bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Magnetized Coagulants on Wastewater Treatment: Rice Starch and Chitosan Ratios Evaluation
Authors: Sibiya Nomthandazo Precious , Amo-Duodu Gloria , Tetteh Emmanuel Kweinor , Rathilal Sudesh
Published: October 2022

Coagulation with synthetic chemicals has been used to treat a wide range of industrial effluents. Herein, the unique characteristics of industrial effluents being detrimental to the environment warrants urgent resource-efficient and eco-friendly solutions. Therefore, the study investigated the use of two magnetized coagulants (chitosan magnetite (CF) and rice starch magnetite (RF)), prepared via co-precipitation in three different ratios (1:2, 1:1 and 2:1) of natural coagulants (chitosan or rice starch) and magnetite nanoparticles (F) as alternative coagulants to alum for the treatment of wastewater. A Brunauer–Emmett–Teller (BET) analyzer, an X-ray diffraction (XRD) analyzer, and energy-dispersive X-ray (EDX) spectroscopy were used to characterize the surface area, crystal structure, and elemental composition of the coagulants. The influences of settling time (10–60 min) on the reduction of turbidity, color, phosphate, and absorbance were studied. This was carried out with a jar test coupled with six beakers operated under coagulation conditions of rapid stirring (150 rpm) and gentle stirring (30 rpm). Wastewater with an initial concentration of 45.6 NTU turbidity, 315 Pt. Co color, 1.18 mg/L phosphate, 352 mg/L chemical oxygen demand (COD), and 73.4% absorbance was used. The RF with a ratio of 1:1 was found to be the best magnetized coagulant with over 80% contaminant removal and 90% absorbance. The treatability performance of RF (1:1) has clearly demonstrated that it is feasible for wastewater treatment.
Supramolecular Structure and Mechanical Performance of κ-Carrageenan–Gelatin Gel
Authors: Makarova Anastasiya O. , Derkach Svetlana R. , Kadyirov Aidar I. , Ziganshina Sufia A. , Kazantseva Mariia A. , Zueva Olga S. , Gubaidullin Aidar T. , Zuev Yuriy F.
Published: October 2022

In this work, by means of complex physicochemical methods the structural features of a composite κ-carrageenan–gelatin system were studied in comparison with initial protein gel. The correlation between the morphology of hydrogels and their mechanical properties was demonstrated through the example of changes in their rheological characteristics. The experiments carried out with PXRD, SAXS, AFM and rheology approaches gave new information on the structure and mechanical performance of κ-carrageenan–gelatin hydrogel. The combination of PXRD, SAXS and AFM results showed that the morphological structures of individual components were not observed in the composite protein–polysaccharide hydrogels. The results of the mechanical testing of initial gelatin and engineered κ-carrageenan–gelatin gel showed the substantially denser parking of polymer chains in the composite system due to a significant increase in intermolecular protein–polysaccharide contacts. Close results were indirectly followed from the SAXS estimations—the driving force for the formation of the common supramolecular structural arrangement of proteins and polysaccharides was the increase in the density of network of macromolecular chains entanglements; therefore, an increase in the energy costs was necessary to change the conformational rearrangements of the studied system. This increase in the macromolecular arrangement led to the growth of the supramolecular associate size and the growth of interchain physical bonds. This led to an increase in the composite gel plasticity, whereas the enlargement of scattering particles made the novel gel system not only more rigid, but also more fragile.
Chemical, Thermal and Mechanical Characterization of Licorice Root, Willow, Holm Oak, and Palm Leaf Waste Incorporated into Maleated Polypropylene (MAPP)
Authors: Gabrielli Serena , Caviglia Miriam , Pastore Genny , Marcantoni Enrico , Nobili Francesco , Bottoni Luca , Catorci Andrea , Bavasso Irene , Sarasini Fabrizio , Tirillò Jacopo , Santulli Carlo
Published: October 2022

The effect of four lignocellulosic waste fillers on the thermal and mechanical properties of biocomposites was investigated. Powdered licorice root, palm leaf, holm oak and willow fillers were melt compounded with polypropylene at two different weight contents, i.e., 10 and 30, and then injection molded. A commercially available maleated coupling agent was used to improve the filler/matrix interfacial adhesion at 5 wt.%. Composites were subjected to chemical (FTIR-ATR), thermal (TGA, DSC, DMA) and mechanical (tensile, bending and Charpy impact) analyses coupled with a morphological investigation by scanning electron microscopy. Although similarities among the different formulations were noted, holm oak fillers provided the best combination of thermal and mechanical performance. In particular, at 30 wt.% content with coupling agent, this composite formulation displayed remarkable increases in tensile strength and modulus, flexural strength and modulus, of 28% and 110%, 58% and 111%, compared to neat PP, respectively. The results imply that all these lignocellulosic waste fillers can be used successfully as raw materials for biocomposites, with properties comparable to those featured by other natural fillers.
Analysis of the Influence of Production Method, Plastic Content on the Basic Performance of Waste Plastic Modified Asphalt
Authors: Li Haibin , Zhou Lichang , Sun Jianmei , Wang Sirui , Zhang Mingming , Hu Yihong , Temitope Ahmed Abdulakeem
Published: October 2022

