bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive Prospecting Using Remote Sensing in a Mountainous Terrestrial Volcanic Area, in Western Bangongco–Nujiang Mineralization Belt, Tibet
Authors: Bai Longyang , Dai Jingjing , Song Yang , Liu Zhibo , Chen Wei , Wang Nan , Wu Changyu
Published: October 2023

The Bangongco–Nujiang metallogenic belt of Tibet is a main suture zone in the Qinghai–Tibet Plateau, which is known as an important porphyry–epithermal–skarn Cu-polymetallic mineralization zone in China. The western part of the Bangongco–Nujiang metallogenic belt exposes several medium high-silica terrestrial alkaline volcanic rocks with strong alteration influenced by collision orogeny. Some research has shown that clues to mineralization such as malachite and gossan are found on the surface. However, volcanic rock areas with varied topography place a huge burden on geological investigation, and the existing research on predicting mineralization is relatively scarce. This paper describes the extraction of alteration mineral information based on medium spatial resolution and hyperspectral resolution images, establishing a spectral library of alteration minerals in this area. By analyzing radar data, digital elevation, and synthesis results of different spectral bands, we combine remote sensing with geographic information technology to establish crater markers. The extraction results from multisource and chemical exploration data are superimposed onto the analysis of mineralization characteristics and geological conditions so as to establish the mineralization signatures for terrestrial volcanic rock areas. Eighteen mineralization prospect areas were identified, which can provide technical support for future mineralization research in this belt.
Wildfire Detection Using Convolutional Neural Networks and PRISMA Hyperspectral Imagery: A Spatial-Spectral Analysis
Authors: Spiller Dario , Carbone Andrea , Amici Stefania , Thangavel Kathiravan , Sabatini Roberto , Laneve Giovanni
Published: October 2023

The exacerbation of wildfires, attributed to the effects of climate change, presents substantial risks to ecological systems, infrastructure, and human well-being. In the context of the Sustainable Development Goals (SDGs), particularly those related to climate action, prioritizing the assessment and management of the occurrence and intensity of extensive wildfires is of utmost importance. In recent times, there has been a significant increase in the frequency and severity of widespread wildfires worldwide, affecting several locations, including Australia, Italy, and the United States of America. The presence of complex phenomena marked by limited predictability leads to significant negative impacts on biodiversity and human lives. The utilization of satellite-derived data with neural networks, such as convolutional neural networks (CNNs), is a potentially advantageous approach for augmenting the monitoring capabilities of wildfires. This research examines the generalization capability of four neural network models, namely the fully connected (FC), one-dimensional (1D) CNN, two-dimensional (2D) CNN, and three-dimensional (3D) CNN model. Each model’s performance, as measured by accuracy, recall, and F1 scores, is assessed through K-fold cross-validation. Subsequently, T-statistics and p-values are computed based on these metrics to conduct a statistical comparison among the different models, allowing us to quantify the degree of similarity or dissimilarity between them. By using training data from Australia and Sicily, the performances of the trained model are evaluated on the test dataset from Oregon. The results are promising, with cross-validation on the training dataset producing mean precision, recall, and F1 scores ranging between approximately 0.97 and 0.98. Especially, the fully connected model has superior generalization capabilities, whilst the 3D CNN offers more refined and less distorted classifications. However, certain issues, such as false fire detection and confusion between smoke and shadows, persist. The aforementioned methodologies offer significant perspectives on the capabilities of neural network technologies in supporting the detection and management of wildfires. These approaches address the crucial matter of domain transferability and the associated dependability of predictions in new regions. This study makes a valuable contribution to the ongoing efforts in climate change by assisting in monitoring and managing wildfires.
Rapid Determination of Soil Horizons and Suborders Based on VIS-NIR-SWIR Spectroscopy and Machine Learning Models
Authors: de Oliveira Karym Mayara , Falcioni Renan , Gonçalves João Vitor Ferreira , de Oliveira Caio Almeida , Mendonça Weslei Augusto , Crusiol Luís Guilherme Teixeira , de Oliveira Roney Berti , Furlanetto Renato Herrig , Reis Amanda Silveira , Nanni Marcos Rafael
Published: October 2023

