bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Serum 25(OH)D Level and Vitamin D Intake in Young Korean Women
Authors: Shin Hye Ran , Park Hyeon Ju , Ly Sun Yung
Published: November 2022

Vitamin D status is essential for preventing bone disease. Young Korean women have the highest vitamin D deficiency prevalence compared with other demographic groups. This study aimed to establish the optimal vitamin D intake level for maintaining an adequate serum 25-hydroxyvitamin D (25[OH]D) level by season in young Korean women (mean age: 23.1 years). Each participant (wintertime, n = 101; summertime, n = 117) completed a lifestyle survey, dietary record, bone mineral density, and biochemical tests. Seasonal factors impacting 25(OH)D were identified, vitamin D intake for sufficient 25(OH)D levels was calculated, and the relationship between 25(OH)D and intact parathyroid hormone (iPTH) was analyzed. During summertime, 25(OH)D levels were higher than in wintertime (17.9 vs. 15.0 ng/mL). A 1 µg/1000 kcal increase in vitamin D intake increased 25(OH)D levels by 0.170 ng/mL in wintertime and 0.149 ng/mL in summertime. iPTH levels reached a theoretical plateau corresponding to an 18.4 ng/mL 25(OH)D level. The vitamin D intake threshold for maintaining 25(OH)D levels at ≥20 and ≥18.4 ng/mL was ≥10.97 μg/day. For a sufficient level of 25(OH)D in young Korean women, increasing summertime UV irradiation time and increasing vitamin D supplements and vitamin D-containing foods throughout the year is beneficial.
Meat Intake, Cooking Methods, Doneness Preferences and Risk of Gastric Adenocarcinoma in the MCC-Spain Study
Authors: Boldo Elena , Fernández de Larrea Nerea , Pollán Marina , Martín Vicente , Obón-Santacana Mireia , Guevara Marcela , Castaño-Vinyals Gemma , Canga Jose María , Pérez-Gómez Beatriz , Gómez-Acebo Inés , Fernández-Tardón Guillermo , Vanaclocha-Espi Mercedes , Olmedo-Requena Rocío , Alguacil Juan , Chirlaque Maria Dolores , Kogevinas Manolis , Aragonés Nuria , Castelló Adela
Published: November 2022

Background: The association of meat intake with gastric adenocarcinoma is controversial. We examined the relation between white, red, and processed meat intake and gastric adenocarcinoma, considering doneness preference and cooking methods, by histological subtype and anatomical subsite. Methods: MCC-Spain is a multicase–control study that included 286 incident gastric adenocarcinoma cases and 2993 controls who answered a food-frequency questionnaire. The association of gastric adenocarcinoma with meat intake, doneness preference and cooking methods was assessed using binary multivariate logistic regression mixed models and a possible interaction with sex was considered. Multinomial logistic regression models were used to estimate risk by tumor subsite (cardia vs. non-cardia) and subtype (intestinal vs. diffuse). Sensitivity analyses were conducted comparing models with and without data on Helicobacter pylori infection. Results: The intake of red and processed meat increased gastric adenocarcinoma risk (OR for one serving/week increase (95% CI) = 1.11 (1.02;1.20) and 1.04 (1.00;1.08), respectively), specifically among men and for non-cardia and intestinal gastric adenocarcinoma. Those who consume well done white or red meat showed higher risk of non-cardia (white: RRR = 1.57 (1.14;2.16); red: RRR = 1.42 (1.00;2.02)) and intestinal tumors (white: RRR = 1.69 (1.10;2.59); red: RRR = 1.61 (1.02;2.53)) than those with a preference for rare/medium doneness. Stewing and griddling/barbequing red and white meat, and oven baking white meat, seemed to be the cooking methods with the greatest effect over gastric adenocarcinoma. The reported associations remained similar after considering Helicobacter pylori seropositivity. Conclusions: Reducing red and processed meat intake could decrease gastric adenocarcinoma risk, especially for intestinal and non-cardia tumors. Meat cooking practices could modify the risk of some gastric cancer subtypes.
Healthcare Workers’ Perception of Measures to Reduce the Risk of New Tuberculosis Infections: A Qualitative Study Report
Authors: Madzinga Debra , Tshitangano Takalani Grace , Raliphaswa Ndidzulafhi Selina , Razwiedani Lufuno
Published: November 2022