The sustainable reuse of waste plastic as an alternative construction material has numerous environmental and economic advantages. New opportunities to recycle waste plastic in asphalt for road construction would mitigate landfill issues and significantly reduce global carbon emissions. With a clear aim to contribute to a more efficient reuse of waste plastic, this paper reutilized two types of waste plastic (polypropylene (PP) and polyethylene (PE)) as asphalt modifiers to improve the performance of asphalt pavement as well as to achieve the purpose of sustainable recycling waste plastic. Therefore, the optimal preparation parameters of plastic-modified asphalt were recommended by the orthogonal test. Then, the dispersion and modification mechanisms of plastic particles in plastic-modified asphalt were further studied by Fourier Transform Infrared Spectroscopy (FTIR) and Thermogravimetric Differential Scanning Calorimetry (TG-DSC). The results show that the asphalt containing PP and PE shows better overall performance at high temperatures compared with the base asphalt. Furthermore, PE-modified asphalt and PP-modified asphalt exhibited optimal properties when prepared at 3000 rpm for 30 min at 170 °C. Moreover, the results of the expansion mechanism show that the main reaction process of plastic asphalt is a physical change. Finally, PP-modified asphalt and PE-modified asphalt generally perform well and are suitable for high-temperature areas. Consequentially, the results of this research promote the recycling of waste plastic, ultimately advocating the recycling of waste materials and environmental protection of pavement construction.
Amphiphilic Diblock Copolymers Bearing Poly(Ethylene Glycol) Block: Hydrodynamic Properties in Organic Solvents and Water Micellar Dispersions, Effect of Hydrophobic Block Chemistry on Dispersion Stability and Cytotoxicity
Authors: Elistratova Anastasiia A. , Gubarev Alexander S. , Lezov Alexey A. , Vlasov Petr S. , Solomatina Anastasia I. , Liao Yu-Chan , Chou Pi-Tai , Tunik Sergey P. , Chelushkin Pavel S. , Tsvetkov Nikolai V.
Published: October 2022

Despite the fact that amphiphilic block copolymers have been studied in detail by various methods both in common solvents and aqueous dispersions, their hydrodynamic description is still incomplete. In this paper, we present a detailed hydrodynamic study of six commercial diblock copolymers featuring the same hydrophilic block (poly(ethylene glycol), PEG; degree of polymerization is ca. 110 ± 25) and the following hydrophobic blocks: polystyrene, PS35-b-PEG115; poly(methyl methacrylate), PMMA55-b-PEG95; poly(1,4-butadyene), PBd90-b-PEG130; polyethylene PE40-b-PEG85; poly(dimethylsiloxane), PDMS15-b-PEG115; and poly(ɛ-caprolactone), PCL45-b-PEG115. The hydrodynamic properties of block copolymers are investigated in both an organic solvent (tetrahydrofuran) and in water micellar dispersions by the combination of static/dynamic light scattering, viscometry, and analytical ultracentrifugation. All the micellar dispersions demonstrate bimodal particle distributions: small compact (hydrodynamic redii, Rh ≤ 17 nm) spherical particles ascribed to “conventional” core–shell polymer micelles and larger particles ascribed to micellar clusters. Hydrodynamic invariants are (2.4 ± 0.4) × 10−10 g cm2 s−2 K−1 mol−1/3 for all types of micelles used in the study. For aqueous micellar dispersions, in view of their potential biomedical applications, their critical micelle concentration values and cytotoxicities are also reported. The investigated micelles are stable towards precipitation, possess low critical micelle concentration values (with the exception of PDMS15-b-PEG115), and demonstrate low toxicity towards Chinese Hamster Ovarian (CHO-K1) cells.
Synergy in Aqueous Systems Containing Bioactive Ingredients of Natural Origin: Saponin/Pectin Mixtures
Authors: Petkova Hristina , Jarek Ewelina , Doychinov Mitko , Krzan Marcel , Mileva Elena
Published: October 2022

Biocompatible and biodegradable ingredients of natural origin are widely used in the design of foam and emulsion systems with various technological applications in the food, cosmetics and pharmaceutical industries. The determination of the precise composition of aqueous solution formulations is a key issue for the achievement of environmentally-friendly disperse systems with controllable properties and reasonable stability. The present work is focused on the investigation of synergistic interactions in aqueous systems containing Quillaja saponins and Apple pectins. Profile analysis tensiometer (PAT-1) is applied to study the surface tension and surface dilational rheology of the adsorption layers at the air/solution interface. The properties and the foam films (drainage kinetics, film thickness, disjoining pressure isotherm, critical pressure of rupture) are investigated using the thin-liquid-film (TLF) microinterferometric method of Scheludko–Exerowa and the TLF-pressure-balance technique (TLF-PBT). The results demonstrate that the structure and stability performance of the complex aqueous solutions can be finely tuned by changing the ratio of the bioactive ingredients. The attained experimental data evidence that the most pronounced synergy effect is registered at a specific saponin:pectin ratio. The obtained information is essential for the further development of aqueous solution formulations intended to achieve stable foams based on mixtures of Quillaja saponins and Apple pectins in view of future industrial, pharmaceutical and biomedical applications.
Photochemical and Thermal Stability of Bionanocellulose/Poly(Vinyl Alcohol) Blends
Authors: Długa Aldona , Bajer Dagmara , Kaczmarek Halina
Published: October 2022