In an effort to improve the efficiency of soil classification, traditional methods are being combined with analytical and computational techniques. This integration has strengthened the connection between conventional classification and the application of machine-learning (ML) models to interpret soil spectral reflectance data. Due to the time and computational cost, several studies are limited to testing the classification performance of a few algorithms and do not always explore the best parameters for model optimization. The study aims to assess the efficiency of combining soil spectral reflectance with prevalent ML models for classifying pedogenetic horizons and soil suborders, enhancing traditional classification methods. We collected seven soil monoliths, previously classified according to the Brazilian Soil Classification System (SiBCS) and soil taxonomy. Using the ASD Fieldspec spectroradiometer, we obtained spectral reflectance samples along each monolith (n = 800 per monolith) to classify horizons and n = 5600 for suborder classification. Spectral fingerprints were obtained and explored by Principal Component Analysis (PCA). The spectral data were subdivided into training (70%) and test (30%) sets and submitted to the Logistic Regression (LR), Artificial Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting (GB) models for the classification of horizons and suborders, considering the model’s adjustment parameters. Accuracy and F-Score were used to verify the performance of the models. There was a significant influence of particle size and soil organic carbon on the spectral fingerprint of the soils. The PCA indicated that topsoil horizons clustered in most of the monoliths analyzed, while most of the subsoil horizons showed data overlap. The NN model showed the highest accuracy in the classification of horizons (97%), while the SVM showed the lowest performance (52% accuracy). The classification of soil suborders presented accuracies between 95% and 98%. Therefore, our study concludes that spectral data combined with ML models can enhance the discrimination and classification of soil horizons and suborders, improving upon traditional methods.
An Overview of Coastline Extraction from Remote Sensing Data
Authors: Zhou Xixuan , Wang Jinyu , Zheng Fengjie , Wang Haoyu , Yang Haitao
Published: October 2023

The coastal zone represents a unique interface between land and sea, and addressing the ecological crisis it faces is of global significance. One of the most fundamental and effective measures is to extract the coastline’s location on a large scale, dynamically, and accurately. Remote sensing technology has been widely employed in coastline extraction due to its temporal, spatial, and sensor diversity advantages. Substantial progress has been made in coastline extraction with diversifying data types and information extraction methods. This paper focuses on discussing the research progress related to data sources and extraction methods for remote sensing-based coastline extraction. We summarize the suitability of data and some extraction algorithms for several specific coastline types, including rocky coastlines, sandy coastlines, muddy coastlines, biological coastlines, and artificial coastlines. We also discuss the significant challenges and prospects of coastline dataset construction, remotely sensed data selection, and the applicability of the extraction method. In particular, we propose the idea of extracting coastlines based on the coastline scene knowledge map (CSKG) semantic segmentation method. This review serves as a comprehensive reference for future development and research pertaining to coastal exploitation and management.
Study on the Regeneration Probability of Understory Coniferous Saplings in the Liangshui Nature Reserve Based on Four Modeling Techniques
Authors: Zhao Haiping , Sun Yuman , Jia Weiwei , Wang Fan , Zhao Zipeng , Wu Simin
Published: October 2023

Forests are one of the most important natural resources for humans, and understanding the regeneration probability of undergrowth in forests is very important for future forest spatial structure and forest management. In addition, the regeneration of understory saplings is a key process in the restoration of forest ecosystems. By studying the probability of sapling regeneration in forests, we can understand the impact of different stand factors and environmental factors on sapling regeneration. This could help provide a scientific basis for the restoration and protection of forest ecosystems. The Liangshui Nature Reserve of Yichun City, Heilongjiang Province, is a coniferous and broadleaved mixed forest. In this study, we assess the regeneration probability of coniferous saplings (CRP) in natural forests in 665 temporary plots in the Liangshui Nature Reserve. Using Sentinel-1 and Sentinel-2 images provided by the European Space Agency, as well as digital elevation model (DEM) data, we calculated the vegetation index, microwave vegetation index (RVI S1), VV, VH, texture features, slope, and DEM and combined them with field survey data to construct a logistic regression (LR) model, geographically weighted logistic regression (GWLR) model, random forest (RF) model, and multilayer perceptron (MLP) model to predict and analyze the CRP value of each pixel in the study area. The accuracy of the models was evaluated with the average values of the area under the ROC curve (AUC), kappa coefficient (KAPPA), root mean square error (RMSE), and mean absolute error (MAE) verified by five-fold cross-validation. The results showed that the RF model had the highest accuracy. The variable factor with the greatest impact on CRP was the DEM. The construction of the GWLR model considered more spatial factors and had a lower residual Moran index value. The four models had higher CRP prediction results in the low-latitude and low-longitude regions of the study area, and in the high-latitude and high-longitude regions of the study area, most pixels had a CRP value of 0 (i.e., no coniferous sapling regeneration occurred).
The Frinco Castle: From an Integrated Survey to 3D Modelling and a Stratigraphic Analysis for Helping Knowledge and Reconstruction
Authors: Diara Filippo , Roggero Marco
Published: October 2023

The Frinco Castle (AT-Italy) was the focus of a critical requalification and restoration project and historical knowledge. The initial medieval nucleus was modified and enriched by other architectural parts giving the current shape over the centuries. These additions gave the castle its actual internal and external complexity and an extreme structural fragility: in 2014, a significant portion collapsed. The main objective of this work was to obtain 3D metric documentation and a historical interpretation of the castle for reconstruction and fruition purposes. The local administration has planned knowledge processes from 2021: an integrated 3D geodetic survey of the entire castle and stratigraphic investigations of masonries. Both surveys were essential for understanding the architectural composition as well as the historical evolution of the court. NURBS modelling and a stratigraphic analysis of masonries allowed for the implementation of 3D immersion related to the historical interpretation. Furthermore, this modelling choice was essential for virtually reconstructing the collapsed area and helping the restoration phase.
A Multi-Domain Joint Novel Method for ISAR Imaging of Multi-Ship Targets
Authors: Zhang Yangyang , Xu Ning , Li Ning , Guo Zhengwei
Published: October 2023