Tuberculosis, which is an infectious airborne disease remained the main leading cause of death in South Africa for three consecutive years from 2016 to 2018. In 2020 alone, the country had an estimated 328,000 people who suffered from TB, with 61,000 dying from it. Collins Chabane Municipality had 129 and 192 new TB cases recorded in 2017 and 2018, respectively, which is far from reaching the END TB STRATEGY targets. WHO scientific evidence demonstrates that TB control measures are effective in reducing the spread and development of new cases. Though scientific evidence revealed negative attitudes towards the recommended TB control measures in public hospitals of the Vhembe district, a deeper understanding of these attitudes is needed to remedy the situation. This study aimed to describe healthcare workers’ perceptions of TB control measures at Collins Chabane Municipality in South Africa. A qualitative, exploratory case study design was adopted. Multi-stage sampling technique was used to select both the healthcare facilities and the participants. Only 24 healthcare workers trained on tuberculosis management were voluntarily recruited. However, data were saturated at the twelfth (12) participant purposively selected from six healthcare facilities of Collins Chabane Municipality. Data collected through unstructured in-depth individual interviews were analyzed thematically. The proposal for this study was ethically cleared by the University of Venda Ethics Committee (SHS/20/PDC/35/1111). Results indicate that TB administrative, environmental and respiratory control measures are well understood by health workers even though there are challenges with implementation concerning some, such as closing windows during winter, UVGI lights that are non-functional and taking too long to be fixed, no specimen collection during weekends and holidays thereby delaying TB diagnosis and lack of skills concerning how to use respirators and cough etiquette. The Vhembe district TB control programme should intensify infection control training and continue monitoring giving the needed support.
Green Synthesized of Thymus vulgaris Chitosan Nanoparticles Induce Relative WRKY-Genes Expression in Solanum lycopersicum against Fusarium solani, the Causal Agent of Root Rot Disease
Authors: Abd-Ellatif Sawsan , Ibrahim Amira A. , Safhi Fatmah A. , Abdel Razik Elsayed S. , Kabeil Sanaa S. A. , Aloufi Salman , Alyamani Amal A. , Basuoni Mostafa M. , ALshamrani Salha Mesfer , Elshafie Hazem S.
Published: November 2022

Fusarium solani is a plant pathogenic fungus that causes tomato root rot disease and yield losses in tomato production. The current study’s main goal is testing the antibacterial efficacy of chitosan nanoparticles loaded with Thyme vulgaris essential oil (ThE-CsNPs) against F. solani in vitro and in vivo. GC-MS analysis was used to determine the chemical constituents of thyme EO. ThE-CsNPs were investigated using transmission electron microscopy before being physicochemically characterized using FT-IR. ThE-CsNPs were tested for antifungal activity against F. solani mycelial growth in vitro. A pot trial was conducted to determine the most effective dose of ThE-CsNPs on the morph/physiological characteristics of Solanum lycopersicum, as well as the severity of fusarium root rot. The relative gene expression of WRKY transcript factors and defense-associated genes were quantified in root tissues under all treatment conditions. In vitro results revealed that ThE-CsNPs (1%) had potent antifungal efficacy against F. solani radial mycelium growth. The expression of three WRKY transcription factors and three tomato defense-related genes was upregulated. Total phenolic, flavonoid content, and antioxidant enzyme activity were all increased. The outfindings of this study strongly suggested the use of ThE-CsNPs in controlling fusarium root rot on tomatoes; however, other experiments remain necessary before they are recommended.
Traditional Ethnobotanical Knowledge of the Central Lika Region (Continental Croatia)—First Record of Edible Use of Fungus Taphrina pruni
Authors: Vitasović-Kosić Ivana , Hodak Antonija , Łuczaj Łukasz , Marić Mara , Juračak Josip
Published: November 2022

This study analyzed the use of plants and fungi, some wild and some cultivated, in three municipalities of Lika-Senj County (Perušić, Gospić and Lovinac). The range of the study area was about 60 km. Forty in-depth semi-structured interviews were performed. The use of 111 plant taxa from 50 plant families and five taxa of mushrooms and fungi belonging to five families was recorded (on average 27 taxa per interview). The results showed quite large differences between the three studied areas in terms of ethnobotanical and ecological knowledge. In the Perušić area, (101 taxa mentioned), some people still use wild plants on a daily basis for various purposes. The most commonly noted plants are Prunus spinosa, Taraxacum spp., Rosa canina, Urtica dioica, Juglans regia and Fragaria vesca. In the Lovinac region, people used fewer species of plants (76 species mentioned). The most common species used there are: Rosa canina, Achillea millefolium, Cornus mas, Crataegus monogyna, Sambucus nigra and Prunus domestica. In the town of Gospić, the collection and use of plants was not so widespread, with only 61 species mentioned, the most common being: Achillea millefolium, Cornus mas, Sambucus nigra, Viola sp., Prunus domestica and Rosa canina. The medicinal use of herbal tea Rubus caesius and Cydonia oblonga against diarrhea was well known in the study area and is used medicinally, mainly in the rural parts of the Gospić area. The consumption of the Sorbus species (S. aria, S. domestica and S. torminalis) is an interesting local tradition in Perušić and Lovinac. Species that are difficult to find in nature today and are no longer used include: Veratrum sp., Rhamnus alpinum ssp. fallax, Gentiana lutea and Ribes uva-crispa. The use of Chenopodium album has also died out. We can assume that the differences in ethnobotanical knowledge between the three studied areas are partly due to minor differences in climate and topography, while other causes lie in the higher degree of rurality and stronger ties to nature in the Lovinac and Perušić areas. The most important finding of the study is the use of the parasitic fungus Taphrina pruni (Fuckel) Tul. as a snack. The use of Helleborus dumetorum for ethnoveterinary practices is also worth noting. The traditional use of plants in the study area shows many signs of abandonment, and therefore efforts must be made to maintain the knowledge recorded in our study.
Peach Palm (Bactris gasipaes Kunth.): Ancestral Tropical Staple with Future Potential
Authors: González-Jaramillo Nancy , Bailon-Moscoso Natalia , Duarte-Casar Rodrigo , Romero-Benavides Juan Carlos
Published: November 2022