This research focuses on novel ecological materials for biomedical and cosmetic applications. The cellulose of bacterial origin is well suited for such purposes, but its functional properties must be modified. In this work, the blends of bionanocellulose and poly(vinyl alcohol), BNC/PVA, were prepared based on in situ and ex situ methodology combined with impregnation and sterilization, using different concentrations of PVA. The main purpose of this work was to check the influence of UV radiation and high temperature, which can be sterilizing factors, on the properties of these mixtures. It was found that the crystallinity degree increases in UV-irradiated samples due to the photodegradation of the amorphous phase. This changes the mechanical properties: the breaking stress and Young’s modulus decreased, while the strain at break increased in most UV-irradiated samples. The surface morphology, which we observed by using AFM, did not change significantly after exposure, but the roughness and surface free energy changed irregularly in samples obtained by different methods. However, the effects induced by UV-irradiation were not so crucial as to deteriorate the materials’ properties designed for medical applications. Thermogravimetric analysis exhibited good thermal stability for all samples up to at least 200 °C, which allows for the prediction of these systems also in industrial sectors.
Microstructure—Thermal Property Relationships of Poly (Ethylene Glycol-b-Caprolactone) Copolymers and Their Micelles
Authors: Faisal Khandokar Sadique , Clulow Andrew J. , MacWilliams Stephanie V. , Gillam Todd A. , Austin Ashlyn , Krasowska Marta , Blencowe Anton
Published: October 2022

The crystallinity of polymers strongly affects their properties. For block copolymers, whereby two crystallisable blocks are covalently tethered to one another, the molecular weight of the individual blocks and their relative weight fraction are important structural parameters that control their crystallisation. In the case of block copolymer micelles, these parameters can influence the crystallinity of the core, which has implications for drug encapsulation and release. Therefore, in this study, we aimed to determine how the microstructure of poly(ethylene glycol-b-caprolactone) (PEG-b-PCL) copolymers contributes to the crystallinity of their hydrophobic PCL micelle cores. Using a library of PEG-b-PCL copolymers with PEG number-average molecular weight (Mn) values of 2, 5, and 10 kDa and weight fractions of PCL (fPCL) ranging from 0.11 to 0.67, the thermal behaviour and morphology were studied in blends, bulk, and micelles using differential scanning calorimetry (DSC), wide-angle X-ray diffraction (WXRD), and Synchrotron wide-angle X-ray scattering (WAXS). Compared to PEG and PCL homopolymers, the block copolymers displayed reduced crystallinity in the bulk phase and the individual blocks had a large influence on the crystallisation of one another. The fPCL was determined to be the dominant contributor to the extent and order of crystallisation of the two blocks. When fPCL < 0.35, the initial crystallisation of PEG led to an amorphous PCL phase. At fPCL values between 0.35 and 0.65, PEG crystallisation was followed by PCL crystallisation, whereas this behaviour was reversed when fPCL > 0.65. For lyophilised PEG-b-PCL micelles, the crystallinity of the core increased with increasing fPCL, although the core was predominately amorphous for micelles with fPCL < 0.35. These findings contribute to understanding the relationships between copolymer microstructure and micelle core crystallinity that are important for the design and performance of micellar drug delivery systems, and the broader application of polymer micelles.
Potential of a Composite Conduit with Bacterial Nanocellulose and Fish Gelatin for Application as Small-Diameter Artificial Blood Vessel
Authors: Bao Luhan , Li Can , Tang Man , Chen Lin , Hong Feng F.
Published: October 2022

Bacterial nanocellulose (BNC) has received great attention for application as an artificial blood vessel material. However, many results showed that pristine BNC could not perfectly meet all the demands of blood vessels, especially for rapid endothelialization. In order to improve the properties of small-caliber vessels, different concentrations of fish gelatin (Gel) were deposited into the 3D network tubes and their properties were explored. The BNC/Gel composite tubes were treated with glutaraldehyde to crosslink BNC and fish gelatin. Compared with pristine BNC tubes, the BNC/Gel tubes had a certain improvement in mechanical properties. In vitro cell culture demonstrated that the human endothelial cells (HUVECs) and human smooth muscle cells (HSMCs) planted on the internal walls of BNC/Gel tubes showed better adhesion, higher proliferation and differentiation potential, and a better anticoagulation property, as compared to the cells cultured on pristine BNC tubes. Whole-blood coagulation experiments showed that the BNC/Gel tube had better properties than the BNC tube, and the hemolysis rate of all samples was less than 1.0%, satisfying the international standards for medical materials. An increase in the content of fish gelatin also increased the mechanical properties and the biocompatibility of small-caliber vessels. Considering the properties of BNC/Gel tubes, 1.0 wt/v% was selected as the most appropriate concentration of fish gelatin for a composite.
The Impact of Water-Soluble Chitosan on the Inhibition of Crystal Nucleation of Alpha-Mangostin from Supersaturated Solutions
Authors: Budiman Arif , Nurfadilah Nisrina , Muchtaridi Muchtaridi , Sriwidodo Sriwidodo , Aulifa Diah Lia , Rusdin Agus
Published: October 2022

