bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated Effects of Water and Nitrogen Coupling on Eggplant Productivity, Fruit Quality, and Resource Use Efficiency in a Cold and Arid Environment
Authors: Li Jie , Zhang Hengjia , Zhou Chenli , Teng Anguo , Lei Lian , Ba Yuchun , Yu Jiandong , Li Fuqiang
Published: January 2025

In order to explore the water and fertilizer requirements of eggplants in the western oasis of the river, the experiment was conducted in Minle County of Gansu Province in 2022 and 2023 under three water stress gradients and three nitrogen application levels: (1) moderate water stress (W1, 50–60% in field water capacity [FC]), mild water stress (W2, 60–70% in FC), and full irrigation (W3, 70–80% in FC); (2) low nitrogen (N1, 215 kg·ha−1), medium nitrogen (N2, 270 kg·ha−1), and high nitrogen (N3, 325 kg·ha−1). Moderate and mild water stress were applied during eggplant flowering and fruiting while full irrigation was provided during the other growth stages; a control class (CK) was established with full irrigation throughout the whole plant growth without nitrogen application. This study investigated the effects of water-saving and nitrogen reduction on the yield, quality, and water-nitrogen use efficiency of eggplants in a cold and arid environment in the Hexi Oasis irrigation area of China. Using the EWM-TOPSIS model, we evaluated different water-nitrogen treatments and determined the optimal irrigation-nitrogen application model for eggplants in this region. The results showed that the W2N2 treatment had the highest yield, which was not significantly (p > 0.05) different from the W3N2 treatment while significantly (p < 0.05) 35.06% higher than CK in 2022 and 36.91% higher in 2023. In the W2N2 treatment, the transverse diameter of eggplants, as well as the contents of soluble protein, soluble sugar, soluble solids, and vitamin C, were all the highest. The W2N2 treatment had the maximum water use efficiency and irrigation water use efficiency, which were significantly higher than other water and nitrogen application treatments and CK by 14.79–42.51% in 2022 and 8.79–44.88% in 2023, and 15.86–45.55% in 2022 and 4.68–40.22% in 2023, respectively. By employing the EWM-TOPSIS model for comprehensive evaluation, the results indicated that mild water deficit (60–70% in FC) and moderate nitrogen application (270 kg·ha−1) at flowering and fruiting of eggplants was the optimal water and nitrogen application mode under mulched drip irrigation in the Hexi region of northwest China. The results will provide some theoretical basis for water-saving, productive, high-quality, and high-efficiency cultivation of eggplant in cold and arid environments.
Electric Conductivity Transitions of Water-Absorbable Polybenzimidazole Films
Authors: Watanabe Kaito , Ikeda Junko , Zhong Xianzhu , Zhou Jiabei , Kaneko Tatsuo , Kawai Mika , Mitsumata Tetsu
Published: January 2025

Transitions seen in the electric properties of water-absorbable poly(2,5-benzimidazole) (ABPBI) films were confirmed by electric conductivity, dielectric constant, and time-domain nuclear magnetic resonance (NMR) measurements. The electric resistance of the films was measured at room temperature using a high-resistance meter, and the dielectric constant at room temperature was measured using an LCR meter in the frequency range of 90 Hz to 8 MHz. The water absorption ratio at equilibrium absorption for the films was 37%, which corresponded to a volume fraction of water of 0.33. The electric conductivity of the films without water absorption was ~1014 S·cm−1, and it increased to ~1010 S·cm−1 with increasing volume fraction, showing a percolation threshold at a volume fraction of 0.025, and remarkable transitions at volume fractions of 0.075 and 0.135. The dielectric constant of the films without water absorption was 3.4, and it increased to 8.1 with increasing volume fraction, showing a transition only at a volume fraction of 0.135. Above a volume fraction of 0.075, where a transition in conductivity was observed, there were two relaxation times at 18–31 μs and 20–93 μs, as determined from the time-domain NMR, and these relaxation times increased with increasing volume fraction. The longer relaxation time increased significantly at a volume fraction of 0.072, which was close to the volume fraction of the transition seen in conductivity. The relationship between the chain mobility of ABPBI and the deterioration in electric insulating properties is discussed.
Microbial-Derived Biopolymers: A Pathway to Sustainable Civil Engineering
Authors: Kannan Govindarajan , Sujatha Evangelin Ramani , Almajed Abdullah , Moghal Arif Ali Baig
Published: January 2025

Modern innovations increasingly prioritize eco-friendliness, aiming to pave the way for a sustainable future. The field of civil engineering is no exception to this approach, and, in fact, it is associated with almost every sustainable development goal framed by the United Nations. Therefore, the sector has a pivotal role in achieving these goals. One such innovation is exploring the possibilities of using nature-friendly materials in different applications. Biopolymers are substances that are produced either by the chemical synthesis of natural materials or by the biosynthesizing activities of microorganisms. Microbial-derived biopolymers are known for their non-toxic and nature-friendly characteristics. However, their applications are mostly restricted to the field of biotechnology and not fully explored in civil engineering. This article reviews various microbial-derived biopolymers, focusing on the types available on the market, their source and properties, and more importantly, their wide range of applications in the civil engineering field. Additionally, the article explores the prospects for future research and the potential for the practical implementation of these techniques in the pursuit of a sustainable future.
Decoding the Biobased Blueprint: Key Players and Evolutionary Trends in Materials Innovation
Authors: Sedita Silvia Rita , Di Maria Eleonora , Mazzoni Leonardo , Bekele Negalegn Alemu
Published: January 2025