A pre-Columbian staple, Bactris gasipaes Kunth. is a palm tree domesticated around 4000 years ago, so appreciated that a Spanish chronicler wrote in 1545, “only their wives and children were held in higher regard” by the Mesoamerican natives. The peach palm is an integral part of the foodways and gastronomy of Ecuador, Colombia, Bolivia, Peru, Brazil, and other tropical American countries; meanwhile, it is almost unknown in the rest of the world, except for hearts of palm. Although abundant, the species faces anthropogenic threats. The purpose of this study is to describe and summarize the physicochemical, nutritional, and bioactive characteristics of the peach palm and its two main alimentary products: hearts of palm and fruits, highlighting the functional and antioxidant potential of the latter, showing both ancestral and modern uses. There is active research on peach palm products and coproducts that aim for better, more sustainable uses of its traditional and recently found properties. The review and presentation of studies on this strategically relevant species can motivate the protection of endangered populations and stimulate new lines of research to advance development in the food, pharmaceutical, and cosmetic industries, with fair trade, sustainable development goals, and adaptation to climate change in mind.
Genome-Wide Association Study of Zinc Toxicity Tolerance within a Rice Core Collection (Oryza sativa L.)
Authors: Zhong Kaizhen , Xie Lihong , Hu Shikai , Shao Gaoneng , Sheng Zhonghua , Jiao Guiai , Wang Ling , Chen Ying , Tang Shaoqing , Wei Xiangjin , Zhang Peng , Hu Peisong
Published: November 2022

Zinc (Zn) is an essential micronutrient for rice, but it is toxic at a high concentration, especially in acid soils. It is yet unknown which genes regulate Zn tolerance in rice. In the present study, a genome-wide association study (GWAS) was performed for Zn tolerance in rice at the seedling stage within a rice core collection, named Ting’s core collection, which showed extensive phenotypic variations in Zn toxicity with high-density single-nucleotide polymorphisms (SNPs). A total of 7 and 19 quantitative trait loci (QTL) were detected using root elongation (RE) and relative root elongation (RRE) under high Zn toxicity, respectively. Among them, 24 QTL were novel, and qRRE15 was located in the same region where 3 QTL were reported previously. In addition, qRE4 and qRRE9 were identical. Furthermore, we found eight candidate genes that are involved in abiotic and biotic stress, immunity, cell expansion, and phosphate transport in the loci of qRRE8, qRRE9, and qRRE15. Moreover, four candidate genes, i.e., Os01g0200700, Os06g0621900, Os06g0493600, and Os06g0622700, were verified correlating to Zn tolerance in rice by quantitative real time-PCR (qRT-PCR). Taken together, these results provide significant insight into the genetic basis for Zn toxicity tolerance and tolerant germplasm for developing rice tolerance to Zn toxicity and improving rice production in Zn-contaminated soils.
Molecular Dynamics Studies of the Mechanical Behaviors and Thermal Conductivity of Polyisoprene with Different Degrees of Polymerization
Authors: Chen Zhiyuan , Tu Qunzhang , Fang Zhonghang , Shen Xinmin , Yin Qin , Zhang Xiangpo , Pan Ming
Published: November 2022

Polyisoprene, with a high degree of polymerization, is the main component of natural rubber. In the industrial production process, it is necessary to adjust the length of the macromolecule of polyisoprene to improve its plasticity. It is thus of vital importance to explore the effect of the degree of polymerization of polyisoprene on its properties, e.g., mechanical property and thermal property. Molecular dynamics simulations link microstructure to macroscopic properties. In this paper, Moltemplate was used to establish polyisoprene models with different degrees of polymerization, and the mechanical properties of polyisoprene under uniaxial tension were analyzed under an OPLS all-atom force field. The results showed that the strength and elastic modulus of the material increased with the increase in the degree of polymerization of the molecular chain. In the process of tensile loading, the non-bonded potential energy played a dominant role in the change of the total system potential energy. Then, the thermal conductivity of polyisoprene with different degrees of polymerization was calculated by the non-equilibrium molecular dynamics method (NEMD). The thermal conductivity of PI was predicted to converge to 0.179 W/(m·K). The mechanism of thermal conductivity of the polymer containing branched chains was also discussed and analyzed. The research content of this paper aims to provide theoretical support for improving the mechanical and thermal properties of natural rubber base materials.
Modeling and Analysis of Mass Transport Losses of Proton Exchange Membrane Water Electrolyzer
Authors: Miličić Tamara , Altaf Haashir , Vorhauer-Huget Nicole , Živković Luka A. , Tsotsas Evangelos , Vidaković-Koch Tanja
Published: November 2022