The use of an amorphous drugs system to generate supersaturated solutions is generally developed to improve the solubility and dissolution of poorly soluble drugs. This is because the drug in the supersaturation system has a high energy state with a tendency to precipitate. In the amorphous solid dispersion (ASD) formulation, it was discovered that polymer plays a critical role in inhibiting nucleation or crystal growth of the drugs. Therefore, this study aimed to evaluate the crystallization inhibition of water-soluble chitosan (WSC) on nucleation as well as crystal growth from alpha-mangostin (AM) and elucidate its inhibition mechanism in the supersaturated solutions. During the experiment, WSC was used as a polymer to evaluate its ability to inhibit AM nucleation. The interaction between WSC and AM was also estimated using FT-IR, NMR, and in silico study. The result showed that in the absence of polymer, the concentration of AM rapidly decreased due to the precipitation in one minute. Meanwhile, the addition of WSC effectively inhibited AM crystallization and maintained a supersaturated state for the long term. FT-IR measurement also revealed that the shift in the amine primer of WSC occurred because of the interaction between WSC and AM. In the 1H NMR spectra, the proton peaks of WSC showed an upfield shift with the presence of AM, indicating the intermolecular interactions between AM and WSC. Moreover, in silico study revealed the hydrogen bond interaction between the carbonyl group of AM with hydrocarbon groups of WSC. This indicated that WSC interacted with AM in the supersaturated solution and suppressed their molecular mobility, thereby inhibiting the formation of the crystal nucleus. Based on these results, it can be concluded that the interaction between drug polymers contributed to the maintenance of the drug supersaturation by inhibiting both nucleation and growth.
Waste Eggshells as a Natural Filler for the Poly(Vinyl Chloride) Composites
Authors: Skórczewska Katarzyna , Lewandowski Krzysztof , Szewczykowski Piotr , Wilczewski Sławomir , Szulc Joanna , Stopa Paulina , Nowakowska Paulina
Published: October 2022

The paper presents the characteristics of unplasticized PVC composites modified with biofiller obtained from the waste eggshells of hen eggs. The composites obtained by extrusion contained from 10 phr to 40 phr of biofiller. The filler was characterized using the SEM, TG, and sieve analysis methods. The influence of the filler on the processing properties was determined using plastographometric and MFR tests. Fundamental analysis of mechanical properties was also performed, i.e., Charpy impact strength and determination of tensile properties. The mechanical properties were supported with dynamical mechanical thermal analysis, time of thermal stability, and thermogravimetric analysis. Structure analysis was also performed using SEM and X-ray microcomputed tomography (micro-CT). The processing properties of the tested composites do not give grounds for disqualifying such material from traditional processing PVC mixtures. Notably, the biofiller significantly improves thermal stability. Ground eggshells (ES) work as scavengers for the Cl radicals released in the first stage, which delays the PVC chain’s decay. Additionally, a significant increase in the value of the modulus of elasticity and softening point (VST) of the composites concerning PVC was found. Ground hen eggshells can be used as an effective filler for PVC composites.
High-Resolution, Transparent, and Flexible Printing of Polydimethylsiloxane via Electrohydrodynamic Jet Printing for Conductive Electronic Device Applications
Authors: Hassan Rizwan Ul , Khalil Shaheer Mohiuddin , Khan Saeed Ahmed , Ali Shahzaib , Moon Joonkyeong , Cho Dae-Hyun , Byun Doyoung
Published: October 2022

In the field of soft electronics, high-resolution and transparent structures based on various flexible materials constructed via various printing techniques are gaining attention. With the support of electrical stress-induced conductive inks, the electrohydrodynamic (EHD) jet printing technique enables us to build high-resolution structures compared with conventional inkjet printing techniques. Here, EHD jet printing was used to fabricate a high-resolution, transparent, and flexible strain sensor using a polydimethylsiloxane (PDMS)/xylene elastomer, where repetitive and controllable high-resolution printed mesh structures were obtained. The parametric effects of voltage, flow rate, nozzle distance from the substrate, and speed were experimentally investigated to achieve a high-resolution (5 µm) printed mesh structure. Plasma treatment was performed to enhance the adhesion between the AgNWs and the elastomer structure. The plasma-treated functional structure exhibited stable and long strain-sensing cycles during stretching and bending. This simple printing technique resulted in high-resolution, transparent, flexible, and stable strain sensing. The gauge factor of the strain sensor was significantly increased, owing to the high resolution and sensitivity of the printed mesh structures, demonstrating that EHD technology can be applied to high-resolution microchannels, 3D printing, and electronic devices.
Characterization and Prediction of Physical Properties of Luanta Fir Wood with Vacuum Hydrothermal Treatment
Authors: Hsieh Ming-Chi , Hung Ke-Chang , Xu Jin-Wei , Chang Wen-Shao , Wu Jyh-Horng
Published: October 2022

This study used the luanta fir (Cunninghamia konishii Hayata) wood, one of the most used wood construction and building materials in Taiwan, as specimens to examine the impact of different conditions of vacuum hydrothermal (VH) treatment on the physical properties of this wood. A prediction model for these properties was created using a nondestructive spectroscopy technique. The test results revealed that the mass loss, moisture exclusion efficiency, anti-swelling efficiency, color difference, and surface contact angle of the VH-treated wood all increased under increasing heat treatment temperature and time. Moreover, the use of near-infrared (NIR) spectroscopy in creating the prediction model for the physical properties of the VH-treated luanta fir wood revealed that the ratios of performance to deviation (RPD) for mass loss, equilibrium moisture content, and color difference were all above 2.5, indicating a high prediction accuracy. These results suggested that an NIR spectrometer can serve as a useful instrument for the accurate prediction of the physical properties or for controlling the quality of VH-treated wood.
Design Evaluation of FFF-Printed Transtibial Prosthetic Sockets Using Follow-Up and Finite Element Analysis
Authors: van der Stelt Merel , Stenveld Fianna , Bitter Thom , Maal Thomas J. J. , Janssen Dennis
Published: October 2022

