bluuebunny/crossref_metadata_2025 huggingface dataset:
Silver and Copper Nanoparticles Induce Oxidative Stress in Bacteria and Mammalian Cells
Authors: Ameh Thelma , Gibb Matthew , Stevens Dinny , Pradhan Sahar H. , Braswell Evan , Sayes Christie M.
Published: July 2022

Silver and copper nanoparticles (AgNPs and CuNPs) coated with stabilizing moieties induce oxidative stress in both bacteria and mammalian cells. Effective antibacterial agents that can overcome existing mechanisms of antibacterial resistance will greatly improve biomedical interventions. In this study, we analyzed the effect of nanoparticle-induced stress. Escherichia coli and normal human bronchial epithelial (BEAS-2B) cells were selected for this study. The nanoparticle constructs tested showed low toxicity to mammalian cells except for the polyvinylpyrrolidone-surface-stabilized copper nanoparticles. In fact, both types of copper nanoparticles used in this study induced higher levels of reactive oxygen species than the surface-stabilized silver nanoparticles. In contrast to mammalian cells, the surface-stabilized silver and copper nanoparticles showed varying levels of toxicity to bacteria cells. These data are expected to aid in bridging the knowledge gap in differential toxicities of silver and copper nanoparticles against bacteria and mammalian cells and will also improve infection interventions.
Structure Modification, Evolution, and Compositional Changes of Highly Conductive La:BaSnO3 Thin Films Annealed in Vacuum and Air Atmosphere
Authors: Murauskas Tomas , Kubilius Virgaudas , Raudonis Rimantas , Skapas Martynas , Plausinaitiene Valentina
Published: July 2022

Perovskite-type La:BaSnO3 (LBSO) has been drawing considerable attention due to its high electron mobility and optical transparency. Its thin film electrical properties, however, remain inferior to those of single crystals. This work investigates the thermal post-treatment process of films deposited using the metalorganic chemical vapor deposition method to improve the electrical properties of different stoichiometry films, and demonstrates the modification of thin film’s structural properties using short and excessive annealing durations in vacuum conditions. Using vacuum post-treatment, we demonstrate the improvement of electrical properties in Ba-rich, near-stoichiometric, and Sn-rich samples with a maximum electron mobility of 116 cm2V−1s−1 at r.t. However, the improvement of electrical properties causes surface morphology and internal structural changes, which depend on thin film composition. At temperatures of 900 °C–1400 °C the volatile nature of LBSO constituting elements is described, which reveals possible deterioration mechanisms of thin LBSO air. At higher than 1200 °C, LBSO film’s decomposition rate increases exponentially. Thin film structure evolution and previously unreported decomposition is demonstrated by Ba and La diffusion to the substrate, and by evaporation of SnO-SnOx species.
Role of Nitrogen and Yttrium Contents in Manufacturing (Cr, Y)Nx Film Nanostructures
Authors: Apolinario Raira Chefer , Rodrigues Alisson Mendes , Avila Pedro Renato Tavares , Pereira Júlia Nascimento , Ramirez Carlos Alberto Ospina , Daum Philipp , Costa Fabiana Pereira da , Lira Hélio de Lucena , Neves Gelmires de Araújo , Greiner Christian , Pinto Haroldo Cavalcanti
Published: July 2022

The high-power impulse magnetron sputtering (HiPIMS) technique was applied to deposit multilayer-like (Cr, Y)Nx coatings on AISI 304L stainless steel, using pendular substrate oscillation and a Cr-Y target and varying the nitrogen flow rate from 10 to 50 sccm. The microstructure, mechanical and tribological properties were investigated by scanning and transmission electron microscopy, X-ray photoelectron spectroscopy, X-ray diffraction, instrumented nano-hardness, and wear tests. The columnar grain structure became highly segmented and nanosized due to pendular substrate oscillation and the addition of yttrium. The deposition rate increased continuously with the growing nitrogen flow rate. The increase in nitrogen flow from 10 to 50 sccm increased the hardness of the coatings (Cr, Y)Nx, with a maximum hardness value of 32.7 GPa for the coating (Cr, Y)Nx with a nitrogen flow of 50 sccm, which greatly surpasses the hardness of CrN films with multilayer-like (Cr, Y)Nx coatings architecture. The best mechanical and tribological performance was achieved for a nitrogen flow rate of 50 sccm. This was enabled by more elevated compressive stresses and impact energies of the impinging ions during film growth, owing to an increase of HiPIMS peak voltage with a rising N2/Ar ratio.
Optimization of Technological Parameters of the Process of Forming Therapeutic Biopolymer Nanofilled Films
Authors: Bembenek Michał , Popadyuk Oleg , Shihab Thaer , Ropyak Liubomyr , Uhryński Andrzej , Vytvytskyi Vasyl , Bulbuk Oleksandr
Published: July 2022