Proton exchange membrane water electrolyzers (PEMWEs) coupled with renewable energy resources are considered to be a key technology for producing green hydrogen. However, the high current density PEMWE operation features remarkable voltage losses. A significant part of these losses is due to the mass transport resistance in the PEMWE. Even though the importance of mass transport resistance is widely recognized, it is still poorly understood. Currently, the two-phase transport through the anode porous transport layer (PTL) and catalyst layer is considered to be the main cause of the mass transport losses. In this work, a dynamic macroscopic mathematical model, coupling electrochemical reaction with mass transport through the PTL and flow channels, has been developed to study the two-phase flow in the PTL and mass transport losses of a PEMWE. The influence of the current density, inlet water flow rate, PTL structural parameters, and capillary pressure curve was evaluated. The existence of the critical current density was observed, as well as its dependence on the operating parameters and PTL structure. Even though the results show that the PTL structure has a significant influence on the PEMWE performance, they indicate that a better mathematical description of the two-phase flow in the PTL is necessary.
Modeling and Optimization of Continuous Viral Vaccine Production
Authors: Morris Caitlin S. , Yoon Seongkyu
Published: November 2022

A model that captures realistic viral growth dynamics has been developed based on a continuous and semi-continuous production model of an influenza A virus. This model considers viral growth parameters such as viral latency. It also captures the lag observed during the early production of viruses in a culture and explains later-phase growth dynamics. Furthermore, a sensitivity analysis was performed to investigate the effects of each input on each output. This revealed that production of defective interfering particles (DIPs) highly depends on the number of cells introduced to the viral reactor. The rationale for this is, as per the model, that a reduction in number of cells to be infected causes a reduction in DIPs formed as rate of viral infection decreases. Finally, a flowsheet model was created to optimize the continuous platform, including number of cells supplied to the viral reactor. From this, it was observed that the peak number of DIPs formed could be reduced by one-third. Finally, this model is tailorable to different viral particles using parameter estimation. Therefore, the proposed mathematical model provides a versatile, comprehensive platform that can be tailored to various viral cultures with or without a latent phase.
A Multibranch Crossover Feature Attention Network for Hyperspectral Image Classification
Authors: Liu Dongxu , Wang Yirui , Liu Peixun , Li Qingqing , Yang Hang , Chen Dianbing , Liu Zhichao , Han Guangliang
Published: November 2022

Recently, hyperspectral image (HSI) classification methods based on convolutional neural networks (CNN) have shown impressive performance. However, HSI classification still faces two challenging problems: the first challenge is that most existing classification approaches only focus on exploiting the fixed-scale convolutional kernels to extract spectral–spatial features, which leads to underutilization of information; the second challenge is that HSI contains a large amount of redundant information and noise, to a certain extent, which influences the classification performance of CNN. In order to tackle the above problems, this article proposes a multibranch crossover feature attention network (MCFANet) for HSI classification. The MCFANet involves two primary submodules: a cross feature extraction module (CFEM) and rearranged attention module (RAM). The former is devised to capture joint spectral–spatial features at different convolutional layers, scales and branches, which can increase the diversity and complementarity of spectral–spatial features, while the latter is constructed to spontaneously concentrate on recalibrating spatial-wise and spectral-wise feature responses, meanwhile exploit the shifted cascade operation to rearrange the obtained attention-enhanced features to dispel redundant information and noise, and thus, boost the classification performance. Compared with the state-of-the-art classification methods, massive experiments on four benchmark datasets demonstrate the meliority of our presented method.
Compact Mesoscale Eddies in the South Brazil Bight
Authors: Rocha Cesar B. , Simoes-Sousa Iury T.
Published: November 2022

