bluuebunny/crossref_metadata_2025 huggingface dataset:
Oligosaccharides Ameliorate Acute Kidney Injury by Alleviating Cluster of Differentiation 44-Mediated Immune Responses in Renal Tubular Cells
Authors: Chen Tso-Hsiao , Liu Chung-Te , Cheng Chung-Yi , Sue Yuh-Mou , Huang Nai-Jen , Chen Cheng-Hsien
Published: February 2022

Acute kidney injury (AKI) is a sudden episode of kidney damage that commonly occurs in patients admitted to hospitals. To date, no ideal treatment has been developed to reduce AKI severity. Oligo-fucoidan (FC) interferes with renal tubular cell surface protein cluster of differentiation 44 (CD44) to prevent renal interstitial fibrosis; however, the influence of oligosaccharides on AKI remains unknown. In this study, FC, galacto-oligosaccharide (GOS), and fructo-oligosaccharide (FOS) were selected to investigate the influence of oligosaccharides on AKI. All three oligosaccharides have been proven to be partially absorbed by the intestine. We found that the oligosaccharides dose-dependently reduced CD44 antigenicity and suppressed the hypoxia-induced expression of CD44, phospho-JNK, MCP-1, IL-1β, and TNF-α in NRK-52E renal tubular cells. Meanwhile, CD44 siRNA transfection and JNK inhibitor SP600125 reduced the hypoxia-induced expression of phospho-JNK and cytokines. The ligand of CD44, hyaluronan, counteracted the influence of oligosaccharides on CD44 and phospho-JNK. At 2 days post-surgery for ischemia–reperfusion injury, oligosaccharides reduced kidney inflammation, serum creatine, MCP-1, IL-1β, and TNF-α in AKI mice. At 7 days post-surgery, kidney recovery was promoted. These results indicate that FC, GOS, and FOS inhibit the hypoxia-induced CD44/JNK cascade and cytokines in renal tubular cells, thereby ameliorating AKI and kidney inflammation in AKI mice. Therefore, oligosaccharide supplementation is a potential healthcare strategy for patients with AKI.
Nutrition Practices among Adult Cancer Survivors Living on the Island of Ireland: A Cross-Sectional Study
Authors: O'Callaghan Niamh , Douglas Pauline , Keaver Laura
Published: February 2022

The purpose of this research was to explore the nutrition practices among post-treatment cancer survivors across Ireland. Cancer survivors aged 18+ years living across Ireland, who were not palliative and had completed active cancer treatment at least six months previous, were recruited to complete an online survey assessing dietary quality, food choice and satisfaction with food-related life as well as clinical and nutrition status. It was circulated by cancer support networks and on social media. Descriptive statistics are presented. The cohort (n = 170) was predominantly female (85.9%) and had breast cancer (64.7%). Mean age was 51.5 ± 10.9 years and 42.7% of the cohort were >five years post-treatment. Only 20% and 12% of the cohort had been assessed by a dietitian during and post-treatment, respectively. The mean dietary quality score was 10.3 ± 1.7, which was measured by the Leeds short-form food frequency questionnaire (SFFFQ). Using a 5-point Likert scale, the median satisfaction with food-related life score was 19 (3.3), which evaluates cognitive judgements on the person’s food-related life. The food choice questionnaire (FCQ) assesses the relative importance of a range of factors related to dietary choice to individuals. The primary determinant of food choice in this cohort was the natural content (31.7%) followed by health (24.7%). Vitamin and mineral supplement use was reported by 69.8% of the cohort; the most consumed was Vitamin D. Four themes emerged from an optional open-ended question: awareness of nutritional importance; desire for specific nutritional advice and dietetic referral; cancer and treatment nutrition impacts were highlighted; as well as struggles with weight gain. This research provides useful insight into the nutrition practices of Irish cancer survivors. A desire and need for individualised and specific advice are evident.
Genetic Biomarkers of Metabolic Detoxification for Personalized Lifestyle Medicine
Authors: Aronica Lucia , Ordovas Jose M. , Volkov Andrey , Lamb Joseph J. , Stone Peter Michael , Minich Deanna , Leary Michelle , Class Monique , Metti Dina , Larson Ilona A. , Contractor Nikhat , Eck Brent , Bland Jeffrey S.
Published: February 2022

Metabolic detoxification (detox)—or biotransformation—is a physiological function that removes toxic substances from our body. Genetic variability and dietary factors may affect the function of detox enzymes, thus impacting the body’s sensitivity to toxic substances of endogenous and exogenous origin. From a genetic perspective, most of the current knowledge relies on observational studies in humans or experimental models in vivo and in vitro, with very limited proof of causality and clinical value. This review provides health practitioners with a list of single nucleotide polymorphisms (SNPs) located within genes involved in Phase I and Phase II detoxification reactions, for which evidence of clinical utility does exist. We have selected these SNPs based on their association with interindividual variability of detox metabolism in response to certain nutrients in the context of human clinical trials. In order to facilitate clinical interpretation and usage of these SNPs, we provide, for each of them, a strength of evidence score based on recent guidelines for genotype-based dietary advice. We also present the association of these SNPs with functional biomarkers of detox metabolism in a pragmatic clinical trial, the LIFEHOUSE study.
Lack of Association between Inadequate Micronutrient Intake and Prognosis in Outpatients with Heart Failure
Authors: Torres Núbia Rafaella Soares Moreira , Freire Fernanda Lambert de Andrade , Dantas-Komatsu Raquel Costa Silva , Silva Eduardo Paixão da , Queiroz Salomão Israel Monteiro Lourenço , Lira Niethia Regina Dantas de , Diniz Rosiane Viana Zuza , Lima Severina Carla Vieira Cunha , Pedrosa Lucia Fatima Campos , Lopes Márcia Marília Gomes Dantas , Sena-Evangelista Karine Cavalcanti Maurício
Published: February 2022