The prospects of using biopolymer nano-containing films for wound healing were substantiated. The main components of biopolymer composites are gelatin, polyvinyl alcohol, glycerin, lactic acid, distilled water, and zinc oxide (ZnO) nanoparticles (NPs). Biopolymer composites were produced according to various technological parameters using a mould with a chrome coating. The therapeutic properties of biopolymer films were evaluated by measuring the diameter of the protective effect. Physico-mechanical properties were studied: elasticity, vapour permeability, degradation time, and swelling. To study the influence of technological parameters of the formation process of therapeutic biopolymer nanofilled films on their therapeutic and physico-mechanical properties, the planning of the experiment was used. According to the results of the experiments, mathematical models of the second-order were built. The optimal values of technological parameters of the process are determined, which provide biopolymer nanofilled films with maximum healing ability (diameter of protective action) and sufficiently high physical and mechanical properties: elasticity, vapour permeability, degradation time and swelling. The research results showed that the healing properties of biopolymer films mainly depend on the content of ZnO NPs. Degradation of these biopolymer films provides dosed drug delivery to the affected area. The products of destruction are carbon dioxide, water, and a small amount of ZnO in the bound state, which indicates the environmental safety of the developed biopolymer film.
Amine-Functionalized Natural Halloysite Nanotubes Supported Metallic (Pd, Au, Ag) Nanoparticles and Their Catalytic Performance for Dehydrogenation of Formic Acid
Authors: Song Limin , Tan Kaiyuan , Ye Yingyue , Zhu Baolin , Zhang Shoumin , Huang Weiping
Published: July 2022

In today’s age of resource scarcity, the low-cost development and utilization of renewable energy, e.g., hydrogen energy, have attracted much attention in the world. In this work, cheap natural halloysite nanotubes (HNTs) were modified with γ-aminopropyltriethoxysilane (APTES), and the functionalized HNTs were used as to support metal (Pd, Au, Ag) catalysts for dehydrogenation of formic acid (DFA). The supports and fabricated catalysts were characterized with ICP, FT-IR, XRD, XPS and TEM. The functional groups facilitate the anchoring of metal particles to the supports, which brings about the high dispersion of metallic particles in catalysts. The catalysts show high activity against DFA and exhibit selectivity of 100% toward H2 at room temperature or less. The interactions between active centers and supports were investigated by evaluation and comparison of the catalytic performances of Pd/NH2-HNTs, PdAg/NH2-HNTs and PdAu/NH2-HNTs for DFA.
Does Food Intake of Australian Toddlers 12–24 Months Align with Recommendations: Findings from the Australian Feeding Infants and Toddlers Study (OzFITS) 2021
Authors: Moumin Najma A. , Netting Merryn J. , Golley Rebecca K. , Mauch Chelsea E. , Makrides Maria , Green Tim J.
Published: July 2022

(1) Background: Food-based dietary guidelines promote population health and well-being through dietary patterns that reduce chronic disease risk while providing adequate energy and nutrients. In Australia, recommended dietary patterns based on servings per day from the five food groups—fruits, vegetables, cereals and grains, meats and alternatives, and dairy—have been developed for toddlers 1–2 years of age. However, no study has assessed the intake of the five food groups in this age group nationally. (2) Aim: To compare daily servings and the percentage of energy from the five food groups and discretionary foods in toddlers 1–2 years old to the Australian Dietary Guidelines. (3) Methods: Dietary intake was assessed using a one-day food record for 475 toddlers. (4) Results: Apart from fruit and dairy, servings of the five food groups were below the recommendations. Two-thirds of toddlers did not consume enough vegetables, and only 10% consumed the recommended number of servings for cereals and grains. On average, toddlers consumed only half the recommended servings of meat and alternatives. Nearly all toddlers (89%) consumed discretionary foods, which accounted for ~12% of total energy. Forty-five percent of toddlers received breastmilk. On average, breastfed toddlers consumed fewer servings from the five food groups than non-breastfed toddlers. Dairy contributed 20% of daily energy in all toddlers; however, this food group accounted for 13% in breastfed and 32% in non-breastfed toddlers on the day of the food record. (4) Conclusions: Compared to the recommendations, alignment with the servings of the five food group foods was not achieved by most toddlers, except for fruit and dairy. Discretionary foods may have displaced nutritious family foods. Consistent with Australian Infant Feeding Guidelines, many toddlers in this study continued to receive breastmilk but the recommended dietary patterns do not include breastmilk. Dietary modeling, including breastmilk as the primary milk source, is urgently needed, along with practical advice on incorporating breastmilk in a toddler’s diet while optimizing food consumption.
The Role of Interventional Irisin on Heart Molecular Physiology
Authors: Alzoughool Foad , Al-Zghoul Mohammad Borhan , Ghanim Bayan Y. , Gollob Michael , Idkaidek Nasir , Qinna Nidal A.
Published: July 2022

Irisin, encoded by the FNDC5 (fibronectin type III domain containing 5) gene, is a novel myokine that has been implicated as an essential mediator of exercise benefits. Effects of irisin on heart physiology is still ambiguous. This study aimed to evaluate the impact of exogenous administration of irisin on heart physiology and the pharmacokinetic profile of pump-administered irisin. To do so, Sprague Dawley rats were implanted with an irisin-loaded osmotic pump (5 μg/kg/day) for 42 days, and other animals were administered with single bolus subcutaneous injections of irisin (5 µg/kg). Body weights and blood samples were collected weekly for 42 days for serum irisin quantification and histopathology. Clinical biochemistry analyses were performed. Heart mRNA expression was assessed in 26 selected genes. Chronic interventional exogenous irisin significantly reduced body weight without affecting the heart myocyte size and significantly reduced creatine kinase enzyme level. Blood CBC, serum biochemistry, and heart morphology were normal. Gene expression of FNCD5, Raf1, CPT1, IGF-1, and CALCIN, encoding for heart physiology, increased while PGC1, Nox4, and Mfn1 significantly decreased. Nevertheless, irisin increased the expression of cardioprotective genes and inhibited some genes that harm heart physiology. Administration of irisin promotes myocardial functions and could be translated into clinical settings after preclinical profiling.
Fully Automated, High-Dose Radiosynthesis of [18F]PARPi
Authors: Pacelli Anna , Zarrad Fadi , Warnier Corentin , Gendron Thibault , Otabashi Muhammad , Vriamont Charles , Jackson Alex , Fendler Wolfgang , Herrmann Ken , Nader Michael
Published: July 2022

