bluuebunny/crossref_metadata_2025 huggingface dataset:
Significance of PET/CT Imaging in Myeloma Assessment: Exploring Novel Applications beyond Osteolytic Lesion Detection and Treatment Response
Authors: Zirakchian Zadeh Mahdi
Published: January 2024

In multiple myeloma (MM), specific cytokines produced by plasma cells disrupt the equilibrium between osteoblasts and osteoclasts. As a result, MM patients experience an increase in osteoclast activity and a decrease in osteoblast activity. This disparity is fundamental to the development of myeloma bone disease. Lytic lesions, which are a feature of MM, can result in pathologic fractures and excruciating pain. For many years, whole-body X-ray radiography has been the standard imaging method for identifying lytic lesions. However, its sensitivity is limited because it can only detect lesions once the bone mass has been reduced by 30% to 50%. Hence, utilizing advanced and sensitive imaging modalities, such as positron emission tomography (PET) fused with computed tomography (CT), is crucial for the early detection of osteolytic lesions. Among radiotracers used in PET imaging, 1⁸F-fluorodeoxyglucose ([18F]FDG) is the most commonly employed in the field of oncology. Currently, most guidelines include [18F]FDG PET/CT in the assessment of myeloma patients, particularly for detecting osteolytic lesions, evaluating treatment response, and assessing extramedullary and residual disease. Nonetheless, in recent years, new applications of PET/CT for evaluating myeloma have been investigated. These include assessing aspects such as bone turnover, dual-time-point imaging (early and delayed scans), the impact of chemotherapy on the brain (commonly known as ‘chemo brain’), innovative PET radiotracers, and the use of artificial intelligence technology. This article aims to provide a comprehensive review of both conventional and innovative uses of PET/CT in evaluating multiple myeloma.
Paracrine Signaling Mediated by the Cytosolic Tryparedoxin Peroxidase of Trypanosoma cruzi
Authors: Chiribao María Laura , Díaz-Viraqué Florencia , Libisch María Gabriela , Batthyány Carlos , Cunha Narcisa , De Souza Wanderley , Parodi-Talice Adriana , Robello Carlos
Published: January 2024

Peroxiredoxins are abundant and ubiquitous proteins that participate in different cellular functions, such as oxidant detoxification, protein folding, and intracellular signaling. Under different cellular conditions, peroxiredoxins can be secreted by different parasites, promoting the induction of immune responses in hosts. In this work, we demonstrated that the cytosolic tryparedoxin peroxidase of Trypanosoma cruzi (cTXNPx) is secreted by epimastigotes and trypomastigotes associated with extracellular vesicles and also as a vesicle-free protein. By confocal microscopy, we show that cTXNPx can enter host cells by an active mechanism both through vesicles and as a recombinant protein. Transcriptomic analysis revealed that cTXNPx induces endoplasmic reticulum stress and interleukin-8 expression in epithelial cells. This analysis also suggested alterations in cholesterol metabolism in cTXNPx-treated cells, which was confirmed by immunofluorescence showing the accumulation of LDL and the induction of LDL receptors in both epithelial cells and macrophages. BrdU incorporation assays and qPCR showed that cTXNPx has a mitogenic, proliferative, and proinflammatory effect on these cells in a dose–dependent manner. Importantly, we also demonstrated that cTXNPx acts as a paracrine virulence factor, increasing the susceptibility to infection in cTXNPx-pretreated epithelial cells by approximately 40%. Although the results presented in this work are from in vitro studies and likely underestimate the complexity of parasite–host interactions, our work suggests a relevant role for this protein in establishing infection.
The Immune-Stimulating and Anti-Diabetic Effects of Allium hookeri Leaves Grown in a Plant Factory with Artificial Lights in Immunosuppressed Obese C57BL/6 Mice
Authors: Jung Jieun , Kim Ji-Su , Jeong Un-Yul , Bae Ui-Jin , Kim Mina , Park Shin-Young , Hwang In-Guk , Heo Jeong-Wook , Shim Chang-Ki , Ham Jun-Sang , Lee Sung-Hyen
Published: January 2024

We investigated the immune-stimulating and anti-diabetic effects of Allium hookeri leaves grown in a plant factory with artificial lights. The immunomodulatory effects of A. hookeri leaves’ ethanol extracts were evaluated with immune-related hematological factors in blood, the proliferation of splenocytes, NK cell activity, IgG and cytokine levels, and their mechanisms in immunosuppressed obese mice. Anti-diabetic effects were determined by the inhibitory activity against α-amylase and α-glucosidase in vitro and fasting blood glucose levels and biochemical factors in the serum of immunosuppressed obese mice. A. hookeri leaf extracts increased WBC and LYM counts, the proliferation of splenocytes, and serum IgG and IL-1β concentrations compared to those of the NC group, which was used as a negative control. A. hookeri leaf extracts also improved serum HDL levels while they decreased the activities of digestive enzymes, fasting blood glucose, and biochemical factors (ALT, AST, T-Chol, TG, LDL, and GLU). The expressions of IL-1β, JNK, c-Jun, p65, and iNOS in the thymus of immunosuppressed mice were activated by the treatment of A. hookeri leaf extracts. The results suggest that A. hookeri leaves grown in a plant factory with artificial lights also have immune-stimulatory and anti-diabetic effects and can be used as novel functional supplements to control related diseases and to improve public health.
Cross-Linked Alginate Dialdehyde/Chitosan Hydrogel Encompassing Curcumin-Loaded Bilosomes for Enhanced Wound Healing Activity
Authors: Sideek Sarah A. , El-Nassan Hala B. , Fares Ahmed R. , Elkasabgy Nermeen A. , ElMeshad Aliaa N.
Published: January 2024

