bluuebunny/crossref_metadata_2025 huggingface dataset:
A Genome-Wide Alternative Splicing Analysis of Gossypium arboreum and Gossypium raimondii During Fiber Development
Authors: Hao Jianfeng , Wen Xingpeng , Zhu Yuxian
Published: October 2024

Alternative splicing (AS) is a crucial post-transcriptional regulatory mechanism that contributes to proteome complexity and versatility in different plant species. However, detailed AS exploration in diploid cotton during fiber development has not been reported. In this study, we comparatively analyzed G. arboreum and G. raimondii AS events during fiber development using transcriptome data and identified 9690 and 7617 AS events that were distributed in 6483 and 4859 genes, respectively. G. arboreum had more AS genes and AS events than G. raimondii, and most AS genes were distributed at both ends of all 13 chromosomes in both diploid cotton species. Four major AS types, including IR, SE, A3SS, and A5SS, were all experimentally validated through RT-PCR assays. G. arboreum and G. raimondii had only 1888 AS genes in common, accounting for one-third and one-half of the total number of AS genes, respectively. Furthermore, we found a lysine-specific demethylase coding gene with a different AS mechanism in G. arboreum and G. raimondii, in which AS isoforms lacked part of a key conserved domain. Our findings may provide new directions for the discovery of functional genes involved in cotton species differentiation.
A Novel Plasma-Enhanced Solvolysis as Alternative for Recycling Composites
Authors: Marinis Dimitrios , Markatos Dionysios , Farsari Ergina , Amanatides Eleftherios , Mataras Dimitrios , Pantelakis Spiros
Published: October 2024

In this work, a plasma-assisted solvolysis method is proposed as an alternative method for the oxidative degradation of carbon fiber-reinforced composites (CFRCs). Nitrogen plasma ignition within bubbles in a concentrated nitric acid solution is employed, combining the synergistic effects of traditional nitric acid solvolysis and plasma chemistry. A comprehensive process flowchart, including steps such as composite pretreatment, matrix dissolution, fiber recovery and cleaning, solvent regeneration and reuse, and waste treatment, is also discussed, highlighting their importance in process effectiveness. Moreover, a study on the effect of the composite’s mass on the plasma-enhanced solvolysis process is conducted, and the results are exploited for the calculation of critical parameters such as efficiency, recovery rates, capacity, fibers quality, energy consumption, consumption of raw materials, operational and installation costs, and environmental impact. A preliminary comparison to other recycling methods based on the literature findings is also attempted, and preliminary metrics to assess the sustainability of the recycling process are proposed.
Advances in the Application of Sulfonated Poly(Ether Ether Ketone) (SPEEK) and Its Organic Composite Membranes for Proton Exchange Membrane Fuel Cells (PEMFCs)
Authors: Li Xiang , Ye Tengling , Meng Xuan , He Dongqing , Li Lu , Song Kai , Jiang Jinhai , Sun Chuanyu
Published: October 2024

This review discusses the progress of research on sulfonated poly(ether ether ketone) (SPEEK) and its composite membranes in proton exchange membrane fuel cells (PEMFCs). SPEEK is a promising material for replacing traditional perfluorosulfonic acid membranes due to its excellent thermal stability, mechanical property, and tunable proton conductivity. By adjusting the degree of sulfonation (DS) of SPEEK, the hydrophilicity and proton conductivity of the membrane can be controlled, while also balancing its mechanical, thermal, and chemical stability. Researchers have developed various composite membranes by combining SPEEK with a range of organic and inorganic materials, such as polybenzimidazole (PBI), fluoropolymers, and silica, to enhance the mechanical, chemical, and thermal stability of the membranes, while reducing fuel permeability and improving the overall performance of the fuel cell. Despite the significant potential of SPEEK and its composite membranes in PEMFCs, there are still challenges and room for improvement, including proton conductivity, chemical stability, cost-effectiveness, and environmental impact assessments.
Sustainable Drilling Fluids: A Review of Nano-Additives for Improved Performance and Reduced Environmental Impact
Authors: Asad Maaly Salah , Jaafar Mohammed Thamer , Rashid Farhan Lafta , Togun Hussein , Rasheed Musaab K. , Al-Obaidi Mudhar A. , Al-Amir Qusay Rasheed , Mohammed Hayder I. , Sarris Ioannis E.
Published: October 2024

