bluuebunny/crossref_metadata_2025 huggingface dataset:
Geographic Distribution Pattern Determines Soil Microbial Community Assembly Process in Acanthopanax senticosus Rhizosphere Soil
Authors: Wang Mingyu , Xing Xiangyu , Zhang Youjia , Sui Xin , Zheng Chunying
Published: December 2024

The geographic distribution patterns of soil microbial communities associated with cultivated Acanthopanax senticosus plants in Northeast China were investigated. High-throughput sequencing revealed that the diversity and community assembly of bacterial and fungal communities in the inter-root soil varied significantly with geographic location. The study found that bacterial communities were predominantly assembled through stochastic processes at most sites, while fungal communities showed greater variation, with both stochastic and deterministic processes involved. The complexity of bacterial–fungal co-occurrence networks also varied with longitude and latitude, demonstrating both positive and negative interactions. PICRUSt 2.0 and FUNGuild were used to predict the potential functions of soil bacterial and fungal microbiota, respectively, during different land use patterns. The average taxonomic distinctness (AVD) index indicated varying degrees of community stability across sites. Key microbial taxa contributing to community variability were identified through Random Forest modeling, with Bacteriap25 and Sutterellaceae standing out among bacteria, and Archaeorhizomyces and Clavaria among fungi. Soil chemical properties, including pH, TN, TP, EC, and SOC, significantly correlated with microbial diversity, composition, and co-occurrence networks. Structural equation modeling revealed that geographic distribution patterns directly and indirectly influenced soil chemical properties and microbial communities. Overall, the study provides insights into the geographic distribution patterns of soil microbial communities associated with A. senticosus and highlights the need for further research into the underlying mechanisms shaping these patterns.
Novel Nuclease MbovP701 with a Yqaj Domain Is Interrelated with the Growth of Mycoplasma bovis
Authors: Hao Zhiyu , Lu Doukun , Li Xixi , Raheem Abdul , Zhao Gang , Dawood Ali Sobhy , Chen Yingyu , Chen Xi , Hu Changmin , Chen Jianguo , Zhang Lei , Zhu Xifang , Guo Aizhen
Published: December 2024

Mycoplasma bovis (M. bovis) is characterized by a reduced genomic size and limited synthetic capacity, including the inability to synthesize nucleotides de novo, relies on nucleases for nutrient acquisition and survival. A number of nucleases have been implicated in M. bovis pathogenicity, facilitating substrate degradation and contributing to DNA repair mechanisms that enhance bacterial persistence. The present study confirmed that the T5.808 mutant, in which a novel nuclease gene (Mbov_0701) was disrupted by the mini-Tn4001 transposon, exhibits a growth defect when co-cultured with EBL cells. However, the restoration of Mbov_0701 resulted in the resumption of growth in the mutant. The characterization of MbovP701 revealed that it had high activity in hydrolyzing dsDNA with 5′- to 3′- polarity. Furthermore, the substrates of MbovP701 were extended to include linear dsDNA, ssDNA, RNA, and plasmid DNA. The exonuclease activity is dependent on the presence of Mn2+ and/or Mg2+ ions, with an optimal pH and temperature of 8.3 and 43 °C, respectively. The truncation experiments of rMbovP701 revealed that YqaJ (41–185 aa) is the key functional domain of MbovP701 exonuclease. In conclusion, the present study identified a novel nuclease in M. bovis that plays an essential role in the proliferation of this minimal organism. This finding elucidates the survival strategy and pathogenesis of M. bovis, suggesting a potential therapeutic strategy for the treatment of M. bovis through targeting the inhibition of MbovP701. Moreover, it provides a foundation for future investigations into the interactions between MbovP701 and other nucleases involved in M. bovis biology.
From Chains to Arrays: Substrate-Mediated Self-Assembly of Diboron Molecules
Authors: Hao Xiaoyu , Yang Huixia , Niu Mengmeng , Wang Tingting , Ji Hongyan , Brumboiu Iulia Emilia , Grazioli Cesare , Guarnaccio Ambra , Cossaro Albano , Li Yan , Qiao Jingsi , Zhang Quanzhen , Liu Liwei , Zhang Teng , Wang Yeliang
Published: December 2024

In this study, we explore the substrate-mediated control of self-assembly behavior in diboron molecules (C12H8B2O4, B2Cat2) using scanning tunneling microscopy (STM). The structural transformation of B2Cat2 molecules from one-dimensional (1D) molecular chains to two-dimensional (2D) molecular arrays was achieved by changing the substrate from Au(111) to bilayer graphene (BLG), highlighting the key role of substrate interactions in determining the assembly structure. Notably, the B-B bond in the molecular arrays on BLG is distinctly pronounced, reflecting a more refined molecular resolution with distinct electronic states than that on Au(111). Density functional theory (DFT) calculations confirm the weak interaction between B2Cat2 molecules and the BLG substrate, which facilitates the formation of 2D molecular arrays on BLG. This work demonstrates how controlling substrate properties enables the formation of 1D chains and 2D arrays, providing valuable insights for the design of next-generation molecular electronics and catalysis systems.
Early Therapeutic Plasma Exchange in Pediatric Transverse Myelitis: A Case Report and Scoping Review
Authors: Khan Akram , Peña José , Briceño Genesis , Gronquist Juliann M. , Khan Khurram , Reddy Raju , Yadav Vijayshree , Singh Asha
Published: December 2024