[18F]PARPi is currently undergoing clinical trials as a PET tracer for many applications. However, only manual radiosynthesis was reported; this has several drawbacks, including an increased risk of contamination from the operator, and the need to limit the starting activity. The automation of the previously reported protocol for [18F]PARPi synthesis is challenging, as it requires transferring microvolumes of reagents, which many platforms cannot accommodate. We report a revised, high yield, and automated protocol for the radiosynthesis of [18F]PARPi, with final doses of over 20 GBq.
Chalcones as Anti-Glioblastoma Stem Cell Agent Alone or as Nanoparticle Formulation Using Carbon Dots as Nanocarrier
Authors: Veliz Eduardo A. , Kaplina Anastasiia , Hettiarachchi Sajini D. , Yoham Athina L. , Matta Carolina , Safar Sabrin , Sankaran Meghana , Abadi Esther L. , Cilingir Emel Kirbas , Vallejo Frederic A. , Walters Winston M. , Vanni Steven , Leblanc Roger M. , Graham Regina M.
Published: July 2022

The current prognosis for glioblastoma is dismal. Treatment-resistant glioblastoma stem cells (GSCs) and the failure of most drugs to reach therapeutic levels within the tumor remain formidable obstacles to successful treatment. Chalcones are aromatic ketones demonstrated to reduce malignant properties in cancers including glioblastoma. Nanomedicines can increase drug accumulation and tumor cell death. Carbon-dots are promising nanocarriers that can be easily functionalized with tumor-targeting ligands and anti-cancer drugs. Therefore, we synthesized a series of 4′-amino chalcones with the rationale that the amino group would serve as a “handle” to facilitate covalent attachment to carbon-dots and tested their cytotoxicity toward GSCs. We generated 31 chalcones (22 4′-amino and 9 4′ derivatives) including 5 novel chalcones, and found that 13 had an IC50 below 10 µM in all GSC lines. After confirming that the 4-amino group was not part of the active pharmacophore, chalcones were attached to transferrin-conjugated carbon-dots. These conjugates were significantly more cytotoxic than the free chalcones, with the C-dot-transferrin-2,5, dimethoxy chalcone conjugate inducing up to 100-fold more GSC death. Several of the tested chalcones represent promising lead compounds for the development of novel anti-GSC drugs. Furthermore, designing amino chalcones for carbon-dot mediated drug delivery is a rational and effective methodology.
Leaf Economic and Hydraulic Traits Signal Disparate Climate Adaptation Patterns in Two Co-Occurring Woodland Eucalypts
Authors: Prober Suzanne M. , Potts Brad M. , Harrison Peter A. , Wiehl Georg , Bailey Tanya G. , Costa e Silva João , Price Meridy R. , Speijers Jane , Steane Dorothy A. , Vaillancourt René E.
Published: July 2022

With climate change impacting trees worldwide, enhancing adaptation capacity has become an important goal of provenance translocation strategies for forestry, ecological renovation, and biodiversity conservation. Given that not every species can be studied in detail, it is important to understand the extent to which climate adaptation patterns can be generalised across species, in terms of the selective agents and traits involved. We here compare patterns of genetic-based population (co)variation in leaf economic and hydraulic traits, climate–trait associations, and genomic differentiation of two widespread tree species (Eucalyptus pauciflora and E. ovata). We studied 2-year-old trees growing in a common-garden trial established with progeny from populations of both species, pair-sampled from 22 localities across their overlapping native distribution in Tasmania, Australia. Despite originating from the same climatic gradients, the species differed in their levels of population variance and trait covariance, patterns of population variation within each species were uncorrelated, and the species had different climate–trait associations. Further, the pattern of genomic differentiation among populations was uncorrelated between species, and population differentiation in leaf traits was mostly uncorrelated with genomic differentiation. We discuss hypotheses to explain this decoupling of patterns and propose that the choice of seed provenances for climate-based plantings needs to account for multiple dimensions of climate change unless species-specific information is available.
Genome-Wide Characterization and Expression Analysis of GeBP Family Genes in Soybean
Authors: Liu Sushuang , Liu Yanmin , Liu Chundong , Zhang Feixue , Wei Jiaping , Li Bingxuan
Published: July 2022