Inadequate nutrient intake can lead to worse outcomes in patients with heart failure (HF). This prospective cohort study aimed to assess the prevalence of inadequate micronutrient intake and their association with prognosis in 121 adult and elderly outpatients with HF. Habitual micronutrient intake was evaluated using 24-h dietary recalls (minimum 2 and maximum 6). Participants were grouped into moderate (n = 67) and high (n = 54) micronutrient deficiency groups, according to the individual assessment of each micronutrient intake. Patients’ sociodemographic, clinical, and anthropometric data and clinical outcomes (hospitalization and mortality) within 24 months were collected. Overall and event-free survival rates were calculated using Kaplan–Meier estimates, and curves were compared using the log-rank test. The death risk rate (hazard ratio (HR)) was calculated using Cox’s univariate model. The rate of inadequate intake was 100% for vitamins B1 and D and above 80% for vitamins B2, B9, and E, calcium, magnesium, and copper. No differences in overall survival and event-free survival were observed between groups of HF outpatients with moderate and high micronutrient deficiencies (HR = 0.94 (CI = 0.36–2.48), p = 0.91, and HR = 1.63 (CI = 0.68–3.92), p = 0.26, respectively), as well as when the inadequacy of each micronutrient intake was evaluated alone (all p > 0.05). In conclusion, a high prevalence of inadequate micronutrient intake was observed in outpatients with HF. Inadequate micronutrient intake was not associated with hospitalization and mortality in this group of patients.
Pharmaceuticals Influence on Phragmites australis Phytoremediation Potential in Cu Contaminated Estuarine Media
Authors: Fraga-Santiago Pedro , Dias Sofia , Silva Cristiana , Gomes Carlos R. , Almeida C. Marisa R.
Published: February 2022

The aim of the present work was to evaluate the influence of two different pharmaceutical compounds (bezafibrate and paroxetine) on the phytoremediation potential of Phragmites australis in an estuarine medium contaminated by copper. Plants were exposed for seven days to a simplified estuarine medium, elutriate solution, with or without sediment. The medium was doped with copper and bezafibrate or paroxetine. P. australis plants were able to accumulate a significant amount of Cu, particularly in their roots (600 and 250 times increase in copper levels in the absence and presence of sediment, respectively), corroborating the phytostabilization potential of salt marsh plants. Metal uptake and translocation was significantly lower in the presence of sediment (Cu in leaves increased 20 times in the absence and only 4 times in the presence of sediment). An effect of either pharmaceutical compound on metal accumulation was not observed (levels of Cu in plants tissues were in general identical) but, in the presence of sediment, both bezafibrate and paroxetine changed Cu solubility in elutriate solution, either decreasing or increasing it. The current study highlights the possible influence the presence of contaminants of different characteristics (inorganic and organic contaminants) can have on salt marsh phytoremediation potential in the long run, and the effects pollutants might have in the environment.
Applications of the ROS-Responsive Thioketal Linker for the Production of Smart Nanomedicines
Authors: Rinaldi Arianna , Caraffi Riccardo , Grazioli Maria Vittoria , Oddone Natalia , Giardino Luciana , Tosi Giovanni , Vandelli Maria Angela , Calzà Laura , Ruozi Barbara , Duskey Jason Thomas
Published: February 2022

Reactive oxygen species (ROS)-sensitive drug delivery systems (DDS) specifically responding to altered levels of ROS in the pathological microenvironment have emerged as an effective means to enhance the pharmaceutical efficacy of conventional nanomedicines, while simultaneously reducing side effects. In particular, the use of the biocompatible, biodegradable, and non-toxic ROS-responsive thioketal (TK) functional group in the design of smart DDS has grown exponentially in recent years. In the design of TK-based DDS, different technological uses of TK have been proposed to overcome the major limitations of conventional DDS counterparts including uncontrolled drug release and off-target effects. This review will focus on the different technological uses of TK-based biomaterials in smart nanomedicines by using it as a linker to connect a drug on the surface of nanoparticles, form prodrugs, as a core component of the DDS to directly control its structure, to control the opening of drug-releasing gates or to change the conformation of the nano-systems. A comprehensive view of the various uses of TK may allow researchers to exploit this reactive linker more consciously while designing nanomedicines to be more effective with improved disease-targeting ability, providing novel therapeutic opportunities in the treatment of many diseases.
Investigation of the Interlaminar Shear Performance of Tufted Preforms and Composites under Mode II Loading Condition
Authors: Hui Chan , Chen Chen , Legrand Xavier , Wang Peng
Published: February 2022

