bluuebunny/crossref_metadata_2025 huggingface dataset:
Technical Report: A Comprehensive Comparison between Different Quantification Versions of Nightingale Health’s 1H-NMR Metabolomics Platform
Authors: Bizzarri Daniele , Reinders Marcel J. T. , Beekman Marian , Slagboom P. Eline , van den Akker Erik B. ,   on behalf of the BbmriNl
Published: November 2023

1H-NMR metabolomics data is increasingly used to track health and disease. Nightingale Health, a major supplier of 1H-NMR metabolomics, has recently updated the quantification strategy to further align with clinical standards. Such updates, however, might influence backward replicability, particularly affecting studies with repeated measures. Using data from BBMRI-NL consortium (~28,000 samples from 28 cohorts), we compared Nightingale data, originally released in 2014 and 2016, with a re-quantified version released in 2020, of which both versions were based on the same NMR spectra. Apart from two discontinued and twenty-three new analytes, we generally observe a high concordance between quantification versions with 73 out of 222 (33%) analytes showing a mean ρ > 0.9 across all cohorts. Conversely, five analytes consistently showed lower Spearman’s correlations (ρ < 0.7) between versions, namely acetoacetate, LDL-L, saturated fatty acids, S-HDL-C, and sphingomyelins. Furthermore, previously trained multi-analyte scores, such as MetaboAge or MetaboHealth, might be particularly sensitive to platform changes. Whereas MetaboHealth replicated well, the MetaboAge score had to be retrained due to use of discontinued analytes. Notably, both scores in the re-quantified data recapitulated mortality associations observed previously. Concluding, we urge caution in utilizing different platform versions to avoid mixing analytes, having different units, or simply being discontinued.
Extraction Kinetics of Rare Earth Elements from Ion-Adsorbed Underclays
Authors: Prem Priscilla , Burgess Ward , Yang Jon , Verba Circe
Published: November 2023

Citric acid has been identified as an environmentally sustainable organic acid capable of leaching up to ~30% of easily accessible REEs from underclay material. An analysis of the leaching profiles was performed to discern the reaction rates, extraction efficiencies, and potential leaching mechanisms of REEs and cations of interest from ion-adsorbed underclays. The initial leaching stage follows a slow intraparticle diffusion mechanism followed by a second stage controlled by a mixed diffusion regime. The leaching profiles of Ca and P were similar to those of REEs, suggesting that REEs are most likely derived from mineral surfaces such as hydroxyapatite or crandallite rather than predominately from underclays. Fitting to a modified diffusion control model found diffusion-controlled leaching to be the primary mechanism whereas non-diffusive mechanisms made up about 22% of the extracted REEs. Gangue cations associated with underclays had less non-diffusive leaching than REE species, indicating that their leaching kinetics may be dominated by diffusion from within the material or potentially from product layer formation. Fitting to Boyd plots further indicated that REEs were leached following intraparticle diffusion control. These results have important implications for the development of more efficient and sustainable methods for extracting REEs or critical minerals from alternative feedstocks.
Deeply Derived Magma Controlling the Polymetallic Mineralization at Shuikoushan, South China: Constraints from Mineral U–Pb Dating and Whole-Rock Geochemistry
Authors: Wang Jionghui , Du Yulong , Zhang Fanghua , Li Qiushi , Zuo Changhu , Zhang Xi , Wang Yong , Wu Jiangwei , Ma Shengchao
Published: November 2023

Various magmatic–hydrothermal activities have resulted in different styles of polymetallic mineralization in South China. Shuikoushan is a large Fe-Cu-Pb-Zn-Au-Ag orefield situated in fold-and-thrust belts within the South China Block. Two types of granodiorite have been identified in recent drilling work. The early-stage, coarse-grained granodiorite has developed magnetite-bearing skarns in the deep level. The late-stage, fine-grained granodiorite is associated with garnet-hematite–magnetite–pyrite–sphalerite–chalcopyrite-bearing skarns in its contact zone. Away from the garnet-bearing skarn are calcite–quartz–pyrite–sphalerite–galena veinlets in faulted breccia. Fieldwork has identified iron mineralization in both skarns, whereas copper mineralization was only discovered in the garnet-bearing skarns. Lead, zinc, gold, and silver mineralization were observed in the garnet-bearing skarns and faulted breccia. Zircon U–Pb analyses suggested the emplacement of two granodiorite at 167.8 ± 0.8 Ma (MSWD = 1.1, N = 31) and 163.6 ± 0.7 Ma (MSWD = 1.3, N = 32). Apatite and garnet U–Pb dating further indicated the magnetite-bearing skarns of 166.2 ± 1.9 Ma (MSWD = 4.5, N = 27), the hematite–magnetite–sulfide-bearing skarns of 158.6 ± 2.8 Ma (MSWD = 1.3, N = 34), and the calcite–quartz–sulfide veinlets of 159.5 ± 5.2 Ma (MSWD = 1.7, N = 24). The time–space relationship between the two intrusions and hydrothermal activities suggests that the fine-grained granodiorite is responsible for polymetallic mineralization. Whole-rock geochemistry analyses demonstrated the enrichment of LILEs and the depletion of Nb and Ta in two granodiorites, with a slight enrichment in LREEs and flat HREE patterns. These granodiorite bodies therefore belong to high-K calc-alkaline magma generated via the crust’s partial melting. The fine-grained granodiorite generally has a lower HREE and higher Dy/Yb, Sr/Y ratios than coarse-grained granodiorite, corresponding to the source of magma in garnet stable lower crust. The residual garnet keeps ferric iron in melts, leaving the fine-granodiorite more oxidized for copper and gold concentration. Through these analyses and our drilling work, a continuous skarn–hydrothermal–epithermal system has been identified for Cu-Pb-Zn-Au-Ag targeting in Shuikoushan.
Synthesis of Nanocomposites and Catalysis Applications II
Authors: Gerasimov Evgeny
Published: November 2023