As a key object on the ocean, regulating civilian and military ship targets more effectively is a very important part of maintaining maritime security. One of the ways to obtain high-resolution images of ship targets is the inverse synthetic aperture radar (ISAR) imaging technique. However, in the actual ISAR imaging process, ship targets in a formation often lead to complicated motion conditions. Due to the close distance between the ship targets, the rough imaging results of the targets cannot be completely separated in the image domain, and the small differences in motion parameters lead to overlapping phenomena in the Doppler history. Therefore, for situations in which ship formation targets with little difference in motion parameters are included in the same radar beam, this paper proposes a multi-domain joint ISAR separation imaging method for multi-ship targets. First, the method performs echo separation using the Hough transform (HT) with the minimum entropy autofocus method in the image domain. Secondly, the time–frequency curve is extracted in the time–frequency domain using the short-time Fourier transform (STFT) for time–frequency analysis, which solves the problem of the ship formation targets being aliased on both echo and Doppler history after range compression and achieves the purpose of separating the echo signals of the sub-ship targets with high accuracy. Eventually, better-focused images of each target are obtained via further motion compensation and precise imaging. Finally, the effectiveness of the proposed method is verified using a simulation and measured data.
Performance of the Atmospheric Radiative Transfer Simulator (ARTS) in the 600–1650 cm−1 Region
Authors: Jin Zichun , Long Zhiyong , Wang Shaofei , Liu Yunmeng
Published: October 2023

The Atmospheric Radiative Transfer Simulator (ARTS) has been widely used in the radiation transfer simulation from microwave to terahertz. Due to the same physical principles, ARTS can also be used for simulations of thermal infrared (TIR). However, thorough evaluations of ARTS in the TIR region are still lacking. Here, we evaluated the performance of ARTS in 600–1650 cm−1 taking the Line-By-Line Radiative Transfer Model (LBLRTM) as a reference model. Additionally, the moderate resolution atmospheric transmission (MODTRAN) band model (BM) and correlated-k (CK) methods were also used for comparison. The comparison results on the 0.001 cm−1 spectral grid showed a high agreement (sub-0.1 K) between ARTS and LBLRTM, while the mean bias difference (MBD) and root mean square difference (RMSD) were less than 0.05 K and 0.3 K, respectively. After convolving with the spectral response functions of the Atmospheric Infra-Red Sounder (AIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS), the brightness temperature (BT) differences between ARTS and LBLRTM became smaller with RMSDs of <0.1 K. The comparison results for Jacobians showed that the Jacobians calculated by ARTS and LBLRTM were close for temperature (can be used for Numerical Weather Prediction application) and O3 (excellent Jacobian fit). For the water vapor Jacobian, the Jacobian difference increased with an increasing water vapor content. However, at extremely low water vapor values (0.016 ppmv in this study), LBLRTM exhibited non-physical mutations, while ARTS was smooth. This study aims to help users understand the simulation accuracy of ARTS in the TIR region and the improvement of ARTS via the community.
Analysis of Livestock Mobility and Implications for the Risk of Foot-and-Mouth Disease Virus Spread in Iran
Authors: Mirzaie Kamran , Mowlaei Shahir , Arsevska Elena , Ahmadi Bouda Vosough , Ambrosini Francesca , Rosso Fabrizio , Chevanne Etienne
Published: October 2023

Foot-and-mouth disease (FMD) is endemic in Iran and associated with a large impact on the livestock industry. Livestock mobility is recognized as one of the most important risk factors for FMD and other infectious livestock diseases’ introduction and dissemination. The description of temporal and spatial aspects of livestock mobility networks in Iran provides insights into FMD epidemiology. It also assists in the formulation of recommendations to mitigate the risk of animal disease transmission through livestock movements. This study is the first spatiotemporal description of official/registered cattle, sheep, goat, and camel movements in Iran, using records related to the period from March 2020 to August 2021 extracted from the Iran Veterinary Organization (IVO) Quarantine system. It shows that the static networks drawn by the movements of small ruminants, cattle, and camels to farms or slaughterhouses are complex and highlights the predominance of a few provinces and towns. In particular, the results show that Razavi Khorasan and West Azerbaijan provinces, major provinces for the Iranian livestock sector, are provinces where significant volumes of small ruminants and cattle are moved (from, to, or within) and, therefore, should be prioritized for targeted and timely risk reduction interventions. This study produces some of the necessary inputs for the risk assessment of FMD and similar transboundary animal diseases (TADs) spread within Iran, which is needed to regularly update the national risk-based control strategy for FMD and other TADs.
Direction of Arrival Estimation and Highlighting Characteristics of Testing Wideband Echoes from Multiple Autonomous Underwater Vehicles
Authors: Yin Xiaofeng , Zhang Peizhen , Zhou Guangbo , Feng Ziyi
Published: October 2023