The influences of reinforcement by tufting on the interlaminar shear performance of laminated preforms and composites are studied in the present paper. A modified T steel shearing test was established and used to achieve a pure Mode II loading (sliding). Dry tufted preform (DTP) and cured tufted composites (CTC) with varied tufting spacing are considered for the understanding of the role of infused resin and the tufting density on the mechanical properties. Meanwhile, knowledge about the role of infused resins is gained. Additionally, cured tufted composites without threads (CT’C) were prepared under the identical tufting density to evaluate the effect of tufting threads. The results show that the denser the tufting density, the stronger the interlaminar shear strength of CTC, its improvement reaches 12% compared to the non tufted composites. However, the decreased effect also exists for the tufting spacing of 9 mm. Therefore, the tufting density needs to be optimized during the tufting process to improve the interlaminar shear properties of tufted reinforcement and composites. On the contrary, tufting without thread does not affect its mechanical properties compared to the non tufted composites.
Poly(β-hydroxyl amine)s: Valuable Building Blocks for Supramolecular Elastomers with Tunable Mechanical Performance and Superior Healing Capacity
Authors: Wang Linlin , Zhou Jie , Li Lei , Feng Shengyu
Published: February 2022

Supramolecular elastomers integrated with high mechanical toughness and excellent self-healing ability offer attractive applications in various fields such as biomedical materials and wearable electronics. However, the multistep preparation process for creating functional polymer precursors and the expensive stock materials required are two factors that limit the widespread use of supramolecular elastomers. Herein, for the first time, poly(β-hydroxyl amine)s generated by amine-epoxy polymerization were used in the development of supramolecular polymer materials. Based on the novel silicon-containing poly(β-hydroxyl amine)s synthesized by the polymerization between 1,3-bis(3-glycidyloxypropyl)tetramethyldisiloxane and 3-amino-1,2-propanediol, dually cross-linked supramolecular elastomers with both hydrogen bonding and metal coordination were achieved, displaying adjustable mechanical properties with the tensile strength varying from 0.70 MPa to 2.52 MPa, respectively. Thanks to the dynamic nature of the supramolecular interactions, these elastomers exhibited favorable hot-pressing reprocessability and excellent self-healing performance, with the healing efficiency reaching up to 98% at 60 °C for 48 h. Potential applications for photoluminescent materials and flexible electronic devices were demonstrated. We believe that its simplicity of synthesis, adjustable mechanical properties, and robust self-healing capacities bode well for future applications of this new supramolecular elastomer.
Filler Effects on H2 Diffusion Behavior in Nitrile Butadiene Rubber Blended with Carbon Black and Silica Fillers of Different Concentrations
Authors: Jung Jae Kap , Lee Chang Hoon , Son Min Seok , Lee Ji Hun , Baek Un Bong , Chung Ki Soo , Choi Myung Chan , Bae Jong Woo
Published: February 2022

Filler effects on H2 diffusion in nitrile butadiene rubbers (NBRs) blended with carbon black and silica fillers of different concentrations are first investigated by employing a volumetric analysis. Total uptake, solubility, and diffusivity of hydrogen for ten filled-NBR, including neat NBR, are determined in an exposed pressure range of 1.3 MPa~92.6 MPa. Filler dependence on hydrogen uptake and diffusion is distinctly observed in the NBRs blended with high abrasion furnace (HAF) carbon black (CB) fillers compared to NBRs blended with medium thermal furnace (MT) CB and silica filler, which is related to the specific surface area of carbon black and interface structure. The HAF CB filled-NBR follows dual sorption behavior combined with Henry’s law and the Langmuir model, responsible for two contributions of solubility from polymer and filler. However, a single gas sorption behavior coming from the polymer is observed satisfying Henry’s law up to 92.6 MPa for NBR blended with MT CB filled-NBR and silica filled-NBR. Diffusion demonstrates Knudsen and bulk diffusion behavior below and above, respectively, at certain pressures. With increasing pressure, the filler effect on diffusion is reduced, and diffusivity converges to a value. The correlation observed between diffusivity and filler content (or crosslink density) is discussed.
Mechanical and Thermal Properties of Geopolymer Foams (GFs) Doped with By-Products of the Secondary Aluminum Industry
Authors: Ercoli Roberto , Laskowska Dorota , Nguyen Van Vu , Le Van Su , Louda Petr , Łoś Piotr , Ciemnicka Justyna , Prałat Karol , Renzulli Alberto , Paris Eleonora , Basilici Matteo , Rapiejko Cezary , Buczkowska Katarzyna Ewa
Published: February 2022