Nanocomposites, which refer to materials composed of nanoparticles dispersed in a matrix, have gained significant attention in various fields due to their unique properties and potential applications [...]
Zero- to One-Dimensional Zn24 Supraclusters: Synthesis, Structures and Detection Wavelength
Authors: Chen Yating , Chen Zhonghang , Wang Jiming , Ma Xuandi , Yuan Linyu , Zhang Shuhua , Tang Fushun
Published: November 2023

A zinc supracluster [Zn24(ATZ)18(AcO)30(H2O)1.5]·(H2O)3.5 (Zn24), and a 1D zinc supracluster chain {[Zn24(ATZ)18(AcO)30(C2H5OH)2(H2O)3]·(H2O)2.5}n (1-D⊂Zn24) with molecular diameters of 2 nm were synthesized under regulatory solvothermal conditions or the micro bottle method. In an N,N-dimethylformamide solution of Zn24, Fe3+, Ni2+, Cu2+, Cr2+ and Co2+ ions exhibited fluorescence-quenching effects, while the rare earth ions Ce3+, Dy3+, Er3+, Eu3+, Gd3+, Ho3+, La3+, Nd3+, Sm3+, and Tb3+showed no obvious fluorescence quenching. In ethanol solution, the Zn24 supracluster can be used to selectively detect Ce3+ ions with excellent efficiency (limit of detection (LOD) = 8.51 × 10−7 mol/L). The Zn24 supracluster can also detect wavelengths between 302 and 332 nm using the intensity of the emitted light.
Combating Obesity: Harnessing the Synergy of Postbiotics and Prebiotics for Enhanced Lipid Excretion and Microbiota Regulation
Authors: Zhao Yueming , Zheng Yaping , Xie Kui , Hou Yanmei , Liu Qingjing , Jiang Yujun , Zhang Yu , Man Chaoxin
Published: November 2023

Obesity is a chronic metabolic disease that can be induced by a high-fat diet (HFD) and predisposes to a variety of complications. In recent years, various bioactive substances, such as probiotics, prebiotics, and postbiotics, have been widely discussed because of their good anti-lipid and anti-inflammatory activities. In this paper, soybean protein isolate was used as a substrate to prepare the postbiotic. Compound prebiotics (galactose oligosaccharides, fructose oligosaccharides, and lactitol) preparation Aunulife Postbiotics and Prebiotics Composition (AYS) is the research object. Weight loss and bowel movements in mice induced by a high-fat diet were studied. Moreover, qualitative and quantitative analyses of small-molecule metabolites in AYS were performed to identify the functional molecules in AYS. After 12 weeks of feeding, the weight gain of mice that were fed with high-dose AYS (group H) and low-dose AYS (group L) from 4 to 12 weeks was 6.72 g and 5.25 g (p < 0.05), both of which were significantly lower than that of the high-fat diet (group DM, control group) group (7.73 g) (p < 0.05). Serum biochemical analysis showed that TC, TG, and LDL-C levels were significantly lower in mice from the H and L groups (p < 0.05). In addition, the fecal lipid content of mice in the L group reached 5.89%, which was significantly higher than that of the DM group at 4.02% (p < 0.05). The study showed that AYS changed the structure of the intestinal microbiota in mice on a high-fat diet, resulting in a decrease in the relative abundance of Firmicutes and Muribaculaceae and an increase in the relative abundance of Bacteroidetes, Verrucomicrobia, and Lactobacillus. The metabolomics study results of AYS showed that carboxylic acids and derivatives, and organonitrogen compounds accounted for 51.51% of the AYS metabolites, among which pantothenate, stachyose, betaine, and citrate had the effect of preventing obesity in mice. In conclusion, the administration of prebiotics and postbiotic-rich AYS reduces weight gain and increases fecal lipid defecation in obese mice, potentially by regulating the intestinal microbiota of mice on a high-fat diet.
Preterm Birth and Its Association with Maternal Diet, and Placental and Neonatal Telomere Length
Authors: Lis Nikoletta , Lamnisos Demetris , Bograkou-Tzanetakou Aikaterini , Hadjimbei Elena , Tzanetakou Irene P.
Published: November 2023

Preterm birth (PTB), a multi-causal syndrome, is one of the global epidemics. Maternal nutrition, but also neonatal and placental telomere length (TL), are among the factors affecting PTB risk. However, the exact relationship between these factors and the PTB outcome, remains obscure. The aim of this review was to investigate the association between PTB, maternal nutrition, and placental-infant TL. Observational studies were sought with the keywords: maternal nutrition, placental TL, newborn, TL, and PTB. No studies were found that included all of the keywords simultaneously, and thus, the keywords were searched in dyads, to reach assumptive conclusions. The findings show that maternal nutrition affects PTB risk, through its influence on maternal TL. On the other hand, maternal TL independently affects PTB risk, and at the same time PTB is a major determinant of offspring TL regulation. The strength of the associations, and the extent of the influence from covariates, remains to be elucidated in future research. Furthermore, the question of whether maternal TL is simply a biomarker of maternal nutritional status and PTB risk, or a causative factor of PTB, to date, remains to be answered.
Diagnostic Accuracy of [68Ga]Ga Labeled Fibroblast-Activation Protein Inhibitors in Detecting Head and Neck Cancer Lesions Using Positron Emission Tomography: A Systematic Review and a Meta-Analysis
Authors: Rizzo Alessio , Miceli Alberto , Racca Manuela , Bauckneht Matteo , Morbelli Silvia , Albano Domenico , Dondi Francesco , Bertagna Francesco , Galizia Danilo , Muoio Barbara , Annunziata Salvatore , Treglia Giorgio
Published: November 2023