The implication of nano-additives in drilling fluids introduces a promising avenue for enhancing sustainability in the oil and gas industry. By upgrading the properties of drilling fluids, nano-additives can contribute to mitigating the drilling costs, improving wellbore stability, and minimizing the environmental impact. For example, the use of nano-additives can diminish the amount of drilling fluid required, thus reducing the volume of waste generated. Also, nano-additives can enhance the efficacy of drilling operations, leading to reduced energy consumption and greenhouse gas emissions. This review researches the potential of nano-additives in enhancing sustainable drilling practices, emphasizing the environmental advantages and economic advantages associated with their usage. Specifically, this comprehensive review will elucidate the most recent developments in drilling fluids by evaluating the impact of nano-additives. Referring to the conclusions, adding nanoparticles to drilling fluids significantly improves their characteristics. At 0.2 parts per billion (ppb), for example, the yield stress increases by 36% and the plastic viscosity increases by 17%. In addition, the inclusion of nanoparticles at a concentration of 0.6 ppb led to a significant decrease of 60% in the loss of filtrate. The measured enhancements highlight the capacity of nano-additives to augment the properties of drilling fluid, necessitating additional investigation into their prospective applications for enhancing competitiveness in the gas and oil industry. This study methodically examines the effects of these breakthroughs on scientific, commercial, and industrial sectors. It intends to provide an inclusive understanding of the possible advantages of nano-additives in drilling operations.
Intelligent Lost Circulation Monitoring Method Based on Data Augmentation and Temporal Models
Authors: Zhou Detao , Zhou Chenzhan , Zhang Ziyue , Zhou Mengmeng , Zhang Chengkai , Zhu Lin , Li Qihao , Wang Chaochen
Published: October 2024

Deep and offshore drilling operations face complex geological formations, uncertain formation pressures, and narrow safety density windows, making them susceptible to lost circulation risks. To address these challenges, this paper introduces an innovative, intelligent lost circulation monitoring model that incorporates geological lithology information. This model not only utilizes real-time drilling parameters, but also encodes geological information such as rock type as inputs to the model. By combining these key lithological features, the model can comprehensively assess wellbore stability and reduce the lost circulation risks. In this paper, the Conditional Tabular Generative adversarial network (CTGAN) model is used to enhance the data of small-sample risk data, which can effectively expand the data distribution space and improve the performance of the model. This paper conducts a comparative analysis of intelligent monitoring results using artificial neural networks (ANNs), long short-term memory (LSTM), and temporal convolutional networks (TCNs). The results show that the TCN achieves an identification accuracy of 93.7%. Furthermore, the analysis reveals that the inclusion of lithology information significantly enhances the model’s performance, resulting in a 7.1% increase in accuracy. The false alarm rate of the model can be reduced by 10.2%, considering the fluctuation of the logging curve caused by the on/off condition of the pump. This indicates that the introduction of lithology information and the condition of the pump on−off provide advantages in monitoring and identifying lost circulation risks, enabling a more precise assessment of wellbore stability and a reduction in lost circulation incidents. The method of lost circulation monitoring proposed in this paper provides an important safety guarantee for the oil drilling industry.
A Predictive Model for Sintering Ignition Temperature Based on a CNN-LSTM Neural Network with an Attention Mechanism
Authors: Xiong Da-Lin , Ning Hou-Yin , Xie Meng , Pan Cong-Yuan , Chen Liang-Jun , Yu Zheng-Wei , Long Hong-Ming
Published: October 2024

The sintering ignition process parameters fluctuate frequently and significantly, resulting in large variations in ignition temperature, which in severe cases can exceed 200 °C. This not only increases gas consumption but also affects the quality of the sinter. Because the intelligent control model based on feedback mechanisms struggles to deal with high-frequency fluctuation conditions over time, the prediction of sintering ignition temperature using feedforward regulation is attracting increasing attention. Given the multi-variable, time-sequential and strongly coupled characteristics of the sintering ignition process, a convolutional neural network (CNN) and a long short-term memory (LSTM) network are deeply integrated, with an attention mechanism incorporated to develop the sintering ignition temperature prediction model, enabling the accurate prediction of the ignition temperature. The research demonstrates that the combination of a CNN and the attention mechanism effectively addresses the challenges posed by the multi-variable and strongly coupled nature of sintering ignition data to predictive modeling. The LSTM network resolves the sequential data issues through its gating mechanism. As a result, the coefficient of determination (R2 ) of the CNN_LSTM-Attention model in predicting the sintering ignition temperature can reach 0.97, with a mean absolute error (MAE) as low as 10.23 °C. The predicted values closely match the actual values, achieving a hit rate of 93% within the acceptable error range. These performance metrics are significantly superior to those of the CNN-Attention and LSTM-Attention models, greatly enhancing the control accuracy of the ignition temperature.
Doing Violence to Darwin: Conflicting Christian Evaluations of Darwinism and Violence
Authors: Cross Malcolm L.
Published: October 2024

At issue is the degree to which Charles Darwin’s theory of evolution by means of natural selection is to blame for violence caused by communism, Nazism, and other societal dysfunctions. Conservative Christian opponents claim Darwinism undermines Biblical authority and supports ideologies causing violence. Secular and Christian supporters of Darwinism argue that Darwinism has not promoted violence but has been used to provide a scientific rationale for violence that would have been caused anyway. Moreover, Christian supporters of Darwinism maintain that Darwinism is by no means incompatible with the Bible. This paper examines claims by both sides as well as the attempts by Darwinism’s Christian opponents to supplant Darwinism with theories which they hope will restore Biblical authority, including Creationism, Creation Science, and Intelligent Design theory. The paper concludes that despite the legal setbacks encountered by adherents to these alternative theories, the conflict continues.
A Scoping Review: Risk of Autism in Children Born from Assisted Reproductive Technology
Authors: Muller Kelly , Carballo Amelie , Vega Karina , Talyn Becky
Published: October 2024