The current study aimed to fabricate curcumin-loaded bilosomal hydrogel for topical wound healing purposes, hence alleviating the poor aqueous solubility and low oral bioavailability of curcumin. Bilosomes were fabricated via the thin film hydration technique using cholesterol, Span® 60, and two different types of bile salts (sodium deoxycholate or sodium cholate). Bilosomes were verified for their particle size (PS), polydispersity index (PDI), zeta potential (ZP), entrapment efficiency (EE%), and in vitro drug release besides their morphological features. The optimum formulation was composed of cholesterol/Span® 60 (molar ratio 1:10 w/w) and 5 mg of sodium deoxycholate. This optimum formulation was composed of a PS of 246.25 ± 11.85 nm, PDI of 0.339 ± 0.030, ZP of −36.75 ± 0.14 mv, EE% of 93.32% ± 0.40, and the highest percent of drug released over three days (96.23% ± 0.02). The optimum bilosomal formulation was loaded into alginate dialdehyde/chitosan hydrogel cross-linked with calcium chloride. The loaded hydrogel was tested for its water uptake capacity, in vitro drug release, and in vivo studies on male Albino rats. The results showed that the loaded hydrogel possessed a high-water uptake percent at the four-week time point (729.50% ± 43.13) before it started to disintegrate gradually; in addition, it showed sustained drug release for five days (≈100%). In vivo animal testing and histopathological studies supported the superiority of the curcumin-loaded bilosomal hydrogel in wound healing compared to the curcumin dispersion and plain hydrogel, where there was a complete wound closure attained after the three-week period with a proper healing mechanism. Finally, it was concluded that curcumin-loaded bilosomal hydrogel offered a robust, efficient, and user-friendly dosage form for wound healing.
The Effect of External Treatment of Arabidopsis thaliana with Plant-Derived Stilbene Compounds on Plant Resistance to Abiotic Stresses
Authors: Aleynova Olga A. , Ogneva Zlata V. , Suprun Andrey R. , Ananev Alexey A. , Nityagovsky Nikolay N. , Beresh Alina A. , Dubrovina Alexandra S. , Kiselev Konstantin V.
Published: January 2024

Stilbenes are a group of plant phenolic secondary metabolites, with trans-resveratrol (3,5,4′-trihydroxy-trans-stilbene) being recognized as the most prominent and studied member. Stilbenes have a great potential for use in agriculture and medicine, as they have significant activities against plant pathogens and have valuable beneficial effects on human health. In this study, we analyzed the effects of direct application of stilbenes, stilbene precursor, and stilbene-rich extract solutions to the plant foliar surface for increasing the resistance of Arabidopsis thaliana to various abiotic stresses (heat, cold, drought, and soil salinity). Exogenous treatment of A. thaliana with stilbenes (trans-resveratrol, piceid, and spruce bark extract) and phenolic precursor (p-coumaric acid or CA) during germination resulted in considerable growth retardation of A. thaliana plants: a strong delay in the root and stem length of 1-week-old seedlings (in 1.3–4.5 fold) and rosette diameter of 1-month-old plants (in 1.2–1.8 fold), while the 2-month-old treated plants were not significantly different in size from the control. Plant treatments with stilbenes and CA increased the resistance of A. thaliana to heat and, to a lesser extent, to soil salinity (only t-resveratrol and spruce extract) to drought (only CA), while cold resistance was not affected. Plant treatments with stilbenes and CA resulted in a significant increase in plant resistance and survival rates under heat, with plants showing 1.5–2.3 times higher survival rates compared to untreated plants. Thus, exogenous stilbenes and a CA are able to improve plant survival under certain abiotic stresses via specific activation of the genes involved in the biosynthesis of auxins, gibberellins, abscisic acid, and some stress-related genes. The present work provides new insights into the application of stilbenes to improve plant stress tolerance.
Effect of Na, K and Ca Salts on Growth, Physiological Performance, Ion Accumulation and Mineral Nutrition of Mesembryanthemum crystallinum
Authors: Jēkabsone Astra , Karlsons Andis , Osvalde Anita , Ievinsh Gederts
Published: January 2024