Background/Objectives: Transverse myelitis (TM) is a rare, acute inflammatory disorder affecting the spinal cord, with severe potential consequences, particularly in pediatric patients. Therapeutic plasma exchange (TPE) has emerged as a possible intervention for children unresponsive to high-dose corticosteroids. This study explores the efficacy of early TPE in pediatric TM through a case report and scoping review aiming to clarify the therapeutic benefits of TPE when used in conjunction with corticosteroids in children. Methods: We present a scoping review of existing literature on the early administration of TPE in pediatric patients with TM, supplemented by a case report of a 5-year-old boy with Longitudinally Extensive Transverse Myelitis (LETM), who received early TPE and corticosteroid therapy. Clinical progression, response to TPE, and functional outcomes were documented over a 9-month follow-up period. Results: Among the reviewed cases, early TPE demonstrated potential to expedite neurological recovery and improve functional outcomes. In our case report, the patient showed rapid recovery, achieving unassisted ambulation by day four of TPE. No adverse effects were observed. MRI findings revealed substantial resolution of spinal cord lesions by three months, with near-complete symptom resolution at nine months. Conclusions: Early initiation of TPE, in conjunction with corticosteroids, may offer significant therapeutic benefit in pediatric TM, potentially accelerating recovery and improving outcomes. This case highlights the need for further controlled studies to establish evidence-based guidelines for TPE use in pediatric TM.
Pre-Implementation Strategies to Support Adaptation of Thrive: A Care Transitions Model for Economically Disadvantaged Patients with Serious Mental Illness
Authors: Brooks Carthon J. Margo , Tibbitt Celsea , Amenyedor Kelvin Eyram , Bettencourt Amanda P. , Babe Erin , Cacchione Pamela Z. , Brom Heather
Published: December 2024

Background: Economically disadvantaged patients diagnosed with serious mental illness (SMI) experience post-hospitalizations disparities due to fragmented care transitions. Purpose: To describe the pre-implementation strategies used to adapt and implement a nurse-led transitional care intervention (Thrive) to meet the needs of economically disadvantaged patients diagnosed with an SMI. Methods: Two pre-implementation strategies, Evidence Based Quality Improvement (EBQI) meetings and Formative Evaluation (FE) research, were used to adapt intervention components. FE data included semi-structured interviews analyzed using Rapid Qualitative Analysis. Findings: Adaptations were made to core components of Thrive and strategies to support implementation were identified. Conclusions: Participatory strategies help to adapt interventions that are person-centered and tailored to the organizational context. Trial: NCT06203509.
Study of Interactions Between Gadolinium-Based Contrast Agents and Collagen by Taylor Dispersion Analysis and Frontal Analysis Continuous Capillary Electrophoresis
Authors: Somnin Chutintorn , Chamieh Joseph , Leclercq Laurent , Medina Christelle , Rousseaux Olivier , Cottet Hervé
Published: December 2024

Background: Gadolinium-based contrast agents (GBCA) are widely used in magnetic resonance imaging (MRI) to enhance image contrast by interacting with water molecules, thus improving diagnostic capabilities. However, understanding the residual accumulation of GBCA in tissues after administration remains an area of active research. This highlights the need for advanced analytical techniques capable of investigating interactions between GBCAs and biopolymers, such as type I collagen, which are abundant in the body. Objective: This study explores the interactions of neutral and charged GBCAs with type I collagen under physiological pH conditions (pH 7.4) using Taylor dispersion analysis (TDA) and frontal analysis continuous capillary electrophoresis (FACCE). Methods: Collagen from bovine achilles tendon was ground using a vibratory ball mill to achieve a more uniform particle size and increased surface area. Laser granulometry was employed to characterize the size distributions of both raw and ground collagen suspensions in water. TDA was used to assess the hydrodynamic radius (Rh) of the soluble collagen fraction present in the supernatant. Results: From the TDA and FACCE results, it was shown that there were no significant interactions between the tested GBCAs and either the ground collagen or its soluble fraction at pH 7.4. Interestingly, we also observed that collagen interacts with filtration membranes, indicating that careful selection of membrane material, or the absence of filtration in the experimental protocol, is essential in interaction studies involving collagen. Conclusion: These findings bring valuable insights into the behavior of GBCAs in biological systems with potential implications for clinical applications.
Polyphenol Profile and Antioxidant, Antityrosinase, and Anti-Melanogenesis Activities of Ethanol Extract of Bee Pollen
Authors: He Qiang , Wang Jie , Li Jingjing , Yang Wenchao
Published: December 2024