Background: Participants in Sierra Leone received a Fused Filament Fabrication (FFF)-printed transtibial prosthetic socket. Follow-up was conducted on this group over a period of 21 months. To investigate the failure of some of the FFF-printed transtibial sockets, further strength investigation is desired. Methods: A finite element (FE) analysis provided an extensive overview of the strength of the socket. Using follow-up data and FE analyses, weak spots were identified, and the required optimization/reinforcement of the socket wall was determined. Results: Five sockets with a 4 mm wall thickness were tested by five participants. The strength of the 4 mm prosthetic socket seemed to be sufficient for people with limited activity. The 4 mm sockets used by active participants failed at the patella tendon or popliteal area. One socket with a wall thickness of 6 mm was used by an active user and remained intact after one year of use. An FE analysis of the socket showed high stresses in the patella tendon area. An increased wall thickness of 7 mm leads to a decrease of 26% in the stress corresponding to the observed failure in the patella tendon area, compared to the 4 mm socket. Conclusions: Follow-up in combination with an FE analysis can provide insight into the strength of the transtibial socket. In future designs, both the patella tendon and popliteal area will be reinforced by a thickened trim line of 7 mm. A design with a thickened trimline of 7 mm is expected to be sufficiently strong for active users. Another follow-up study will be performed to confirm this.
Proteomic Approach for Comparative Analysis of the Spike Protein of SARS-CoV-2 Omicron (B.1.1.529) Variant and Other Pango Lineages
Authors: Jain Mukul , Patil Nil , Gor Darshil , Sharma Mohit , Goel Neha , Kaushik Prashant
Published: October 2022

The novel SARS-CoV-2 variant, Omicron (B.1.1.529), is being testified, and the WHO has characterized Omicron as a variant of concern due to its higher transmissibility and very contagious behavior, immunization breakthrough cases. Here, the comparative proteomic study has been conducted on spike-protein, hACE2 of five lineages (α, β, δ, γ and Omicron. The docking was performed on spike protein- hACE-2 protein using HADDOCK, and PRODIGY was used to analyze the binding energy affinity using a reduced Haddock score. Followed by superimposition in different variant-based protein structures and calculated the esteem root mean square deviation (RMSD). This study reveals that Omicron was seen generating a monophyletic clade. Further, as α variant is the principal advanced strain after Wuhan SARS-CoV-2, and that is the reason it was showing the least likeness rate with the Omicron and connoting Omicron has developed of late with the extreme number of mutations. α variant has shown the highest binding affinity with hACE2, followed by β strain, and followed with γ. Omicron showed a penultimate binding relationship, while the δ variant was seen as having the least binding affinity. This proteomic basis in silico analysis of variable spike proteins of variants will impart light on the development of vaccines and the identification of mutations occurring in the upcoming variants.
Older Adults with Dementia: Association of Prayer with Neuropsychiatric Symptoms, Cognitive Function, and Sleep Disturbances
Authors: Britt Katherine Carroll , Richards Kathy C. , Acton Gayle , Hamilton Jill , Radhakrishnan Kavita
Published: October 2022

Protective factors that slow dementia progression and improve quality of life are needed. Neuropsychiatric symptoms (NPS), cognitive decline, and sleep disturbances are commonly found in dementia, indicate progression, and increase caregiver distress. The purpose of this study was to examine the association of private prayer with NPS, cognitive function, and sleep disturbances in older adults with dementia. We analyzed data from the Health and Retirement Study in 2000, 2006, and 2008 and Aging, Demographics, and Memory Sub study in 2001–2003, 2006–2007, and 2008–2009 among 40 older adults (age 70–100 years, mean age = 84.67, 29 females and 11 males, 73.9% non-Hispanic White, and 19.2% Non-Hispanic Black, and 3% Hispanic, cognitive function = 1.169 indicating mild cognitive impairment) using correlational analysis. The results indicated that increased frequency of private prayer was significantly associated with lower NPS, better cognitive function, and lower sleep disturbances. In total, 100% of Non-Hispanic Black and Hispanic participants reported praying at least once per week. Findings could be due to use of cognitive processes used in prayer during supplication, requesting aid, and through communication with the divine, reducing loneliness. Longitudinal studies including historically underrepresented populations are needed to examine these associations over time.
A Novel Dual-Branch Neural Network Model for Flood Monitoring in South Asia Based on CYGNSS Data
Authors: Song Dongmei , Zhang Qiqi , Wang Bin , Yin Cong , Xia Junming
Published: October 2022

Microwave remote sensing is widely applied in flood monitoring due to its independence from severe weather conditions, which usually restrict the usage of optical sensors. However, it is challenging to track the variation process of flood events in a timely manner by traditional active and passive microwave techniques, since they cannot simultaneously provide measurements with high spatial and temporal resolution. The emerging Global Navigation Satellite System Reflectometry (GNSS-R) technique with high spatio-temporal resolution offers a new solution to the dynamic monitoring of flood inundation. Considering the high sensitivity of GNSS-R signals to flooding, this paper proposes a dual-branch neural network (DBNN) with a convolution neural network (CNN) and a back propagation (BP) neural network for flood monitoring. The CNN module is used to automatically extract the abstract features from delay-Doppler maps (DDMs), while the BP module is fed with GNSS-R typical features, such as surface reflectivity and power ratio, as well as vegetation information from Soil Moisture Active Passive satellite (SMAP) data. In the experiments, the superiority of the DBNN method is firstly demonstrated by comparing it with the surface reflectivity and power ratio methods. Then, the spatio-temporal variation process of the 2020 South Asian flood events is analyzed by the proposed method based on Cyclone Global Navigation Satellite System (CYGNSS) data. The understanding of flood change processes could help enhance the capacity for resisting flood disasters.
Google Earth Engine for Informal Settlement Mapping: A Random Forest Classification Using Spectral and Textural Information
Authors: Matarira Dadirai , Mutanga Onisimo , Naidu Maheshvari
Published: October 2022