Mesembryanthemum crystallinum L. is an obligatory halophyte species showing optimum growth at elevated soil salinity levels, but the ionic requirements for growth stimulation are not known. The aim of the present study was to compare the effects of sodium, potassium and calcium in the form of chloride and nitrate salts on the growth, physiological performance, ion accumulation and mineral nutrition of M. crystallinum plants in controlled conditions. In a paradoxical way, while sodium and potassium had comparable stimulative effect on plant growth, the effect of calcium was strongly negative even at a relatively low concentration, eventually leading to plant death. Moreover, the effect of Ca nitrate was less negative in comparison to that of Ca chloride, but K in the form of nitrate had some negative effects. There were three components of the stimulation of biomass accumulation by NaCl and KCl salinity in M. crsytallinum: the increase in tissue water content, increase in ion accumulation, and growth activation. As optimum growth was in a salinity range from 20 to 100 mM, the increase in the dry biomass of plants at a moderate (200 mM) and high (400 mM) salinity in comparison to control plants was mostly due to ion accumulation. Among physiological indicators, changes in leaf chlorophyll concentration appeared relatively late, but the chlorophyll a fluorescence parameter, Performance Index Total, was the most sensitive to the effect of salts. In conclusion, both sodium and potassium in the form of chloride salts are efficient in promoting the optimum growth of M. crystallinum plants. However, mechanisms leading to the negative effect of calcium on plants need to be assessed further.
Effects of Thermoforming on the Mechanical, Optical, Chemical, and Morphological Properties of PET-G: In Vitro Study
Authors: Staderini Edoardo , Chiusolo Giuseppe , Guglielmi Federica , Papi Massimiliano , Perini Giordano , Tepedino Michele , Gallenzi Patrizia
Published: January 2024

The effectiveness of clear aligners in correcting malocclusions is closely linked to the properties of the materials used to make them. The polymers used in the manufacture of clear aligners have well-established properties. However, the process of manufacturing clear aligners, known as thermoforming, involves thermal and mechanical shocks that may alter these properties. The objective of this study was to evaluate the effects of thermoforming on the mechanical, optical, chemical, and morphological properties of sixty PET-G specimens. The study compared the thickness, weight, absorbance, chemical structure, surface roughness, elastic modulus, yield strength, and breaking load of thirty thermoformed specimens with thirty non-thermoformed specimens. The study introduces a new approach by using standardized samples to analyze both chemical and physical properties. The results showed statistically significant differences in thickness (−15%), weight (−11%), and surface roughness (+1233% in roughness average; +1129% in RMS roughness) of the material. Additionally, a correlation was found between reduction in thickness and increase in opalescence. There was no significant change in the functionality of the aligners after thermoforming, as no significant mechanical changes were found. However, the increase in surface roughness may lead to plaque and fluid accumulation and worsen the fit of the aligners.
Effect of Liquid Glass-Modified Lignin Waste on the Flammability Properties of Biopolyurethane Foam Composites
Authors: Kairytė Agnė , Makowska Sylwia , Rybiński Przemysław , Strzelec Krzysztof , Kremensas Arūnas , Šeputytė-Jucikė Jurga , Vaitkus Saulius
Published: January 2024

Water-blown biopolyurethane (bioPUR) foams are flammable and emit toxic gases during combustion. Herein, a novel approach suggested by the current study is to use different amounts of lignin waste (LigW), which increases the thermal stability and delays the flame spread and sodium silicate (LG), which has foaming ability at high temperatures and acts as a protective layer during a fire. However, there have been no studies carried out to investigate the synergy between these two materials. Therefore, two different ratios, namely 1/1 and 1/2 of LigW/LG, were used to prepare bioPUR foam composites. The obtained bioPUR foam composites with a 1/2 ratio of LigW/LG exhibited inhibition of flame propagation during the ignitability test by 7 s, increased thermal stability at higher temperatures by 40 °C, reduced total smoke production by 17%, reduced carbon monoxide release by 22%, and increased compressive strength by a maximum of 123% and 36% and tensile strength by a maximum of 49% and 30% at 100 °C and 200 °C, respectively, compared to bioPUR foam composites with unmodified LigW. Additionally, thanks to the sufficient compatibility between the polymeric matrix and LigW/LG particles, bioPUR foam composites were characterised by unchanged or even improved physical and mechanical properties, as well as increased glass transition temperature by 16% compared to bioPUR foam composites with unmodified LigW particles, making them suitable for application as a thermal insulating layer in building envelopes.
Degradable Polymeric Bio(nano)materials and Their Biomedical Applications: A Comprehensive Overview and Recent Updates
Authors: Kuperkar Ketan , Atanase Leonard , Bahadur Anita , Crivei Ioana , Bahadur Pratap
Published: January 2024

Degradable polymers (both biomacromolecules and several synthetic polymers) for biomedical applications have been promising very much in the recent past due to their low cost, biocompatibility, flexibility, and minimal side effects. Here, we present an overview with updated information on natural and synthetic degradable polymers where a brief account on different polysaccharides, proteins, and synthetic polymers viz. polyesters/polyamino acids/polyanhydrides/polyphosphazenes/polyurethanes relevant to biomedical applications has been provided. The various approaches for the transformation of these polymers by physical/chemical means viz. cross-linking, as polyblends, nanocomposites/hybrid composites, interpenetrating complexes, interpolymer/polyion complexes, functionalization, polymer conjugates, and block and graft copolymers, are described. The degradation mechanism, drug loading profiles, and toxicological aspects of polymeric nanoparticles formed are also defined. Biomedical applications of these degradable polymer-based biomaterials in and as wound dressing/healing, biosensors, drug delivery systems, tissue engineering, and regenerative medicine, etc., are highlighted. In addition, the use of such nano systems to solve current drug delivery problems is briefly reviewed.
Visual Traditions in the Formation of the Iconographic Types of the Investiture and Triumph of Patriarch Joseph
Authors: Martí Bonafé María Ángeles
Published: January 2024