Background/Objective: Bee pollen, a rich nutritional food, was employed to develop a raw material for skin whitening. Methods: The polyphenol profile and antioxidant, antityrosinase, and anti-melanogenesis activities of the ethanol extracts of five species of bee pollens (EEBPs) were determined. Results: The results showed that there were a total of 121 phenolic compounds in these EEBPs. Each type of bee pollen had unique substances. The best anti-melanogenesis activity was observed for sunflower EEBP, about 25% at a concentration of 25 μg/mL BEEP. The anti-melanogenesis activities of EEBPs from high to low were sunflower, apricot, camellia, rapeseed, and lotus EEBPs. The anti-melanogenesis activity in B16F10 cells was positively correlated with the antityrosinase activity and total phenol content, with coefficients of 0.987 and 0.940. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis results of untargeted proteomics revealed that sunflower EEBP inhibited melanogenesis in B16F10 cells by reducing the expression of the proteins MAP2K1, NFKB2, RELB, RPS6KA3, CASP3, TRAF6, MAP2K5, MAPKAPK3, STRADA, CCNA2, and FASN involved in the cAMP, MAPK, and TNF signaling pathways, even though these pathways were not significantly different from the control group. Conclusions: The sunflower EEBP has high inhibition effect on melanogenesis than other species EEBPs. The results provide a basis for the future industrial development of a raw material for skin whitening.
Vegetation Dynamics and Recovery Potential in Arid and Semi-Arid Northwest China
Authors: Sui Xiran , Xu Qiongling , Tao Hui , Zhu Bin , Li Guangshuai , Zhang Zengxin
Published: December 2024

The arid and semi-arid regions of northwest China are characterized by sparse vegetation and fragile ecosystems, making them highly susceptible to the impacts of climate change and human activities. Based on observed meteorological data, the Normalized Difference Vegetation Index (NDVI), the Lund–Potsdam–Jena dynamic global vegetation model (LPJ), a vegetation recovery potential model, and the MK trend test method, this study investigated the spatiotemporal distribution of vegetation recovery potential in northwest China and its relationship with global warming and increasing precipitation. The results indicated that vegetation in northwest China significantly increased, with greening closely related to trends in warming and wetting during 1982–2019. However, the vegetation recovery potential declined due to climate change. Central and southern Xinjiang and central Qinghai exhibited higher grassland recovery potential, while the central Gobi Desert areas of northwest China had lower recovery potential. The eastern part of northwest China was highly sensitive to drought, with moderate vegetation growth and recovery potential. Remote sensing data indicated a 2.3% increase in vegetation coverage in the region, with an average vegetation recovery potential index (IVCP) of 0.31. According to the results of LPJ model, the average vegetation recovery potential index for northwest China was 0.14, indicating a 1.1% improvement potential in vegetation coverage. Overall, climate warming and wetting facilitated vegetation recovery in northwest China, particularly in mountainous areas. The findings provide valuable insights for ecological restoration efforts and offer practical guidance for combating desertification and enhancing sustainable development. Moreover, these results underline the importance of incorporating vegetation recovery potential into regional policy-making to improve environmental resilience in the face of ongoing climate change.
Changes of Photosynthetic Parameters in Melatonin-Treated Wheat Subjected to Drought
Authors: Todorova Dessislava , Anev Svetoslav , Iliev Martin , Petrakova Margarita , Sergiev Iskren
Published: December 2024

Drought stress affects many aspects of plant biochemistry, with photosynthesis being one the most significantly impaired physiological processes. Melatonin is a natural antioxidant with growth-regulating properties in plants. Its diverse physiological functions have been extensively studied in recent decades. Changes in leaf gas exchange and chlorophyll a fluorescence parameters were investigated in young wheat plants (Triticum aestivum L.) cv. Fermer and cv. Gines which were characterized to differ in their responses to drought, with cv. Gines being more tolerant than cv. Fermer. The plants were subjected to drought for five days by withholding their water supply. Melatonin was applied as a root supplement to the irrigation water before or after the drought period. Analyses were performed before and at the end of the stress period, as well as during the recovery phase. Changes in leaf pigment content, photosynthetic rate, stomatal conductance, and transpiration, as well as some chlorophyll a fluorescence parameters, were recorded. Melatonin alone did not cause considerable changes in the measured traits. We found a significant decrease in leaf gas exchange parameters, Fv/Fm and Fv/F0 values, and leaf pigments due to drought, especially in cv. Fermer. The data show that the application of melatonin favorably influenced the efficiency of the photosynthetic apparatus under water deprivation and during plant recovery. The pre-treatment with melatonin maintained the photosynthesis-related parameters closer to the control levels during the stress period. Both melatonin treatments supported the recovery of photosynthesis when the water supply was restored and the post-drought treatment showed a similar but weaker effect than pre-drought treatment.
The Impact of Temperature on Host–Parasite Interactions and Metabolomic Profiles in the Marine Diatom Coscinodiscus granii
Authors: O’Niel Ruchicka Annie , Pohnert Georg , Vallet Marine
Published: December 2024