Recent studies suggest that the South Brazil Bight (SBB) hosts strong westward propagating mesoscale eddies. We use 28 years of satellite altimetry data and a new Eddy Atlas to estimate how much of the eddy kinetic energy (EKE) observed in the SBB is accounted for by local eddies, generated in the Brazil Current (BC) region, versus remote eddies generated eastward of the BC region. First, we estimate a BC frontal density to obtain a robust definition of BC region. The BC front is well-defined throughout the SBB, occupying the region between the 200-m and 1000-m isobath, except in eddy hotspots downstream of sharp inflections of the continental slope, where the EKE far exceeds the mean kinetic energy (MKE). Compact, closed-contour mesoscale eddies account for 30–50% of the total EKE observed in the SBB, with local eddies accounting for most of the compact EKE in the BC region, defined as the area within 200 km of the 28-year mean BC front. Remote compact eddies account for less than 10% of the EKE observed in the BC region; compact eddies generated at long distances from the SBB, including eddies generated in the Southeastern Atlantic, contribute an insignificant fraction of EKE in the BC region.
VLF/LF Lightning Location Based on LWPC and IRI Models: A Quantitative Study
Authors: Xu Xin , Huang Ling , Wang Shun , Ji Yicai , Liu Xiaojun , Fang Guangyou
Published: November 2022

The group velocity of lightning electromagnetic signals plays an important role in lightning location systems using the time difference of arrival (TDOA) method. Accurate estimation of group velocity is difficult due to the space- and time-varying properties of the Earth-ionosphere waveguide. Besides, the analytical solution of the group velocity is difficult to obtain from the classic mode theory, especially when higher-order modes, anisotropic geomagnetic background, diffuse ionosphere profile, and propagation path segmentation are all taken into consideration. To overcome these challenges, a novel numerical method is proposed in this paper to estimate the group velocity of the lightning signal during ionospheric quiet periods. The well-known Long Wavelength Propagation Capability (LWPC) code is used to model the propagation of VLF/LF radio waves. Since LWPC uses a simplified ionospheric model which is unable to describe the subtle variations of ionospheric parameters over time and space, the IRI-2016 model is incorporated into the numerical modeling process to provide more accurate ionosphere parameters. Experimental results of a VLF/LF lightning location network are demonstrated and analyzed to show the effectiveness of our method. The proposed method is also applicable when there is a sudden ionospheric disturbance as long as the parameters of the ionosphere are obtained in real time by remote sensing methods.
Extracting Urban Water Bodies from Landsat Imagery Based on mNDWI and HSV Transformation
Authors: Chang Liwei , Cheng Lei , Huang Chang , Qin Shujing , Fu Chenhao , Li Shiqiong
Published: November 2022

Urban water bodies are critical for sustainable urban ecological and social development. However, the complex compositions of urban land cover and small water bodies pose considerable challenges to urban water surface delineation. Here, we propose a novel urban water extraction algorithm (UWEA) that is efficient in distinguishing water and other low-reflective objects by combining the modified normalized difference water index (mNDWI) and HSV transformation. The spectral properties of urban land covers were analyzed and the separability of objects in different color spaces was compared before applying the HSV transformation. The accuracy and robustness of the UWEA were validated in six highly urbanized subregions of Beijing, Tokyo, and New York, and compared with the mNDWI and HIS methods. The results show that the UWEA had the fewest total errors (sum of omission and commission errors) for all the validation sites, which was approximately 3% fewer errors than those of the mNDWI and 17% fewer errors than those of the HIS method. The UWEA performed best because it was good at identifying small water bodies and suppressing reflective surfaces. The UWEA is effective in urban water monitoring and its thresholds are also robust in various situations. The resulting highly accurate water map could support water-related analyses. This method is also useful for scientists, managers, and planners in water resource management, urban hydrological applications, and sustainable urban development.
Fusion and Analysis of Land Use/Cover Datasets Based on Bayesian-Fuzzy Probability Prediction: A Case Study of the Indochina Peninsula
Authors: Wang Hao , Hu Yunfeng , Feng Zhiming
Published: November 2022

Land use/cover (LUC) datasets are the basis of global change studies and cross-scale land planning. Data fusion is an important direction for correcting errors and improving the reliability of multisource LUC datasets. In this study, a new fusion method based on Bayesian fuzzy probability prediction was developed, and a case study was conducted in five countries of the Indochina Peninsula to form a fusion dataset with a resolution of 30 m in 2020 (BeyFusLUC30). After precision and uncertainty analysis, it was found that: (1) using accuracy validation information as prior knowledge and considering spatial relations can be well applied to LUC data fusion. (2) When compared to the four source datasets (LSV10, GLC_FCS30, ESRI10, and Globeland30), the accuracy indices of BeyFusLUC30 are all optimal. The average overall consistency increased by 6.42–13.61%, the overall accuracy increased by 4.84–7.11%, and the kappa coefficient increased by 4.98–7.60%. (3) The accuracy of the fusion result improved less for land types with good original accuracy (cropland, forest, water area, and built-up land), and the improved range of F1 score was at least 0.40–2.29%, and at most 6.66–9.88%. For the land types with poor original accuracy (grassland, shrubland, wetland, and bare land), the accuracy of the fusion result improved more, and the F1 score improved by at least 4.02–5.82%, and at most 14.41–48.35%. The LUC dataset fusion and quality improvement method developed in this study can be applied to other regions of the world as well. BeyFusLUC30 can provide reliable LUC data for scientific research and government applications in the peninsula.
Long-Time Trends in Night Sky Brightness and Ageing of SQM Radiometers
Authors: Fiorentin Pietro , Binotto Renata , Cavazzani Stefano , Bertolo Andrea , Ortolani Sergio , Saviane Ivo
Published: November 2022