The story of the patriarch Joseph is a very recurring theme in medieval visual artistic Christian tradition. Joseph, Jacob’s beloved son, is a prefiguration of Christ. The story in Genesis 41, 37–44 fosters the creation of two iconographic types: Joseph’s investiture and Joseph on the Pharaoh’s chariot. The narrative places patriarch Joseph in the court of the Pharaoh of Egypt. However, Christian visuality was created according to the iconic criteria for the representation of political power, contemporary to the configuration of both iconographic types. The aim of this paper is to study the visual mechanisms used in the iconic configuration of the iconographic types of Joseph’s investiture and Joseph on the Pharaoh’s chariot, when the monarch bestows upon Joseph the privilege of his trust. The iconographic analysis of some early and medieval examples of the artistic visuality of Joseph’s story, in Eastern and Western traditions, confirms that they refer back to late ancient and medieval Byzantine tradition. Likewise, it was detected that the resources used in the visual configuration of both iconographic types are linked to the conventionalised mechanisms of the symbolic construction of power.
A Geoscience-Aware Network (GASlumNet) Combining UNet and ConvNeXt for Slum Mapping
Authors: Lu Wei , Hu Yunfeng , Peng Feifei , Feng Zhiming , Yang Yanzhao
Published: January 2024

Approximately 1 billion people worldwide currently inhabit slum areas. The UN Sustainable Development Goal (SDG 11.1) underscores the imperative of upgrading all slums by 2030 to ensure adequate housing for everyone. Geo-locations of slums help local governments with upgrading slums and alleviating urban poverty. Remote sensing (RS) technology, with its excellent Earth observation capabilities, can play an important role in slum mapping. Deep learning (DL)-based RS information extraction methods have attracted a lot of attention. Currently, DL-based slum mapping studies typically uses three optical bands to adapt to existing models, neglecting essential geo-scientific information, such as spectral and textural characteristics, which are beneficial for slum mapping. Inspired by the geoscience-aware DL paradigm, we propose the Geoscience-Aware Network for slum mapping (GASlumNet), aiming to improve slum mapping accuracies via incorporating the DL model with geoscientific prior knowledge. GASlumNet employs a two-stream architecture, combining ConvNeXt and UNet. One stream concentrates on optical feature representation, while the other emphasizes geo-scientific features. Further, the feature-level and decision-level fusion mechanisms are applied to optimize deep features and enhance model performance. We used Jilin-1 Spectrum 01 and Sentinel-2 images to perform experiments in Mumbai, India. The results demonstrate that GASlumNet achieves higher slum mapping accuracy than the comparison models, with an intersection over union (IoU) of 58.41%. Specifically, GASlumNet improves the IoU by 4.60~5.97% over the baseline models, i.e., UNet and ConvNeXt-UNet, which exclusively utilize optical bands. Furthermore, GASlumNet enhances the IoU by 10.97% compared to FuseNet, a model that combines optical bands and geo-scientific features. Our method presents a new technical solution to achieve accurate slum mapping, offering potential benefits for regional and global slum mapping and upgrading initiatives.
Automated Building Height Estimation Using Ice, Cloud, and Land Elevation Satellite 2 Light Detection and Ranging Data and Building Footprints
Authors: Cai Panli , Guo Jingxian , Li Runkui , Xiao Zhen , Fu Haiyu , Guo Tongze , Zhang Xiaoping , Li Yashuai , Song Xianfeng
Published: January 2024

Accurately estimating building heights is crucial for various applications, including urban planning, climate studies, population estimation, and environmental assessment. However, this remains a challenging task, particularly for large areas. Satellite-based Light Detection and Ranging (LiDAR) has shown promise, but it often faces difficulties in distinguishing building photons from other ground objects. To address this challenge, we propose a novel method that incorporates building footprints, relative positions of building and ground photons, and a self-adaptive buffer for building photon selection. We employ the Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2) photon-counting LiDAR, specifically the ICESat-2/ATL03 data, along with building footprints obtained from the New York City (NYC) Open Data platform. The proposed approach was applied to estimate the heights of 17,399 buildings in NYC, and the results showed strong consistency with the reference building heights. The root mean square error (RMSE) was 8.1 m, and for 71% of the buildings, the mean absolute error (MAE) was less than 3 m. Furthermore, we conducted an extensive evaluation of the proposed approach and thoroughly investigated the influence of terrain, region, building height, building density, and parameter selection. We also verified the effectiveness of our approach in an experimental area in Beijing and compared it with other existing methods. By leveraging ICESat-2 LiDAR data, building footprints, and advanced selection techniques, the proposed approach demonstrates the potential to accurately estimate building heights over broad areas.
Combining Hydrological Models and Remote Sensing to Characterize Snowpack Dynamics in High Mountains
Authors: Ougahi Jamal Hassan , Rowan John S.
Published: January 2024