Accurate and reliable informal settlement maps are fundamental decision-making tools for planning, and for expediting informed management of cities. However, extraction of spatial information for informal settlements has remained a mammoth task due to the spatial heterogeneity of urban landscape components, requiring complex analytical processes. To date, the use of Google Earth Engine platform (GEE), with cloud computing prowess, provides unique opportunities to map informal settlements with precision and enhanced accuracy. This paper leverages cloud-based computing techniques within GEE to integrate spectral and textural features for accurate extraction of the location and spatial extent of informal settlements in Durban, South Africa. The paper aims to investigate the potential and advantages of GEE’s innovative image processing techniques to precisely depict morphologically varied informal settlements. Seven data input models derived from Sentinel 2A bands, band-derived texture metrics, and spectral indices were investigated through a random forest supervised protocol. The main objective was to explore the value of different data input combinations in accurately mapping informal settlements. The results revealed that the classification based on spectral bands + textural information yielded the highest informal settlement identification accuracy (94% F-score). The addition of spectral indices decreased mapping accuracy. Our results confirm that the highest spatial accuracy is achieved with the ‘textural features’ model, which yielded the lowest root-mean-square log error (0.51) and mean absolute percent error (0.36). Our approach highlights the capability of GEE’s complex integrative data processing capabilities in extracting morphological variations of informal settlements in rugged and heterogeneous urban landscapes, with reliable accuracy.
Analyses of the Impact of Soil Conditions and Soil Degradation on Vegetation Vitality and Crop Productivity Based on Airborne Hyperspectral VNIR–SWIR–TIR Data in a Semi-Arid Rainfed Agricultural Area (Camarena, Central Spain)
Authors: Milewski Robert , Schmid Thomas , Chabrillat Sabine , Jiménez Marcos , Escribano Paula , Pelayo Marta , Ben-Dor Eyal
Published: October 2022

Soils are an essential factor contributing to the agricultural production of rainfed crops such as barley and triticale cereals. Changing environmental conditions and inadequate land management are endangering soil quality and productivity and, in turn, crop quality and productivity are affected. Advances in hyperspectral remote sensing are of great use for the spatial characterization and monitoring of the soil degradation status, as well as its impact on crop growth and agricultural productivity. In this study, hyperspectral airborne data covering the visible, near-infrared, short-wave infrared, and thermal infrared (VNIR–SWIR–TIR, 0.4–12 µm) were acquired in a Mediterranean agricultural area of central Spain and used to analyze the spatial differences in vegetation vitality and grain yield in relation to the soil degradation status. Specifically, leaf area index (LAI), crop water stress index (CWSI), and the biomass of the crop yield are derived from the remote sensing data and discussed regarding their spatial differences and relationship to a classification of erosion and accumulation stages (SEAS) based on previous remote sensing analyses during bare soil conditions. LAI and harvested crop biomass yield could be well estimated by PLS regression based on the hyperspectral and in situ reference data (R2 of 0.83, r of 0.91, and an RMSE of 0.2 m2 m−2 for LAI and an R2 of 0.85, r of 0.92, and an RMSE of 0.48 t ha−1 for grain yield). In addition, the soil erosion and accumulation stages (SEAS) were successfully predicted based on the canopy spectral signal of vegetated crop fields using a random forest machine learning approach. Overall accuracy was achieved above 71% by combining the VNIR–SWIR–TIR canopy reflectance and emissivity of the growing season with topographic information after reducing the redundancy in the spectral dataset. The results show that the estimated crop traits are spatially related to the soil’s degradation status, with shallow and highly eroded soils, as well as sandy accumulation zones being associated with areas of low LAI, crop yield, and high crop water stress. Overall, the results of this study illustrate the enormous potential of imaging spectroscopy for a combined analysis of the plant-soil system in the frame of land and soil degradation monitoring.
Wetlands Classification Using Quad-Polarimetric Synthetic Aperture Radar through Convolutional Neural Networks Based on Polarimetric Features
Authors: Zhang Shuaiying , An Wentao , Zhang Yue , Cui Lizhen , Xie Chunhua
Published: October 2022