Diatoms are single-celled photosynthetic eukaryotes responsible for CO2 fixation and primary production in aquatic ecosystems. The cosmopolitan marine diatom Coscinodiscus granii can form seasonal blooms in coastal areas and interact with various microorganisms, including the parasitic oomycete Lagenisma coscinodisci. This unicellular eukaryote is mainly present in the northern hemisphere as an obligate parasite of the genus Coscinodiscus. Understanding the interplay of abiotic factors such as temperature and biotic factors like parasitism on algal physiology is crucial as it dictates plankton community composition and is especially relevant during environmental changes and warming events. This study investigates the impact of two temperatures, 13 °C and 25 °C, on Coscinodiscus granii under laboratory conditions. A decreased infection rate of the parasite was observed at the elevated temperature. Comparative metabolomic analysis using UHPLC-HRMS revealed that temperature and parasitism significantly affect the algal cell metabolome. Abundances of metabolites related to sulfur metabolism, including cysteinoleic acid and dimethylsulfoniopropionate, as well as molecules linked to fatty acid metabolism, e.g., carnitine, acetylcarnitine, and eicosapentanoic acid, significantly increase in cells grown at a higher temperature, suggesting the enhanced rate of metabolism of host cells as the temperature rises. Our study reveals how temperature-induced metabolic changes can influence host–parasite dynamics in a changing environment.
Morphological Evidence Supports the Taxonomic Reinstatement of the Endemic Chinese Species Iris pandurata (Iridaceae) by Segregation from I. tigridia
Authors: Boltenkov Eugeny V.
Published: December 2024

Unfortunately, the statuses of the numerous names of the genus Iris at specific rank remain unresolved. This study considers I. pandurata, the species that was first described in 1880 and then 30 years later and is, however, still synonymized with I. tigridia. The morphological relationship between these two species and I. trippneriana, a previously unplaced name, has been assessed here. The morphological analysis has revealed that I. pandurata and I. trippneriana are actually a single species that can easily be distinguished from I. tigridia by the rhizome shape, the adventitious roots shape, the flowering stem structure, and the falls ornamentation. The results support the reinstatement and recognition of I. pandurata at specific rank, including I. trippneriana as a synonym. Being endemic to China, I. pandurata has a narrow distribution range in the Qilian Mountains in the Gansu and Qinghai provinces. This report provides an updated nomenclature for I. pandurata, including I. tigridia, detailed photographs of living plants to facilitate identification, images of type specimens, a list of specimens examined, and comments on their distributions and habitats. A lectotype for I. trippneriana is designated here.
Antibiofilm Effects of Modifying Polyvinylidene Fluoride Membranes with Polyethylenimine, Poly(acrylic acid) and Graphene Oxide
Authors: Castillo-Ruiz Mario , Negrete Constanza , Espinoza Juan Pablo , Martínez Iván , Daille Leslie K. , González Christopher , Rodríguez Bárbara
Published: December 2024

Biofouling in membrane filtration systems poses significant operational challenges, leading to decreased permeate flux. The aim of this work was to study the anti-biofilm properties of new nanofiltration membranes produced via layer-by-layer, LBL, assembly by coating a polyvinylidene fluoride (PVDF) support with a polyethylenimine (PEI) and poly(acrylic acid)/graphene oxide (PAA-GO) mixture. The membranes were characterized according to contact angle, scanning electron microscopy (SEM), atomic force microscopy and their Z-potential. Biofilm quantification and characterization were carried out using crystal violet staining and SEM, while bacterial viability was assessed by using colony-forming units. The membrane with three bilayers ((PAA-PEI)3/PVDF) showed a roughness of 77.78 nm. The incorporation of GO ((GO/PAA-PEI)3/PVDF) produced a membrane with a smoother surface (roughness of 26.92 nm) and showed salt rejections of 16% and 68% for NaCl and Na2SO4, respectively. A significant reduction, ranging from 82.37 to 77.30%, in biofilm formation produced by S. aureus and E. coli were observed on modified membranes. Additionally, the bacterial viability on the modified membranes was markedly reduced (67.42–99.98%). Our results show that the modified membranes exhibited both antibiofilm and antimicrobial capacities, suggesting that these properties mainly depend on the properties of the modifying agents, as the initial adherence on the membrane surface was not totally suppressed, but the proliferation and formation of EPSs were prevented.
Testing, Experimental Design, and Numerical Analysis of Nanomechanical Properties in Epoxy Hybrid Systems Reinforced with Carbon Nanotubes and Graphene Nanoparticles
Authors: Spinelli Giovanni , Guarini Rosella , Batakliev Todor , Guadagno Liberata , Raimondo Marialuigia
Published: December 2024

Hybrid nanocomposites incorporating multiple fillers are gaining significant attention due to their ability to enhance material performance, offering superior properties compared to traditional monophase systems. This study investigates hybrid epoxy-based nanocomposites reinforced with multi-walled carbon nanotubes (MWCNTs) and graphene nanosheets (GNs), introduced at two different weight concentrations of the mixed filler, i.e., 0.1 wt% and 0.5 wt% which are, respectively, below and above the Electrical Percolation Threshold (EPT) for the two binary polymer composites that solely include one of the two nanofillers, with varying MWCNTs:GNs ratios. Mechanical properties, such as contact depth, hardness, and reduced modulus, were experimentally assessed via nanoindentation, while morphological analysis supported the mechanical results. A Design of Experiments (DoE) approach was utilized to evaluate the influence of filler concentrations on the composite’s mechanical performance, and Response Surface Methodology (RSM) was applied to derive a mathematical model correlating the filler ratios with key mechanical properties. The best and worst-performing formulations, based on hardness and contact depth results, were further investigated through detailed numerical simulations using a multiphysics software. After validation considering experimental data, the simulations provided additional insights into the mechanical behavior of the hybrid composites. This work aims to contribute to the knowledge base on hybrid composites and promote the use of computational modeling techniques for optimizing the design and mechanical performance of advanced materials.
In Situ Thermosensitive Mucoadhesive Nasal Gel Containing Sumatriptan: In Vitro and Ex Vivo Evaluations
Authors: Alshraim Aseel , Alshora Doaa , Ashri Lubna , Alhusaini Ahlam , Alanazi Nawal , Safwan Nisreen M.
Published: December 2024