Background/Objectives: As the incidence of autism spectrum disorder (ASD) and use of assisted reproductive technologies (ART) continue to rise in tandem, their relationship to one another, as well as the general risks of ART, are increasingly being explored. The purpose of this review is to summarize the literature on ASD risk, as well as the risks for other neurological and neurodevelopmental disorders, in children born following the implementation of ART. Methods: Here we review studies published between 2000−2023 that elucidate relationships between ASD and some of the most common forms of ART, including in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), using fresh vs. frozen embryo transfer. Articles were identified by searching Google Scholar and PubMed databases. Results: Though some studies report adverse neurodevelopmental outcomes in ART-conceived children, such as ASD, attention-deficit/hyperactivity disorder (ADHD), and cerebral palsy, a majority of studies do not show a significant association between ART and neurodevelopmental disorders. Additionally, many confounding factors like multiple and preterm births, underlying infertility, and advanced parental age have been discussed, highlighting the need for studies that effectively control for these confounders. Potential mechanisms implicated in the pathogenesis of ASD, including epigenetic mechanisms of gene expression, that may be related to ART procedures, are also discussed. Conclusion: ART may pose a low additional risk to development of ASD, but confounding factors likely account for most of this risk. Several steps in the process of ART may cause epigenetic changes that are implicated in the development of ASD.
A Remote-Sensing-Based Method Using Rockfall Inventories for Hazard Mapping at the Community Scale in the Arequipa Region of Peru
Authors: Grady Cassidy L. , Santi Paul M. , Walton Gabriel , Luza Carlos , Salas Guido , Meza Pablo , Riega Segundo Percy Colque
Published: October 2024

Small communities in the Arequipa region of Peru are susceptible to rockfall hazards, which impact their lives and livelihoods. To mitigate rockfall hazards, it is first necessary to understand their locations and characteristics, which can be compiled into an inventory used in the creation of rockfall hazard rating maps. However, the only rockfall inventory available for Arequipa contains limited data of large, discrete events, which is insufficient for characterizing rockfall hazards at the community scale. A more comprehensive inventory would result in a more accurate rockfall hazard rating map—a significant resource for hazard mitigation and development planning. This study addresses this need through a remote method for rockfall hazard characterization at a community scale. Three communities located in geographically diverse areas of Arequipa were chosen for hazard inventory and characterization, with a fourth being used for validation of the method. Rockfall inventories of source zones and rockfall locations were developed using high-resolution aerial imagery, followed by field confirmation, and then predictions of runout distances using empirical models. These models closely matched the actual runout distance distribution, with all three sites having an R2 value of 0.98 or above. A semi-automated method using a GIS-based model was developed that characterizes the generation and transport of rockfall. The generation component criteria consisted of source zone height, slope angle, and rockmass structural condition. Transport was characterized by rockfall runout distance, estimated rockfall trajectory paths, and hazard ratings of corresponding source zones. The representative runout distance inventory model of the validation site matched that of a nearby site with an R2 of 0.98, despite inventorying less than a third of the number of rockfalls. This methodology improves upon current approaches and could be tested in other regions with similar climatic and geomorphic settings. These maps and methodology could be used by local and regional government agencies to warn residents of rockfall hazards, inform zoning regulations, and prioritize mitigation efforts.
A New NDSA (Normalized Differential Spectral Attenuation) Measurement Campaign for Estimating Water Vapor along a Radio Link
Authors: Facheris Luca , Cuccoli Fabrizio , Cortesi Ugo , del Bianco Samuele , Gai Marco , Macelloni Giovanni , Montomoli Francesco
Published: October 2024

The Normalized Differential Spectral Attenuation (NDSA) technique was proposed years ago as an active method for measuring integrated water vapor (IWV) along a Ku/K-band radio link immersed (totally or partially) in the troposphere. The approach is of the active kind, as it relies on the transmission of a couple of sinusoidal signals, whose power is measured at the receiver, thus providing the differential attenuation measurements from which IWV estimates can be in turn derived. In 2018, a prototype instrument providing such differential attenuation measurements was completed and set up for a first measurement campaign aimed at demonstrating the NDSA method. By the end of June 2022, the instrument was profoundly modified and upgraded so that a second measurement campaign could be carried out from 1 August to 30 November 2022. The transmitter was placed on the top of Monte Gomito (44.1277°lat, 10.6434°lon, 1892 m a.s.l.) and the receiver on the roof of the Department of Information Engineering of the University of Florence (43.7985°lat, 11.2528°lon, 50 m a.s.l.). The resulting radio link length was 61.15 km. Four ground weather stations of the regional weather service were selected among those available. In this paper, we describe the upgraded instrument and present the outcomes of the new measurement campaign, whose purpose was mainly to compare the IWV estimates provided by the instrument with the ground sensor measurements of air temperature, air humidity, barometric pressure, and rainfall. In particular, we show that the temporal trends of the two IWV estimates are qualitatively consistent, and that the instrument is able to provide IWV estimates also in the presence of fog and rainfall. Conversely, a quantitative evaluation through comparison with IWV data from point weather station measurements appears challenging due to the significant spatial variability in temperature and relative humidity, even between couples of stations that are quite close to each other.
Analyzing Temporal Characteristics of Winter Catch Crops Using Sentinel-1 Time Series
Authors: Selvaraj Shanmugapriya , Bargiel Damian , Htitiou Abdelaziz , Gerighausen Heike
Published: October 2024