The article deals with the investigation of geopolymer foams (GFs) synthesized using by-products coming from the (i) screening-, (iv) pyrolysis-, (iii) dust abatement- and (iv) fusion-processes of the secondary aluminum industry. Based on principles of the circular economy to produce new technological materials, the experimental study involves industrial by-products management through the recovery, chemical neutralization, and incorporation of these relatively hazardous waste into the GFs. The geopolymeric matrix, consisting of metakaolin (MK) and silica sand (SA) with a 1:1 wt.% ratio, and chopped carbon fibers (CFs, 1 wt.% MK), was doped with the addition of different aluminum-rich industrial by-products with a percentage from 1 to 10 wt.% MK. The gas (mainly hydrogen) produced during the chemical neutralization of the by-products represents the foaming agents trapped in the geopolymeric structure. Several experimental tests were carried out to characterize the mechanical (flexural, compressive, and Charpy impact strengths) and thermal properties (thermal conductivity, and diffusivity, and specific heat) of the GFs. Results identify GFs with good mechanical and thermal insulation properties, encouraging future researchers to find the best combination (for types and proportions) of the different by-products of the secondary aluminum industry to produce lightweight geopolymer foams. The reuse of these industrial by-products, which according to European Regulations cannot be disposed of in the landfill, also brings together environmental sustainability and safe management of hazardous material in workplaces addressed to the development of new materials.
Constraint Release for Reptating Filaments in Semiflexible Networks Depends on Background Fluctuations
Authors: Händler Tina , Tutmarc Cary , Freitag Jessica S. , Smith David M. , Schnauß Jörg
Published: February 2022

Entangled semiflexible polymer networks are usually described by the tube model, although this concept has not been able to explain all experimental observations. One of its major shortcomings is neglecting the thermal fluctuations of the polymers surrounding the examined test filament, such that disentanglement effects are not captured. In this study, we present experimental evidence that correlated constraint release which has been predicted theoretically occurs in entangled, but not in crosslinked semiflexible polymer networks. By tracking single semiflexible DNA nanotubes embedded both in entangled and crosslinked F-actin networks, we observed different reptation dynamics in both systems, emphasizing the need for a revision of the classical tube theory for entangled polymer solutions.
Use of Natural and Synthetic Fiber-Reinforced Composites for Punching Shear of Flat Slabs: A Comparative Study
Authors: Joyklad Panuwat , Yooprasertchai Ekkachai , Wiwatrojanagul Pongsak , Chaiyasarn Krisada , Ali Nazam , Hussain Qudeer
Published: February 2022

Over the last two decades, considerable attention has been devoted to the strengthening of sub-standard flat-slab constructions. With the evolution of composite materials and an increasing emphasis on the economical and sustainable use of natural fibers, many researchers have utilized them in the strengthening of flat flabs mitigating punching failures. This study aims at investigating and comparing the behavior of flat slabs strengthened with post-installed composite and natural reinforcements. An experimental program was devised consisting of eight flat-slab specimens. One specimen was tested in as-built condition to provide a reference. The remaining specimens were strengthened with Carbon Fiber-Reinforced Polymer (CFRP), Aramid Fiber-Reinforced Polymer (AFRP), and sisal rods. The pattern of post-installed rods was varied as single line, double line, and star shapes around the column. The results indicated that the single-line pattern could only enhance the maximum sustained load by up to 6% compared to that of the reference specimen. On the contrary, double line and star shape configurations resulted in a substantial increase in the maximum sustained load. An analytical assessment of ACI 318-19 provisions resulted in an over-estimation of the shear strengths of CFRP- and AFRP-strengthened slabs. Furthermore, the same provisions led to lower yields than experimental shear strengths for sisal-strengthened slabs.
Fabrication of Polyethyleneimine-Functionalized Magnetic Cellulose Nanocrystals for the Adsorption of Diclofenac Sodium from Aqueous Solutions
Authors: Zhu Xiaoyan , Tong Jiaqi , Lan Hangzhen , Pan Daodong
Published: February 2022

Diclofenac sodium (DS), one of the most used non-steroidal anti-inflammatory drugs worldwide, is often detected in wastewater and natural water. This drug is ecotoxic, even at low concentrations. Therefore, it is essential to fabricate low-cost adsorbents that can easily and effectively remove DS from contaminated water bodies. In this study, a polyethyleneimine (PEI)-modified magnetic cellulose nanocrystal (MCNC) was prepared with a silane coupling agent as a bridge. TEM, FTIR, XRD, and VSM were used to demonstrate the successful preparation of MCNC-PEI. This composite adsorbent exhibited efficient DS removal. Furthermore, the adsorption performance of MCNC-PEI on DS was optimal under mildly acidic conditions (pH = 4.5). Adsorption kinetics showed that the adsorption process involves mainly electrostatic interactions. Moreover, the maximum adsorption capacity reached 299.93 mg/g at 25 °C, and the adsorption capacity only decreased by 9.9% after being reused five times. Considering its low cost, low toxicity, and high DS removal capacity, MCNC-PEI could be a promising adsorbent for treating DS-contaminated water.
Noninvasive Detection, Tracking, and Characterization of Aerogel Implants Using Diagnostic Ultrasound
Authors: Ghimire Sagar , Sala Martina Rodriguez , Chandrasekaran Swetha , Raptopoulos Grigorios , Worsley Marcus , Paraskevopoulou Patrina , Leventis Nicholas , Sabri Firouzeh
Published: February 2022