The aim of this study was to develop a thermosensitive mucoadhesive (MA) in situ nasal gel for sumatriptan. A 3D response surface methodology (Design of Expert version 11) was employed to formulate nine different formulations. The Pluronic F-127 concentration (X1) and chitosan concentration (X2) were selected as independent factors. The formulas were studied in terms of pH, clarity, drug content, gelation temperature, gelation time, gel strength, MA strength, viscosity, % release after 5 h, and release kinetics. The optimized formulas were studied for % permeated after 5 h and stability in addition to previous tests. The study of the stability of the optimized formula was performed under accelerated conditions (40 ± 2 °C, 75 ± 5% RH) for 3 months. The outcomes of the optimized formula were a clear gel with a gelation temperature of 33 °C and a reasonable gelation time of less than one minute, and the release and permeation during 5 h were 40% and 50%, respectively. The formulated gel decreased the mucociliary clearance (MCC) and thus increased the retention time in the nasal cavity, resulting in enhancing SMT absorption, which could improve the drug efficacy.
Molecular Simulation Study on the Adsorption Mechanisms of Microbial Components and Metabolic Products on Activated Carbon in HVAC Systems
Authors: Zhang Ge , Peng Zhiyuan , Liu Shuai , Li Xiaochen
Published: December 2024

Activated carbon is widely known for its porous structure and diverse surface functional groups, making it an effective adsorbent for removing various organic and inorganic pollutants from air and water. However, as a filtration material in air conditioning systems, activated carbon can also provide favorable conditions for microbial growth, potentially leading to the proliferation of microorganisms on its surface. These microorganisms, along with their metabolic products, can be released into indoor environments, posing potential health risks. This study employs molecular simulation to investigate the adsorption and release mechanisms of microorganisms and their volatile organic compound (VOC) metabolic products on activated carbon. Peptidoglycan (PDG) (as a representative bacterial cell wall component) and p-xylene (as a representative microbial metabolic product) were used as model compounds. The adsorption behavior of these compounds was simulated on activated carbon under different environmental conditions, including varying temperatures. The study found that activated carbon has a higher affinity for peptidoglycan than for p-xylene; at 303.15 K, the diffusion coefficients of peptidoglycan and p-xylene in activated carbon are 0.842 × 10−9 m2/s and 0.587 × 10−8 m2/s, respectively. Temperature plays an important role in affecting adsorption capacity; when the temperature rises by 10 K, the diffusion coefficients of peptidoglycan and p-xylene in activated carbon increase by 32.8% and 34.3%, respectively. These insights contribute to the development of efficient and health-conscious air purification materials, offering theoretical and practical guidance for optimizing the use of activated carbon in HVAC systems.
Efficient Photocatalytic Degradation of Methylene Blue and Methyl Orange Using Calcium-Polyoxometalate Under Ultraviolet Irradiation
Authors: Bani-Atta Suhair A. , Darwish A. A. A. , Shwashreh Leena , Alotaibi Fatimah A. , Al-Tweher Jozaa N. , Al-Aoh Hatem A. , El-Zaidia E. F. M.
Published: December 2024

With the increasing demand for eco-friendly water treatment solutions, the development of novel photocatalysts such as calcium polyanion (Ca-POM) plays a vital role in mitigating industrial wastewater pollution. In this research, calcium polyanion, H60N6Na2Ca2W12O60 (Ca–POM), was successfully synthesized via a self-assembly reaction from metal-oxide subunits. The synthesized Ca–POM was verified to have a polycrystalline structure with a broad size distribution, with an average particle diameter of approximately 623.62 nm. Powder X-ray diffraction (XRD) analysis confirmed the polycrystalline structure of the Ca–POM, with a calculated band gap energy of 3.29 eV. The photocatalytic behavior of the Ca-POM sample was tested with two model dyes, methylene blue (MB) and methyl orange (MO). The reaction mixture was then exposed to ultraviolet (UV) irradiation for durations ranging from 20 to 140 min. The synthesized cluster demonstrated photocatalytic efficiency (PCE%) values of 81.21% for MB and 25.80% for MO. This work offers a valuable basis for applying Ca–POM as a heterogeneous photocatalyst for treating industrial wastewater organic pollutants and highlights the potential of Ca–POM in sustainable water treatment applications.
EWAIS: An Ensemble Learning and Explainable AI Approach for Water Quality Classification Toward IoT-Enabled Systems
Authors: Rezk Nermeen Gamal , Alshathri Samah , Sayed Amged , El-Din Hemdan Ezz
Published: December 2024