Catch crops are intermediate crops sown between two main crop cycles. Their adoption into the cropping system has increased considerably in the last years due to its numerous benefits, in particular its potential in carbon fixation and preventing nitrogen leaching during winter. The growth period of catch crops in Germany is often marked by dense cloud cover, which limits land surface monitoring through optical remote sensing. In such conditions, synthetic aperture radar (SAR) emerges as a viable option. Despite the known advantages of SAR, the understanding of temporal behavior of radar parameters in relation to catch crops remains largely unexplored. Hence, in this study, we exploited the dense time series of Sentinel-1 data within the Copernicus Space Component to study the temporal characteristics of catch crops over a test site in the center of Germany. Radar parameters such as VV, VH, VH/VV backscatter, dpRVI (dual-pol Radar Vegetation Index) and VV coherence were extracted, and temporal profiles were interpreted for catch crops and preceding main crops along with in situ, temperature, and precipitation data. Additionally, we examined the temporal profiles of winter main crops (winter oilseed rape and winter cereals), that are grown parallel to the catch crop growing cycle. Based on the analyzed temporal patterns, we defined 22 descriptive features from VV, VH, VH/VV and dpRVI, which are specific to catch crop identification. Then, we conducted a Kruskal–Wallis test on the extracted parameters, both crop-wise and group-wise, to assess the significance of statistical differences among different catch crop groups. Our results reveal that there exists a unique temporal pattern for catch crops compared to main crops, and each of these extracted parameters possess a different sensitivity to catch crops. Parameters VV and VH are sensitive to phenological stages and crop structure. On the other hand, VH/VV and dpRVI were found to be highly sensitive to crop biomass. Coherence can be used to detect the sowing and harvest events. The preceding main crop analysis reveals that winter wheat and winter barley are the two dominant main crops grown before catch crops. Moreover, winter main crops (winter oilseed rape, winter cereals) cultivated during the catch crop cycle can be distinguished by exploiting the observed sowing window differences. The extracted descriptive features provide information about sowing, harvest, vigor, biomass, and early/late die-off nature specific to catch crop types. In the Kruskal–Wallis test, the observed high H-statistic and low p-value in several predictors indicates significant variability at 0.001 level. Furthermore, Dunn’s post hoc test among catch crop group pairs highlights the substantial differences between cold-sensitive and legume groups (p < 0.001).
Remote Sensing Mapping and Analysis of Spatiotemporal Patterns of Land Use and Cover Change in the Helong Region of the Loess Plateau Region (1986–2020)
Authors: Li Jingyu , Chen Yangbo , Gu Yu , Wang Meiying , Zhao Yanjun
Published: October 2024

Land use and cover change (LUCC) is directly linked to the sustainability of ecosystems and the long-term well-being of human society. The Helong Region in the Loess Plateau has become one of the areas most severely affected by soil and water erosion in China due to its unique geographical location and ecological environment. The long-term construction of terraces and orchards is one of the important measures for this region to combat soil erosion. Despite the important role that terraces and orchards play in this region, current studies on their extraction and understanding remain limited. For this reason, this study designed a land use classification system, including terraces and orchards, to reveal the patterns of LUCC and the effectiveness of ecological restoration projects in the area. Based on this system, this study utilized the Random Forest classification algorithm to create an annual land use and cover (LUC) dataset for the Helong Region that covers eight periods from 1986 to 2020, with a spatial resolution of 30 m. The validation results showed that the maps achieved an average overall accuracy of 87.54% and an average Kappa coefficient of 76.94%. This demonstrates the feasibility of the proposed design and land coverage mapping method in the study area. This study found that, from 1986 to 2020, there was a continuous increase in forest and grassland areas, a significant reduction in cropland and bare land areas, and a notable rise in impervious surface areas. We emphasized that the continuous growth of terraces and orchards was an important LUCC trend in the region. This growth was primarily attributed to the conversion of grasslands, croplands, and forests. This transformation not only reduced soil erosion but also enhanced economic efficiency. The products and insights provided in this study help us better understand the complexities of ecological recovery and land management.
Research on Digital Twin Method for Spaceborne Along-Track Interferometric Synthetic Aperture Radar Velocity Inversion of Ocean Surface Currents
Authors: Min Zhou , Yan He , Jiang Xinrui , Chen Xin , Zhou Junyi , Zhu Daiyin
Published: October 2024