Several studies have examined the use of positron emission tomography (PET) using [68Ga]Ga-radiolabeled fibroblast-activation protein inhibitors (FAPi) across multiple subtypes of head and neck cancer (HNC). The purpose of the present study was to evaluate the diagnostic accuracy of a newly developed molecular imaging approach in the context of HNC through a comprehensive review and meta-analysis. A thorough literature review was conducted to identify scholarly articles about the diagnostic effectiveness of FAP-targeted PET imaging. The present study incorporates original publications assessing the efficacy of this innovative molecular imaging test in both newly diagnosed and previously treated HNC patients. This systematic review examined eleven investigations, of which nine were deemed suitable for inclusion in the subsequent meta-analysis. The quantitative synthesis yielded a pooled detection rate of 99% for primary HNC lesions. Additionally, on a per patient-based analysis, the pooled sensitivity and specificity for regional lymph node metastases were found to be 90% and 84%, respectively. The analysis revealed a statistical heterogeneity among the studies for the detection rate of primary HNC lesions. The quantitative findings presented in this study indicate a favorable diagnostic performance of FAP-targeted PET imaging in detecting primary HNC tumors. In contrast, discordant results concerning the diagnostic accuracy of lymph node metastases were found. However, further multicentric trials are required to validate the efficacy of FAP-targeted PET in this specific group of patients.
The Anti-Nociceptive Effects of Nicotine in Humans: A Systematic Review and Meta-Analysis
Authors: Luo Yujia , Yang Yating , Schneider Carl , Balle Thomas
Published: November 2023

Background: Pain can have a serious impact on a patient’s physical, mental, and social health, often causing their quality of life to decline. Various nicotine dosage forms, such as nicotine patches and nasal spray, have been developed and used as analgesics in clinical settings. However, there is controversy over the anti-nociceptive effects of nicotine among different clinical trials. The purpose of this meta-analysis is to quantify the analgesic effect of nicotine patches, nicotine nasal spray, and tobacco smoking on pain in humans. Methods: Relevant articles published in English prior to July 2023 were identified using the PubMed, Cochrane Library, and Embase online databases in accordance with PRISMA (2020) guidelines. Two reviewers independently screened and selected studies, extracted data, and assessed the quality of the included studies using version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB 2). RStudio was used for data synthesis, heterogeneity assessment, sensitivity analysis, publication bias assessment, trim-and-fill analyses, and generating forest plots. Results: Sixteen eligible articles, including k = 5 studies of pain tolerance (n = 210), k = 5 studies of pain threshold (n = 210), and k = 12 studies of pain scores (N = 1249), were included for meta-analysis. Meta-analytic integration for pain threshold (Hedges’ g = 0.28, 95% CI = 0–0.55, Z = 1.99, p = 0.05) and pain tolerance (Hedges’ g = 0.32, 95% CI = 0.05–0.59, Z = 2.30, p = 0.02) revealed that nicotine administered via tobacco smoke generated acute analgesic effects to thermal stimuli. Meta-analytic integration for pain scores revealed that nicotine had a weak anti-nociceptive effect on postoperative pain of −0.37 (95% CI = −0.77 to 0.03, Z = −1.80) but with no statistical significance (p = 0.07). In addition, a limited number of included studies revealed that long-term smoking produced hyperalgesia that may be characterized as small to medium in magnitude (Hedges’ g = 0.37, 95% CI = 0.29–0.64, Z = 5.33, p < 0.01). Conclusion: These results help to clarify the mixed outcomes of trials and may ultimately inform the treatment of pain. We observed that acute nicotine administration prolonged the laboratory-induced pain threshold and tolerance time and may mildly relieve postoperative pain. In addition, long-term tobacco smoking may have a nociceptive effect on different types of chronic pain. More research is needed to determine the anti-nociceptive effects of nicotine in humans, and to understand the optimal timing, dose, and method of delivery of nicotine.
Stability Studies of Antipseudomonal Beta Lactam Agents for Outpatient Therapy
Authors: Fernández-Rubio Beatriz , Herrera-Hidalgo Laura , de Alarcón Arístides , Luque-Márquez Rafael , López-Cortés Luis E. , Luque Sònia , Gutiérrez-Urbón José María , Fernández-Polo Aurora , Gutiérrez-Valencia Alicia , Gil-Navarro María V.
Published: November 2023