The glabrous-enhancer-binding protein (GeBP) family is a family of plant-specific transcription factors, whose members share a central DNA-binding domain. Previous studies have already proven that GeBP genes are involved in the control of cell expansion but not cell proliferation in Arabidopsis. However, there has not yet been a versatile analysis of the GeBP genes’ function in soybean (Glycine max L.). Here, we identified and named 9 GmGeBP genes in the soybean genome. These genes were distributed on 7 of the 20 chromosomes and the intron numbers ranged from zero to one. According to the phylogenetic tree, 52 GeBP genes obtained from four plant species were clustered into major four groups. Through the RNA-seq analysis of the nine GmGeBP genes, 8 of 9 GmGeBP genes were be found to expressed differentially across the 14 tissues. Additionally, among nine GmGeBP genes, only GeBP4 were highly expressed in abnormal trichome soybeans, which was predicted to be involved in trichome development. This genome-wide analysis of GmGeBP genes helps to provide an overview of the evolution and functions of two kinds of soybean plants. These results will help to clarify the potential functions and characteristics of GmGeBP genes in the soybean life cycle.
Quantitative Proteomics of Chromochloris zofingiensis Reveals the Key Proteins Involved in Cell Growth and Bioactive Compound Biosynthesis
Authors: Qiu Wen , Chen Rongfeng , Wang Xianxian , Liu Junying , Lv Weiguang
Published: July 2022

Glucose metabolism regulates cell growth and affects astaxanthin accumulation in the green algae Chromochloris zofingiensis. Hub gene functioning in this bioactive compound has been illustrated at the genome, transcriptome and metabolome level, but is rather limited from a proteome aspect. Microalgal cell produce an enhanced biomass (8-fold higher) but decreased lipid and astaxanthin content (~20% less) in the glucose condition compared to the control. Here, we investigate the proteomic response of C. zofingiensis grown with and without glucose using an LC-MS/MS-based Tandem Mass Tag (TMT) approach. The proteomic analysis demonstrated that glucose supplementation triggers the upregulation of 105 proteins and downregulation of 151 proteins. Thus, the carbon and energy flux might flow to cell growth, which increased the associated protein abundance, including DNA polymerase, translation initiation factor, 26S proteasome regulatory subunits, and the marker enzyme of the TCA cycle ribosomal protein. Moreover, the glucose supplement triggered the downregulation of proteins mainly involved in photosynthesis, chloroplasts, valine, leucine and isoleucine biosynthesis, 2-oxocarboxylic acid metabolism, and pantothenate and CoA biosynthesis pathways. This proteomic analysis is likely to provide new insights into algal growth and lipid or astaxanthin accumulation upon glucose supplementation, providing a foundation for further development of C. zofingiensis as oleaginous microalga for bioengineering applications.
Secular Mysticism
Authors: Jones Richard H.
Published: July 2022

How a positive naturalist understanding of mystical experiences is possible and how these experiences and accompanying practices can be incorporated into a secular mysticism are discussed. Philosophical issues related to such a secular mysticism are also raised: is a truly secular mysticism possible? Are mystical experiences cognitive of transcendent non-natural realities? Can secular mysticism address the issue of the possible construction of mystical experiences? Can one find meaning or a purpose to life when non-natural realities and life after death are not parts of the picture?
Comparison between Physical and Empirical Methods for Simulating Surface Brightness Temperature Time Series
Authors: Bian Zunjian , Lu Yifan , Du Yongming , Zhao Wei , Cao Biao , Hu Tian , Li Ruibo , Li Hua , Xiao Qing , Liu Qinhuo
Published: July 2022

Land surface temperature (LST) is a vital parameter in the surface energy budget and water cycle. One of the most important foundations for LST studies is a theory to understand how to model LST with various influencing factors, such as canopy structure, solar radiation, and atmospheric conditions. Both physical-based and empirical methods have been widely applied. However, few studies have compared these two categories of methods. In this paper, a physical-based method, soil canopy observation of photochemistry and energy fluxes (SCOPE), and two empirical methods, random forest (RF) and long short-term memory (LSTM), were selected as representatives for comparison. Based on a series of measurements from meteorological stations in the Heihe River Basin, these methods were evaluated in different dimensions, i.e., the difference within the same surface type, between different years, and between different climate types. The comparison results indicate a relatively stable performance of SCOPE with a root mean square error (RMSE) of approximately 2.0 K regardless of surface types and years but requires many inputs and a high computational cost. The empirical methods performed relatively well in dealing with cases either within the same surface type or changes in temporal scales individually, with an RMSE of approximately 1.50 K, yet became less compatible in regard to different climate types. Although the overall accuracy is not as stable as that of the physical method, it has the advantages of fast calculation speed and little consideration of the internal structure of the model.
Depth-Specific Soil Electrical Conductivity and NDVI Elucidate Salinity Effects on Crop Development in Reclaimed Marsh Soils
Authors: Gómez Flores José Luis , Ramos Rodríguez Mario , González Jiménez Alfonso , Farzamian Mohammad , Herencia Galán Juan Francisco , Salvatierra Bellido Benito , Cermeño Sacristan Pedro , Vanderlinden Karl
Published: July 2022