A very wide-used instrument for the measurement of the Night Sky Brightness (NSB) is the Sky Quality Meter (SQM). One of its important issues is tracking NSB for long time and connecting its variations to changes in outdoor lighting. The stability of these radiometers is fundamental; variation on the instrument behaviour could be confused with changes of the sky brightness. The SQMs of the network of the Veneto Region (Italy) and the SQM installed at La Silla (Chile) are analysed by using the twilight method considering both sunset and dawn measurements, which allows to compensate for shifts in the SQM internal clock. The slope of the observed long-term trends ranges between 29 ± 5 and 86 ± 22 mmagSQM arcsec−2 year−1. These high values require a correction of the measurements to continue to track NSB by those instruments. The correction is presented for an Italian site, for example: raw measures show an apparent trend towards darker sky (30 ± 5 mmagSQM arcsec−2 year−1), after the correction a clear tendency towards a brighter polluted sky appears (−21 ± 8 mmagSQM arcsec−2 year−1), in agreement with the estimated trend of the installed luminous flux of outdoor lighting for that area.
Bias Analysis and Correction for Ill-Posed Inversion Problem with Sparsity Regularization Based on L1 Norm for Azimuth Super-Resolution of Radar Forward-Looking Imaging
Authors: Han Jie , Zhang Songlin , Zheng Shouzhu , Wang Minghua , Ding Haiyong , Yan Qingyun
Published: November 2022

The sparsity regularization based on the L1 norm can significantly stabilize the solution of the ill-posed sparsity inversion problem, e.g., azimuth super-resolution of radar forward-looking imaging, which can effectively suppress the noise and reduce the blurry effect of the convolution kernel. In practice, the total variation (TV) and TV-sparsity (TVS) regularizations based on the L1 norm are widely adopted in solving the ill-posed problem. Generally, however, the existence of bias is ignored, which is incomplete in theory. This paper places emphasis on analyzing the partially biased property of the L1 norm. On this basis, we derive the partially bias-corrected solution of TVS and TV, which improves the rigor of the theory. Lastly, two groups of experimental results reflect that the proposed methods with partial bias correction can preserve higher quality than those without bias correction. The proposed methods not only distinguish the adjacent targets, suppress the noise, and preserve the shape and size of targets in visual terms. Its improvement of Peak Signal-to-Noise Ratio, Structure-Similarity, and Sum-Squared-Errors assessment indexes are overall 2.15%, 1.88%, and 4.14%, respectively. As such, we confirm the theoretical rigor and practical feasibility of the partially bias-corrected solution with sparsity regularization based on the L1 norm.
Global Dynamic Rainfall-Induced Landslide Susceptibility Mapping Using Machine Learning
Authors: Li Bohao , Liu Kai , Wang Ming , He Qian , Jiang Ziyu , Zhu Weihua , Qiao Ningning
Published: November 2022

Precipitation is the main factor that triggers landslides. Rainfall-induced landslide susceptibility mapping (LSM) is crucial for disaster prevention and disaster losses mitigation, though most studies are temporally ambiguous and on a regional scale. To better reveal landslide mechanisms and provide more accurate landslide susceptibility maps for landslide risk assessment and hazard prediction, developing a global dynamic LSM model is essential. In this study, we used Google Earth Engine (GEE) as the main data platform and applied three tree-based ensemble machine learning algorithms to construct global, dynamic rainfall-induced LSM models based on dynamic and static landslide influencing factors. The dynamic perspective is used in LSM: dynamic changes in landslide susceptibility can be identified on a daily scale. We note that Random Forest algorithm offers robust performance for accurate LSM (AUC = 0.975) and although the classification accuracy of LightGBM is the highest (AUC = 0.977), the results do not meet the sufficient conditions of a landslide susceptibility map. Combined with quantitative precipitation products, the proposed model can be used for the release of historical and predictive global dynamic landslide susceptibility information.
Analysis of the Spatial and Temporal Patterns of Ground-Level Ozone Concentrations in the Guangdong–Hong Kong–Macao Greater Bay Area and the Contribution of Influencing Factors
Authors: Tan Xi , Qian Yun , Wang Han , Fu Jiayi , Wu Jiansheng
Published: November 2022