Multiple autonomous underwater vehicles (AUVs) have gradually become the trend in underwater operations. Identifying and detecting these new underwater multi-targets is difficult when studying underwater moving targets. A 28-element transducer is used to test the echo of multiple AUVs with different layouts in a lake. The characteristics of the wideband echo signals are studied. Under the condition that the direction of arrival (DOA) is not known, an autofocus coherent signal subspace (ACCSM) method is proposed. The focusing matrix is constructed based on the received data. The spatial spectrum of the array signal of multiple AUVs at different attitudes is calculated. The algorithm estimates the DOA of the echo signals to overcome the shortcomings of traditional wideband DOA estimation and improve its accuracy. The results show that the highlights are not only related to the number of AUVs, but are also modified by scale and attitude. The contribution of the microstructure of the target in the overall echo cannot be ignored. Different parts of the target affect the number of highlights, thus resulting in varying numbers of highlights at different attitude angle intervals. The results have significant implications for underwater multi-target recognition.
Illumination-Based Color Reconstruction for the Dynamic Vision Sensor
Authors: Cohen Khen , Hershko Omer , Levy Homer , Mendlovic David , Raviv Dan
Published: October 2023

This work demonstrates a novel, state-of-the-art method to reconstruct colored images via the dynamic vision sensor (DVS). The DVS is an image sensor that indicates only a binary change in brightness, with no information about the captured wavelength (color) or intensity level. However, the reconstruction of the scene’s color could be essential for many tasks in computer vision and DVS. We present a novel method for reconstructing a full spatial resolution, colored image utilizing the DVS and an active colored light source. We analyze the DVS response and present two reconstruction algorithms: linear-based and convolutional-neural-network-based. Our two presented methods reconstruct the colored image with high quality, and they do not suffer from any spatial resolution degradation as other methods. In addition, we demonstrate the robustness of our algorithm to changes in environmental conditions, such as illumination and distance. Finally, compared with previous works, we show how we reach the state-of-the-art results. We share our code on GitHub.
The Ways of Overcoming the Impact of Graduation from School on the Mental State of Students and Their Parents: Counseling with a Social Worker to Solve Social and Psychological Problems
Authors: Gad Salah , Youssef Enaam , Yousif Nagwa Babiker Abdalla , Almalek Mahra
Published: October 2023

The study identifies and measures the emotional aspects affecting students’ learning and motivation as well as their relationship with the social and psychological environment in their family. Solving emotional problems was also one of the goals. In total, 50 schoolchildren, 16 to 18 years of age, took part in the experiment. Their parents also participated in the study for family therapy sessions. The experiment was conducted at Ajman Private School, Ajman Emirate, Ajman, United Arab Emirates. Prior to the study, graduates took a series of questionnaires to measure their emotional state. During the experiment, respondents had conversations with a social worker and an art therapist once a week. During conversations, a social worker helped the students and their parents to understand the difficulties in their relationships and to come to compromises. In art therapy sessions, respondents expressed their negative emotions on the canvas using art materials. The study lasted four months. Also, at the middle and end of the experiment, respondents took a series of tests to measure their progress over time. The outcomes demonstrated not only the interrelation of family support and emotional state but also the effectiveness of the chosen methodology. The average score on the Beck Depression Inventory prior to the study was 6.8 out of 10 points. On the Taylor’s Manifest Anxiety Scale, the average score was 7.4 points. According to the WAM test, the ‘wellbeing’ factor before the beginning of the experiment was equal to 4.9 points.
“Actually Changing Our Way of Being”: Transformative Organizing and Implications for Critical Community-Engaged Scholarship
Authors: Lin May
Published: October 2023

Because research alone cannot dismantle racial inequity, this article focuses on lessons for critical community-engaged scholarship (CCES) based on the Relationship-Centered Schools campaign of Californians for Justice (CFJ), an educational and racial justice youth organizing group. The campaign embraced transformative organizing—an approach to social change that encompasses reshaping oppressive institutions and healing trauma wounds wrought by injustice. I discuss findings and methodological implications for CCES, considering challenges in translating research to policy change for racial equity. This article situates the power and limitations of research within CFJ’s broad array of transformative organizing strategies to create more caring and equitable schools. Strategies include youth-led action research, voter engagement, lobbying, youth sharing power with adults, and healing practices of slowing down and relationship building to rehumanize youth of color. I then discuss implications for CCES. First, research supported CFJ youth leaders’ efforts to press institutions to value their full, emotionally complex humanity and legitimize their emotional knowledge. Yet because research is only one of many strategies for transformative change, fully participatory research is not always within organizing groups’ capacity. Thus, researchers can act more expansively by lending our time, energy, and labor to power building. Second, care and healing practices embodied by CFJ can inspire researchers to center relationship building and care as praxis and translate these lessons to transform the academy into a more equitable place. Ultimately, transformative organizing shows how CCES can extend beyond equitable research practices to include more liberatory ways of being, feeling, and acting towards justice.
Unpacking Gender for Flat Breast Cancer Survivors Assigned Female at Birth: A Methodological Application of Visually Informed, Critical Discursive Psychology
Authors: Raque Trisha L. , McCullough Keiko M. , Creegan Maggie A.
Published: October 2023