In the context of smart cities with advanced Internet of Things (IoT) systems, ensuring the sustainability and safety of freshwater resources is pivotal for public health and urban resilience. This study introduces EWAIS (Ensemble Learning and Explainable AI System), a novel framework designed for the smart monitoring and assessment of water quality. Leveraging the strengths of Ensemble Learning models and Explainable Artificial Intelligence (XAI), EWAIS not only enhances the prediction accuracy of water quality but also provides transparent insights into the factors influencing these predictions. EWAIS integrates multiple Ensemble Learning models—Extra Trees Classifier (ETC), K-Nearest Neighbors (KNN), AdaBoost Classifier, decision tree (DT), Stacked Ensemble, and Voting Ensemble Learning (VEL)—to classify water as drinkable or non-drinkable. The system incorporates advanced techniques for handling missing data and statistical analysis, ensuring robust performance even in complex urban datasets. To address the opacity of traditional Machine Learning models, EWAIS employs XAI methods such as SHAP and LIME, generating intuitive visual explanations like force plots, summary plots, dependency plots, and decision plots. The system achieves high predictive performance, with the VEL model reaching an accuracy of 0.89 and an F1-Score of 0.85, alongside precision and recall scores of 0.85 and 0.86, respectively. These results demonstrate the proposed framework’s capability to deliver both accurate water quality predictions and actionable insights for decision-makers. By providing a transparent and interpretable monitoring system, EWAIS supports informed water management strategies, contributing to the sustainability and well-being of urban populations. This framework has been validated using controlled datasets, with IoT implementation suggested to enhance water quality monitoring in smart city environments.
Assimilation of Fengyun-4A Atmospheric Motion Vectors and Its Impact on China Meteorological Administration—Beijing System Forecasts
Authors: Xie Yanhui , Zhang Shuting , Sun Xin , Chen Min , Shi Jiancheng , Xia Yu , Liu Ruixia
Published: December 2024

The ever-increasing capacity of numerical weather prediction (NWP) models requires accurate flow information at higher spatial and temporal resolutions. The atmospheric motion vectors (AMVs) extracted from the Advanced Geostationary Radiation Imager (AGRI) mounted on the Fengyun-4A (FY-4A) satellite can provide information about atmospheric flow fields on small scales. This study focused on the assimilation of FY-4A AMVs and its impact on forecasts in the regional NWP system of the China Meteorological Administration—Beijing (CAM-BJ). The statistical characterization of FY-4A AMVs was firstly analyzed, and an optimal observation error in each vertical level was obtained. Three groups of retrospective runs over a one-month period were conducted, and the impact of assimilating the AMVs with different strategies on the forecasts of the CMA-BJ system were compared and evaluated. The results suggested that the optimal observation errors reduced the standard deviation of the background departures for U and V wind, leading to an improvement in the standard deviation in the corresponding analysis departures of about 8.3% for U wind and 7.3% for V wind. Assimilating FY-4A AMV data with a quality indicator (QI) above 80 and the optimal observation errors reduced the error of upper wind forecast in the CMA-BJ system. A benefit was also obtained in the error of surface wind forecast after 6 h of the forecasts, although it was not significant. For rainfall forecast with different thresholds, the score skills increased slightly after 6 h of the forecasts. There was an overall improvement for the overprediction of 24 h accumulated precipitation forecast including the AMVs, even when conventional observations were relatively rich. The application of FY-4A AMVs with a QI > 80 and adjustment to observation errors has a positive impact on the upper wind forecast in the CMA-BJ system, improving the score skill of rainfall forecasting.
On the Approximation of Precision Matrices for Wide-Swath Altimetry
Authors: Yaremchuk Max , Beattie Christopher , Panteleev Gleb
Published: December 2024

New observations of ocean surface topography obtained by wide-swath satellite interferometry require new capabilities to process spatially correlated errors in order to assimilate these data into numerical models. The sea surface height (SSH) variations have to be weighted against other types of assimilated data using information on their precision, as represented by the inverse of the SSH error covariance matrix R. The latter can be well approximated by a block-circulant (BC) structure and, therefore, allows numerically efficient implementation in operational data assimilation (DA) systems. In this note, we extend the technique of approximating R for wide-swath altimeters by including the uncertainties associated with the state of the atmosphere. It is shown that such an extension keeps the BC approximation error within acceptable (±10%) bounds in a wide range of environmental conditions and could be beneficial for improving the accuracy of SSH retrievals from wide-swath altimeter observations.
Reconstructing Long-Term, High-Resolution Groundwater Storage Changes in the Songhua River Basin Using Supplemented GRACE and GRACE-FO Data
Authors: Liu Chuanqi , Zhang Zhijie , Xu Chi , Zhang Wanchang
Published: December 2024