In this paper, an end-to-end system framework is proposed for the Digital Twin study of spaceborne ATI-SAR ocean current velocity inversion. Within this framework, a fitting inversion approach is proposed to enhance the conventional spaceborne ATI-SAR ocean current velocity inversion algorithm. Consequently, the issue of possible local inversion errors stemming from the mismatch between the traditional spaceborne ATI-SAR inversion algorithm and various dual-antenna configurations is resolved to a certain extent. A simulated spaceborne ATI-SAR system, featuring a dual-antenna configuration comprising a baseline direction perpendicular to the track and a squint angle, is presented to validate the efficacy of the Digital Twin methodology. Under the specified simulation parameters, the average inversion error for the final ocean current velocity is recorded at 0.0084 m/s, showcasing a reduction of 0.0401 m/s compared with the average inversion error prior to optimization.
Galileo and BeiDou AltBOC Signals and Their Perspectives for Ionospheric TEC Studies
Authors: Chen Chuanfu , Pavlov Ilya , Padokhin Artem , Yasyukevich Yury , Demyanov Vladislav , Danilchuk Ekaterina , Vesnin Artem
Published: October 2024

For decades, GNSS code measurements were much noisier than phase ones, limiting their applicability to ionospheric total electron content (TEC) studies. Ultra-wideband AltBOC signals changed the situation. This study revisits the Galileo E5 and BeiDou B2 AltBOC signals and their potential applications in TEC estimation. We found that TEC noises are comparable for the single-frequency AltBOC phase-code combination and those of the dual-frequency legacy BPSK/QPSK phase combination, while single-frequency BPSK/QPSK TEC noises are much higher. A two-week high-rate measurement campaign at the ACRG receiver revealed a mean 100 sec TEC RMS (used as the noise proxy) of 0.26 TECU, 0.15 TECU, and 0.09 TECU for the BeiDou B2(a+b) AltBOC signal and satellite elevations 0–30°, 30–60°, and 60–90°, correspondingly, and 0.22 TECU, 0.14 TECU, and 0.09 TECU for the legacy B1/B3 dual-frequency phase combination. The Galileo E5(a+b) AltBOC signal corresponding values were 0.25 TECU, 0.14 TECU, and 0.09 TECU; for the legacy signals’ phase combination, the values were 0.19 TECU, 0.13 TECU, and 0.08 TECU. The AltBOC (for both BeiDou and Galileo) SNR exceeds those of BPSK/QPSK by 7.5 dB-Hz in undisturbed conditions. Radio frequency interference (the 28 August 2022 and 9 May 2024 Solar Radio Burst events in our study) decreased the AltBOC SNR 5 dB-Hz more against QPSK SNR, but, due to the higher initial SNR, the threshold for the loss of the lock was never broken. Today, we have enough BeiDou and Galileo satellites that transmit AltBOC signals for a reliable single-frequency vTEC estimation. This study provides new insights and evidence for using Galileo and BeiDou AltBOC signals in high-precision ionospheric monitoring.
Energy-Efficient Adaptive Bidirectional Transmission Strategy in Simultaneous Wireless Information and Power Transfer (SWIPT)-Enabled Cognitive Relay Network
Authors: Cai Caixia , Zhang Jiayao , Zhong Fuli , Hai Han
Published: October 2024

Introducing collaborative relay and simultaneous wireless information and power transfer (SWIPT) techniques into a cognitive wireless network, named the SWIPT-enabled cognitive relay network (CRN), is considered a promising approach to deal with insufficiency and the low utilization of spectrum resources, as well as the node’s energy-constrained issues in wireless networks. In this paper, to improve the network spectrum efficiency (SE) and energy efficiency (EE) of the SWIPT-enabled CRN, we design an energy-efficient adaptive bidirectional transmission strategy. To be specific, we first select an energy-constrained best relay node with the consideration of signal-to-noise ratio and global channel gain to achieve a better bidirectional relay transmission (BRT). At the same time, we let the energy-constrained best relay node transmit a signal with the SWIPT technique, which can solve the node’s energy-constrained issue and improve the network EE. Then, with the selected energy-constrained best relay node, we design a total transmit power threshold (TTPT) determining algorithm to find the TTPT, which lets the total transmission rate of the BRT be equal to the bidirectional direct transmission (BDT). Based on this TTPT, we further design an adaptive bidirectional transmission strategy and let the network achieve adaptive transmission between the BRT and BDT to obtain a higher network SE. Furthermore, to further achieve the energy-efficient transmission of the adaptive bidirectional transmission strategy, we optimize the nodes’ power under the requirement of primary users’ interference threshold and obtain the analytical expressions of the optimal power. Simulation results show that the transmission rate, the outage probability, and the EE of the designed energy-efficient adaptive bidirectional transmission strategy in the SWIPT-enabled CRN are, respectively, 3.01, 0.07, and 3.10 times that of the non-collaborative transmission, which show the effectiveness of our designed transmission strategy.
Comparative Microstructure Characteristics of Synthesized PbS Nanocrystals and Galena
Authors: AlShamaileh Ehab , Lahlouh Bashar , AL-Masri Ahmed N. , Al-Qderat Mariam , Mahmoud Wadah , Alrbaihat Mohammad , Moosa Iessa Sabbe
Published: October 2024