In the rapidly evolving biobased materials innovation landscape, our research identifies key players and explores the evolutionary perspective of biobased innovation, offering insights into promising research areas to be further developed by biobased material scientists in search of exploiting their knowledge in novel applications. Despite the crucial role of these materials in promoting sustainable production and consumption models, systematic studies on the current innovation terrain are lacking, leaving gaps in understanding key players, emerging technologies, and market trends. To address this void, we focused on examining patents related to biobased monomers and polymers, aiming to describe the innovation strategies and business dynamics of leading assignees. Embedded within the European Sustainable BIO-based nanoMAterials Community (BIOMAC) project, a Horizon 2020 initiative, our research leverages this unique framework dedicated to advancing the innovation landscape, specifically emphasizing the market readiness of biobased materials. We implemented a multi-stage strategy, prioritizing validated keyword queries to ensure the superior quality and reliability of the collected data. To understand primary contributors within these landscapes, we conducted an in-depth analysis of innovation strategies employed by leading companies. Findings from the ORBIT platform highlighted a remarkable increase in patent publications in the past decade, with China standing out as a key hub of innovation, signaling a strong focus on the development of these materials. Our research explores technological advancements in biobased materials to identify specific areas with potential for further development. By analyzing innovation trends in five key industries, we pinpoint opportunities for innovative solutions to be commercially exploited while ensuring compliance with intellectual property rights within a freedom-to-operate framework.
Advancing Energy Recovery: Evaluating Torrefaction Temperature Effects on Food Waste Properties from Fruit and Vegetable Processing
Authors: Škorjanc Andreja , Gruber Sven , Rola Klemen , Goričanec Darko , Urbancl Danijela
Published: January 2025

Most organic waste from food production is still not used for energy production. From the perspective of energy production, one option is to valorise the properties of organic waste. The fruit juice industry is growing rapidly and generates large amounts of waste. One of the main wastes in food and fruit juice processing is peach pits and apple peels. The aim of this study was to analyse the influence of torrefaction temperature on the properties of food waste, namely apple peels, peach pits and pea shells, in order to improve their energy value and determine their potential for further use and valorisation as a renewable energy source. The aim was to analyse the influence of different torrefaction temperatures on the heating value (HHV), mass yield (MY) and energy yield (EY) in order to better understand the behavior of the thermal properties of individual selected samples. The torrefaction process was carried out at temperatures of 250 °C, 350 °C and 450 °C. The obtained biomass was compared with dried biomass. For apple peels, HHV after torrefaction was (28 kJ/kg), MY decreased by (66–34%), while EY fell by (97–83%). Peach pits, despite a higher HHV after torrefaction (18 kJ/kg), achieved low MY (38–89%) and EY (59–99%), which reduces their efficiency in biochar production. Pea peels had EY (82–97%) and a lower HHV after torrefaction (11 kJ/kg), but their high ash content limits their wider use. The results confirm that, with increasing temperature, MY and EY for all selected biomasses decrease, which is a consequence of the degradation of hemicellulose and cellulose and the loss of volatile compounds. In most cases, increasing the torrefaction temperature improved the resistance to moisture adsorption, as this is related to the thermal process that causes structural changes. The results showed that the torrefaction process improved the hydrophobic properties of the biomass samples. Temperature was seen to have a great impact on mass energy efficiency. Apple peels generally had the highest mass and energy yield.
Novel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis
Authors: Wang Fei , Jin Liang , Wang Xue , Cui Baoliang , Yang Yingli , Duggan Lori , Schwartz Sterman Annette , Lloyd Sarah M. , Hazelwood Lisa A. , Chaudhary Neha , Bawa Bhupinder , Phillips Lucy A. , He Yupeng , Tian Yu
Published: January 2025

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by repetitive alveolar injuries with excessive deposition of extracellular matrix (ECM) proteins. A crucial need in understanding IPF pathogenesis is identifying cell types associated with histopathological regions, particularly local fibrosis centers known as fibroblast foci. To address this, we integrated published spatial transcriptomics and single-cell RNA sequencing (scRNA-seq) transcriptomics and adopted the Query method and the Overlap method to determine cell type enrichments in histopathological regions. Distinct fibroblast cell types are highly associated with fibroblast foci, and transitional alveolar type 2 and aberrant KRT5-/KRT17+ (KRT: keratin) epithelial cells are associated with morphologically normal alveoli in human IPF lungs. Furthermore, we employed laser capture microdissection-directed mass spectrometry to profile proteins. By comparing with another published similar dataset, common differentially expressed proteins and enriched pathways related to ECM structure organization and collagen processing were identified in fibroblast foci. Importantly, cell type enrichment results from innovative spatial proteomics and scRNA-seq data integration accord with those from spatial transcriptomics and scRNA-seq data integration, supporting the capability and versatility of the entire approach. In summary, we integrated spatial multi-omics with scRNA-seq data to identify disease-associated cell types and potential targets for novel therapies in IPF intervention. The approach can be further applied to other disease areas characterized by spatial heterogeneity.
Effect of Dy3+ Ions on Structural, Thermal and Spectroscopic Properties of L-Threonine Crystals: A Visible Light-Emitting Material
Authors: Oliveira Neto João G. de , Silva Neto Otávio C. da , Rodrigues Jéssica A. O. , Viana Jailton R. , Steimacher Alysson , Pedrochi Franciana , Sousa Francisco F. de , Santos Adenilson O. dos
Published: January 2025

