agglomeration, environmental regulation, and haze pollution. It further adopts a dynamic spatial moderation effect model to explore the spatial regulatory mechanism of environmental regulation. The results show that both local and neighboring industrial agglomeration have a significant “inverted U-shaped” relationship with local haze pollution, and the scale cumulative optimization effect can only be effectively played after the industrial agglomeration level of the locality and neighboring areas exceeds the inflection point. Local environmental regulation significantly inhibits haze pollution, while neighboring environmental regulation plays a promoting role. The moderating effect of environmental regulation on the relationship between industrial agglomeration and haze pollution shows spatial heterogeneity in the local and neighboring areas. Local environmental regulation has a “U-shaped” non-linear moderating effect while neighboring environmental regulation has a positive linear moderating effect. Therefore, the government should pay attention to the joint effort and coordinated advancement of industrial agglomeration and environmental regulation to further reduce urban haze pollution and enhance urban air quality.
Sustainable Growth through Thai Native Chicken Farming: Lessons from Rural Communities
Authors: Loengbudnark Wipas , Chankitisakul Vibuntita , Duangjinda Monchai , Boonkum Wuttigrai
Published: September 2024

Thai native chickens hold significant value in rural communities due to their adaptability and suitability for local rearing conditions. However, there are challenges in the commercial raising of these chickens. This study aimed to evaluate and promote the potential of Thai native chickens (Pradu Hang Dum) for commercial purposes and the development of sustainable native chicken farming. Out of 110 interested farmers, 88 met preliminary conditions and 62 were well-prepared and willing to comply with project conditions. Some farmers were disqualified for not understanding the project conditions or having inadequately prepared chicken coops. The survival rate of native chickens provided to farmers through the project was 52%. Among the surviving birds, 40% were male and 60% were female. The most common causes of death in the project were sickness, accidents, and fighting. The average body weights and average daily gains at different ages were significantly different among farm groups. The average egg production per hatch per hen was 13 ± 2.4 eggs. The highest egg production was in the good farms compared to moderate and poor farms. Better farm management led to higher egg production. In conclusion, this study demonstrates that effective farm management significantly enhances the productivity of Thai native chickens, highlighting their potential as an income-generating activity for rural communities. While challenges such as sickness and accidents impact survival rates, the findings suggest that improved management practices can lead to better production outcomes.
Sustainable Paddy Farming in Edirne: Evaluating the Impacts of Excessive Fertilizer and Pesticide Use
Authors: Gaytancıoğlu Okan , Yılmaz Fuat
Published: September 2024

This study examines the environmental and economic impacts of chemical fertilizer and pesticide use in paddy fields in Edirne Province, Türkiye. Chemical fertilizers, especially nitrogen and phosphorus, are crucial for boosting paddy yield and ensuring food security. However, recent trends indicate significant potassium deficiency and excessive pesticide use, leading to environmental degradation and higher production costs. Incorrect fertilization techniques and pesticide usage can lower product quality and yield, adversely affecting farmers’ incomes and the national economy. Surveying 139 paddy farmers, the research found that farmers apply the herbicidal active ingredients Tefuryltrione, Clomazone, Tembotrione, and Quinclorac at rates of 129.35%, 34.27%, 18.06%, and 155.29% above the recommended levels, respectively. The excessive use of pesticides costs each farmer an additional USD 925.67, totaling USD 5.32 million for Edirne. The majority of farmers (69.2%) do not conduct soil analysis, indicating a potential gap in adopting the best practices for soil management and fertilization. Farmers use 84% less potassium than recommended while applying nitrogen and phosphorus 13% and 14% above the recommended levels, respectively. The extra cost of fertilizer use in Edirne is calculated as USD 833,135.49. This situation harms the economy and may have adverse effects on the environment and potential health effects on consumers.
Morphological and Functional Polycentric Urbanization in Colombo Metropolitan of Sri Lanka Using Time-Series Satellite Images from 1988–2022
Authors: Fonseka H. P. U. , Premasiri H. M. R. , Chaminda S. P. , Zhang Hongsheng
Published: September 2024

Examining urban growth in metropolitan areas from both morphological and functional perspectives is paramount for sustainable development in developing and developed countries. As a collaborative and critical approach, polycentrism operates concurrently at local, regional, and national levels. However, the decentralized morphologies and functional attributes of polycentric urban spaces are yet to be adequately explored, despite their significant influence on sustainable urban planning and management. Colombo, the only metropolitan area in Sri Lanka, has experienced considerable yet ambiguously imbalanced spatial growth due to insufficient data. This study employed time-series satellite imagery from 1988 to 2022, in conjunction with a network model, to elucidate Colombo’s uneven urban patterns, while achieving an accuracy of over 80% throughout the period. The results revealed that the metropolis has evolved into a polynuclear city, complicating the identification of centers and their corresponding developmental stages. Nevertheless, the study successfully pinpointed the morphological and functional Grama Niladhari divisions, disclosing the morphological features of centralized dispersion and the functional traits of decentralized concentration. These insights provide significant implications for local government, guiding urban planning initiatives to achieve sustainable development goals.