Outpatient parenteral antimicrobial therapy (OPAT) is a useful treatment strategy against Pseudomonas aeruginosa and other multidrug-resistant bacteria. However, it is hindered by the lack of stability data for the administration of antibiotics under OPAT conditions. Our objective was to investigate the stability of nine antipseudomonal and broad-spectrum beta lactam antibiotics (aztreonam, cefepime, cefiderocol, ceftazidime, ceftazidime/avibactam, ceftolozane/tazobactam, meropenem, meropenem/vaborbactam, and piperacillin/tazobactam) to allow the spread of OPAT programs. All the antibiotics were diluted in 500 mL 0.9% sodium chloride and stored at 4, 25, 32, and 37 °C for 72 h in two different devices (infusion bags and elastomeric pumps). The solutions were considered stable if the color, clearness, and pH remained unchanged and if the percentage of intact drug was ≥90%. All the antimicrobials remained stable 72 h under refrigerated conditions and at least 30 h at 25 °C. At 32 °C, all the antibiotics except for meropenem and meropenem/vaborbactam remained stable for 24 h or more. At 37 °C, only aztreonam, piperacillin/tazobactam, cefepime, cefiderocol, and ceftolozane/tazobactam were stable for at least 24 h. The stability results were the same in the two devices tested. All the antibiotics studied are actual alternatives for the treatment of antipseudomonal or multidrug-resistant infections in OPAT programs, although the temperature of the devices is crucial to ensure antibiotic stability.
New Approach for Processing Recycled Carbon Staple Fiber Yarns into Unidirectionally Reinforced Recycled Carbon Staple Fiber Tape
Authors: Detzel Martin , Mitschang Peter , Breuer Ulf
Published: November 2023

This study describes a novel process in which staple fiber yarns made from recycled carbon fibers (rCFs) and polyamide 6 (PA6) fibers are further processed into semi-finished tape products in a modified impregnation and calendaring process. In this process, the staple fiber yarns are heated above the melting temperature of the polymer, impregnated, and stretched to staple fiber tapes (SF tapes) in the calendaring unit. SF tapes with different degrees of stretching and/or repasses were produced. The individual width and thickness were measured in line by a laser profile sensor. From these tapes, preforms were manually laid and processed into laminates in an autoclave. The important physical properties of the unidirectionally reinforced laminates made of the tapes were compared with organic sheets wound from staple fiber yarns. With increasing stretching, both the fiber orientation and mechanical properties improved compared to the organic sheets made from unstretched staple fiber yarns. An improvement in fiber orientation relative to the process direction from 66.3% to 91.9% (between ±10°) and 39.1% to 71.6% (between ±5°), respectively, was achieved for a two-stage stretched tape. The tensile and flexural moduli were increased by 15.2% and 14.5%, respectively.
Dynamic Behavior Modeling of Natural-Rubber/Polybutadiene-Rubber-Based Hybrid Magnetorheological Elastomer Sandwich Composite Structures
Authors: N Ahobal , Jakkamputi Lakshmi Pathi , Gnanasekaran Sakthivel , Thangamuthu Mohanraj , Rakkiyannan Jegadeeshwaran , Bhalerao Yogesh Jayant
Published: November 2023

This study investigates the dynamic characteristics of natural rubber (NR)/polybutadiene rubber (PBR)-based hybrid magnetorheological elastomer (MRE) sandwich composite beams through numerical simulations and finite element analysis, employing Reddy’s third-order shear deformation theory. Four distinct hybrid MRE sandwich configurations were examined. The validity of finite element simulations was confirmed by comparing them with results from magnetorheological (MR)-fluid-based composites. Further, parametric analysis explored the influence of magnetic field intensity, boundary conditions, ply orientation, and core thickness on beam vibration responses. The results reveal a notable 10.4% enhancement in natural frequencies in SC4-based beams under a 600 mT magnetic field with clamped–free boundary conditions, attributed to the increased PBR content in MR elastomer cores. However, higher magnetic field intensities result in slight frequency decrements due to filler particle agglomeration. Additionally, augmenting magnetic field intensity and magnetorheological content under clamped–free conditions improves the loss factor by from 66% to 136%, presenting promising prospects for advanced applications. This research contributes to a comprehensive understanding of dynamic behavior and performance enhancement in hybrid MRE sandwich composites, with significant implications for engineering applications. Furthermore, this investigation provides valuable insights into the intricate interplay between magnetic field effects, composite architecture, and vibration response.
Siloxane-Modified UV-Curable Castor-Oil-Based Waterborne Polyurethane Superhydrophobic Coatings
Authors: Yu Qianhui , Zhang Zengshuai , Tan Pengyun , Zhou Jiahao , Ma Xiaojing , Shao Yingqing , Wei Shuangying , Gao Zhenhua
Published: November 2023

In recent years, superhydrophobic coatings with self-cleaning abilities have attracted considerable attention. In this study, we introduced hydroxyl-terminated polydimethylsiloxane (OH−PDMS) into castor-oil-based waterborne polyurethanes and synthesized silicone-modified castor-oil-based UV-curable waterborne polyurethanes (SCWPU). Further, we identified the optimal amount of OH−PDMS to be added and introduced different amounts of micro- and nanoscale heptadecafluorodecyltrimethoxysilane-modified SiO2 particles (FAS−SiO2) to prepare rough-surface SCWPU coatings with dense micro- and nanostructures, thus realizing waterborne superhydrophobic coatings. The results show that when the OH−PDMS content was 11 wt% and the total addition of FAS−SiO2 particles was 50% (with a 1:1:1 ratio of 100 nm, 1 µm, and 10 nm particles), the coatings exhibited a self-cleaning ability and superhydrophobicity with a contact angle of (152.36 ± 2.29)° and a roll-off angle of (4.9 ± 1.0)°. This castor-oil-based waterborne superhydrophobic coating has great potential for waterproofing, anti-fouling, anti-corrosion, and other applications.
Study on Self-Humidification in PEMFC with Crossed Flow Channels and an Ultra-Thin Membrane
Authors: Wang Chenlong , Chen Xiaosong , Xiang Xin , Zhang Heng , Huang Zhiping , Huang Xinhao , Zhan Zhigang
Published: November 2023