Medical implants are routinely tracked and monitored using different techniques, such as MRI, X-ray, and ultrasound. Due to the need for ionizing radiation, the two former methods pose a significant risk to tissue. Ultrasound imaging, however, is non-invasive and presents no known risk to human tissue. Aerogels are an emerging material with great potential in biomedical implants. While qualitative observation of ultrasound images by experts can already provide a lot of information about the implants and the surrounding structures, this paper describes the development and study of two simple B-Mode image analysis techniques based on attenuation measurements and echogenicity comparisons, which can further enhance the study of the biological tissues and implants, especially of different types of biocompatible aerogels.
Preparation of a Novel Organic Phosphonic Acid Intercalated Phosphate Tailings Based Hydrotalcite and Its Application in Enhancing Fire Safety for Epoxy Resin
Authors: Zhang Huali , Jin Lingzi , Wu Hanjun , Zhang Zhenyue , Yu Junxia , Zhang Wenjun , Pan Yi , Pan Zhiquan
Published: February 2022

Phosphate tailings (PTs) are solid waste, which is produced by phosphate flotation. In this work, PTs were used as raw materials for the preparation of diethylenetriamine pentamethronic acid (DTPMP) intercalated trimetal (Ca-Mg-Al) layered double hydroxides (TM-DTPMP LDHs) by co-precipitation method. TM-DTPMP LDHs were characterized by X-ray diffraction, fourier-transform infrared spectroscopy, scanning electron microscopy, differential thermal gravimetric analysis, X-ray photoelectron spectroscopy and applied as a flame retardant to improve the fire safety of epoxy resin (EP). The results showed that the composite materials exhibited obvious layered structure. After intercalation, layer spacing increased from 0.783 to 1.78 Å. When the amount of TM-DTPMP LDH in EP was 8%, the limitted oxygen index of the composite material increased from the original 19.2% to 30.2%. In addition, Cone calorimeter (CC) and Raman spectrum results indicated that with the addition of TM-DTPMP LDHs, the value of heat release rate peak (pHRR) and total heat release (THR) were reduced by more than 43% and 60%, while the value of smoke formation rate (pSPR) and the total smoke production (TSP) decreased nearly 64% and 83%, respectively. The significant reduction in the release of combustion heat and harmful smoke during EP combustion may be attributed to the synergistic flame-retardant effect between hydrotalcite and DTPMP. This work exhibited great potential for the green recycling of PTs and the enhancement of the fire safety of EP.
Quantum Neurobiology
Authors: Swan Melanie , dos Santos Renato P. , Witte Franke
Published: February 2022

Quantum neurobiology is concerned with potential quantum effects operating in the brain and the application of quantum information science to neuroscience problems, the latter of which is the main focus of the current paper. The human brain is fundamentally a multiscalar problem, with complex behavior spanning nine orders of magnitude-scale tiers from the atomic and cellular level to brain networks and the central nervous system. In this review, we discuss a new generation of bio-inspired quantum technologies in the emerging field of quantum neurobiology and present a novel physics-inspired theory of neural signaling (AdS/Brain (anti-de Sitter space)). Three tiers of quantum information science-directed neurobiology applications can be identified. First are those that interpret empirical data from neural imaging modalities (EEG, MRI, CT, PET scans), protein folding, and genomics with wavefunctions and quantum machine learning. Second are those that develop neural dynamics as a broad approach to quantum neurobiology, consisting of superpositioned data modeling evaluated with quantum probability, neural field theories, filamentary signaling, and quantum nanoscience. Third is neuroscience physics interpretations of foundational physics findings in the context of neurobiology. The benefit of this work is the possibility of an improved understanding of the resolution of neuropathologies such as Alzheimer’s disease.
Precipitation Retrieval from Fengyun-3D Microwave Humidity and Temperature Sounder Data Using Machine Learning
Authors: Liu Kangwen , He Jieying , Chen Haonan
Published: February 2022

As an important component of the Earth system, precipitation plays a vital role in regional and global water cycles. Based on Microwave Humidity and Temperature Sounder (MWHTS) onboard FY-3D satellite, four machine learning models, random forest regression (RFR), support vector machine (SVM), multilayer perceptron (MLP), and gradient boosting regression tree (GBRT), are implemented to retrieve precipitation rate, and verified with Integrated Multi-satellite Retrievals for GPM (IMERG). This paper determines the optimal hyperparameters of the machine models and proposes three linear combinations of MWHTS channels (183.31 ± 1.0–183.31 ± 3.0 GHz, 183.31 ± 1.0–183.31 ± 7.0 GHz, and 183.31 ± 3.0–183.31 ± 7.0 GHz), which can better characterize precipitation of different intensities. With the inclusion of three linear combinations, the performances of all four machine learning models are significantly improved. It is concluded that the RFR and GBRT have the best retrieval accuracy. Over ocean, the MSE, MAE, and R2 values of precipitation estimates using RFR are 1.75 mm/h, 0.44 mm/h, and 0.80, respectively, and are 1.80 mm/h, 0.45 mm/h, and 0.78 for GBRT. Simultaneously, this paper analyzes the retrieval results from the perspective of the different rain rates and temporal matching difference between MWHTS and IMERG data. The RFR and GBRT also maintain the best retrieval accuracy under the condition of Gaussian noise, indicating the relatively strong robustness and antinoise performance of ensemble learning models for precipitation retrieval.
Fusion Classification of HSI and MSI Using a Spatial-Spectral Vision Transformer for Wetland Biodiversity Estimation
Authors: Gao Yunhao , Song Xiukai , Li Wei , Wang Jianbu , He Jianlong , Jiang Xiangyang , Feng Yinyin
Published: February 2022