Given the high prevalence rates of breast cancer and mastectomy as recommended treatment, a large number of breast cancer survivors assigned female at birth may face contradicting messages about whether to pursue reconstruction. Survivors desire information outside of standard biased pro-reconstruction messages, with an increase in utilization of online social platforms to learn of the lived experiences of survivors who have gone flat. As breasts are socially constructed symbols connected to femininity, fertility, motherhood, and (hetereo)sexualization, the application of visually informed, critical discursive psychology holds promise as a method for analyzing how survivors “do” gender after going flat. This paper summarizes prior research on messages around reconstruction before diving into how breasts hold sociocultural meanings in relation to gender performance. A preliminary reading of a photo posted on Twitter by Tig Notaro, a comedian who has been public about breast cancer, and a photo posted on Instagram by entrepreneur Jamie Kastelic were analyzed using a visually informed, critical discursive psychology lens. Our preliminary analysis illustrates the utility of this method for understanding how flat survivors assigned female at birth construct gender for both themselves and a social media audience. This paper challenges assumptions regarding what a “healthy” breast cancer survivor looks like and aims to encourage future inquiries into how social media functions as a space where survivors can perform gender online after going flat themselves.
The Relationship between Career Calling and Workaholism: The Mediating Role of Career Orientation
Authors: Pitacho Liliana , Cordeiro João Pedro
Published: October 2023

The difference between having workers involved in their work, on the one hand, or too exhausted to contribute, on the other, can be tenuous and compromise work orientation. The positive outcomes of career calling (a deep purpose and meaningfulness in work characterized by vigor, dedication, and absorption) to organizations are clear, namely the relationship of career calling with high levels of commitment and engagement. However, the dark side of career calling remains a less explored point. The main purpose of this study analyzes this side of career calling and explores the relationship between sense of work purpose—perceived career calling—and workaholism. The sample consists of 743 Portuguese employees from different sectors of activity. The main hypothesis intends to test the presence of career orientation as a mechanism to explain the ambiguity of career calling outcomes, that is, the mediating effect of career orientation on the relationship between career calling and workaholism. The results showed that the workers’ career orientation helps to explain this relationship. Career orientation partially mediated the relation between career calling and the positive dimension of workaholism, involvement and enjoyment, and completely mediated the relation between career calling and negative dimensions of workaholism, drive. These results allow us to reflect on career calling, and how organizations manage workforce efforts to avoid work addiction and the negative consequences that compromise workforce sustainability. Career calling was looked at as an element of a mixed profile work orientation, rather than not just as a pure work orientation. Theoretical and practical implications are discussed.
Artificial Intelligence Program for Predicting Wrestlers’ Sports Performances
Authors: Nagovitsyn Roman Sergeevich , Valeeva Roza Alexeevna , Latypova Liliia Agzamovna
Published: October 2023

To date, there are conflicting opinions about the effectiveness of the introduction of artificial intelligence technologies in sports. In this regard, the purpose of the study was to develop and integrate an intellectual program for predicting competitive success into the process of selecting wrestlers to increase its effectiveness. The authors developed a program for predicting the sports performance of wrestlers on the basis of artificial intelligence technology. To implement the study, the individual data of Greco-Roman wrestlers (n = 72) were collected and processed on 36 comparison traits, ranked into categories according to three key areas: sports space, hereditary data and individual achievements. As a result of data processing through means of deep neural networks and machine learning algorithms, two prediction categories were identified: athletes who performed at the sport rank or the highest standard and athletes who did not achieve this standard. Control testing of the created program showed only 11% of error probability in predicting a given wrestler’s competitive performance. As for the functionality of the program in the area of classification of the features by category, the authors’ artificial intelligence program with 100% probability identified key categories of traits that reliably affect the results of the future sports performance of a young wrestler. Thus, the use of neural networks and machine learning algorithms, according to the results of the study, improves the quality of sports selection, which will allow further timely individualization and improvement of the training process of young wrestlers.
From Incremental Test to Continuous Running at Fixed Lactate Thresholds: Individual Responses on %VO2max, %HRmax, Lactate Accumulation, and RPE
Authors: Fleckenstein Daniel , Seelhöfer Jannik , Walter Nico , Ueberschär Olaf
Published: October 2023