Ozone (O3) pollution has negative impacts on human health and property. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is facing severe O3 pollution problems due to rapid economic development. In this paper, we used sensitivity experiments and GeoDetector to analyze the effects of meteorological factors, anthropogenic emissions, and landscape patterns on O3 concentrations as well as the contributions of NOx and NMVOC (non-methane volatile organic compounds) to the variation of O3 concentrations and the causes of sectoral emissions in the GBA in 2017. The results revealed that, in GBA, the contribution of meteorology to the variation of O3 concentration was dominant both in terms of region and extent, and the contribution of emissions was relatively weak. The contribution of meteorology and emissions to O3 production was mainly contributory. Meteorology contributed significantly to O3, and its non-linear interaction with anthropogenic emissions and surface landscape affected O3 concentration changes. The degree of contribution of NOx and NMVOC varied widely among seasons, and the variation of their relative contribution areas was related to residential sector emissions and agricultural sector emissions. This article enriches the exploration of the O3 formation mechanism in the GBA and provides theoretical support for the implementation of differentiated regional and seasonal mitigation strategies for O3 concentration.
GLSNN Network: A Multi-Scale Spatiotemporal Prediction Model for Urban Traffic Flow
Authors: Cai Benhe , Wang Yanhui , Huang Chong , Liu Jiahao , Teng Wenxin
Published: November 2022

Traffic flow prediction is a key issue in intelligent transportation systems. The growing trend in data disclosure has created more potential sources for the input for predictive models, posing new challenges to the prediction of traffic flow in the era of big data. In this study, the prediction of urban traffic flow was regarded as a spatiotemporal prediction problem, focusing on the traffic speed. A Graph LSTM (Long Short-Term Memory) Spatiotemporal Neural Network (GLSNN) model was constructed to perform a multi-scale spatiotemporal fusion prediction based on the multi-source input data. The GLSNN model consists of three parts: MS-LSTM, LZ-GCN, and LSTM-GRU. We used the MS-LSTM module to scale the traffic timing data, and then used the LZ-GCN network and the LSTM-GRU network to capture both the time and space dependencies. The model was tested on a real traffic dataset, and the experiment results verified the superior performance of the GLSNN model on both a high-precision and multi-scale prediction of urban traffic flow.
Modeling Deformation and Fracture of Boron-Based Ceramics with Nonuniform Grain and Phase Boundaries and Thermal-Residual Stress
Authors: Clayton John D.
Published: November 2022

A phase field framework of elasticity, inelasticity, and fracture mechanics is invoked to study the behavior of ceramic materials. Mechanisms addressed by phase field theory include deformation twinning, dislocation slip, amorphization, and anisotropic cleavage fracture. Failure along grain and phase boundaries is resolved explicitly, whereWeibull statistics are used to characterize the surface energies of such boundaries. Residual stress incurred by mismatching coefficients of thermal expansion among phases is included. Polycrystalline materials of interest are the ultra-hard ceramics boron carbide (B4C) and boron carbide-titanium diboride (B4C-TiB2), the latter a dual-phase composite. Recent advancements in processing technology enable the production of these materials via spark-plasma sintering (SPS) at nearly full theoretical density. Numerical simulations invoking biaxial loading (e.g., pure shear) demonstrate how properties and mechanisms at the scale of the microstructure influence overall strength and ductility. In agreement with experimental inferences, simulations show that plasticity is more prevalent in the TiB2 phase of the composite and reduces the tendency for transgranular fracture. The composite demonstrates greater overall strength and ductility than monolithic B4C in both simulations and experiments. Toughening of the more brittle B4C phase from residual stress, in addition to crack mitigation from the stronger and more ductile TiB2 phase are deemed advantageous attributes of the composite.
Usefulness of Skin Autofluorescence as a Biomarker of Acute Oxidative Stress in Young Male Japanese Long-Distance Runners: A Cross-Sectional Study
Authors: Fujiwara Rei , Anzai Natsume , Ishikawa Motoyasu , Takahashi Atsuhiko
Published: November 2022

Chronic oxidative stress in long-distance runners adversely affects conditioning. It is important to objectively assess and monitor oxidative stress, but measuring oxidative stress can be invasive or require skill to measure. Therefore, this study aimed to verify whether skin autofluorescence (SAF), a non-invasive, rapid, and easily calculable metric for calculating advanced glycation end products (AGEs), is useful as an oxidative stress biomarker. The subjects were 50 young Japanese male long-distance runners (aged 20.2 ± 1.2 years); 35 average-sized male university students (aged 19.8 ± 1.1 years) served as controls. The interactions and relationships between SAF and plasma pentosidine and oxidative stress markers (reactive oxygen metabolite-derived compounds [d-ROMs], biological antioxidant potential [BAP], and the BAP/d-ROMs ratio) in runners were examined, and SAF in the runners and controls was compared. The results suggest that plasma pentosidine in runners is associated with oxidative stress markers and that it can assess oxidative stress. However, as SAF was not associated with oxidative stress markers, it was not validated as one. In future, clarifying the factors affecting SAF may also clarify the relationship between SAF, plasma pentosidine, and oxidative stress markers.
Distribution Prediction of Strategic Flight Delays via Machine Learning Methods
Authors: Wang Ziming , Liao Chaohao , Hang Xu , Li Lishuai , Delahaye Daniel , Hansen Mark
Published: November 2022