Lead sulfide (PbS) on the nanoscale was synthesized via a chemical route at room temperature using lead nitrate {Pb(NO3)2} and sodium sulfide (Na2S). The Na2S was prepared at ~105 °C using sodium hydroxide (NaOH) and sulfur (S) powder. The produced PbS, denoted as Lab-PbS, was compared with a high-concentration PbS phase of galena. The produced Na2S and Lab-PbS were examined using scanning electron microscopy and energy dispersive X-ray spectroscopy for microstructural and chemical analysis. The results confirmed a high-purity PbS compound (>99%) with a nanoscale particle size. The results showed that ultrasonic agitation was vital for obtaining the nanoparticle size of the Lab-PbS. Furthermore, thin films from the synthesized Lab-PbS and galena were successfully thermally evaporated on glass, quartz, and silicon substrates. The formation of nanometric grains was confirmed by scanning electron microscopy (SEM). XRD and FTIR spectroscopy were carried out for the Lab-PbS, galena fine powders, and galena thin films. The average crystal diameter was calculated for the galena thin films and was found to be approximately 26.6 nm. Moreover, the UV–Visible transmission curve was measured for the thin films in the wavelength range of 200–1100 nm in order to calculate the bandgap energy (Eg) for the thin films. The values of Eg were approximately 2.65 eV and 2.85 eV for the galena and Lab-PbS thin films, respectively. Finally, the sintering of the Lab-PbS and galena powders was carried out at ~700 °C for 1 h under vacuum, achieving relative densities of ~98.1% and ~99.2% for the Lab-PbS and galena, respectively.
Interpretability of Methods for Switch Point Detection in Electronic Dance Music
Authors: Zehren Mickaël , Alunno Marco , Bientinesi Paolo
Published: October 2024

Switch points are a specific kind of cue point that DJs carefully look for when mixing music tracks. As the name says, a switch point is the point in time where the current track in a DJ mix is replaced by the upcoming track. Being able to identify these positions is a first step toward the interpretation and the emulation of DJ mixes. With the aim of automatically detecting switch points, we evaluate one experience-driven and several statistics-driven methods. By comparing the decision process of each method, contrasted by their performance, we deduce the characteristics linked to switch points. Specifically, we identify the most impactful features for their detection, namely, the novelty in the signal energy, the timbre, the number of drum onsets, and the harmony. Furthermore, we expose multiple interactions among these features.
CO-TSM: A Flexible Model for Secure Embedded Device Ownership and Management
Authors: Markantonakis Konstantinos , Arfaoui Ghada , Ghazalah Sarah Abu , Shepherd Carlton , Akram Raja Naeem , Sauveron Damien
Published: October 2024

The Consumer-Oriented Trusted Service Manager (CO-TSM) model has been recognised as a significant advancement in managing applications on Near Field Communication (NFC)-enabled mobile devices and multi-application smart cards. Traditional Trusted Service Manager (TSM) models, while useful, often result in market fragmentation and limit widespread adoption due to their centralised control mechanisms. The CO-TSM model addresses these issues by decentralising management and offering greater flexibility and scalability, making it more adaptable to the evolving needs of embedded systems, particularly in the context of the Internet of Things (IoT) and Radio Frequency Identification (RFID) technologies. This paper provides a comprehensive analysis of the CO-TSM model, highlighting its application in various technological domains such as smart cards, HCE-based NFC mobile phones, TEE-enabled smart home IoT devices, and RFID-based smart supply chains. By evaluating the CO-TSM model’s architecture, implementation challenges, and practical deployment scenarios, this paper demonstrates how CO-TSM can overcome the limitations of traditional TSM approaches. The case studies presented offer practical insights into the model’s adaptability and effectiveness in real-world scenarios. Through this examination, the paper aims to underscore the CO-TSM model’s role in enhancing scalability, flexibility, and user autonomy in secure embedded device management, while also identifying areas for future research and development.
Artificial Neural Networks and Ensemble Learning for Enhanced Liquefaction Prediction in Smart Cities
Authors: Cong Yuxin , Inazumi Shinya
Published: October 2024

This paper examines how smart cities can address land subsidence and liquefaction in the context of rapid urbanization in Japan. Since the 1960s, liquefaction has been an important topic in geotechnical engineering, and extensive efforts have been made to evaluate soil resistance to liquefaction. Currently, there is a lack of machine learning applications in smart cities that specifically target geological hazards. This study aims to develop a high-performance prediction model for estimating the depth of the bearing layer, thereby improving the accuracy of geotechnical investigations. The model was developed using actual survey data from 433 points in Setagaya-ku, Tokyo, by applying two machine learning techniques: artificial neural networks (ANNs) and bagging. The results indicate that machine learning offers significant advantages in predicting the depth of the bearing layer. Furthermore, the prediction performance of ensemble learning improved by about 20% compared to ANNs. Both interdisciplinary approaches contribute to risk prediction and mitigation, thereby promoting sustainable urban development and underscoring the potential of future smart cities.
Low Energy Availability Risk Is Associated with Anxiety in Female Collegiate Athletes
Authors: Scheid Jennifer L. , Basile Sabrina , West Sarah L.
Published: October 2024