Seasonal snowpacks, characterized by their snow water equivalent (SWE), can play a major role in the hydrological cycle of montane environments with months of snow accretion followed by episodes of melt controlling flood risk and water resource availability downstream. Quantifying the temporal and spatial patterns of snowpack accumulation and its subsequent melt and runoff is an internationally significant challenge, particularly within mountainous regions featuring complex terrain with limited or absent observational data. Here we report a new approach to snowpack characterization using open-source global satellite and modelled data products (precipitation and SWE) greatly enhancing the utility of the widely used Soil and Water Assessment Tool (SWAT). The paper focusses on the c. 23,000 km2 Chenab river basin (CRB) in the headwaters of the Indus Basin, globally important because of its large and growing population and increasing water insecurity due to climate change. We used five area-weighted averaged satellite, gridded and reanalysis precipitation datasets: ERA5-Land, CMORPH, TRMM, APHRODITE and CPC UPP. As well as comparison to local weather station data, these were used in SWAT to model streamflow for evaluation against observed streamflow at the basin outlet. ERA5-Land data provided the best streamflow match-ups and was used to infer snowpack (SWE) dynamics at basin and sub-basin scales. Snow reference data were derived from remote sensing and modelled SWE re-analysis products: ULCA-SWE and KRA-SWE, respectively. Beyond conventional auto-calibration and single-variable approaches we undertook multi-variable calibration using R-SWAT to manually adjust snow parameters alongside observed streamflow data. Characterization of basin-wide patterns of snowpack build-up and melt (SWE dynamics) were greatly strengthened using KRA-SWE data accompanied by improved streamflow simulation in sub-basins dominated by seasonal snow cover. UCLA-SWE data also improved SWE estimations using R-SWAT but weakened the performance of simulated streamflow due to under capture of seasonal runoff from permanent snow/ice fields in the CRB. This research highlights the utility and value of remote sensing and modelling data to drive better understanding of snowpack dynamics and their contribution to runoff in the absence of in situ snowpack data in high-altitude environments. An improved understanding of snow-bound water is vital in natural hazard risk assessment and in better managing worldwide water resources in the populous downstream regions of mountain-fed large rivers under threat from climate change.
Effective Risk Detection for Natural Gas Pipelines Using Low-Resolution Satellite Images
Authors: Ochs Daniel , Wiertz Karsten , Bußmann Sebastian , Kersting Kristian , Dhami Devendra Singh
Published: January 2024

Natural gas pipelines represent a critical infrastructure for most countries and thus their safety is of paramount importance. To report potential risks along pipelines, several steps are taken such as manual inspection and helicopter flights; however, these solutions are expensive and the flights are environmentally unfriendly. Deep learning has demonstrated considerable potential in handling a number of tasks in recent years as models rely on huge datasets to learn a specific task. With the increasing number of satellites orbiting the Earth, remote sensing data have become widely available, thus paving the way for automated pipeline monitoring via deep learning. This can result in effective risk detection, thereby reducing monitoring costs while being more precise and accurate. A major hindrance here is the low resolution of images obtained from the satellites, which makes it difficult to detect smaller changes. To this end, we propose to use transformers trained with low-resolution images in a change detection setting to detect pipeline risks. We collect PlanetScope satellite imagery (3 m resolution) that captures certain risks associated with the pipelines and present how we collected the data. Furthermore, we compare various state-of-the-art models, among which ChangeFormer, a transformer architecture for change detection, achieves the best performance with a 70% F1 score. As part of our evaluation, we discuss the specific performance requirements in pipeline monitoring and show how the model’s predictions can be shifted accordingly during training.
Multi-Year Time Series Transfer Learning: Application of Early Crop Classification
Authors: Račič Matej , Oštir Krištof , Zupanc Anže , Čehovin Zajc Luka
Published: January 2024

Crop classification is an important task in remote sensing with many applications, such as estimating yields, detecting crop diseases and pests, and ensuring food security. In this study, we combined knowledge from remote sensing, machine learning, and agriculture to investigate the application of transfer learning with a transformer model for variable length satellite image time series (SITS). The objective was to produce a map of agricultural land, reduce required interventions, and limit in-field visits. Specifically, we aimed to provide reliable agricultural land class predictions in a timely manner and quantify the necessary amount of reference parcels to achieve these outcomes. Our dataset consisted of Sentinel-2 satellite imagery and reference crop labels for Slovenia spanning over years 2019, 2020, and 2021. We evaluated adaptability through fine-tuning in a real-world scenario of early crop classification with limited up-to-date reference data. The base model trained on a different year achieved an average F1 score of 82.5% for the target year without having a reference from the target year. To increase accuracy with a new model trained from scratch, an average of 48,000 samples are required in the target year. Using transfer learning, the pre-trained models can be efficiently adapted to an unknown year, requiring less than 0.3% (1500) samples from the dataset. Building on this, we show that transfer learning can outperform the baseline in the context of early classification with only 9% of the data after 210 days in the year.
Automatic Rice Early-Season Mapping Based on Simple Non-Iterative Clustering and Multi-Source Remote Sensing Images
Authors: Wang Gengze , Meng Di , Chen Riqiang , Yang Guijun , Wang Laigang , Jin Hailiang , Ge Xiaosan , Feng Haikuan
Published: January 2024