In this study, L-threonine crystals (L-thr) containing Dy3+ ions (L-thrDy5 and L-thrDy10) with varying mass concentrations (5% and 10%) were successfully synthesized using a solvent slow evaporation method. The structural properties were characterized by Powder X-ray diffraction and Rietveld refinement. The data revealed that all three samples crystallized in orthorhombic symmetry (P212121-space group) and presented four molecules per unit cell (Z = 4). However, the addition of Dy3+ ions induced a dilation effect in the lattice parameters and cell volume of the organic structure. Additionally, the average crystallite size, lattice microstrain, percentage of void centers, and Hirshfeld surface were calculated for the crystals. Thermogravimetric and differential thermal analysis experiments showed that L-thr containing Dy3+ ions are thermally stable up to 214 °C. Fourier transform infrared and Raman spectroscopy results indicated that the Dy3+ ions interact indirectly with the L-thr molecule via hydrogen bonds, slightly affecting the crystalline structure of the amino acid. Optical analysis in the ultraviolet–visible region displayed eight absorption bands associated with the electronic transitions characteristic of Dy3+ ions in samples containing lanthanides. Furthermore, L-thrDy5 and L-thrDy10 crystals, when optically excited at 385 nm, exhibited three photoluminescence bands centered around approximately 554, 575, and 652 nm, corresponding to the 4F7/2 → 6H11/2, 4F9/2 → 6H13/2, and 4F9/2 → 6H11/2 de-excitations. Therefore, this study demonstrated that L-thr crystals containing Dy3+ ions are promising candidates for the development of optical materials due to their favorable physical and chemical properties. Additionally, it is noteworthy that the synthesis of these systems is cost-effective, and the synthesis method used is efficient.
The Missionary-Colonial Forms of Marriages and Sexualities Within African Pentecostalism: A Sankofa-De-Colonial Perspective
Authors: Shingange Themba
Published: January 2025

Looking retrospectively at pre-colonial African marriages and sexualities is critical in the urge to transform the contemporary narratives about marriage and sexuality within African Christian spaces. In Africa, marriage and sexuality had cultural, spiritual, and religious intersectionality. However, the advent of the missionary-colonial enterprise reconstructed the concepts of marriage and sexuality by imposing the supremacy of Christianity and Civilization agendas. Thus, Africans were compelled to discard their views of marriage and sexuality to comply with the prescripts of Christianity, baptism, and church membership. This paper used the Sankofa and Decolonial theories to investigate the perpetual influence of the 19th-century missionary-colonial enterprise within the contemporary African Pentecostal views of marriage and sexuality. It debunked the heterotopias of the born-again experience which propels the supremacy of Christianity and civilization agendas. The findings indicated that these agendas manifest in the form of hetero-monogamous aspirations of missionaries that undermined the African views of marriage and sexuality, thus, rendering them as demonic, backward, barbaric, and something to be forgotten. Lamentably, the same narrative has shaped the views of Pentecostal Christians within the contemporary African context. However, this has created a myriad of problems for both Africans and Christianity in Africa. In conclusion, the study emphasized the need to delink from Western conceptualizations by rethinking African marriages and sexualities. This could be done by revisiting pre-colonial African marriage systems and sexualities to challenge the current distorted narrative while embracing the positive elements of Christianity.
Multi-Scale Long- and Short-Range Structure Aggregation Learning for Low-Illumination Remote Sensing Imagery Enhancement
Authors: Cao Yu , Tian Yuyuan , Su Xiuqin , Xie Meilin , Hao Wei , Wang Haitao , Wang Fan
Published: January 2025