The Gravity Recovery and Climate Experiment (GRACE) enables large-scale monitoring of terrestrial water storage changes, significantly contributing to hydrology and related fields. However, the coarse resolution of groundwater storage anomaly (GWSA) data limits local-scale research utilizing GRACE and GRACE-FO missions. In this study, we develop a regional downscaling model based on the linear regression relationship between GWSA and environmental variables, reducing the grid resolution of GWSA obtained from GRACE from approximately 25 km to 1 km. First, we estimate the missing values of monthly continuous terrestrial water storage anomaly (TWSA) for the period from 2003 to 2020 using interpolated multi-channel singular spectrum analysis (IMSSA). Next, we apply the water balance equation to separate GWSA from TWSA, which is provided jointly by the Global Land Data Assimilation System (GLDAS) and the distributed ecohydrological model ESSI-3. We then employ a partial least squares regression (PLSR) model to identify the most significant environmental variables related to GWSA. Precipitation (Prec), normalized difference vegetation index (NDVI), and actual evapotranspiration (AET), with variable importance in projection (VIP) values greater than 1.0, are recognized as effective variables for reconstructing long-term, high-resolution groundwater storage changes. Finally, we downscale and reconstruct the long-term (2003–2020), high-resolution (1 km × 1 km) monthly GWSA in the Songhua River Basin using fused and supplemented GRACE/GRACE-FO data, employing either geographically weighted regression (GWR) or random forest (RF) models. The results demonstrate superior performance of the GWR model (CC = 0.995, NSE = 0.989, RMSE = 2.505 mm) compared to the RF model in downscaling. The downscaled GWSA in the Songhua River Basin not only achieves high spatial resolution but also exhibits improved accuracy when compared to in situ groundwater observation records. This research enhances understanding of spatiotemporal variations in regional groundwater due to local agricultural and industrial water use, providing a scientific basis for regional water resource management.
A Legendre Neural Network-Based Approach to Multiparameter Identification of Traffic Loads Across the Full Spatiotemporal Domain
Authors: Zhang He , Shen Ruihong , Zhou Yuhui , Zhang Cun , Zhang Zhicheng
Published: December 2024

The accurate identification of traffic loads acting on bridges provides an effective basis for the traffic control and operation of in-service bridges. To improve the efficiency and accuracy of loading identification, we propose an efficient multiparameter identification method with a Legendre neural network (LNN) for the monitoring of traffic loads across the full spatiotemporal domain. Compared to conventional studies that suffer from ill-posed problems and neural network-based means that lack a physically interpretable model, with the proposed strategy, both the explicit expression and time histories of the traffic load can be simultaneously obtained. Meanwhile, inaccurate load identification at the bridge’s supports, which is caused by ill-posed problems, does not exist in the identification process using the LNN. After the training and optimization of the LNN, its identification accuracy for speed and the magnitude of forces reached 98.6% and 98.3%, respectively. The results suggest that an identification method with a well-trained LNN is insensitive to noise.
MST-G: Micro Suction Tape Gripper Climbing Robot with Active Detachment Capability
Authors: Xiao Jichun , Nie Jiawei , Hao Lina , Li Zhi
Published: December 2024

Effective adaptive grasping capability is regarded as crucial for climbing robots. However, many dry adhesion legged climbing robots are primarily focused on mobility and load capacity to perform various climbing tasks, often overlooking their operational grasping abilities. Furthermore, flexible grippers designed for adaptive grasping are typically not capable of supporting autonomous climbing or perching motions; they must be rigidly integrated with legged climbing robots, which results in increased weight and reduced load capacity. To address this challenge, a novel dry adhesion climbing robot, MST-G, is proposed, featuring autonomous climbing, perching, and flexible adaptive grasping capabilities. During operation, MST-G is integrated with a legged climbing robot to perform tasks, but can autonomously climb when no task is present, thereby reducing load and ensuring stable motion. Additionally, a robust controller based on prescribed performance is introduced and tested on MST-G, which limits the joint tracking error to a prescribed safety limit, ensuring that motion trajectories can be executed safely and reliably.
Examining the Intersections of Family Risk, Foster Care, and Outcomes for Commercially Sexually Exploited Children
Authors: Furlong Courtney , Hinnant James Benjamin
Published: December 2024

Purpose: When individuals under the age of 18 are victimized by sex trafficking, it is termed commercial sexual exploitation of children (CSEC) in the United States. It is suggested that a history of engagement with the foster care system is one of the leading risk factors for CSEC. However, it is possible that it is the very factors that facilitate engagement with the foster care system (e.g., neglect, abuse, etc.) that establish vulnerability for CSEC victimization rather than the foster care system itself and that the foster care system serves a protective role for such victims. The purpose of this investigation is to examine the relationship between risk factors within the family of origin, foster care experiences, and outcomes for CSEC victims. Methods: Between 2014 and 2023, data were collected on minor victims of CSEC (n = 884) via the Child and Adolescent Needs and Strengths Assessment for Commercial Sexual Exploitation (CANS-CSE). Investigators conducted regression analyses to examine the relationship between family risk and foster care engagement (Aim 1). Foster care engagement (Aim 2) and number of foster care placements (Aim 3) are tested as moderators of associations between family risk factors and outcomes for youth. Results: Family risk is significantly associated with negative outcomes. Foster care placement and number of foster care placements do not moderate the link between family risk factors and negative outcomes for victims of CSEC. Conclusions: Results suggest that foster care does not protect against risks associated with families of origin and negative outcomes, a finding that may be unique for CSEC victims. Therefore, specialized, trauma-informed services should be implemented with CSEC victims who are engaged in the foster care system. In doing so, foster care could begin to serve a protective role in supporting young victims of CSEC and producing more positive outcomes.
Reducing the Consumption Gap Between Urban and Rural Areas: The Role of Rural Industrial Integration in China
Authors: Jin Huawang , Du Chuanzhong , Wang Mengchen , Wang Yameng , Chen Lei
Published: December 2024