This study investigated the association between the risk of low energy availability, disordered eating, and anxiety in collegiate female athletes. Female athletes (n = 115) completed questionnaires that assessed disordered eating (Disordered Eating Screen for Athletes, DESA-6; and the Eating Disorder Examination Questionnaire Short, EDE-QS), anxiety (Generalized Anxiety Disorder-7) and the risk of low energy availability (Low Energy Availability in Females Questionnaire; LEAF-Q). The athletes were 19.9 ± 0.1 years old and presented with no anxiety (14.8%), mild (33.0%), moderate (24.3%), and severe (27.8%) anxiety. The EDE-QS scores revealed that 22.6% of the participants had a high risk of an eating disorder, while the DESA-6 scores revealed that 31.3% of the participants scored positive for a risk of disordered eating. The LEAF-Q total scores revealed that 68.7% of the participants were at risk of low energy availability. Increased GAD-7 scores were associated (p < 0.001) with measures of disordered eating (EDE-QS and DESA-6) and the risk of low energy availability (LEAF-Q total score). Non-parametric partial correlations demonstrated that anxiety (increased GAD-7 scores) correlated with the risk of low energy availability (increased LEAF-Q total scores) while controlling for eating disorder scores (EDE-QS) (r (112) = 0.353, p < 0.001), or while controlling for the risk of disordered eating (DESA-6 scores) (r (112) = 0.349, p < 0.001). In female collegiate athletes, both disordered eating and the risk of low energy availability were positively associated with increased anxiety.
University Students’ Attitudes and Perceptions towards AI Tools: Implications for Sustainable Educational Practices
Authors: Fošner Ajda
Published: October 2024

The integration of artificial intelligence (AI) tools in educational settings offers significant opportunities to promote sustainability by transforming learning experiences. This study analyses the usage, attitudes, and perceptions of AI tools among university students in Slovenia providing a comprehensive analysis that informs both academic practices and policy-making with emphasis on sustainability. We used a structured questionnaire with a sample of 422 participants reflecting a diverse demographic profile across various fields of study. The questionnaire was designed to measure the frequency of AI tool usage, the purposes for which these tools are employed, and students’ attitudes and perceptions towards AI’s potential benefits and drawbacks in education. Statistical analyses, including Analysis of Variance (ANOVA), were utilized to test hypotheses concerning differences in AI tool usage based on the level and field of study. Findings reveal that students recognize the efficiency of AI, but express concerns about its impact on learning quality and academic integrity, emphasizing the need for a balanced and responsible integration of AI in education to achieve sustainable outcomes. Results indicated that a majority of students are engaging with AI tools, with varied frequencies of use largely dependent on their field of study and academic level. The findings suggest that while AI tools are becoming an integral part of the educational landscape in Slovenia, there is a critical need to address the educational, ethical, and psychological impacts of these technologies. The results highlight the necessity for further research into the educational implications of AI, suggesting a balanced and sustainable approach to integrating these technologies into higher education curricula. Such an approach ensures that the adoption of AI not only enhances learning outcomes but also aligns with the principles of sustainability, promoting long-term benefits for both education and society.
Bibliometric Trends and Insights into the Potential of Maize (Zea mays) under the Framework of Conservation Agriculture
Authors: Padhan Smruti Ranjan , Saini Sushmita , Jat Shankar Lal , Rathore Sanjay Singh , Gathala Mahesh Kumar , Radheshyam  , Padhan Soumya Ranjan , El-Hendawy Salah , Mattar Mohamed A.
Published: October 2024

In spite of the detrimental effects of climate change and decreasing resource efficiency, maize farming is essential to the world’s food and nutritional security. With regard to sustainable maize farming in this environment, conservation agriculture (CA) offers a framework that holds promise in terms of low soil disturbance, perennial soil cover, and sustainable crop rotation. In order to acquire more profound information on the research advancements and publication patterns related to maize under CA scenarios, a bibliometric analysis was conducted. This involved utilizing René Descartes’s Discourse Framework to extract and screen 2587 documents spanning the years 2001 to 2023 from the Dimensions.ai database. The mapping showed that different stakeholders were becoming more interested in maize research under various CA pathways, with a greater emphasis on reaching the second sustainable development target, or “zero hunger”. The most influential journals were “Soil and Tillage Research” and “Field Crops Research”, with 131 and 85 papers with 6861 and 6186 citations, respectively. The performance analysis found “Christian L. Thierfelder” and “Mangi Lal Jat” as the eminent researchers in the areas of maize research under CA. Thus, the International Maize and Wheat Improvement Center (CIMMYT) and the Indian Agricultural Research Institute (IARI) were identified as the important institutions in conducting research pertaining to maize under CA systems, while the United States, India, and Mexico emerged as prominent countries with notable collaboration efforts for imparting research under the given scenarios. Three thematic clusters delineating keywords from three distinct sections—key drivers, objectives, and methodology—were identified through co-word analysis using word clouds, tree maps, and thematic networking of the keywords from the abstract and titles of screened publications. These thematic clusters highlighted the growing emphasis on region-specific studies under CA, particularly in sub-Saharan Africa and the Indo-Gangetic plain, to enhance the resilience of the agri-food system. Therefore, mapping maize’s potentialities within the CA framework has revealed the field’s dynamic nature and offers insightful information to researchers and policymakers that could help them plan future studies and cooperative initiatives aimed at boosting the productivity and sustainability of maize-based systems under the CA framework.
Dynamic Interactive Effects of Technological Innovation, Transportation Industry Development, and CO2 Emissions
Authors: An Kaige , Wang Xiaowei , Wang Zhenning , Zhao He , Zhong Yao , Shen Jia , Ren Xiaohong
Published: October 2024