In this study, a 3D model of a proton exchange membrane fuel cell (PEMFC) with crossed channels and an ultra-thin membrane is developed to investigate the feasibility of self-humidification; experiments utilizing a PEMFC stack with identical configurations are conducted to validate the simulation results and further investigate the effects of various operating conditions (OCs) on self-humidification. The results indicate that the crossed flow channel leads to enhanced uniformity of water distribution, resulting in improved cell performance under low/no humidification conditions. External humidifiers for the anode can be removed since the performance difference is negligible (≤3%) between RHa = 0% and 100%. Self-humidification can be achieved in the stack at 90 °C or below with an appropriate back pressure among 100–200 kPa. As the current density increases, there is a gradual convergence and crossing of the voltage at low RH with that at high RH, and the crossover points are observed at 60–80 °C with suitable pressure when successful self-humidification is achieved. Below the current density of the point, the stack’s performance is inferior at lower RH due to membrane unsaturation, and conversely, the performance is inferior at higher RH due to flooding; this current density decreases with higher pressure and lower temperature.
Recycled PET Composites Reinforced with Stainless Steel Lattice Structures Made by AM
Authors: Rusu Mircea , Balc Nicolae , Moldovan Marioara , Cuc Stanca , Petean Ioan , Cosma Cosmin , Leordean Dan
Published: November 2023

Polyethylene terephthalate (PET) recycling is one of the most important environmental issues, assuring a cleaner environment and reducing the carbon footprint of technological products, taking into account the quantities used year by year. The recycling possibilities depend on the quality of the collected material and on the targeted product. Current research aims to increase recycling quantities by putting together recycled PET in an innovative way as a filler for the additive manufactured metallic lattice structure. Starting from the structures mentioned above, a new range of composite materials was created: IPC (interpenetrating phase composites), materials with a complex architecture in which a solid phase, the reinforcement, is uniquely combined with the other phase, heated to the temperature of melting. The lattice structure was modeled by the intersection of two rings using Solid Works, which generates the lattice structure, which was further produced by an additive manufacturing technique from 316L stainless steel. The compressive strength shows low values for recycled PET, of about 26 MPa, while the stainless-steel lattice structure has about 47 MPa. Recycled PET molding into the lattice structure increases its compressive strength at 53 MPa. The Young’s moduli are influenced by the recycled PET reinforcement by an increase from about 1400 MPa for the bare lattice structure to about 1750 MPa for the reinforced structure. This sustains the idea that recycled PET improves the composite elastic behavior due to its superior Young’s modulus of about 1570 MPa, acting synergically with the stainless-steel lattice structure. The morphology was investigated with SEM microscopy, revealing the binding ability of recycled PET to the 316L surface, assuring a coherent composite. The failure was also investigated using SEM microscopy, revealing that the microstructural unevenness may act as a local tensor, which promotes the interfacial failure within local de-laminations that weakens the composite, which finally breaks.
RANet: Relationship Attention for Hyperspectral Anomaly Detection
Authors: Shao Yingzhao , Li Yunsong , Li Li , Wang Yuanle , Yang Yuchen , Ding Yueli , Zhang Mingming , Liu Yang , Gao Xiangqiang
Published: November 2023

Hyperspectral anomaly detection (HAD) is of great interest for unknown exploration. Existing methods only focus on local similarity, which may show limitations in detection performance. To cope with this problem, we propose a relationship attention-guided unsupervised learning with convolutional autoencoders (CAEs) for HAD, called RANet. First, instead of only focusing on the local similarity, RANet, for the first time, pays attention to topological similarity by leveraging the graph attention network (GAT) to capture deep topological relationships embedded in a customized incidence matrix from absolutely unlabeled data mixed with anomalies. Notably, the attention intensity of GAT is self-adaptively controlled by adjacency reconstruction ability, which can effectively reduce human intervention. Next, we adopt an unsupervised CAE to jointly learn with the topological relationship attention to achieve satisfactory model performance. Finally, on the basis of background reconstruction, we detect anomalies by the reconstruction error. Extensive experiments on hyperspectral images (HSIs) demonstrate that our proposed RANet outperforms existing fully unsupervised methods.
Surface Soil Moisture Determination of Irrigated and Drained Agricultural Lands with the OPTRAM Method and Sentinel-2 Observations
Authors: Stańczyk Tomasz , Kasperska-Wołowicz Wiesława , Szatyłowicz Jan , Gnatowski Tomasz , Papierowska Ewa
Published: November 2023