With Norway’s successes in middle and long-distance running, lactate-guided threshold training has regained importance in recent years. Therefore, the aim of the present study was to investigate the individual responses on common monitoring parameters based on a lactate-guided conventional training method. In total, 15 trained runners (10 males, 5 females; 18.6 ± 3.3 years; VO2max: 59.3 ± 5.9 mL kg−1 min−1) completed a 40-min continuous running session at a fixed lactate threshold load of 2 mmol L−1. Lactate (La), oxygen uptake (VO2), heart rate (HR), and rating of perceived exertion (RPE) were recorded. The chosen workload led to lactate values of 2.85 ± 0.56 mmol L−1 (range: 1.90–3.80), a percentage of VO2max utilization (%VO2max) of 79.2 ± 2.5% (range: 74.9–83.8), a percentage of HRmax utilization (%HRmax) of 92.2 ± 2.5% (range: 88.1–95.3), and an RPE of 6.1 ± 1.9 (range: 3–10) at the end of the running session. Thereby, the individual responses differed considerably. These results indicate that a conventional continuous training method based on a fixed lactate threshold can lead to different individual responses, potentially resulting in various physiological impacts. Moreover, correlation analyses suggest that athletes with higher lactate threshold performance levels must choose their intensity in continuous training methods more conservatively (lower percentage intensity based on a fixed threshold) to avoid eliciting excessively strong metabolic responses.
Enhanced Recovery of Alginate-like Extracellular Polymers (ALE) from Waste-Activated Sludge Using Sodium Percarbonate: Performance and Characteristics
Authors: Liu Xiaoping , Ren Wanying , Zhai Yunbo , Xie Yu , Liang Fashen , Xu Zhixiang
Published: October 2023

Resource recovery from waste-activated sludge is of great practical significance to achieve sustainable wastewater treatment. Alginate-like extracellular polymers (ALE), a typical class of extracellular polymer substances, are valuable bio-based products with broad application prospects. However, due to the low extraction efficiency of the current method, its practical applications are severely limited. In this study, sodium percarbonate (SPC) was first applied to enhance ALE extraction from conventional activated sludge to replace the sodium carbonate (SC) in the heating-SC method. The results showed that the ALE extracted by the heating-SPC method increased by 30.11% compared to the heating-SC method, and the alginate equivalent was slightly improved. Monosaccharide composition analysis showed that the ALE primarily comprised galactose and glucose, indicating the potential for biomedical applications. The particle size distribution and extracellular polymeric substances (EPS) composition of the sludge indicated that SPC could improve the cracking of the sludge flocs and the organic release. In addition, due to SPC’s ability to oxidize, the molecular composition of the ALE extract changed. In conclusion, SPC used as a substitute for SC in the heating-SC method could be effectively employed to recover ALE from waste-activated sludge. In future studies, further optimization of the operational conditions needs to be considered.
Quantitative Evaluation of Carbon Reduction Policy Based on the Background of Global Climate Change
Authors: Meng Junyan , Xu Wei
Published: October 2023

High-quality carbon reduction policies play a crucial role in tackling global climate change and reducing carbon dioxide emissions. China, as the world’s largest emitter of carbon dioxide, has committed to peaking its carbon emission by 2030. This study focuses on the evaluation of 12 carbon reduction policies implemented by the Chinese government. A quantitative evaluation index system for carbon reduction policies was designed. Next, the policy modeling consistency (PMC) index method was utilized to assess the quality of these policies. The findings are as follows: Firstly, the average PMC index value of the 12 carbon reduction policies is 6.75, indicating a good performance overall. Secondly, the carbon reduction policies established by the Chinese government are generally effective; among the twelve policies analyzed, one policy received a perfect evaluation grade, four policies were graded as excellent, six policies were graded as good, and one policy received a bad evaluation grade. Thirdly, the indicators Z3, Z4, Z5, and Z9 in the evaluation index system for carbon reduction policies scored relatively low, suggesting that there are some deficiencies in terms of policy timeliness, issuing institutions, policy tools, and policy evaluation within the 12 policies. Fourthly, this study presents a PMC curved surface diagram to visually illustrate the strengths and weaknesses of the carbon reduction policies. Finally, based on the research findings, recommendations are provided to enhance the quality of carbon reduction policies.
Adaptive Compressive Sensing: An Optimization Method for Pipeline Magnetic Flux Leakage Detection
Authors: Zhang Shuai , Liu Jinhai , Zhang Xin
Published: October 2023

Leakage from a submarine oil pipeline would have a great impact on the environment and ecological balance. Accurate detection of pipeline defects can ensure safety in the transportation of oil resources. The traditional detection optimization algorithm may lead to the absence of effective features. An adaptive compressive sensing image data augmentation method that analyzes the pixel distribution of small defect features has been proposed to solve these issues. On the basis of Focal-EIoU, a new box loss of Focal-GIoU is proposed which is suitable for pipeline defect detection. Furthermore, the incorporation of bi-level routing attention diminishes the reliance of Yolov5 on specific inputs effectively, thereby enhancing the generalization ability of the detection model. Comparative experiments show that compared with the conventional Yolov5 model, this method improves mAP50 and mAP50:95 by 6.4% and 15.1%, respectively, with mAP50 reaching 91.5% and mAP50:95 reaching 52.9%.
Effects of Chlortetracycline on the Growth of Eggplant and Associated Rhizosphere Bacterial Communities
Authors: Li Lingling , Xue Yuanyuan , Wang Hengsheng , Chen Yansong
Published: October 2023