Profiting from the surprising non-linear expressive capacity, deep convolutional neural networks have inspired lots of progress in low illumination (LI) remote sensing image enhancement. The key lies in sufficiently exploiting both the specific long-range (e.g., non-local similarity) and short-range (e.g., local continuity) structures distributed across different scales of each input LI image to build an appropriate deep mapping function from the LI images to their corresponding high-quality counterparts. However, most existing methods can only individually exploit the general long-range or short-range structures shared across most images at a single scale, thus limiting their generalization performance in challenging cases. We propose a multi-scale long–short range structure aggregation learning network for remote sensing imagery enhancement. It features flexible architecture for exploiting features at different scales of the input low illumination (LI) image, with branches including a short-range structure learning module and a long-range structure learning module. These modules extract and combine structural details from the input image at different scales and cast them into pixel-wise scale factors to enhance the image at a finer granularity. The network sufficiently leverages the specific long-range and short-range structures of the input LI image for superior enhancement performance, as demonstrated by extensive experiments on both synthetic and real datasets.
Research on the Adaptive Fusion Timing Algorithm for BeiDou and LORAN Based on the EKF
Authors: Guan Xiaolong , Wu Jianfeng , Li Yuji , Zhou Zhibo , Xing Yan , Wu Huabing , Zhao Aiping
Published: January 2025

This paper addresses the issue of limited timing accuracy in complex environments for both the BeiDou system (BD) and the long-range navigation system (LORAN). We delve into the correction algorithm for LORAN timing signals and an adaptive fusion timing algorithm based on the extended Kalman filter (EKF). First, we introduce the advantages and limitations of the BD and LORAN systems in timing applications, as well as the principles of the EKF algorithm and its application in multisource information fusion. Next, we propose a correction algorithm signal to address the significant fluctuations in LORAN timing signals. Building on this, we continue to study an adaptive BD and LORAN fusion timing algorithm based on the EKF. This involves optimising system noise covariance through adaptive adjustments and establishing a fusion timing algorithm model based on the EKF. Finally, we construct a test platform to verify the effectiveness of the proposed algorithms. The experimental results demonstrate that, compared to a single navigation system, the adaptive BD and LORAN fusion timing algorithm based on the EKF significantly improves the accuracy and stability of system timing. Additionally, correcting the LORAN timing results before fusion further enhances system fusion timing performance metrics. The algorithm still maintains high performance in complex environments, showing great application prospects.
Accelerating CO2 Outgassing in the Equatorial Pacific from Satellite Remote Sensing
Authors: Shang Yiwu , Xi Jingyuan , Yu Yi , Ma Wentao , Chen Shuangling
Published: January 2025

The equatorial Pacific serves as the world’s largest oceanic source of CO2. The contrasting ocean environment in the eastern (i.e., upwelling) and western (i.e., warm pool) regions makes it difficult to fully characterize its CO2 dynamics with limited in situ observations. In this study, we addressed this challenge using monthly surface partial pressure of CO2 (pCO2sw) and air-sea CO2 fluxes (FCO2) data products reconstructed from satellite and reanalysis data at a spatial resolution of 1° × 1° in the period of 1982–2021. We found that during the very strong El Niño events (1997/1998, 2015/2016), both pCO2sw and FCO2 showed a significant decrease of 41–58 μatm and 0.5–0.8 mol·m−2·yr−1 in the eastern equatorial Pacific, yet they remained at normal levels in the western equatorial Pacific. In contrast, during the very strong La Niña events (1999/2000, 2007/2008, and 2010/2011), both pCO2sw and FCO2 showed a strong increase of 40–48 μatm and 1.0–1.4 mol·m−2·yr−1 in the western equatorial Pacific, yet with little change in the eastern equatorial Pacific. In the past 40 years, pCO2sw in the eastern equatorial Pacific was increasing at a higher rate (2.32–2.51 μatm·yr−1) than that in the western equatorial Pacific (1.75 μatm·yr−1), resulting in an accelerating CO2 outgassing (at a rate of 0.03 mol·m−2·yr−2) in the eastern equatorial Pacific. We comprehensively analyzed the potential effects of different factors, such as sea surface temperature, sea surface wind speed, and ΔpCO2 in driving CO2 fluxes in the equatorial Pacific, and found that ΔpCO2 had the highest correlation (R ≥ 0.80, at p ≤ 0.05), highlighting the importance of accurate estimates of pCO2sw from satellites. Further studies are needed to constrain the retrieval accuracy of pCO2sw in the equatorial Pacific from satellite remote sensing.
Hybrid Model–Data-Driven Radar Jamming Effectiveness Evaluation Method for Accuracy Improvement
Authors: Chen Runyang , Zhang Yi , Li Xiuhe , Ran Jinhe , Shi Qianqian
Published: January 2025

Accurate and effective radar jamming effectiveness evaluation is the key to forming the radar jamming OODA (Observe, Orient, Decide, Act) loop. The current model-driven evaluation method has low confidence and the data-driven evaluation method lacks sufficient high-quality data; thus, the evaluations that are solely model-driven or data-driven are not effective. In order to solve this problem, we propose a radar jamming effectiveness hybrid model–data-driven evaluation method. Firstly, the mechanism of the model is constructed based on the jamming equations. Secondly, the quality of training data is improved by data cleaning and model correction, after which the hybrid model is realized by training with simulated data and fine-tuning it with real-world data. Finally, the validity of the method is proved by simulation experiments, which show that the method is capable of effectively improving the accuracy of prediction and evaluation, and has good practicability. Compared with the model-driven method, the RMSE (Root Mean Square Error) of the prediction results of this method is reduced by 88.26% and the MRE (Mean Relative Error) is reduced by 92.00%.
A Scene-Adaptive Phase Gradient Autofocus Algorithm
Authors: Luo Caizhen , Liang Yi , Gao Jian , Lei Gang , Han Chaolei
Published: January 2025