Agricultural management decision-making in salinization-prone environments requires efficient soil salinity monitoring methods. This is the case in the B-XII irrigation district in SW Spain, a heavy clay reclaimed marsh area where a shallow saline water table and intensively irrigated agriculture create a fragile balance between salt accumulation and leaching in the root zone, which might be disrupted by the introduction of new crops and increasing climate variability. We evaluated the potential of electromagnetic induction (EMI) tomography for field-scale soil salinity assessment in this hyper-conductive environment, using EMI and limited analytical soil data measured in 2017 and 2020 under a processing tomato–cotton–sugar beet crop rotation. Salinity effects on crop development were assessed by comparing Sentinel 2 NDVI imagery with inverted depth-specific electrical conductivity (EC). Average apparent electrical conductivity (ECa) for the 1-m depth signal was 20% smaller in 2020 than in 2017, although the spatial ECa pattern was similar for both years. Inverted depth-specific EC showed a strong correlation (R ≈ 0.90) with saturated paste extract EC (ECe), [Na+] and sodium absorption ratio (SAR), resulting in linear calibration equations with R2 ≈ 0.8 for both years and leave-one-out cross validation Nash–Sutcliffe Efficiency Coefficient, ranging from 0.57 to 0.74. Overall, the chemical parameter estimation improved with depth and soil wetness (2017), yielding 0.83 < R <0.98 at 0.9 m. The observed spatial EC distributions showed a steadily increasing inverse correlation with NDVI during the growing season, particularly for processing tomato and cotton, reaching R values of −0.71 and −0.85, respectively. These results confirm the potential of EMI tomography for mapping and monitoring soil salinity in the B-XII irrigation district, while it allows, in combination with NDVI imagery, a detailed spatial assessment of soil salinity impacts on crop development throughout the growing season. Contrary to the popular belief among farmers in the area, and despite non-saline topsoil conditions, spatial EC and subsoil salinity patterns were found to affect crop development negatively in the studied field.
An Impervious Surface Spectral Index on Multispectral Imagery Using Visible and Near-Infrared Bands
Authors: Su Shanshan , Tian Jia , Dong Xinyu , Tian Qingjiu , Wang Ning , Xi Yanbiao
Published: July 2022

The accurate mapping of urban impervious surfaces from remote sensing images is crucial for understanding urban land-cover change and addressing impervious-surface-change-related environment issues. To date, the authors of most studies have built indices to map impervious surfaces based on shortwave infrared (SWIR) or thermal infrared (TIR) bands from middle–low-spatial-resolution remote sensing images. However, this limits the use of high-spatial-resolution remote sensing data (e.g., GaoFen-2, Quickbird, and IKONOS). In addition, the separation of bare soil and impervious surfaces has not been effectively solved. In this article, on the basis of the spectra analysis of impervious surface and non-impervious surface (vegetation, water, soil and non-photosynthetic vegetation (NPV)) data acquired from world-recognized spectral libraries and Sentinel-2 MSI images in different regions and seasons, a novel spectral index named the Normalized Impervious Surface Index (NISI) was proposed for extracting impervious area information by using blue, green, red and near-infrared (NIR) bands. We performed comprehensive assessments for the NISI, and the results demonstrated that the NISI provided the best studied performance in separating the soil and impervious surfaces from Sentinel-2 MSI images. Furthermore, regarding impervious surfaces mapping accuracy, the NISI had an overall accuracy (OA) of 89.28% (±0.258), a producer’s accuracy (PA) of 89.76% (±1.754), and a user’s accuracy (UA) of 90.68% (±1.309), which were higher than those of machine learning algorithms, thus supporting the NISI as an effective measurement for urban impervious surfaces mapping and analysis. The results indicate the NISI has a high robustness and a good applicability.
Assessment of Large-Scale Seasonal River Morphological Changes in Ayeyarwady River Using Optical Remote Sensing Data
Authors: Bhatpuria Dhyey , Matheswaran Karthikeyan , Piman Thanapon , Tha Theara , Towashiraporn Peeranan
Published: July 2022

Monitoring morphologically dynamic rivers over large spatial domains at an adequate frequency is essential for informed river management to protect human life, ecosystems, livelihoods, and critical infrastructures. Leveraging the advancements in cloud-based remote sensing data processing through Google Earth Engine (GEE), a web-based, freely accessible seasonal river morphological monitoring system for Ayeyarwady River, Myanmar was developed through a collaborative process to assess changes in river morphology over time and space. The monitoring system uses Landsat satellite data spanning a 31-year long period (1988–2019) to map river planform changes along 3881.4 km of river length including Upper Ayeyarwady, Lower Ayeyarwady, and Chindwin. It is designed to operate on a seasonal timescale by comparing pre-monsoon and post-monsoon channel conditions to provide timely information on erosion and accretion areas for the stakeholders to support planning and management. The morphological monitoring system was validated with 85 reference points capturing the field conditions in 2019 and was found to be reliable for operational use with an overall accuracy of 89%. The average eroded riverbank area was calculated at around 45, 101, and 134 km2 for Chindwin, Upper Ayeyarwady, and Lower Ayeyarwady, respectively. The historical channel change assessment aided us to identify and categorize river reaches according to the frequency of changes. Six hotspots of riverbank erosion were identified including near Mandalay city, the confluence of Upper Ayeyarwady and Chindwin, near upstream of Magway city, downstream of Magway city, near Pyay city, and upstream of the Ayeyarwady delta. The web-based monitoring system simplifies the application of freely available remote sensing data over the large spatial domain to assess river planform changes to support stakeholders’ operational planning and prioritizing investments for sustainable Ayeyarwady River management.
Location Accuracy Improvement of Long-range Lightning Detection Network In China by Compensating Ground Wave Propagation Delay
Authors: Zhang Junchao , Zhou Jiahao , Li Jie , Gu Jiaying , Zhang Qilin , Dai Bingzhe , Wang Yao , Wang Jialei , Zhong Yuqing , Li Qingda
Published: July 2022