Surface soil moisture (SSM) is one of the factors affecting plant growth. Methods involving direct soil moisture measurement in the field or requiring laboratory tests are commonly used. These methods, however, are laborious and time-consuming and often give only point-by-point results. In contrast, SSM can vary across a field due to uneven precipitation, soil variability, etc. An alternative is using satellite data, for example, optical data from Sentinel-2 (S2). The main objective of this study was to assess the accuracy of SSM determination based on S2 data versus standard measurement techniques in three different agricultural areas (with irrigation and drainage systems). In the field, we measured SSM manually using non-destructive techniques. Based on S2 data, we estimated SSM using the optical trapezoid model (OPTRAM) and calculated eighteen vegetation indices. Using the OPTRAM model gave a high SSM estimating accuracy (R2 = 0.67, RMSE = 0.06). The use of soil porosity in the OPTRAM model significantly improved the results. Among the vegetation indices, at the NDVI ≤ 0.2, the highest value of R2 was obtained for the STR to OPTRAM index, while at the NDVI > 0.2, the shadow index had the highest R2 comparable with OPTRAM.
Optical and Thermal Image Processing for Monitoring Rainfall Triggered Shallow Landslides: Insights from Analogue Laboratory Experiments
Authors: Cosentino Antonio , Marmoni Gian Marco , Fiorucci Matteo , Mazzanti Paolo , Scarascia Mugnozza Gabriele , Esposito Carlo
Published: November 2023

This study explores the innovative use of digital image processing (DIP) techniques, also named PhotoMonitoring, for analysing the triggering conditions of shallow landslides. The approach, based on the combination of optical and infrared thermographic imaging (IRT), was applied to a laboratory-scale slope, reproduced in a flume test apparatus. Three experiments were conducted to replicate rainfall-induced shallow landslides, applying change detection and digital image correlation analysis to both optical and thermal images. The method combines IRT’s ability to measure ground surface temperature changes with DIP’s capacity to track movement and displacement. Results showed the high reliability of the displacement time-series obtained through IRT-DIP with respect to the reference optical-DIP. The IRT-DIP technique also detects anomaly signals two minutes before landslide occurrence that can be regarded as a possible failure precursor. This study testifies to the potential of image analysis as a remote sensing technique, demonstrating the ability of DIP to capture the dynamics of shallow landslides, as well as the advantages of optical–IRT combinations to follow slope deformation processes during night-time. This approach, if properly adapted to real-scale scenarios, may contribute to a better understanding of landslide behaviour, improve landslide monitoring strategies, and promote more effective early warning systems (EWS).
Research on the Characteristic Spectral Band Determination for Water Quality Parameters Retrieval Based on Satellite Hyperspectral Data
Authors: Xia Xietian , Lu Hui , Xu Zenghui , Li Xiang , Tian Yu
Published: November 2023

Hyperspectral remote sensing technology has been widely used in water quality monitoring. However, while it provides more detailed spectral information for water quality monitoring, it also gives rise to issues such as data redundancy, complex data processing, and low spatial resolution. In this study, a novel approach was proposed to determine the characteristic spectral band of water quality parameters based on satellite hyperspectral data, aiming to improve data utilization of hyperspectral data and to achieve the same precision monitoring of multispectral data. This paper first introduces the data matching method of satellite hyperspectral data and water quality based on space–time information for guidance in collecting research data. Secondly, the customizable and fixed spectral bands of the existing multispectral camera products were studied and used for the preprocessing of hyperspectral data. Then, the determination approach of characteristic spectral bands of water quality parameters is proposed based on the correlation between the reflectance of different bands and regression modeling. Next, the model performance for retrieval of various water quality parameters was compared between the typical empirical method and artificial neural network (ANN) method of different spectral band sets with different band numbers. Finally, taking the adjusted determination coefficient R2¯ as an evaluation index for the models, the results show that the ANN method has obvious advantages over the empirical method, and band set providing more band options improves the model performance. There is an optimal band number for the characteristic spectral bands of water quality parameters. For permanganate index (CODMn), dissolved oxygen (DO), and conductivity (EC), the R2¯ of the optimal ANN model with three bands can reach about 0.68, 0.43, and 0.49, respectively, whose mean absolute percentage error (MAPE) values are 14.02%, 16.26%, and 17.52%, respectively. This paper provides technical guidance for efficient utilization of hyperspectral data by determination of characteristic spectral bands, the theoretical basis for customization of multispectral cameras, and the subsequent water quality monitoring through remote sensing using a multispectral drone.
A Low-Cost and Robust Multi-Sensor Data Fusion Scheme for Heterogeneous Multi-Robot Cooperative Positioning in Indoor Environments
Authors: Cai Zhi , Liu Jiahang , Chi Weijian , Zhang Bo
Published: November 2023

The latest development of multi-robot collaborative systems has put forward higher requirements for multi-sensor fusion localization. Current position methods mainly focus on the fusion of the carrier’s own sensor information, and how to fully utilize the information of multiple robots to achieve high-precision positioning is a major challenge. However, due to the comprehensive impact of factors such as poor performance, variety, complex calculations, and accumulation of environmental errors used by commercial robots, the difficulty of high-precision collaborative positioning is further exacerbated. To address this challenge, we propose a low-cost and robust multi-sensor data fusion scheme for heterogeneous multi-robot collaborative navigation in indoor environments, which integrates data from inertial measurement units (IMUs), laser rangefinders, cameras, and so on, into heterogeneous multi-robot navigation. Based on Discrete Kalman Filter (DKF) and Extended Kalman Filter (EKF) principles, a three-step joint filtering model is used to improve the state estimation and the visual data are processed using the YOLO deep learning target detection algorithm before updating the integrated filter. The proposed integration is tested at multiple levels in an open indoor environment following various formation paths. The results show that the three-dimensional root mean square error (RMSE) of indoor cooperative localization is 11.3 mm, the maximum error is less than 21.4 mm, and the motion error in occluded environments is suppressed. The proposed fusion scheme is able to satisfy the localization accuracy requirements for efficient and coordinated motion of autonomous mobile robots.
A Real-Time Subway Driver Action Sensoring and Detection Based on Lightweight ShuffleNetV2 Network
Authors: Shen Xing , Wei Xiukun
Published: November 2023