In the process of airborne radar imaging, when encountering certain scenarios (e.g., the Gobi desert), the low number or absence of strong scattering points will lead to azimuth scattering in the imaging results. In this study, we propose an autofocusing method based on the traditional phase gradient autofocus (PGA) algorithm that determines the optimal number of strong scattering points in each azimuth sub-aperture according to the scene (i.e., adaptively) and uses the mean amplitudes of these points in each azimuth sub-aperture of the scene to make a threshold judgment. In this way, the optimal number of strong scattering points is iteratively selected for subsequent PGA processing. The focusing quality of the image is significantly improved through the combination of these algorithms with onboard radar imaging. The simulation results prove the effectiveness of the method proposed in this study, compared with traditional PGA.
Data Fusion Applied to the Leader-Based Bat Algorithm to Improve the Localization of Mobile Robots
Authors: Araujo-Neto Wolmar , Olivi Leonardo Rocha , Villa Daniel Khede Dourado , Sarcinelli-Filho Mário
Published: January 2025

The increasing demand for autonomous mobile robots in complex environments calls for efficient path-planning algorithms. Bio-inspired algorithms effectively address intricate optimization challenges, but their computational cost increases with the number of particles, which is great when implementing algorithms of high accuracy. To address such topics, this paper explores the application of the leader-based bat algorithm (LBBA), an enhancement of the traditional bat algorithm (BA). By dynamically incorporating robot orientation as a guiding factor in swarm distribution, LBBA improves mobile robot localization. A digital compass provides precise orientation feedback, promoting better particle distribution, thus reducing computational overhead. Experiments were conducted using a mobile robot in controlled environments containing obstacles distributed in diverse configurations. Comparative studies with leading algorithms, such as Manta Ray Foraging Optimization (MRFO) and Black Widow Optimization (BWO), highlighted the proposed algorithm’s ability to achieve greater path accuracy and faster convergence, even when using fewer particles. The algorithm consistently demonstrated robustness in bypassing local minima, a notable limitation of conventional bio-inspired approaches. Therefore, the proposed algorithm is a promising solution for real-time localization in resource-constrained environments, enhancing the accuracy and efficiency in the guidance of mobile robots, thus highlighting its potential for broader adoption in mobile robotics.
A Reading Range- and Frequency-Reconfigurable Antenna for Near-Field and Far-Field UHF RFID Applications
Authors: Song Chenyang , Wu Zhipeng
Published: January 2025

In radio frequency identification (RFID), differences in spectrum policies and tag misreading in different countries are the two main issues that limit its application. To solve these problems, this article proposes a composite right/left-handed transmission line (CRLH-TL)-based reconfigurable antenna for ultra-high frequency near-field and far-field RFID reader applications. The CRLH-TL is achieved using a periodically capacitive gap-loaded parallel plate line. By deploying the CRLH-TL operating at zeroth-order resonance, a loop antenna with in-phase radiating current is obtained, which contributes to a strong and uniform H-field and a horizontally polarized omnidirectional radiation pattern. By introducing additional tunable components, frequency and reading range reconfigurabilities are enabled. The frequency tuning range is from 833 MHz to 979 MHz, which covers the worldwide UHF RFID band. Moreover, each operation mode has a narrow frequency band, which means it can operate without violating different countries’ radio frequency policy and reduce the design difficulty of designing multiple versions of a reader. Both the near-field interrogation zone and maximum far-field reading distance of the antenna are adjustable. The near-field interrogation zone is 400 mm × 400 mm × 50 mm and can be further confined. The tuning range for far-field reading distance is from 2.71 m to 0.35 m.
Development of 3D-Formed Textile-Based Electrodes with Flexible Interconnect Ribbon
Authors: Veske-Lepp Paula , Van Steenkiste Glenn , Thienpondt Svea , Cools Joris , De Pauw Herbert , Bossuyt Frederick
Published: January 2025

The integration of electronics into textiles has gained considerable attention in recent years, due to the development and high demand of wearable and flexible electronics. One of the promising fields is healthcare, which often involves the utilization of textile-based electrodes. These electrodes often offer advantages such as conformability, breathability, and comfort. This article presents the development of 3D-formed textile-based electrodes together with a narrow fabric-based interconnect system. This study showcases the methods and materials for the fabrication of the textile-based electrodes and the interconnect system, including a durability assessment, by performing standardized washing (ISO 6330-2012) and user tests. The results demonstrated that the developed 3D-formed textile-based electrodes and stretchable interconnect system are durable and effective for wearable applications, maintaining performance under extensive washing.
Novel RFID Multi-Label Network Location Measurement by Dual CCD and Non-Local Means–Harris Algorithm
Authors: Li Lin , Jin Zhixin , Li Junji , Zhang Zelin
Published: January 2025