Timely and accurate rice spatial distribution maps play a vital role in food security and social stability. Early-season rice mapping is of great significance for yield estimation, crop insurance, and national food policymaking. Taking Tongjiang City in Heilongjiang Province with strong spatial heterogeneity as study area, a hierarchical K-Means binary automatic rice classification method based on phenological feature optimization (PFO-HKMAR) is proposed, using Google Earth Engine platform and Sentinel-1/2, and Landsat 7/8 data. First, a SAR backscattering intensity time series is reconstructed and used to construct and optimize polarization characteristics. A new SAR index named VH-sum is built, which is defined as the summation of VH backscattering intensity for specific time periods based on the temporal changes in VH polarization characteristics of different land cover types. Then comes feature selection, optimization, and reconstruction of optical data. Finally, the PFO-HKMAR classification method is established based on Simple Non-Iterative Clustering. PFO-HKMAR can achieve early-season rice mapping one month before harvest, with overall accuracy, Kappa, and F1 score reaching 0.9114, 0.8240 and 0.9120, respectively (F1 score is greater than 0.9). Compared with the two crop distribution datasets in Northeast China and ARM-SARFS, overall accuracy, Kappa, and F1 scores of PFO-HKMAR are improved by 0.0507–0.1957, 0.1029–0.3945, and 0.0611–0.1791, respectively. The results show that PFO-HKMAR can be promoted in Northeast China to enable early-season rice mapping, and provide valuable and timely information to different stakeholders and decision makers.
Simulation and Analysis of the Mesoscale Vortex Affecting the “21·7” Extreme Rainstorm in Henan
Authors: Xu Lan , Chen Tao , Liu Juanjuan , Fu Shenming , Cheng Wei , Liu Hongbo , Lu Bing , He Yujun , Zhu Shujun , Liu Yiran , Shen Xiao , Wang Bin
Published: January 2024

From 17 to 22 July 2021, the “21·7” extreme rainfall event (“21·7” ERE) hit Henan Province, breaking the record for mainland China with a maximum hourly rainfall of 201.9 mm at the Zhengzhou station. The long-lived (20 h) mesoscale Huang-Huai vortex (HHV) was an important system that directly affected the major rainfall stage, including the extreme hourly rainfall. This study investigates the formation and development mechanism of the HHV, as well as its association with the simulation of extreme hourly rainfall through numerical simulations. The simulated rainfall and radar composite reflectivity were in good agreement with the observations, thus effectively reproducing the generation and developmental process of the HHV. The analysis results showed that the HHV initially formed at 850 hPa on 19 July at 1800 UTC and eventually developed to 550 hPa. The positive feedback formed by the horizontal convergence and vertical vorticity transport was the main mechanism leading to the generation and deepening of the HHV. The stretching effect (STR) term played an absolutely dominant role in the increase in the vorticity tendency, and it primarily originated from the coupling effect of boundary layer jets (BLJs) and synoptic-weather-system-related low-level jets (SLLJs). The accurate simulation of the HHV allowed the early rainfall to reasonably reproduce the surface cold pool near the Zhengzhou station, and then the cooperation of the SLLJs, the BLJs, and the cold pool made the simulated extreme hourly rainfall exactly close to the Zhengzhou station, but with a weaker intensity, due to the fact that the HHV moved northeastward after its formation, resulting in a narrow range of southerly flow in southern Henan, which is not conducive to convective triggering in the southerly flow.
Climate Sensitivity and Drought Legacy of Tree Growth in Plantation Forests in Northeast China Are Species- and Age-Dependent
Authors: Li Ting , Sun Qiaoqi , Zou Hongfei , Marschner Petra
Published: January 2024

The occurrence, frequency, and severity of drought are accelerating due to global warming. Understanding the vulnerability of plantation forests to climate change, particularly to drought events, is critical to revealing the underlying mechanisms of tree resilience, recovery, and acclimation, which are important for plantation management. How the stand age affects the climate sensitivity of tree growth, as well as the direction, magnitude, and duration of the drought legacy, in plantation forests in northeast China is still unclear. In this study, we used MODIS-derived NDVI time series with gridded climate data from 2000 to 2020 to fill this knowledge gap. The selected plantation forests were dominated by four coniferous species: Korean pine (Pinus koraiensis), Scots pine (Pinus sylvestris), Japanese larch (Larix kaempferi), and Dahurian larch (Larix gmelinii). The results show that the climate sensitivity of tree growth differed among species and age groups. The growth of Korean pine and Scots pine was mostly dependent upon precipitation, while the growth of Japanese larch and Dahurian larch was determined primarily by temperature. Old Japanese larch (21–40 years) and Dahurian larch trees (31–60 years) were more sensitive to temperature and precipitation than young conspecifics, whereas old Korean pine (41–60 years) and Scots pine (31–60 years) were less sensitive to precipitation and temperature than young conspecifics. Furthermore, the legacy of drought lasted one year for Korean pine, Japanese larch, and Dahurian larch and over three years for Scots pine. Old trees were more severely affected by drought, particularly Scots pine and Dahurian larch. The findings of the study can help improve plantation forest management for better adaptation to future climate change.
A Novel Multidimensional Tensile, Shear, and Buckling Sensor for the Measurement of Flexible Fibrous Materials
Authors: Luo Liang , Stylios George
Published: January 2024