The rapid development of remote sensing technology provides wealthy data for earth observation. Land-cover mapping indirectly achieves biodiversity estimation at a coarse scale. Therefore, accurate land-cover mapping is the precondition of biodiversity estimation. However, the environment of the wetlands is complex, and the vegetation is mixed and patchy, so the land-cover recognition based on remote sensing is full of challenges. This paper constructs a systematic framework for multisource remote sensing image processing. Firstly, the hyperspectral image (HSI) and multispectral image (MSI) are fused by the CNN-based method to obtain the fused image with high spatial-spectral resolution. Secondly, considering the sequentiality of spatial distribution and spectral response, the spatial-spectral vision transformer (SSViT) is designed to extract sequential relationships from the fused images. After that, an external attention module is utilized for feature integration, and then the pixel-wise prediction is achieved for land-cover mapping. Finally, land-cover mapping and benthos data at the sites are analyzed consistently to reveal the distribution rule of benthos. Experiments on ZiYuan1-02D data of the Yellow River estuary wetland are conducted to demonstrate the effectiveness of the proposed framework compared with several related methods.
Multispectral and SAR Image Fusion Based on Laplacian Pyramid and Sparse Representation
Authors: Zhang Hai , Shen Huanfeng , Yuan Qiangqiang , Guan Xiaobin
Published: February 2022

Complementary information from multi-sensors can be combined to improve the availability and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful spectral information of the Earth’s surface that is beneficial for identifying land cover types, while synthetic aperture radar (SAR) images can provide abundant information on the texture and structure of target objects. Therefore, this paper presents a fusion framework to integrate the information from MS and SAR images based on the Laplacian pyramid (LP) and sparse representation (SR) theory. LP is performed to decompose both the multispectral and SAR images into high-frequency components and low-frequency components, so that different processing strategies can be applied to multi-scale information. Low-frequency components are merged based on SR theory, whereas high-frequency components are combined based on a certain activity-level measurement, identifying salient features. Finally, LP reconstruction is performed to obtain the integrated image. We conduct experiments on several datasets to verify the effectiveness of the proposed method. Both visual interpretation and statistical analyses demonstrate that the proposed method strikes a satisfactory balance between spectral information preservation and the enhancement of spatial and textual characteristics. In addition, a further discussion regarding the adjustability property of the proposed method shows its flexibility for further application scenarios.
Stripe Noise Detection of High-Resolution Remote Sensing Images Using Deep Learning Method
Authors: Li Binbo , Zhou Ying , Xie Donghai , Zheng Lijuan , Wu Yu , Yue Jiabao , Jiang Shaowei
Published: February 2022

Stripe noise is considered one of the largest issues in space-borne remote sensing. The features of stripe noise in high-resolution remote sensing images are varied in different spatiotemporal conditions, leading to limited detection capability. In this study, we proposed a new detection algorithm (LSND: a linear stripe noise detection algorithm) considering stripe noise as a typical linear target. A large-scale stripe noise dataset for remote sensing images was created through linear transformations, and the target recognition of stripe noise was performed using deep convolutional neural networks. The experimental results showed that for sub-meter high-resolution remote sensing images such as GF-2 (GaoFen-2), our model achieved a precision of 98.7%, recall of 93.8%, F1-score of 96.1%, AP of 92.1%, and FPS of 35.71 for high resolution remote sensing images. Furthermore, our model exceeded ~40% on the accuracy and ~20% on the speed of the general models. Stripe noise detection would be helpful to detect the qualities of space-borne remote sensing and improve the quality of the images.
Assessing Surface Water Losses and Gains under Rapid Urbanization for SDG 6.6.1 Using Long-Term Landsat Imagery in the Guangdong-Hong Kong-Macao Greater Bay Area, China
Authors: Deng Yawen , Jiang Weiguo , Wu Zhifeng , Ling Ziyan , Peng Kaifeng , Deng Yue
Published: February 2022

As one of the most open and dynamic regions in China, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has been urbanizing rapidly in recent decades. The surface water in the GBA also has been suffering from urbanization and intensified human activities. The study aimed to characterize the spatiotemporal patterns and assess the losses and gains of surface water caused by urbanization in the GBA via long time-series remote sensing data, which could support the progress towards sustainable development goals (SDGs) set by the United Nations, especially for measuring SDG 6.6.1 indicator. Firstly, utilizing 4750 continuous Landsat TM/ETM+/OLI images during 1986–2020 and the Google Earth Engine cloud platform, the multiple index water detection rule (MIWDR) was performed to extract surface water extent in the GBA. Secondly, we achieved surface water dynamic type classification based on annual water inundation frequency time-series in the GBA. Finally, the spatial distribution and temporal variation of urbanization-induced water losses and gains were analyzed through a land cover transfer matrix. Results showed that (1) the average minimal and maximal surface water extents of the GBA during 1986–2020 were 2017.62 km2 and 6129.55 km2, respectively. The maximal surface water extent fell rapidly from 7897.96 km2 in 2001 to 5087.46 km2 in 2020, with a loss speed of 155.41 km2 per year (R2 = 0.86). (2) The surface water areas of permanent and dynamic types were 1529.02 km2 and 2064.99 km2 during 2000–2020, accounting for 42.54% and 57.46% of all water-related areas, respectively. (3) The surface water extent occupied by impervious land surfaces showed a significant linear downward trend (R2 = 0.98, slope = 36.41 km2 per year), while the surface water restored from impervious land surfaces denoted a slight growing trend (R2 = 0.86, slope = 0.99 km2 per year). Our study monitored the long-term changes in the surface water of the GBA, which can provide valuable information for the sustainable development of the GBA urban agglomeration. In addition, the proposed framework can easily be implemented in other similar regions worldwide.
Application of Shape Moments for Cloudiness Assessment in Marine Environmental Research
Authors: Paszkuta Marcin , Krężel Adam , Ryłko Natalia
Published: February 2022