To improve the performance of Radio Frequency Identification (RFID) multi-label systems, the multi-label network structure needs to be quickly located and optimized. A multi-label location measurement method based on the NLM–Harris algorithm is proposed in this paper. Firstly, multi-label geometric distribution images are obtained through a label image acquisition system of a multi-label semi-physical simulation platform with two vertical Charge-Coupled Device (CCD) cameras, and Gaussian noise is added to the image to simulate thermoelectric interference. Then, a fast NLM algorithm that optimizes the kernel coefficient acquisition speed is used for image denoising. Finally, the Harris corner algorithm is used to obtain the corner points of the images. After screening the diagonal points, the pixel coordinates of the preset origin and the four corners of the labels are obtained. Furthermore, the actual coordinates of the labels are obtained according to the pixel relationship. The results show that the average absolute errors of x, y, and z coordinates are 0.773 mm, 0.782 mm, and 0.807 mm, respectively. In addition, the relative errors are 1.659%, 2.260%, and 0.258%, which shows the high location accuracy of the multi-label network. It is of great significance to measure and optimize the performance of multi-label systems.
In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models Against Variability
Authors: Khaked Azhar Ali , Oishi Nobuyuki , Roggen Daniel , Lago Paula
Published: January 2025

Deep learning (DL)-based Human Activity Recognition (HAR) using wearable inertial measurement unit (IMU) sensors can revolutionize continuous health monitoring and early disease prediction. However, most DL HAR models are untested in their robustness to real-world variability, as they are trained on limited lab-controlled data. In this study, we isolated and analyzed the effects of the subject, device, position, and orientation variabilities on DL HAR models using the HARVAR and REALDISP datasets. The Maximum Mean Discrepancy (MMD) was used to quantify shifts in the data distribution caused by these variabilities, and the relationship between the distribution shifts and model performance was drawn. Our HARVAR results show that different types of variability significantly degraded the DL model performance, with an inverse relationship between the data distribution shifts and performance. The compounding effect of multiple variabilities studied using REALDISP further underscores the challenges of generalizing DL HAR models to real-world conditions. Analyzing these impacts highlights the need for more robust models that generalize effectively to real-world settings. The MMD proved valuable for explaining the performance drops, emphasizing its utility in evaluating distribution shifts in HAR data.
Bias Calibration of Optically Pumped Magnetometers Based on Variable Sensitivity
Authors: Chen Jieya , Ye Chaofeng , Hou Xingshen , Niu Yaqiong , Sun Limin
Published: January 2025

Optically pumped magnetometers (OPMs) functioning in the spin-exchange relaxation-free (SERF) regime have emerged as attractive options for measuring weak magnetic fields, owing to their portability and remarkable sensitivity. The operation of SERF-OPM critically relies on the ambient magnetic field; thus, a magnetic field compensation device is commonly employed to mitigate the ambient magnetic field to near zero. Nonetheless, the bias of the OPM may influence the compensation impact, a subject that remains unexamined. This paper introduced an innovative bias calibration technique for OPMs. The sensitivity of the OPM was altered by adjusting the cell temperature. The output of the OPM was then documented with varying sensitivity. It is assumed that the signal exhibits a linear correlation with the environmental magnetic field, and the statistical characteristics of the magnetic field are identical for both measurements, upon which the bias of the OPM is assessed. The bias was subsequently considered in the feedback magnetic field compensation mechanism. The results indicate that this technique might successfully reduce environmental magnetic fluctuations and enhance the sensitivity of the OPM. This technique measured the magnetic field produced by the human heart, confirming the viability of the ultra-weak biomagnetic field measurement approach.
A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain–Computer Interfaces to Enhance Motor Imagery Classification
Authors: Mallat Souheyl , Hkiri Emna , Albarrak Abdullah M. , Louhichi Borhen
Published: January 2025

Enhancing motor disability assessment and its imagery classification is a significant concern in contemporary medical practice, necessitating reliable solutions to improve patient outcomes. One promising avenue is the use of brain–computer interfaces (BCIs), which establish a direct communication pathway between users and machines. This technology holds the potential to revolutionize human–machine interaction, especially for individuals diagnosed with motor disabilities. Despite this promise, extracting reliable control signals from noisy brain data remains a critical challenge. In this paper, we introduce a novel approach leveraging the collaborative synergy of five convolutional neural network (CNN) models to improve the classification accuracy of motor imagery tasks, which are essential components of BCI systems. Our method demonstrates exceptional performance, achieving an accuracy of 79.44% on the BCI Competition IV 2a dataset, surpassing existing state-of-the-art techniques in using multiple CNN models. This advancement offers significant promise for enhancing the efficacy and versatility of BCIs in a wide range of real-world applications, from assistive technologies to neurorehabilitation, thereby providing robust solutions for individuals with motor disabilities.
Microextraction-Based Techniques for the Determination of Beta-Blockers in Biological Fluids: A Review
Authors: Nisyriou Styliani , Zacharis Constantinos K.
Published: January 2025