To meet the complex and diverse demands for low-stress mechanical measurements of fabrics and other flexible materials, two integrated multidimensional force sensors with the same structure but different ranges were explored. They can support both rapid and precise low-noise, high-precision, low-cost, easy-to-use, reliable, and intelligent solutions for the complex measurement of fabric mechanics. Having analysed the mechanical relationship of the parallel beam theory, and considering the specific requirements of fabric measurement, a novel multi-dimensional force sensor is designed, capable of measuring tensile, shear, and buckling properties. Finite element analysis is used to simulate the mechanical performance of this sensor for fabric-loading/unloading measurement, and the sensitivity of the mechanical quantity transfer, the amount of sensor deformation, the stress distribution, and the degree of inter-dimensional coupling have been investigated and verified. The basis for subsequent digital processing is achieved by a low-offset, low-temperature-drift, low-power-consumption analogue front end, 24-bit ADC circuit, and signal conditioning electronics, suitable for the measurement of fabric mechanics under low stress, which is like the end-user requirements. The sensor information channel is supported by a host microcontroller with a DSP and a floating-point processing instruction set. Information processing is performed in time-sharing with the support of a multitasking real-time operating system. The purpose of designing this sensor is to facilitate the development of a new testing instrument, which will adopt the advances of current instruments whilst eliminating their shortcomings.
A ‘Frugal’ EGFET Sensor for Waterborne H2S
Authors: Alqahtani Zahrah , Grell Martin
Published: January 2024

Hydrogen sulphide (H2S) is a toxic gas soluble in water, H2Saq, as a weak acid. Since H2Saq usually originates from the decomposition of faecal matter, its presence also indicates sewage dumping and possible parallel waterborne pathogens associated with sewage. We here present a low footprint (‘frugal’) H2Saq sensor as an accessible resource for water quality monitoring. As a sensing mechanism, we find the chemical affinity of thiols to gold (Au) translates to H2Saq. When an Au electrode is used as a control gate (CG) or floating gate (FG) electrode in the electric double layer (EDL) pool of an extended gate field effect transistor (EGFET) sensor, EGFET transfer characteristics shift along the CG voltage axis in response to H2Saq. We rationalise this by the interface potential from the adsorption of polar H2S molecules to the electrode. The sign of the shift changes between Au CG and Au FG, and cancels when both electrodes are Au. The sensor is selective for H2Saq over the components of urine, nor does urine suppress the sensor’s ability to detect H2Saq. Electrodes can be recovered for repeated use by washing in 1M HCl. Quantitatively, CG voltage shift is fitted by a Langmuir-Freundlich (LF) model, supporting dipole adsorption over an ionic (Nernstian) response mechanism. We find a limit-of-detection of 14.9 nM, 100 times below potability.
Overview of Health-Monitoring Technology for Long-Distance Transportation Pipeline and Progress in DAS Technology Application
Authors: Wu Yuyi , Gao Lei , Chai Jing , Li Zhi , Ma Chenyang , Qiu Fengqi , Yuan Qiang , Zhang Dingding
Published: January 2024

There are various health issues associated with the different stages of long-distance pipeline transportation. These issues pose potential risks to environmental pollution, resource waste, and the safety of human life and property. It is essential to have real-time knowledge of the overall health status of pipelines throughout their entire lifecycle. This article investigates various health-monitoring technologies for long-distance pipelines, providing references for addressing potential safety issues that may arise during long-term transportation. This review summarizes the factors and characteristics that affect pipeline health from the perspective of pipeline structure health. It introduces the principles of major pipeline health-monitoring technologies and their respective advantages and disadvantages. The review also focuses on the application of Distributed Acoustic Sensing (DAS) technology, specifically time and space continuous monitoring technology, in the field of pipeline structure health monitoring. This paper discusses the process of commercialization development of DAS technology, the main research progress in the experimental field, and the open research issues. DAS technology has broad application prospects in the field of long-distance transportation pipeline health monitoring.
IMU-Based Energy Expenditure Estimation for Various Walking Conditions Using a Hybrid CNN–LSTM Model
Authors: Lee Chang June , Lee Jung Keun
Published: January 2024

In ubiquitous healthcare systems, energy expenditure estimation based on wearable sensors such as inertial measurement units (IMUs) is important for monitoring the intensity of physical activity. Although several studies have reported data-driven methods to estimate energy expenditure during activities of daily living using wearable sensor signals, few have evaluated the performance while walking at various speeds and inclines. In this study, we present a hybrid model comprising a convolutional neural network (CNN) and long short-term memory (LSTM) to estimate the steady-state energy expenditure under various walking conditions based solely on IMU data. To implement and evaluate the model, we performed level/inclined walking and level running experiments on a treadmill. With regard to the model inputs, the performance of the proposed model based on fixed-size sequential data was compared with that of a method based on stride-segmented data under different conditions in terms of the sensor location, input sequence format, and neural network model. Based on the experimental results, the following conclusions were drawn: (i) the CNN–LSTM model using a two-second sequence from the IMU attached to the lower body yielded optimal performance, and (ii) although the stride-segmented data-based method showed superior performance, the performance difference between the two methods was not significant; therefore, the proposed model based on fixed-size sequential data may be considered more practical as it does not require heel-strike detection.
Multi-Channel Soft Dry Electrodes for Electrocardiography Acquisition in the Ear Region
Authors: van der Heijden Patrick , Gilbert Camille , Jafari Samira , Lucchini Mattia Alberto
Published: January 2024