The widespread use of tetracycline antibiotics in the poultry and cattle sectors endangers both human health and the terrestrial ecosystem. Chlortetracyclines (CTCs), in particular, have been proven to affect soil microorganisms in addition to plants in the terrestrial ecosystem. In order to assess the effects of CTC on soil properties, eggplant growth, and soil microorganisms, a potted experiment was carried out in this study. CTC significantly reduced the levels of ammonium nitrogen (NH4+–N) and nitrite nitrogen (NO2−–N) in soil. Meanwhile, the eggplant’s growth was clearly hampered. CTC dramatically and dose-dependently lowered the fluorescence parameters except the quantum yield of non-regulated energy dissipation (ΦNO). Rhodoplanes and Cupriavidus, which were involved in N cycle, were enriched by 10 mg/kg CTC, according to results about different microorganisms at the genus level. Flavisolibacter was reduced by 10 and 50 mg/kg CTC, while Methylosinus and Actinocorallia were enriched by 250 mg/kg CTC. Redundancy analysis highlighted the profound impact of CTC on the soil microbial community, where strong correlations were observed with soil potential of hydrogen (pH), nitrate nitrogen (NO3−–N), and NO2−–N. These findings demonstrated the interdependence between the microbial community and soil characteristics, with CTC primarily affecting the microbes responsible for nitrogen cycling. Consequently, chlortetracycline poses potential hazards to both eggplant plants and the soil microbes in eggplant cultivation soil.
Synthesis and Basic Properties of Y1−xYbxVO4 Obtained by High-Energy Ball Milling and High-Temperature Treatment
Authors: Piz Mateusz , Filipek Elżbieta , Klukowski Daniel , Kochmański Paweł
Published: October 2023

The main objective of this work was to experimentally confirm that a continuous, substitutional solid solution of a general formula Y1−xYbxVO4 is formed in the pseudo-binary system YVO4–YbVO4, and to investigate its basic unknown properties as a function of composition for 0.00 < x < 1.00. To date, such a solid solution has been obtained and characterized to a limited extent, but only for a few selected compositions. This solution was obtained by a high temperature and, for the first time, using mechanochemical methods. For the solution obtained by the high-energy ball-milling method, unknown physicochemical properties were established over its entire range of homogeneity. The solution was synthesized from mixtures of yttrium orthovanadate (V) with ytterbium (III) orthovanadate (V) of different compositions and investigated by XRD, IR, SEM, and UV-Vis(DRS) methods. It was found that Y1−xYbxVO4 crystallizes in a tetragonal system. The results confirmed that the solid solution Y1−xYbxVO4 has a structure of YVO4 and YbVO4, and its structure is composed of YbO6 and YO6 octahedrons and VO4 tetrahedrons. Moreover, if the parameter (x) in the solid solution Y1−xYbxVO4 increases, its crystalline lattice contracts and the value of the energy gap decreases. This solid solution is stable in the air atmosphere at least up to ~1500 °C. The estimated band gap for this solid solution indicates that it belongs to the semiconductors.
Phosphorus Sorption by Purple Soils in Relation to Their Properties: Investigation, Characterization, and Explanation
Authors: Tan Bo , Barrow N. J. , Li Longguo , Zhou Ping , Zhuang Wenhua
Published: October 2023

Improved soil phosphorus (P) management can be achieved through an understanding of regional soil–P interactions and their relation to soil properties. To this end, soil samples from different use types (paddy soils, dry farmland soils, forest soils, and urban green land soils) were collected from 10 sites across the west to the east of Sichuan Basin, China. These samples were analyzed to determine their P sorption properties and physical and chemical compositions. P sorption was described using a modified Freundlich equation. The results demonstrated a gradient in P sorption within the basin, characterized by higher values in urban areas and a west-to-east decrease trend, along with the null-point values of soil sorption–desorption equilibrium. This variation was linked to the extensive use of P fertilizer, which altered soil particle surface conditions and significantly reduced both the quantity and rate of subsequent fertilizer sorption. Furthermore, P sorption was found to be correlated with the soil clay fraction, amorphous aluminum oxides, and soil organic matter contents. Urban expansion and accelerated erosion of productive agricultural land increase mean soil particle size and may decrease soil P holding and retention capacity. As preliminary deterioration in soil properties was found, conservative soil management is needed to address the potential threats of soil degradation in the central Sichuan Basin.
High-Value Utilization of Corn Straw: From Waste to Wealth
Authors: Fu Yanli , Zhang Jie , Guan Tianzhu
Published: October 2023