The search for clouds in satellite images is a challenging subject which still attracts a lot of attention due to the amount and quality of data, which is growing at a tremendous pace, the development of satellite techniques and methods, inexpensive equipment, and automation of satellite imaging processes. This paper presents a new approach to the assessment of cloudiness based on the use of the theory of moments with invariants. The values of moments with invariants, determined on the basis of the available cloudiness maps, create a new, valuable set of data, which are the geometrical parameters of the scene representing the cloud cover. In further research, the obtained data sets will be used in machine learning methods, deep machine learning methods, etc. The method is used for different conditions, including different angular positions of the Sun and time periods. The effectiveness of the method is checked on the basis of comparing the entropy results of the input maps after subtracting clouds masked by various methods. The obtained results additionally indicate the potential of the moments method as a support for the existing methods of estimating cloudiness over the sea surface.
Intra-Annual Variability of Evapotranspiration in Response to Climate and Vegetation Change across the Poyang Lake Basin, China
Authors: Wang Ying , Liu Yuanbo , Jin Jiaxin , Fan Xingwang
Published: February 2022

Improving understanding of changes in intra-annual variability (IAV) of evapotranspiration (ET) and the underlying drivers is an essential step for modeling hydrological processes in response to global change. Previous studies paid special attention to climatic regulations of IAV of ET. However, ignoring the role of landscape characteristics (e.g., vegetation coverage) can introduce great uncertainty in the explanation of ET variance. In this work, the Poyang Lake Basin, which is a typical humid basin in China, was taken as the study area. It has experienced an obvious climate change and revegetation since the 1980s. Here, trends of IAV of ET and their responses to four climatic variables (i.e., air temperature, precipitation, downward shortwave radiation and wind speed) and vegetation coverage were explored from 1983 to 2014. The results show that IAV of ET exhibited contrary trends during the past decades. It significantly (p < 0.05) declined with a significant linear slope of −0.52 mm/year before 2000, and then slightly increased (slope = 0.06 mm/year, p > 0.05) over the basin, which was generally consistent with the IAV of temperature and radiation. The proposed variables could well capture the change in IAV of ET, while their dominators were different during the two contrasting phases mentioned above. The IAV of radiation and temperature dominated the change of the IAV of ET over 77.82% and 35.14% of the basin, respectively, before and after the turning point. Meanwhile, the rapid increase in vegetation coverage, which was associated with afforestation, significantly (p < 0.05) reduced IAV of ET over about 35% of the study area. The achievements of this study should be beneficial for a sophisticated awareness of responses of intra-annual variability of ET to climate and land cover changes at the basin scale.
The Accuracy of Winter Wheat Identification at Different Growth Stages Using Remote Sensing
Authors: Liu Shengwei , Peng Dailiang , Zhang Bing , Chen Zhengchao , Yu Le , Chen Junjie , Pan Yuhao , Zheng Shijun , Hu Jinkang , Lou Zihang , Chen Yue , Yang Songlin
Published: February 2022

The aim of this study was to explore the differences in the accuracy of winter wheat identification using remote sensing data at different growth stages using the same methods. Part of northern Henan Province, China was taken as the study area, and the winter wheat growth cycle was divided into five periods (seeding-tillering, overwintering, reviving, jointing-heading, and flowering-maturing) based on monitoring data obtained from agrometeorological stations. With the help of the Google Earth Engine (GEE) platform, the separability between winter wheat and other land cover types was analyzed and compared using the Jeffries-Matusita (J-M) distance method. Spectral features, vegetation index, water index, building index, texture features, and terrain features were generated from Sentinel-2 remote sensing images at different growth periods, and then were used to establish a random forest classification and extraction model. A deep U-Net semantic segmentation model based on the red, green, blue, and near-infrared bands of Sentinel-2 imagery was also established. By combining models with field data, the identification of winter wheat was carried out and the difference between the accuracy of the identification in the five growth periods was analyzed. The experimental results show that, using the random forest classification method, the best separability between winter wheat and the other land cover types was achieved during the jointing-heading period: the overall identification accuracy for the winter wheat was then highest at 96.90% and the kappa coefficient was 0.96. Using the deep-learning classification method, it was also found that the semantic segmentation accuracy of winter wheat and the model performance were best during the jointing-heading period: a precision, recall, F1 score, accuracy, and IoU of 0.94, 0.93, 0.93, and 0.88, respectively, were achieved for this period. Based on municipal statistical data for winter wheat, the accuracy of the extraction of the winter wheat area using the two methods was 96.72% and 88.44%, respectively. Both methods show that the jointing-heading period is the best period for identifying winter wheat using remote sensing and that the identification made during this period is reliable. The results of this study provide a scientific basis for accurately obtaining the area planted with winter wheat and for further studies into winter wheat growth monitoring and yield estimation.
Citizenship Ability, Homestead Utility, and Rural Homestead Transfer of “Amphibious” Farmers
Authors: Yuan Zhongyou , Fu Chenchen , Kong Shujie , Du Jifeng , Li Wei
Published: February 2022