This paper aims to clarify the intricate relationships between technological innovation, transportation industry development, and CO2 emissions to facilitate a positive synergy among technology, the economy, and climate, advancing the fulfillment of the ‘double carbon’ goal. Utilizing panel data from 30 provinces in China from 2005 to 2020, we employ the panel vector autoregressive model using a generalized method of moments to empirically examine the dynamic interactive effects between these participants. The findings reveal that the transportation industry significantly promoted the inhibitory impact of technological innovation on CO2 emissions. However, such reductions cannot counterbalance the rise in emissions from the transportation industry. Moreover, its effects varied significantly across regions. Specifically, transportation industry development within eastern China contributed to a shift in the local carbon emission effects from positive to negative under the positive influence of technological innovation. In the northeast, the transportation industry enhanced the inhibitory effect of technological innovation on CO2 emissions. In contrast, across the western region, industrial development in transportation intensified the role of technological innovation in promoting CO2 emissions. Furthermore, this work found that CO2 emissions notably diminished the CO2 reduction performance of technological innovation in the eastern part and enhanced this performance in the northeastern region. These findings further revealed the complex interplay between technological innovation, the transportation industry, and CO2 emissions. They offer insights for policymakers to tailor region-specific technologies to bolster the ‘dual carbon’ goal and sustainable transportation development strategies, thereby achieving CO2 reduction.
Motivations behind Active Sport Tourists Participating in Natural and Cultural Landscapes
Authors: Guereño-Omil Basagaitz , León-Guereño Patxi , Garro Eunate , Rozmiarek Mateusz , Malchrowicz-Mośko Ewa , Młodzik Maciej , Włodarczyk Arkadiusz , Łuć Bartłomiej
Published: October 2024

Recreational running, both on roads and in mountains, is one of the most practiced physical activities worldwide, and so, the motivations behind participating have been quite extensively described in the literature. However, the cultural and environmental motivations behind these athletes traveling to other countries or destinations to compete have not been properly addressed yet. The aim of this research is to analyze the motivations of sport tourists and to compare the motivations that cause mountain runners and city runners to compete. A cross-sectional study with a total of 244 athletes, divided into a group of city marathon runners (N = 118) and a group of mountain ultra-marathon runners (N = 126), was conducted. Athletes completed the Sports Tourism Motivation Scale (STMS), composed of 37 items and nine dimensions, through an online survey. Participants were asked questions related to their age, running experience, distance to events, numbers of nights in hotels and volunteering. The results showed that there were statistically significant differences in four out of the nine dimensions of the STMS between city and mountain runners’ motivations and, likewise, statistical differences were found in some dimensions of the scale related to participants’ sex, age, running experience, numbers of nights in a hotel, travel distance and volunteering. In conclusion, the reasons why runners participate in mountain and city running events are different; likewise, some sociodemographic variables should be taken into account when organizing such sporting events in a sustainable way, in order to provide organizers with the most suitable information and attract the most participants.
From Financialization to Sustainability: The Impact of Climate Risks on Shadow Banking Activities in Non-Financial Firms in China
Authors: Zhang Qiuyue , Lin Yili , Cao Yu
Published: October 2024

Climate risks are increasingly shaping corporate strategies, raising important considerations for sustainability. This study explores the impact of climate risks on the shadow banking activities of non-financial firms, examining how these risks influence sustainable financial practices. Analyzing a sample of Chinese listed firms from 2010 to 2022, this study finds that climate risks are negatively associated with shadow banking activities, reflecting a shift towards more sustainable financial management. This finding remains robust through various robustness checks and tests for endogeneity. Heterogeneity results indicate that the reduction in shadow activities due to climate risks is more pronounced in firms with higher dependence on external financing and weaker profitability. Mechanism results suggest that climate risks amplify cross-sectional risks for firms, increasing risk sources. Simultaneously, companies enhance their preference for holding cash to address potential risks. The combined effect of these factors leads to a decrease in shadow banking activities among non-financial firms, aligning with a shift towards sustainability. This study provides new insights into understanding how climate risks drive sustainable financial decision-making and enriches the research on the determinants of firm financialization.