Sample preparation is a critical step in the analytical process. Apart from the traditional sample cleanup approaches, microextraction-based techniques have attracted much attention in recent years and especially from researchers working in the analysis of beta-blockers. Developing sensitive and selective analytical methods is essential for detecting these compounds in complex matrices. The present review aims to provide an overview of microextraction-based analytical techniques for the determination of beta-blockers in biological samples, covering a time frame of the last decade. Detailed information on materials/coatings and instrumental configurations are provided.
Genetic Diversity and Genome-Wide Association Study for Shoot and Root Traits in Rice Grown Under Water Deficit at Early Vegetative Stage
Authors: das Chagas Gabriel Brandão , Machado Rodrigo Pagel , Fils-Aimé Célanet , Perleberg Antônio de Azevedo , da Luz Viviane Kopp , Costa de Oliveira Antonio , da Maia Luciano Carlos , Pegoraro Camila
Published: January 2025

Water deficit affects rice growth, development, and yield. Knowledge of genetic diversity for water deficit tolerance, as well as the genetic architecture that is responsible for this trait, can accelerate rice cultivars’ improvement. In this study, different tools were applied to assess genetic diversity and identify genome regions associated with shoot and root traits in rice germplasm grown under water deficit at an early vegetative stage. A panel of 177 rice genotypes grown under water deficit was evaluated for root length (RL), root dry weight (RDW), shoot length (SL), and shoot dry weight (SDW). Genetic diversity was investigated using means grouping and principal component analysis. For the genome-wide association study, a general linear model was applied, using RL, RDW, SL, and SDW phenotypic data converted into Best Linear Unbiased Prediction (BLUPs); genotypic data (1185 single nucleotide polymorphism—SNPs-loci); and population structure. Overall, little genetic diversity was observed, but genotypes with a higher water deficit tolerance were identified. Several significant SNPs were mapped, 81, 5, 53, and 41 for RL, RDW, SL, and SDW, respectively. Among the identified genes, there are those encoding kinases, proteins involved in phytohormone and cell wall metabolism, and Cytochrome P450. The obtained results provide insight into genetic diversity and the genetic architecture of water deficit tolerance, which will be useful in improving this trait in rice grown in Brazil.
Public Policy for Human Capital: Fostering Sustainable Equity in Disadvantaged Communities
Authors: Ticona Machaca Alejandro , Cano Ccoa Dominga Micaela , Gutiérrez Castillo Félix Henry , Quispe Gomez Fredy , Arroyo Beltrán Martín , Zirena Cano Marisol Gonzaga , Sánchez-Chávez-Arroyo Vladimir , Manrique Chavez Cyntia Primitiva , Romualdo Rosario Abel , Adauto-Medina Willy Andrés , Montes Salcedo Marleny
Published: January 2025

This study presents new empirical findings on the multidimensional barriers that disadvantaged communities must overcome to equitably access quality education and health services. Equitable access to education and health services in disadvantaged communities requires comprehensive public policies that address multidimensional barriers. Through an innovative econometric analysis of primary data collected in 50 rural communities, the most influential factors hindering access to these basic services are identified. This article discusses the most effective public policy strategies for improving access to and the quality of education and health services in disadvantaged communities, and outlines how to implement them sustainably and equitably. The results reveal that a lack of adequate infrastructure, a shortage of qualified personnel, and socioeconomic and cultural barriers are the main obstacles. Based on these findings, a new comprehensive intervention model is proposed, which simultaneously addresses these interconnected barriers. These strategies contribute directly to the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being) and SDG 4 (Quality Education), by addressing critical barriers to equitable access to essential health and education services in marginalized communities. These strategies are based on theories that highlight the importance of investing in education and health for human and economic development, and support the fact that investments in these sectors boost productivity, income, well-being, and equity. The study concludes with practical and applicable recommendations for public policymakers, emphasizing the importance of adapting them to the local context and ensuring the active participation of the beneficiary communities.
The Influence of Ceramsite and Superphosphate on Humification in the Composting Process of Garden Wastes
Authors: Wang Hui , Li Suyan , Sun Xiangyang , Li Yalin , Ding Hao , Hao Dan , Wang Di
Published: January 2025

This study used ceramsite and superphosphate as exogenous additives for composting garden wastes. It investigated the changes in temperature, pH, lignocellulose, enzyme activity, humic substrates, and humification parameters during the composting process. A total of four treatments—T0 (CK), T1 (ceramsite), T2 (superphosphate), and T3 (superphosphate + ceramsite)—were tested in a 50-day composting experiment. It was found that the formation of the compost humic substrate could be increased to 14.69% under the action of ceramsite. In addition, ceramsite promoted lignocellulose degradation, improved enzyme activity, and enhanced the material conversion in the composting process. At the same time, superphosphate also promoted the formation of humic substrates in compost but was less effective than ceramsite. Ceramsite is the best additive in promoting compost maturation.
Mapping of Circular Construction Ecosystems’ Characteristics: Interconnections, Relationships, and Synchronization of Stakeholders at the Micro, Meso, and Macro Scales
Authors: Dautremont Charlotte , Gobbo Emilie
Published: January 2025