Very low frequency (VLF) electromagnetic waves distort along the long propagation path, and that causes the arrival time of the signals measured by the long-range lightning system to be delayed. In this paper, based on the propagation correction method by compensating the peak time delay of the ground wave, the location accuracy of the long-range lightning detection network in China is greatly improved. The improvement of the relative location accuracy and location offsets are evaluated by comparing with the Advanced Direction Time Lightning Detection System (ADTD) datasets. It shows that the mean relative accuracy is improved from 7.74 km to 4.32 km, and the median relative accuracy is improved from 7.28 km to 2.46 km. The mean westwards offset of the total lightning location data drops from 2.05 km to 0.93 km, and the mean southwards offset drops from 1.19 km to 0.63 km. In addition, it is found that the location accuracy will be greatly improved if the observation site affected by the terrain is removed. The mean relative location accuracy is further improved to 4.11 km and the median to 2.32 km.
Enhancement and Noise Suppression of Single Low-Light Grayscale Images
Authors: Nie Ting , Wang Xiaofeng , Liu Hongxing , Li Mingxuan , Nong Shenkai , Yuan Hangfei , Zhao Yuchen , Huang Liang
Published: July 2022

Low-light images have low contrast and high noise, making them not easily readable. Most existing image-enhancement methods focus on color images. In the present study, an enhancement and denoising algorithm for single low-light grayscale images is proposed. The algorithm is based on the multi-exposure fusion framework. First, on the basis of the low-light tone-mapping operators, the optimal virtual exposure image is constructed according to the information entropy criterion. Then, the latent low-rank representation is applied to two images to generate low-ranking parts and saliency parts to reduce noise after fusion. Next, the initial weight map is constructed based on the information contained in the decomposed images, and an adaptive weight refined algorithm is proposed to restore as much structural information as possible and keep the details while avoiding halo artifacts. When solving the weight maps, the decomposition and optimization of the nonlinear problem is converted into a total variation model, and an iterative method is used to reduce the computational complexity. Last, the normalized weight map is used for image fusion to obtain the enhanced image. The experimental results showed that the proposed method performed well both in the subjective and objective evaluation of state-of-the-art enhancement methods for low-light grayscale images.
Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments
Authors: Eirale Andrea , Martini Mauro , Tagliavini Luigi , Gandini Dario , Chiaberge Marcello , Quaglia Giuseppe
Published: July 2022

Population aging and pandemics have been shown to cause the isolation of elderly people in their houses, generating the need for a reliable assistive figure. Robotic assistants are the new frontier of innovation for domestic welfare, and elderly monitoring is one of the services a robot can handle for collective well-being. Despite these emerging needs, in the actual landscape of robotic assistants, there are no platforms that successfully combine reliable mobility in cluttered domestic spaces with lightweight and offline Artificial Intelligence (AI) solutions for perception and interaction. In this work, we present Marvin, a novel assistive robotic platform we developed with a modular layer-based architecture, merging a flexible mechanical design with cutting-edge AI for perception and vocal control. We focus the design of Marvin on three target service functions: monitoring of elderly and reduced-mobility subjects, remote presence and connectivity, and night assistance. Compared to previous works, we propose a tiny omnidirectional platform, which enables agile mobility and effective obstacle avoidance. Moreover, we design a controllable positioning device, which easily allows the user to access the interface for connectivity and extends the visual range of the camera sensor. Nonetheless, we delicately consider the privacy issues arising from private data collection on cloud services, a critical aspect of commercial AI-based assistants. To this end, we demonstrate how lightweight deep learning solutions for visual perception and vocal command can be adopted, completely running offline on the embedded hardware of the robot.
Application of Deep Reinforcement Learning to NS-SHAFT Game Signal Control
Authors: Chang Ching-Lung , Chen Shuo-Tsung , Lin Po-Yu , Chang Chuan-Yu
Published: July 2022

Reinforcement learning (RL) with both exploration and exploit abilities is applied to games to demonstrate that it can surpass human performance. This paper mainly applies Deep Q-Network (DQN), which combines reinforcement learning and deep learning to the real-time action response of NS-SHAFT game with Cheat Engine as the API of game information autonomously. Based on a personal computer, we build an experimental learning environment that automatically captures the NS-SHAFT’s frame, which is provided to DQN to decide the action of moving left, moving right, or stay in same location, survey different parameters: such as the sample frequency, different reward function, and batch size, etc. The experiment found that the relevant parameter settings have a certain degree of influence on the DQN learning effect. Moreover, we use Cheat Engine as the API of NS-SHAFT game information to locate the relevant values in the NS-SHAFT game, and then read the relevant values to achieve the operation of the overall experimental platform and the calculation of Reward. Accordingly, we successfully establish an instant learning environment and instant game training for the NS-SHAFT game.
Soft CNT-Polymer Composites for High Pressure Sensors
Authors: Eisape Adebayo , Rennoll Valerie , Van Volkenburg Tessa , Xia Zhiyong , West James E. , Kang Sung Hoon
Published: July 2022