The development of rural industry integration (RII) is an important way to revitalize China’s rural industry and resolve problems linked to urban–rural imbalance. This paper introduces a framework for theoretical analysis and offers a new insight into the impact mechanism of RII on the consumption gap between urban and rural areas (CGUR) and its sub-dimensions. On the basis of interprovincial panel data from 2011 to 2022, via the panel regression method and spatial econometric and mediating effect models, we empirically investigate the effect of RII on the CGUR. The results show that the development of RII can directly reduce the CGUR and has an obvious spatial spillover effect. Further examination and mechanism analysis indicate that the role of RII in reducing the CGUR is greater in terms of development consumption and enjoyment consumption than in terms of subsistence consumption. Mediating effect analysis shows that RII exerts a negative effect on the CGUR by promoting increases in farmers’ income and rural consumption and driving regional industrial upgrading. The conclusions not only help clarify the relationship between RII and the CGUR but also lead to suggestions for promoting the sustainable development of the rural industry and realizing rural revitalization in China’s new development stage.
A Knowledge Graph-Based Failure Information Fusion Method for Enhancing Reliability in Sustainable Systems
Authors: Zhang Yangqianhui , Yang Huayong , Han Dong
Published: December 2024

Failure Mode and Effects Analysis (FMEA) serves as a fundamental process in reliability analysis, providing critical insights into support system planning and equipment design optimization. However, traditional FMEA processes encounter several limitations, including restricted data availability, subjective expert assessments, and rigid structural requirements. The current evaluation approaches for expert opinions are constrained by small sample sizes, stringent requirements for structural consistency, and high demands for logical cohesion. To address these issues, this paper proposes a failure information fusion method utilizing a knowledge graph. By improving decision-making reliability and resource efficiency, the proposed method contributes to sustainable maintenance practices and operational sustainability. Furthermore, the method incorporates knowledge embedding technologies, facilitating reasoning through the transformation of graph structures into matrix representations. This process uncovers potential failure relationships and improves analytical depth. A case study involving an aircraft system is presented to demonstrate the method’s effectiveness and versatility, showcasing its potential to enhance reliability and support system planning.
Enhancement Effect of Phragmites australis Roots on Soil Shear Strength in the Yellow River Delta
Authors: Li Xinyue , Jin Kai , Qin Peng , Liu Chunxia , Zhu Xiuzhi , Zhang Yuyang , Zong Quanli
Published: December 2024

Soil erosion is one of the causes of ecosystem fragility in the Yellow River Delta. Plant roots can improve soil shear strength and effectively prevent soil erosion. However, there are no studies on soil shear strength in the Yellow River Delta. In this study, Phragmites australis (PA) root–soil composites with different root area ratios (RARs) (RARs = 0%, 0.06%, 0.14%, 0.17%, 0.19%, 0.24%, 0.36%) were prototypically sampled from the Yellow River Delta. Direct shear tests of root–soil composites were performed by a ZJ-type (three-speed) strain-controlled direct shear apparatus. The normal stresses were 25, 50, 100, and 200 kPa, and the shear rate was 1.2 mm/min. The results showed that PA roots significantly increased soil shear strength and cohesion with maximum growth rates of 219.0% and 440.1%, respectively. An optimal RAR of 0.14% in the range of 0~0.36% maximized the shear strength and cohesion of the root–soil composites. The internal friction angles of root–soil composites with different RARs did not differ significantly from those of the rootless soil. This indicates that the increase in shear strength was mainly due to an increase in cohesion. In addition, overall shear failure was the primary failure mode of rootless soil, with the roots pulled out of the soil in the root–soil composite failure mode. It is important to note that the root is deflected during shear in the direction opposite to the direction of the shear stress. These findings deepen our understanding of the effect of vegetation roots on soil shear characteristics and provide a scientific basis for the protection of bank slopes, soil and water conservation, and vegetation restoration in the Yellow River Delta.
Microgrid Optimization Strategy for Charging and Swapping Power Stations with New Energy Based on Multi-Agent Reinforcement Learning
Authors: Sun Hongbin , Duan Zhenyu , Yang Anyun
Published: December 2024

Aiming at the coordinated control of charging and swapping loads in complex environments, this research proposes an optimization strategy for microgrids with new energy charging and swapping stations based on adaptive multi-agent reinforcement learning. First, a microgrid model including charging and swapping loads, photovoltaic power generation, and wind power generation was constructed, and the Markov decision process was used to characterize the stochastic characteristics of new energy power generation, including charging and swapping loads. The deep relationship between uncertainty factors and charging and swapping laws was explored, and an adaptive multi-agent deep reinforcement learning method was used to optimize the random action selection process, improve the convergence speed of the coordinated optimization model, and realize coordinated control of multiple charging and swapping loads. Finally, through the analysis of different scenarios, the effectiveness of the proposed adaptive multi-agent reinforcement learning model for coordinated control of charging and swapping loads was verified. The results show that the proposed method has a faster convergence speed and can effectively optimize the charging process of charging and swapping loads, reducing power fluctuations of the newly connected energy grid.