The application of circular strategies in the architecture, engineering, construction, and operations (AECO) sector has been extensively researched, demonstrating the significance of technical approaches. However, research also focuses on the organizational challenges that arise within circular networks. Recent studies emphasize the importance of collective action in fostering cooperation across the value chain to achieve circular economy (CE) goals. Nevertheless, a considerable amount of research, including EU policies, tends to concentrate on “end-of-pipe” solutions, while failing to adequately address the socio-ecological challenges inherent in the transition to a CE. This study aims to explore collective activities and work in circular construction ecosystems at the macro, meso, and micro scales, identifying their interconnections. The findings of the literature review indicate that a successful transition to a CE requires a deeper commitment from stakeholders, which is influenced by the structure and relationships within the ecosystem. The increasing complexity of these ecosystems necessitates a redefinition of stakeholder roles and competencies, emphasizing a collective perception of value. Given the lack of tools and research on collaboration, we propose developing a map of circular construction ecosystems to improve the visualization and understanding of their dynamics.
An Integrated Two-Step Optimization Model and Aggregative Multi-Criteria Approach for Establishing Sustainable Tram Transportation Plan
Authors: Stoilova Svetla , Pulevski Ivan
Published: January 2025

The choice of the most appropriate sustainable scheme for the organization of tram transportation in cities is of great importance for tram operators, for users of transportation services, and for the protection of the environment from harmful emissions. This study aims to propose a methodology for formulating a tram transportation plan considering technological, environmental, economic, and social indicators. The variant schemes represent the routes of a tram in the tram network. The methodology includes four stages. The first stage involves the determination of variant schemes for a transportation plan of service with trams. In the second stage, a two-step optimization model is proposed to determine the number and trams by types for each tram route for each variant scheme, and also to establish the distribution of trams by depots. The third stage includes ranking the variant schemes by applying the sequential interactive model for urban systems (SIMUS) multi-criteria method. Eleven quantitative and qualitative criteria for evaluating the tram transportation plan were introduced. A verification of the results is performed in the fourth stage. For this purpose, a comparison of the preference ranking organization method for enrichment of evaluations (PROMETHEE) method and the technique for order of preference by similarity to ideal solution (TOPSIS) method is made. Both methods have different approaches for decision making and differ from the SIMUS method. Two strategies were proposed to determine the criteria weights. One is based on the Shannon entropy method and the other uses the objective weights obtained through the SIMUS method. Finally, in the fifth stage, the results obtained through the SIMUS, PROMEHEE and TOPSIS methods are combined using the expected value obtained by applying the program evaluation and review technique method (PERT). The proposed methodology was applied to study tram transportation in Sofia, Bulgaria. Five variant schemes were considered. The schemes are optimized through the criterion of minimum energy consumption. The number of trams by routes and by type was determined. An improved scheme for tram transportation in Sofia was proposed. The scheme makes it possible to increase the frequency of the trams by 13%, to reduce the zero mileage of rolling stock, and to reduce carbon dioxide pollution by 11%.
Dynamics Analysis of Spatial Distribution and Landscape Pattern of Wetlands in the Weihe River Basin from 1980 to 2020
Authors: Wu Aijiao , Li Junbao , Zhang Dan , Chen Min , Fan Miaochun , Yang Bo , Yu Jing , Gao Yani , Li Liandui , Xie Zhiguo
Published: January 2025

The wetland ecosystem is one of the most important carbon sinks on Earth, the most biodiverse ecological landscape in nature, and one of the most important living environments for human beings. The Weihe River wetland is located in the Guanzhong Plain urban agglomeration, with extreme climate and urban expansion having a great impact on its dynamic changes. Revealing the characteristics of and trends in wetland dynamics in the Weihe River Basin is the key to protecting and maintaining the healthy development of the Weihe River wetlands. This paper analyzed the changing characteristics of land use types and landscape patterns in the wetlands of the Weihe River Basin using wetland land use data from six periods in the Weihe River wetland from 1980 to 2020 and explored the spatial and temporal distribution characteristics and dynamic changes in wetlands in the Weihe River Basin. The results showed the following: (1) Wetlands in the Weihe River Basin, dominated by rivers, saw area fluctuations with an initial decline followed by an increase. Land use changes followed a slow–fast–slow trend. (2) From 1980 to 2020, frequent conversions among wetland types were observed. The primary transformation was the conversion of marshes into lakes (18.05 km2) and reservoirs/ponds (17.98 km2). Approximately 0.06 km2 of lakes were transformed into canals/channels. (3) River patches have the largest area, while canals/channels have the smallest. The patch density (PD) and landscape shape index (LSI) of wetlands fluctuate significantly, and the reduction in area leads to a 3.46% decrease in aggregation index (AI). Shannon’s diversity index (SHDI) has decreased by 5.41%. (4) The centroid of marshes experiences significant changes, while river changes are complex. The centroid changes in reservoirs/ponds are located along the southeast–northwest line. Canals/watercourses remain stable. Lakes exhibit the longest migration. This study provides robust scientific support for wetland ecological protection, policy formulation, and social sustainable development by conducting an in-depth analysis of the dynamic change characteristics of wetlands in the Weihe River Basin.