In-ear acquisition of physiological signals, such as electromyography (EMG), electrooculography (EOG), electroencephalography (EEG), and electrocardiography (ECG), is a promising approach to mobile health (mHealth) due to its non-invasive and user-friendly nature. By providing a convenient and comfortable means of physiological signal monitoring, in-ear signal acquisition could potentially increase patient compliance and engagement with mHealth applications. The development of reliable and comfortable soft dry in-ear electrode systems could, therefore, have significant implications for both mHealth and human–machine interface (HMI) applications. This research evaluates the quality of the ECG signal obtained with soft dry electrodes inserted in the ear canal. An earplug with six soft dry electrodes distributed around its perimeter was designed for this study, allowing for the analysis of the signal coming from each electrode independently with respect to a common reference placed at different positions on the body of the participants. An analysis of the signals in comparison with a reference signal measured on the upper right chest (RA) and lower left chest (LL) was performed. The results show three typical behaviors for the in-ear electrodes. Some electrodes have a high correlation with the reference signal directly after inserting the earplug, other electrodes need a settling time of typically 1–3 min, and finally, others never have a high correlation. The SoftPulseTM electrodes used in this research have been proven to be perfectly capable of measuring physiological signals, paving the way for their use in mHealth or HMI applications. The use of multiple electrodes distributed in the ear canal has the advantage of allowing a more reliable acquisition by intelligently selecting the signal acquisition locations or allowing a better spatial resolution for certain applications by processing these signals independently.
Recent Trends in Chemical Sensors for Detecting Toxic Materials
Authors: Kim Yeonhong , Jeon Yangwon , Na Minyoung , Hwang Soon-Jin , Yoon Youngdae
Published: January 2024

Industrial development has led to the widespread production of toxic materials, including carcinogenic, mutagenic, and toxic chemicals. Even with strict management and control measures, such materials still pose threats to human health. Therefore, convenient chemical sensors are required for toxic chemical monitoring, such as optical, electrochemical, nanomaterial-based, and biological-system-based sensors. Many existing and new chemical sensors have been developed, as well as new methods based on novel technologies for detecting toxic materials. The emergence of material sciences and advanced technologies for fabrication and signal-transducing processes has led to substantial improvements in the sensing elements for target recognition and signal-transducing elements for reporting interactions between targets and sensing elements. Many excellent reviews have effectively summarized the general principles and applications of different types of chemical sensors. Therefore, this review focuses on chemical sensor advancements in terms of the sensing and signal-transducing elements, as well as more recent achievements in chemical sensors for toxic material detection. We also discuss recent trends in biosensors for the detection of toxic materials.
Social Media, Newsworthiness, and Missing White Woman Syndrome: A Criminological Analysis
Authors: Brandon Avril Margaret , Emandache Erika , Iwaniec Aleksandra
Published: January 2024

Missing White Woman Syndrome has been widely acknowledged within traditional mainstream media, resulting in a heavy focus on missing white women and a simultaneous underrepresentation of missing women from minority ethnic communities. However, less is known about whether this has carried through to social media, wherein users play a key role in determining what becomes widespread news. This review seeks to examine this issue with reference to existing research. It begins by exploring the concept of newsworthiness and the ways in which social media influences the distribution of news. It will then review the concept of the ‘ideal victim’, and its continued association with ethnicity. Finally, the review will examine Missing White Woman Syndrome and the ways in which it has historically manifested within traditional media and continues to manifest on social media. The review will conclude with a discussion on findings and avenues for future research in Ireland and internationally.
After Being Granted or Refused Asylum in Norway: Relational Migration Journeys among Afghan Unaccompanied Young Men
Authors: Lønning Moa Nyamwathi
Published: January 2024

This article considers experiences of moving and dwelling in Europe among Afghan unaccompanied young men in the context of stringent migration, asylum, and settlement processes. The young men embarked as minors and arrived unaccompanied in Norway. There, their claims for asylum had radically different outcomes: some were granted international protection and others were refused asylum. The article sheds light on forms of relationality on migration journeys by focusing on relational selves and subjectivities regarding trajectories, processes of inclusion and exclusion, and family. Participants shared numerous challenges and struggles arising from their journeys, but also possibilities and transformations taking place alongside developmental changes and life transitions. While some attached meaning to experienced hardships and drew on a sense of direction, others spoke of exhaustion or inoculated themselves from an inability to pursue a direction they desired and saw as necessary for their lives. They made sense of their experiences relationally, relating to hopes and fears, idealised and longed for kinship ties and care, and the ongoing processes and positionings involved in shaping their present situations and imaginings of the future.