The driving operations of the subway system are of great significance in ensuring the safety of trains. There are several hand actions defined in the driving instructions that the driver must strictly execute while operating the train. The actions directly indicate whether equipment is normally operating. Therefore, it is important to automatically sense the region of the driver and detect the actions of the driver from surveillance cameras to determine whether they are carrying out the corresponding actions correctly or not. In this paper, a lightweight two-stage model for subway driver action sensoring and detection is proposed, consisting of a driver detection network to sense the region of the driver and an action recognition network to recognize the category of an action. The driver detection network adopts the pretrained MobileNetV2-SSDLite. The action recognition network employs an improved ShuffleNetV2, which incorporates a spatial enhanced module (SEM), improved shuffle units (ISUs), and shuffle attention modules (SAMs). SEM is used to enhance the feature maps after convolutional downsampling. ISU introduces a new branch to expand the receptive field of the network. SAM enables the model to focus on important channels and key spatial locations. Experimental results show that the proposed model outperforms 3D MobileNetV1, 3D MobileNetV3, SlowFast, SlowOnly, and SE-STAD models. Furthermore, a subway driver action sensoring and detection system based on a surveillance camera is built, which is composed of a video-reading module, main operation module, and result-displaying module. The system can perform action sensoring and detection from surveillance cameras directly. According to the runtime analysis, the system meets the requirements for real-time detection.
Riverine Microplastic Quantification: A Novel Approach Integrating Satellite Images, Neural Network, and Suspended Sediment Data as a Proxy
Authors: Mohsen Ahmed , Kovács Ferenc , Kiss Tímea
Published: November 2023

Rivers transport terrestrial microplastics (MP) to the marine system, demanding cost-effective and frequent monitoring, which is attainable through remote sensing. This study aims to develop and test microplastic concentration (MPC) models directly by satellite images and indirectly through suspended sediment concentration (SSC) as a proxy employing a neural network algorithm. These models relied upon high spatial (26 sites) and temporal (198 samples) SSC and MPC data in the Tisza River, along with optical and active sensor reflectance/backscattering. A feedforward MLP neural network was used to calibrate and validate the direct models employing k-fold cross-validation (five data folds) and the Optuna library for hyperparameter optimization. The spatiotemporal generalization capability of the developed models was assessed under various hydrological scenarios. The findings revealed that hydrology fundamentally influences the SSC and MPC. The indirect estimation method of MPC using SSC as a proxy demonstrated higher accuracy (R2 = 0.17–0.88) than the direct method (R2 = 0–0.2), due to the limitations of satellite sensors to directly estimate the very low MPCs in rivers. However, the estimation accuracy of the indirect method varied with lower accuracy (R2 = 0.17, RMSE = 12.9 item/m3 and MAE = 9.4 item/m3) during low stages and very high (R2 = 0.88, RMSE = 7.8 item/m3 and MAE = 10.8 item/m3) during floods. The worst estimates were achieved based on Sentinel-1. Although the accuracy of the MPC models is moderate, it still has practical applicability, especially during floods and employing proxy models. This study is one of the very initial attempts towards MPC quantification, thus more studies incorporating denser spatiotemporal data, additional water quality parameters, and surface roughness data are warranted to improve the estimation accuracy.
Chewing Analysis by Means of Electromagnetic Articulography: Current Developments and New Possibilities
Authors: Marinelli Franco , Venegas Camila , Alarcón Josefa , Navarro Pablo , Fuentes Ramón
Published: November 2023

Chewing is a complex procedure that involves sensory feedback and motor impulses controlled by the trigeminal system in the brainstem. The analysis of mandibular movement is a first approximation to understanding these mechanisms. Several recording methods have been tested to achieve this. Video, ultrasound, the use of external markers and kinesiographs are examples of recording systems used in research. Electromagnetic articulography is an alternative method to those previously mentioned. It consists of the use of electromagnetic fields and receiver coils. The receiver coils are placed on the points of interest and the 3D coordinates of movement are saved in binary files. In the Oral Physiology Laboratory of the Dental Sciences Research Center (Centro de Investigación en Ciencias Odontológicas—CICO), in the Faculty of Dentistry at the Universidad de La Frontera (Temuco, Chile) several research studies have been carried out using the AG501 3D EMA articulograph (Carstens Medizinelektronik, Lenglern, Germany). With this device, they developed a series of protocols to record mandibular movement and obtain new information, such as the 3D Posselt polygon, the area of each polygon, individualized masticatory cycles and speed and acceleration profiles. Other investigations have analyzed these parameters, but separately. The AG501 allows for holistic analysis of all these data without altering natural movement. A limitation of this technology is the interference generated by its metallic elements. The aim of the present work is to show the developed methods used to record mandibular movement in the CICO, using the AG501 and compare them with others used in several research studies.
Designing a Tangible User Interface (TUI) for the Elderly Based on Their Motivations and Game Elements
Authors: Salazar-Cardona Johnny Alexander , Cano Sandra , Gutiérrez-Vela Francisco Luis , Arango Jeferson
Published: November 2023