Wetlands are the “kidneys” of the earth and are crucial to the ecological environment. In this study, we utilized GF-3 quad-polarimetric synthetic aperture radar (QP) images to classify the ground objects (nearshore water, seawater, spartina alterniflora, tamarix, reed, tidal flat, and suaeda salsa) in the Yellow River Delta through convolutional neural networks (CNNs) based on polarimetric features. In this case, four schemes were proposed based on the extracted polarimetric features from the polarization coherency matrix and reflection symmetry decomposition (RSD). Through the well-known CNNs: AlexNet and VGG16 as backbone networks to classify GF-3 QP images. After testing and analysis, 21 total polarimetric features from RSD and the polarization coherency matrix for QP image classification contributed to the highest overall accuracy (OA) of 96.54% and 94.93% on AlexNet and VGG16, respectively. The performance of the polarization coherency matrix and polarimetric power features was similar but better than just using three main diagonals of the polarization coherency matrix. We also conducted noise test experiments. The results indicated that OAs and kappa coefficients decreased in varying degrees after we added 1 to 3 channels of Gaussian random noise, which proved that the polarimetric features are helpful for classification. Thus, higher OAs and kappa coefficients can be acquired when more informative polarimetric features are input CNNs. In addition, the performance of RSD was slightly better than obtained using the polarimetric coherence matrix. Therefore, RSD can help improve the accuracy of polarimetric SAR image classification of wetland objects using CNNs.
Multi-Feature Aggregation for Semantic Segmentation of an Urban Scene Point Cloud
Authors: Chen Jiaqing , Zhao Yindi , Meng Congtang , Liu Yang
Published: October 2022

With the rapid development of cities, semantic segmentation of urban scenes, as an important and effective imaging method, can accurately obtain the distribution information of typical urban ground features, reflecting the development scale and the level of greenery in the cities. There are some challenging problems in the semantic segmentation of point clouds in urban scenes, including different scales, imbalanced class distribution, and missing data caused by occlusion. Based on the point cloud semantic segmentation network RandLA-Net, we propose the semantic segmentation networks RandLA-Net++ and RandLA-Net3+. The RandLA-Net++ network is a deep fusion of the shallow and deep features of the point clouds, and a series of nested dense skip connections is used between the encoder and decoder. RandLA-Net3+ is based on the multi-scale connection between the encoder and decoder; it also connects internally within the decoder to capture fine-grained details and coarse-grained semantic information at a full scale. We also propose incorporating dilated convolution to increase the receptive field and compare the improvement effect of different loss functions on sample class imbalance. After verification and analysis of our labeled urban scene LiDAR point cloud dataset—called NJSeg-3D—the mIoU of the RandLA-Net++ and RandLA-Net3+ networks is 3.4% and 3.2% higher, respectively, than the benchmark network RandLA-Net.
Remote Sensing of Chlorophyll-a in Xinkai Lake Using Machine Learning and GF-6 WFV Images
Authors: Xu Shiqi , Li Sijia , Tao Zui , Song Kaishan , Wen Zhidan , Li Yong , Chen Fangfang
Published: October 2022

Lake ecosystem eutrophication is a crucial water quality issue that can be efficiently monitored with remote sensing. GF-6 WFV with a high spatial and temporal resolution provides a comprehensive record of the dynamic changes in water quality parameters in a lake. In this study, based on GF-6 WFV images and the field sampling data of Xingkai Lake from 2020 to 2021, the accuracy of three machine learning models (RF: random forest; SVR: support vector regression; and BPNN: back propagation neural network) was compared by considering 11 combinations of surface reflectance in different wavebands as input variables for machine learning. We mapped the spatiotemporal variations of Chl-a concentrations in Xingkai Lake from 20192021 and integrated machine learning algorithms to demonstrate that RF obtained a better degree of derived-fitting (Calibration: N = 82, RMSE = 0.82 μg/L, MAE = 0.57 μg/L, slope = 0.94, and R2 = 0.98; Validation: N = 40, RMSE = 2.12 μg/L, MAE = 1.58 μg/L, slope = 0.91, R2 = 0.89, and RPD = 2.98). The interannual variation from 2019 to 2021 showed that the Chl-a concentration in Xingkai Lake was low from June to July, while maximum values were observed from October to November, thus showing significant seasonal differences. Spatial distribution showed that Chl-a concentrations were higher in Xiao Xingkai Lake than in Da Xingkai Lake. Nutrient inputs (N, P) and other environmental factors such as high temperature could have an impact on the spatial and temporal distribution characteristics of Chl-a, therefore, combining GF-6 WFV satellite images with RF could realize large-scale monitoring and be more effective. Our results showed that remote-sensing-based machine learning algorithms provided an effective method to monitor lake eutrophication as well as technical support and methodological reference for inland lake water quality parameter inversion.
The Characteristics of Raindrop Size Distributions in Different Climatological Regions in South Korea
Authors: You Cheol-Hwan , Kim Hyeon-Joon , Suh Sung-Ho , Jung Woonseon , Kang Mi-Young
Published: October 2022