As a renewable lignocellulosic biomass resource, corn straw has great potential for waste utilization in agriculture and sustainable development. In recent years, considerable attention has been given to the research on repurposing organic acids, saccharides, and other active substances extracted from corn straw. This review is focused on the progress in the preparative techniques and product development of organic acids and saccharides, realizing the high-value utilization of corn straw. This review also discusses the potential applications of corn straw in the food and biopharmaceutical industries, and sheds light on the current challenges and future directions in the efficient utilization of straw resources.
Probabilistic Risk Assessment of Exposure to Fluoride in Drinking Water in Victoria de Durango, Mexico
Authors: García-Montiel Emily , Zepeda-Mondragón Francisco , Morones-Esquivel Miriam M. , Ramírez-Aldaba Hugo , López-Serrano Pablito M. , Briseño-Reyes Jaime , Montiel-Antuna Eusebio
Published: October 2023

In Mexico, it is estimated that millions of people are affected by the presence of fluoride in groundwater. In wells in the Guadiana Valley in Durango, Mexico, the presence of fluoride has been identified, exceeding the maximum allowable limit established by Mexican regulations (1.5 mg/L). The main purpose of this study was to evaluate the non-carcinogenic risk to the health of the adult population due to fluoride contamination of water, using a Monte Carlo simulation. To this end, the wells were monitored, fluoride concentrations were analyzed according to Mexican regulations and possible concentrations in the vicinity of the sampling zones were determined by applying the ordinary Kriging geospatial tool. Crystal Ball software was used for the simulation, also using data collected through surveys. In terms of dental fluorosis, around 30% of the population mentioned through surveys as having some characteristic of this disease. Of the 70 wells and 2 tanks that were sampled, 90% of them were found to exceed the levels allowed by the regulations. In more than 70% of the wells, the adult population had a non-cancer hazard quotient (HQ) greater than 1. Overall, the HQ for ingestion exceeded 1.8 at the 95th percentile, indicating a significant risk of fluoride-related health problems for the population.
Harnessing Systems Science and Co-Creation Techniques to Develop a Theory of Change towards Sustainable Transport
Authors: Corr Caitriona , Murphy Niamh , Lambe Barry
Published: October 2023

Integrated transport and land-use planning and reduced car dependency proffers a pathway to mobility justice and reduced transport poverty, whilst providing opportunities for potential health benefits and reducing carbon emissions. In spite of this, smaller cities and towns face opposition to the reallocation of road space away from the private car. Traditionally, transport measures have been responsive to growing car-use. To accelerate a behavioural shift to sustainable modes, an evidence-based, transformative approach is required that is consultative in nature, and inclusive of all relevant stakeholders and nurtures innovation. The study aims to achieve this by co-creating a theory of change, with a broad group of stakeholders and the community. Systems science and co-creation techniques were utilised to enable informed decision-making and foster shared learning, resulting in a theory of change formulated by stakeholders with a shared vision. Sixteen objectives were identified under five broad categories, create sustainable systems; design healthy built environments; engage society; empower people and prioritise road safety, informed by the systems-based framework Global Action Plan on Physical Activity. Assumptions, risks and key performance indicators were key elements of the theory of change. Risks identified for successful implementation of the plan were lack of funding and human resources to deliver actions, political challenges, lengthy planning processes, entrenched social norms and resistance from the community. This process, which was adopted, synthesises scientific evidence, a participatory systems approach, informed decision making and the practical application of the embedded researcher, resulting in a pragmatic theory of change to reduce car-dependency and create a shift to sustainable travel modes. The process highlights the importance of stakeholder and community engagement, from participatory mapping of the system to the development of the theory of change to generate local solutions to identified challenges. The resulting theory of change will form the basis of a Sustainable Urban Mobility Plan for Kilkenny City. The theory of change can be adapted to new settings by the participatory processes outlined.
The Sequential Extraction of Municipal Solid Waste Incineration Bottom Ash: Heavy Metals Mobility and Sustainable Application of Ashes
Authors: He Yingzun , Kasina Monika
Published: October 2023

This manuscript focuses on the sustainable utilization of municipal waste incineration ashes in construction, taking into account their substantial concentration of beneficial elements and the potential environmental pollution caused by the leaching of toxic elements due to naturally occurring processes. To assess heavy metal mobility in ashes, a sequential extraction method based on the European Community Bureau of Reference (BCR) was applied. It enables the determination of heavy metal fractions and provides valuable insights into their potential environmental impact and bioavailability. More than 80% of Cd, and Zn, and over 75% of Cu, exhibited strong associations with the most mobile exchangeable fraction, while over 60% of Al and Fe were predominantly bound to reducible. The distribution of As and Cr was relatively balanced between exchangeable and oxidizable fractions, whereas 100% of Pb was exclusively associated with oxidizable fractions, indicating immobilization of this element in the ash. The calculated Risk Assessment Codes and Individual Contamination Factors indicated a quite high to very high risk level for the element’s mobility and environmental contamination. For elements like Pb, Cd, Cu, and Zn, higher concentrations in the samples are associated with higher overall environmental risk. For elements like As and Cr, higher concentrations in the samples are associated with lower overall environmental risk. Studied ash exhibits potential as a resource, but equally it demands rigorous environmental management to ensure responsible utilization. The observed metal mobilization underscores the necessity for stringent containment and treatment measures to mitigate the risk of environmental contamination.