Rural homestead transfer is of considerable significance for the revitalization of rural land assets and sustainable use of land resources. “Amphibious” farmers are the most likely to transfer their homestead. As such, it is important to study their transfer behavior and influencing factors to promote homestead transfer. The study involved distributing questionnaires to 768 “amphibious” farmers in Guangdong Province, China, and 747 samples were valid. The impact of the farmers’ citizenship ability and homestead utility preference on their homestead transfer behavior was analyzed using a binary logistic model. The study found that: (1) the citizenship ability of “amphibious” farmers had a significant positive impact on their willingness; the stronger the citizenship ability was, the stronger the willingness to transfer homesteads was. (2) Property and the guarantee utility of the homestead have an opposite impact on the willingness of “amphibious” farmers to transfer their homestead; if the property utility of the homestead is strong, its transfer intention is strong, but if the guarantee effect is strong, its transfer intention is weak. If the amphibious farmers are older, more educated, and have longer working years in cities, their willingness to transfer homestead will be lower. (3) The “amphibious” farmers working in cities and towns were found to have a stronger willingness to transfer homestead than those working in rural areas. Hence, the government should formulate differentiated policies for homestead transfer according to the ability endowment of farmers, improve various urban services and security infrastructure based on the urban housing of “amphibious” farmers, weaken the security utility of their rural homestead to flexibly realize their homestead property value, help them become citizens, and promote homestead transfer.
Short-Term Prediction of PM2.5 Using LSTM Deep Learning Methods
Authors: Kristiani Endah , Lin Hao , Lin Jwu-Rong , Chuang Yen-Hsun , Huang Chin-Yin , Yang Chao-Tung
Published: February 2022

This paper implements deep learning methods of recurrent neural networks and short-term memory models. Two kinds of time-series data were used: air pollutant factors, such as O3, SO2, and CO2 from 2017 to 2019, and meteorological factors such as temperature, humidity, wind direction, and wind speed. A trained model was used to predict air pollution within an eight-hour period. Correlation analysis was applied using Pearson and Spearman correlation coefficients. The KNN method was used to fill in the missing values to improve the generated model’s accuracy. The average absolute error percentage value was used in the experiments to evaluate the model’s performance. LSTM had the lowest RMSE value at 1.9 than the other models from the experiments. CNN had a significant RMSE value at 3.5, followed by Bi-LSTM at 2.5 and Bi-GRU at 2.7. In comparison, the RNN was slightly higher than LSTM at a 2.4 value.
Study on the Design of a Water Dispenser for Visually Impaired Families
Authors: Shen Qiong , Zhou Feng , Wang Yichen , Tang Shiyuan , Zhang Pengyu
Published: February 2022

In visually impaired families, there are different needs in terms of the access to drinking water, and the existing research on the design of water dispensers is insufficient. In order to solve this problem, a diverse analysis, based on the inclusive design concept, of household users’ operating abilities and water dispenser preferences was carried out. Subsequently and guided by the analysis, a new water dispenser product was developed. The methods used to extrapolate the needs of visually impaired families were observation and interviews, while the questionnaire research was used to understand the user preferences. Secondly, the accessibility of the existing water dispenser was tested for visually impaired, elderly, middle-aged, and young users in the visually impaired family. Three design strategies were proposed that combine the needs and product preferences of the users: the multimode simplification of steps, water quality detection, and adaptive multichannel feedback. The water dispenser was redesigned on the basis of these. On the premise of meeting the different abilities of the users in visually impaired families, the design practice improves the users’ experience of water dispensers, and provides a practical method reference that has value for related product designs.
Human, Organisational and Societal Factors in Robotic Rail Infrastructure Maintenance
Authors: Golightly David , Chan-Pensley Jamie , Dadashi Nastaran , Jundi Shyma , Ryan Brendan , Hall Amanda
Published: February 2022

Robotics are set to play a significant role in the maintenance of rail infrastructure. However, the introduction of robotics in this environment requires new ways of working for individuals, teams and organisations and needs to reflect societal attitudes if it is to achieve sustainable goals. The following paper presents a qualitative analysis of interviews with 25 experts from rail and robotics to outline the human and organisational issues of robotics in the rail infrastructure environment. Themes were structured around user, team, organisational and societal issues. While the results point to many of the expected issues of robotics (trust, acceptance, business change), a number of issues were identified that were specific to rail. Examples include the importance of considering the whole maintenance task lifecycle, conceptualizing robotic teamworking within the structures of rail maintenance worksites, the complex upstream (robotics suppliers) and downstream (third-party maintenance contractors) supply chain implications of robotic deployment and the public acceptance of robotics in an environment that often comes into direct contact with passenger and people around the railways. Recommendations are made in the paper for successful, human-centric rail robotics deployment.