Carbon–polymer composite-based pressure sensors have many attractive features, including low cost, easy integration, and facile fabrication. Previous studies on carbon–polymer composite sensors focused on very high sensitivities for low pressure ranges (10 s of kPa), which saturate quickly at higher pressures and thus are ill-suited to measure the high pressure ranges found in various applications, including those in underwater (>1 atm, 101 kPa) and industrial environments. Current sensors designed for high pressure environments are often difficult to fabricate, expensive, and, similarly to their low-pressure counterparts, have a narrow sensing range. To address these issues, this work reports the design, synthesis, characterization, and analysis of high-pressure TPU-MWCNT based composite sensors, which detect pressures from 0.5 MPa (4.9 atm) to over 10 MPa (98.7 atm). In this study, the typical approach to improve sensitivity by increasing conductive additive concentration was found to decrease sensor performance at elevated pressures. It is shown that a better approach to elevated pressure sensitivity is to increase sensor response range by decreasing the MWCNT weight percentage, which improves sensing range and resolution. Such sensors can be useful for measuring high pressures in many industrial (e.g., manipulator feedback), automotive (e.g., damping elements, bushings), and underwater (e.g., depth sensors) applications.
Guaranteeing QoS for NOMA-Enabled URLLC Based on κ–μ Shadowed Fading Model
Authors: Zeng Jie , Song Yuxin , Wu Teng , Lv Tiejun , Zhou Shidong
Published: July 2022

Sixth-generation (6G) wireless communication scenarios are complex and diverse. Small-scale fading is a key part of wireless channels and its impact on performance in scenarios with time sensitivity and 6G ultrareliable and low latency communications (URLLC) quality-of-service requirements cannot be ignored. Therefore, it is necessary to accurately characterize small-scale fading when designing wireless communication systems. In this paper, we derive approximate closed form expressions for the probability density function, cumulative distribution function and moment-generating function of the postprocessing signal-to-noise ratio following the zero-forcing detector in a cell-free massive multiple-input multiple-output (CF mMIMO) system. CF mMIMO system is a nonorthogonal multiple access (NOMA) system that enables users to share all channel uses and can ensure the fairness of the communication quality experienced by different users. Our key contributions include the extension of the κ–μ shadowed fading model to a CF mMIMO system and the proposal of theoretical tools (the derived closed-form expression) to improve its mathematical tractability. By exploiting the statistical characterizations of the arrival and service processes, another important contribution is the exploitation of the upper bound of the queuing delay violation probability (UB-QDVP) over the Mellin transforms of the arrival and service processes in the proposed CF mMIMO system under the κ–μ shadowed fading model. Corroborated by extensive simulations, our analyses validate that the CF mMIMO system outperforms the orthogonal multiple access and power-domain NOMA systems and reveal the relationships among different small-scale fading types, energy efficiency, delay and the UB-QDVP, as well as the accuracy and effectiveness of the proposed theoretical tools based on the κ–μ shadowed fading model.
The Smaller the Power Distance, the More Genuine the Emotion: Relationships between Power Distance, Emotional Labor, and Emotional Exhaustion among Chinese Teachers
Authors: Zhu Xiaoshuang , Tian Guoxiu , Liu Zhonghui
Published: July 2022

Using Grandey’s model of emotional labor, this study attempted to reveal the effects of cultural and social factors on teachers’ emotions. Specifically, taking a sample of 3312 Chinese teachers, we examined the effects of power distance (PD) and emotional labor on emotional exhaustion, focusing on the mediating role of emotional labor with different interactive partners. The results showed that Chinese teachers used surface acting (SA) the most with parents, and the least with students; they used the expression of naturally felt emotions (ENFE) the most with students, and the least with colleagues and leaders. They also used deep acting more when working with students and parents. In addition, PD negatively influenced ENFE and positively influenced SA with the three interactive partners. Only SA mediated the relationship between PD and exhaustion. These results improve our understanding of teachers’ emotions in terms of power and suggest that we should consider personal psychological factors (i.e., emotional labor), social factors (i.e., interactive partners), and national culture (i.e., PD) to promote teachers’ well-being.
Do an Organization’s Digital Transformation and Employees’ Digital Competence Catalyze the Use of Telepresence?
Authors: Hwang Inho , Shim Hoshik , Lee Woo Jin
Published: July 2022

Rapid changes in the external environment are increasing interest in digital transformation. In particular, the recent breakout of infectious diseases such as COVID-19 has required certain companies to restrict physical exchanges among their members. As a result, companies must strive to maintain productivity and performance by supporting business exchange activities through online platforms. A metaverse technology that supports individuals’ exchange activities in a virtual space based on 3D technology has recently attracted attention from companies. However, as previous studies related to the metaverse have focused on strengthening personalized content and services, additional research is needed in order to understand the metaverse’s effects at the organizational level. This study aims to present the conditions for strengthening the motivation to use the metaverse from the perspective of organizations and members who have applied the metaverse in the workplace on a trial basis. In this study, an online questionnaire was conducted targeting workers of organizations with a history of using the metaverse for business, and the hypotheses were tested using 304 valid samples. As a result of the analysis, it was found that telepresence, a characteristic of the metaverse, influences the intention to continue using the metaverse through informativeness, interactivity, and enjoyment. In addition, the shared goal of the organization’s digital transformation moderated the influence relationship between telepresence and an individual’s motivations, and an individual’s digital competence moderated the influence relationship between motivation and the intention of continuous use. This study suggests a digital transformation strategy for an organization in terms of suggesting ways to strengthen the motivations for the use of the metaverse of employees in the organization.
Ammonium Reactive Migration Process and Functional Bacteria Response along Lateral Runoff Path under Groundwater Exploitation
Authors: Meng Li , Shi Jian , Zhai Yuanzheng , Zuo Rui , Wang Jinsheng , Guo Xueru , Teng Yanguo , Gao Jian , Xu Li , Guo Bingchi
Published: July 2022