The elderly population has grown significantly in recent years, requiring strategies focused on promoting active aging to improve health and well-being. It may be achieved in many ways, including using technology for this population. We propose an interactive system for older adults based on a tangible user interface. A group of 10 experts conducted a heuristic evaluation of a system of this type utilizing a questionnaire and obtaining satisfactory results. This study evaluated the older adult population’s fun and pervasive game experience. The results will provide a basis for continuing to build this interactive system to promote active aging in older adults, either at the cognitive or physical level, depending on the applied approach.
EfficientRMT-Net—An Efficient ResNet-50 and Vision Transformers Approach for Classifying Potato Plant Leaf Diseases
Authors: Shaheed Kashif , Qureshi Imran , Abbas Fakhar , Jabbar Sohail , Abbas Qaisar , Ahmad Hafsa , Sajid Muhammad Zaheer
Published: November 2023

The primary objective of this study is to develop an advanced, automated system for the early detection and classification of leaf diseases in potato plants, which are among the most cultivated vegetable crops worldwide. These diseases, notably early and late blight caused by Alternaria solani and Phytophthora infestans, significantly impact the quantity and quality of global potato production. We hypothesize that the integration of Vision Transformer (ViT) and ResNet-50 architectures in a new model, named EfficientRMT-Net, can effectively and accurately identify various potato leaf diseases. This approach aims to overcome the limitations of traditional methods, which are often labor-intensive, time-consuming, and prone to inaccuracies due to the unpredictability of disease presentation. EfficientRMT-Net leverages the CNN model for distinct feature extraction and employs depth-wise convolution (DWC) to reduce computational demands. A stage block structure is also incorporated to improve scalability and sensitive area detection, enhancing transferability across different datasets. The classification tasks are performed using a global average pooling layer and a fully connected layer. The model was trained, validated, and tested on custom datasets specifically curated for potato leaf disease detection. EfficientRMT-Net’s performance was compared with other deep learning and transfer learning techniques to establish its efficacy. Preliminary results show that EfficientRMT-Net achieves an accuracy of 97.65% on a general image dataset and 99.12% on a specialized Potato leaf image dataset, outperforming existing methods. The model demonstrates a high level of proficiency in correctly classifying and identifying potato leaf diseases, even in cases of distorted samples. The EfficientRMT-Net model provides an efficient and accurate solution for classifying potato plant leaf diseases, potentially enabling farmers to enhance crop yield while optimizing resource utilization. This study confirms our hypothesis, showcasing the effectiveness of combining ViT and ResNet-50 architectures in addressing complex agricultural challenges.
Design and Experimental Results of a Three-Dimensional Force Sensor for Shearer Cutting Pick Force Monitoring
Authors: Miao Bing , Li Yunwang , Guo Yinan , You Xiusong , Ge Shirong
Published: November 2023

The main focus of this work is the design and development of a three-dimensional force sensor for the cutting pick of a coal mining shearer’s simulated drum. This sensor is capable of simultaneously measuring the magnitude of force along three directions of the cutting pick during the cutting sample process. The three-dimensional force sensor is built based on the strain theory of material mechanics, and reasonable structural design is implemented to improve its sensitivity and reduce inter-axis coupling errors. The strain distribution of the sensor is analyzed using finite element analysis software, and the distribution of the strain gauges is determined based on the analysis results. In addition, a calibration test system is designed for the sensor, and the sensitivity, linearity, and inter-axis coupling errors of the sensor are calibrated and tested using loading experiments in three mutually perpendicular directions. Modal simulation analysis and actual cutting pick testing of the coal mining machine’s simulated drum are conducted to study the dynamic characteristics and functionality of the sensor in practical applications. The experimental results depict sensitivities of 0.748 mV/V, 2.367 mV/V, and 2.83 mV/V for the newly developed sensor, respectively. Furthermore, the cross-sensitivity error was lower than 5.02%. These findings validate that the sensor’s structure satisfies the measurement requirements for pick-cutting forces.
A Bibliometric Analysis of Neuroscience Tools Use in Construction Health and Safety Management
Authors: Ding Zhikun , Xiong Zhaoyang , Ouyang Yewei
Published: November 2023

Despite longstanding traditional construction health and safety management (CHSM) methods, the construction industry continues to face persistent challenges in this field. Neuroscience tools offer potential advantages in addressing these safety and health issues by providing objective data to indicate subjects’ cognition and behavior. The application of neuroscience tools in the CHSM has received much attention in the construction research community, but comprehensive statistics on the application of neuroscience tools to CHSM is lacking to provide insights for the later scholars. Therefore, this study applied bibliometric analysis to examine the current state of neuroscience tools use in CHSM. The development phases; the most productive journals, regions, and institutions; influential scholars and articles; author collaboration; reference co-citation; and application domains of the tools were identified. It revealed four application domains: monitoring the safety status of construction workers, enhancing the construction hazard recognition ability, reducing work-related musculoskeletal disorders of construction workers, and integrating neuroscience tools with artificial intelligence techniques in enhancing occupational safety and health, where magnetoencephalography (EMG), electroencephalography (EEG), eye-tracking, and electrodermal activity (EDA) are four predominant neuroscience tools. It also shows a growing interest in integrating the neuroscience tools with artificial intelligence techniques to address the safety and health issues. In addition, future studies are suggested to facilitate the applications of these tools in construction workplaces by narrowing the gaps between experimental settings and real situations, enhancing the quality of data collected by neuroscience tools and performance of data processing algorithms, and overcoming user resistance in tools adoption.