To understand the microphysical characteristics of rainfall in four different climatological regions (called BOS, BUS, CPO, and JIN) in South Korea, DSDs and their variables, including the mass-weighted mean diameter (Dm) and normalized number concentration (logNw), were examined. To examine the characteristics of DSDs at four sites with different climatology and topography, data measured from Parsivel disdrometer and wind direction from Automatic Weather System (AWS) during rainy seasons from June to August for three years (2018 to 2020) were analyzed. The DSDs variables were calculated using Gamma distribution model. In the coastal area, larger raindrops with a lower number concentration occurred, whereas smaller raindrops with a higher number concentration dominated in the middle land and mountain region. The mountain area of CPO and middle land area of JIN had a larger contribution to the rain rate than that of the coastal area of BOS and JIN in the range of the smallest diameter. The contribution of the drop size to the total number concentration at the CPO and JIN sites was larger (smaller) than that at BOS and BUS in the smallest (larger) diameter. The average shape and slope parameter of gamma model were higher values at the mountain area than at other sites for both rain types, Z-R relation and polarimetric variables were also shown different values at the four studied sites. The intercept coefficient of Z-R relation showed higher values in the mountain area and middle land area than the coastal area. The slope values of Z-R relation were the smallest in the mountain area. The polarimetric variables of ZH and ZDR were shown highest (lowest) value at the coastal region of BOS (mountain area of CPO) site for both rain types. The Dm-rose, which shows the Dm distributions with the wind direction, was used in this study. In the coastal area (mountain and middle land area), the dominant wind was east–southeast (east) direction. The ratio of the smaller diameter to the middle size at BOS was much smaller than that at CPO. In the analysis of the hourly distribution of the Dm and logNw, there were two and four peaks of Dm at BUS and BOS, respectively. There was one peak of the Dm at the CPO and JIN sites. The time variation of the Dm was much higher than that of the logNw.
Using Remote Sensing Methods to Study Active Geomorphologic Processes on Cantabrian Coastal Cliffs
Authors: Domínguez-Cuesta María José , Rodríguez-Rodríguez Laura , López-Fernández Carlos , Pando Luis , Cuervas-Mons José , Olona Javier , González-Pumariega Pelayo , Serrano Jaime , Valenzuela Pablo , Jiménez-Sánchez Montserrat
Published: October 2022

Gravitational processes on inaccessible cliffs, especially in coastal areas, are difficult to study in detail with only in situ techniques. This difficulty can be overcome by the complementary application of remote sensing methods. This work focuses on an active complex landslide affecting the slope of the Tazones Lighthouse (Cantabrian coast, North Iberian Peninsula), which has been monitored since June 2018. The aim of this research is to establish a conceptual model of the internal structure of the slope. A remote multitechnique approach was applied, including landscape deformation analysis from photogrammetric surveys, ground motion detection applying A-DInSAR techniques and Sentinel-1 satellite data, and electrical resistivity tomography. The obtained results showed the great potential of some of the remote techniques, such as UAV photogrammetry and electrical tomography, and the ineffectiveness of others, such as A-DInSAR, which failed to provide adequate results due to the profuse vegetation. This work made it possible to establish a geological model of the functioning of the slope of the Tazones Lighthouse and to deduce the surface extent of the destabilized mass (70,750 m2), the rupture surface shape (stepped), its in-depth extent (10–50 m), the volume of materials involved (~3,550,000 m3) and the type of landslide (complex including a predominant translational slide). The combination of field and remote sensing data significantly increased the possibility of reaching a comprehensive geological interpretation of landslides on rocky coasts.
Detecting Wheat Heads from UAV Low-Altitude Remote Sensing Images Using Deep Learning Based on Transformer
Authors: Zhu Jiangpeng , Yang Guofeng , Feng Xuping , Li Xiyao , Fang Hui , Zhang Jinnuo , Bai Xiulin , Tao Mingzhu , He Yong
Published: October 2022

The object detection method based on deep learning convolutional neural network (CNN) significantly improves the detection performance of wheat head on wheat images obtained from the near ground. Nevertheless, for wheat head images of different stages, high density, and overlaps captured by the aerial-scale unmanned aerial vehicle (UAV), the existing deep learning-based object detection methods often have poor detection effects. Since the receptive field of CNN is usually small, it is not conducive to capture global features. The visual Transformer can capture the global information of an image; hence we introduce Transformer to improve the detection effect and reduce the computation of the network. Three object detection networks based on Transformer are designed and developed, including the two-stage method FR-Transformer and the one-stage methods R-Transformer and Y-Transformer. Compared with various other prevalent object detection CNN methods, our FR-Transformer method outperforms them by 88.3% for AP50 and 38.5% for AP75. The experiments represent that the FR-Transformer method can gratify requirements of rapid and precise detection of wheat heads by the UAV in the field to a certain extent. These more relevant and direct information provide a reliable reference for further estimation of wheat yield.
Monitoring and Mapping Vegetation Cover Changes in Arid and Semi-Arid Areas Using Remote Sensing Technology: A Review
Authors: Almalki Raid , Khaki Mehdi , Saco Patricia M. , Rodriguez Jose F.
Published: October 2022

Vegetation cover change is one of the key indicators used for monitoring environmental quality. It can accurately reflect changes in hydrology, climate, and human activities, especially in arid and semi-arid regions. The main goal of this paper is to review the remote sensing satellite sensors and the methods used for monitoring and mapping vegetation cover changes in arid and semi-arid. Arid and semi-arid lands are eco-sensitive environments with limited water resources and vegetation cover. Monitoring vegetation changes are especially important in arid and semi-arid regions due to the scarce and sensitive nature of the plant cover. Due to expected changes in vegetation cover, land productivity and biodiversity might be affected. Thus, early detection of vegetation cover changes and the assessment of their extent and severity at the local and regional scales become very important in preventing future biodiversity loss. Remote sensing data are useful for monitoring and mapping vegetation cover changes and have been used extensively for identifying, assessing, and mapping such changes in different regions. Remote sensing data, such as satellite images, can be obtained from satellite-based and aircraft-based sensors to monitor and detect vegetation cover changes. By combining remotely sensed images, e.g., from satellites and aircraft, with ground truth data, it is possible to improve the accuracy of monitoring and mapping techniques. Additionally, satellite imagery data combined with ancillary data such as slope, elevation, aspect, water bodies, and soil characteristics can detect vegetation cover changes at the species level. Using analytical methods, the data can then be used to derive vegetation indices for mapping and monitoring vegetation.