In order to elucidate the importance of biogeochemical interactions between NH4+ and aquifer media in groundwater runoff paths, a dynamic monitoring section in the riverbank zone, which is most sensitive to environmental characteristics and perpendicular to the flow direction of the Songhua River in northeastern China, was selected for field experiments in this study. The results indicated that the NH4+ concentration decreased gradually along the groundwater runoff path under exploitation conditions. The NH4+ concentrations of J1, J2, and J3 decreased by 8%, 18%, and 22%, respectively, as compared to the starting concentration of 1.3 mg/L. Adsorption of NH4+ by aquifer media at different depths is a monolayer adsorption process in accordance with pseudo-second-order kinetic equation. The maximum reduction of NH4+ from the aquifer media from top to bottom was 76%, 67%, 56%, and 42%, respectively. The function and activity of dominant functional bacteria have characteristics of coevolution with the NH4+ transformation process. The main genera in the fluctuation zone are Pseudomonas (8.83%) and Acinetobacter (4.37%), which mainly transform NH4+ by heterotrophic nitrification–aerobic denitrification (HN–AD). The main genera in the saturated zone are Flavobacterium (32.60%) and Sphingobium (3.54%), which mainly transform NH4+ by anaerobic denitrification. The spatial variations of species and abundance for NH4+ transformation functional bacteria decrease by 2.74% and 3.47%, respectively, along groundwater runoff paths. In the vertical and horizontal directions of groundwater runoff, the percentage of adsorption in NH4+ transformation gradually decreased and the percentage of biotransformation gradually increased. The adsorption processes in the O2/NO3− reduction, Fe/Mn reduction, and SO42− reduction zones were 20.7%, 3.6%, and 1.0%, respectively. The corresponding proportions of the biotransformation process were 79.3%, 96.4%, and 99.0%. This research is critical for elucidating the bio-geochemical interaction between NH4+ and aquifer media along the course of groundwater runoff in order to offer a scientific basis for the prevention and management of groundwater nitrogen pollution.
Study on the Factors Influencing on the Carbon Emissions of Shaanxi Province’s Transportation Industry in China
Authors: Zhu Changzheng , Yang Sha , Liu Pengbo
Published: July 2022

Carbon peaking in the transportation industry is of great significance to achieving the goals of carbon peaks and carbon neutrality. By correcting the energy consumption data of Shaanxi province’s transportation industry in China, adding the energy consumption data of non-operating vehicles to the total energy consumptions and building a more accurate calculation model for the carbon emissions of provincial transportation industry, this paper studies the contribution of the population size, the economic growth, the energy intensity, the energy structure, and the industrial scale of transportation to the carbon emissions, respectively, through the construction of a Logarithmic Mean Divisia Index (LMDI) model. The result shows that the carbon emissions of Shaanxi province’s transportation industry in China increased from 15.730 million tons to 24.652 million tons from 2009 to 2019. Among them, the carbon emissions of the non-operating activities grew rapidly, increasing from 2.694 million tons to 10.334 million tons in the past 10 years. Within the research range, the economic growth effect is the most important factor driving the growth of the carbon emissions of Shaanxi province’s transportation industry in China, increasing total carbon emissions by 22.701 million tons. The energy intensity effect and the industrial scale effect of transportation play the main role in inhibiting the carbon emissions of Shaanxi province’s transportation industry in China, with a cumulative reduction in the total carbon emissions by 13.869 million tons.
Intelligent Identification of the Line-Transformer Relationship in Distribution Networks Based on GAN Processing Unbalanced Data
Authors: Wang Yan , Zhang Xinyu , Liu Haofeng , Li Boqiang , Yu Jinyun , Liu Kaipei , Qin Liang
Published: July 2022

The wrong line-transformer relationship is one of the main reasons that leads to the failure of the line loss assessment of the distribution network with voltage levels of 10 kV and below. The traditional manual method to verify the line-transformer relationship is time-consuming, labor-intensive and inefficient. At the same time, due to the small sample size of the data with abnormal line-transformer relationship, the unbalanced sample data reduces the accuracy of the artificial intelligence algorithm. To this end, this paper proposes an intelligent identification method for distribution network line-transformer relationship based on Generative Adversarial Networks (GAN) processing unbalanced data. Firstly, perform data preprocessing and feature extraction based on the input power of the distribution line and the power consumption of each distribution transformer; then, build a GAN-based model for expanding the data of only a small number of abnormal line-transformer relationship samples, so as to solve the problem of unbalanced sample data distribution; and finally, establish a support vector machine (SVM) to realize the classification of the line-transformer relationship. The results of the example simulation show that, compared with the traditional Synthetic Minority Oversampling Technique (SMOTE) for processing unbalanced data, the classification effect of the proposed GAN-based data augmentation method has been significantly improved. In addition, the recall rate of the three types of the line-transformer relationship (line hanging error, magnification error and normal) under the line-transformer relationship identification method proposed in this paper is more than 92%, which proves the effectiveness and feasibility of the method.