Predicting flight delays has been a major research topic in the past few decades. Various machine learning algorithms have been used to predict flight delays in short-range horizons (e.g., a few hours or days prior to operation). Airlines have to develop flight schedules several months in advance; thus, predicting flight delays at the strategic stage is critical for airport slot allocation and airlines’ operation. However, less work has been dedicated to predicting flight delays at the strategic phase. This paper proposes machine learning methods to predict the distributions of delays. Three metrics are developed to evaluate the performance of the algorithms. Empirical data from Guangzhou Baiyun International Airport are used to validate the methods. Computational results show that the prediction accuracy of departure delay at the 0.65 confidence level and the arrival delay at the 0.50 confidence level can reach 0.80 without the input of ATFM delay. Our work provides an alternative tool for airports and airlines managers for estimating flight delays at the strategic phase.
Identification Method for Crash-Prone Sections of Mountain Highway under Complex Weather Conditions
Authors: Sun Rishuang , Zhang Chi , Xiang Yujie , Hou Lei , Wang Bo
Published: November 2022

Mountain highway crashes usually have a weather tendency, and the crash-prone sections show obvious weather differences. However, there were few targeted quantitative analyses of the impact of weather conditions on crash-prone sections in previous studies. Aiming at the problem that traditional identification methods ignore the difference in weather, this paper proposed the time-spatial density ratio method. The method quantified the length of the road section, the period, and the influence of different weather conditions through the time-spatial density ratio. Then the time-spatial density ratios under different weather conditions were comprehensively sorted in parallel. Finally, the risk threshold was determined according to the characteristics of the cumulative frequency curve’s double inflection points, and the crash-prone sections under each weather condition were identified. This paper evaluated the crash-prone sections of the G76 Expressway. Moreover, the crash risk situation under each weather condition was characterized through kernel density analysis. The method was compared with the cumulative frequency method, a traditional method suitable for Chinese highways with similar application conditions. The effective search index was utilized as a comparison factor. The results showed that the effective search index of the time-spatial density ratio method was more than 80% greater than that of the cumulative frequency method.
Assessing Citizens’ Attitudes and Intentions to Adopt E-Government Services: A Roadmap toward Sustainable Development
Authors: Xin Yongrong , Dilanchiev Azer , Ali Madad , Irfan Muhammad , Hong Yangxiao
Published: November 2022

Technological advances have ushered in the era of “e-services.” Scientists and academics are trying to determine how e-services affect citizens’ lives, satisfaction, and future service quality. As e-government emerges, this knowledge leads to improved frameworks for delivering e-services. This study examined the factors influencing Pakistanis to adopt e-government services, particularly those living abroad. Online surveys (structured questionnaires) were administered primarily among Pakistani citizens, including those residing in China and Turkey, via social media networking techniques. Purposive convenience sampling was used, 599 people were surveyed, and the results were considered complete enough to analyze. Structured equation modeling (SEM) and Amos were used to interpret quantitative research results. Results show that values are strongly correlated with expectations about others’ efforts. An invaluable feature of e-government services is their simplicity of use. It may be possible for policymakers to overcome barriers to e-government by using these research findings.
Comfort Assessment and Optimization Based on FE Simulation for High-Speed Train Seats: Comparison with Different Design Parameters
Authors: Huang Shufang , Sun Dayan , Zhang Liang , Zhou Jiahao , Wang Zhihui
Published: November 2022

Nowadays, riding comfort is more significant than before for evaluating the quality of high–speed railways and sitting is the most common posture for its passengers. This study aimed to analyze and optimize the pressure distribution and sitting comfort of second–class seats with different design parameters. Firstly, 21 pressure features were calculated after the field sitting tests conducted on a CRH Train. The subjective comfort was quantified as a linear combination of 6 pressure features in 21, which were selected using stepwise regression analysis (R2 = 0.684). A seat-human finite element model was established using THUMS for a human body and MAT_57 for the seat foam. Finally, this study analyzed the effects of foam and seat angles on interface pressure distribution and comfort ratings. The set of design parameters with the highest comfort was selected from 12 free combinations. The results show that the seat foam with less stiffness may not improve sitting comfort due to the asymmetry of the seat frame. Moreover, appropriately increasing the stiffness of the cushion and backrest will not lead to a decrease in subjective feelings and the pressure distribution becomes more reasonable as the inclination angle increases within 10 degrees. The final optimization increases the computational comfort of the seat-human model by 6.5 in a −50 to 50 scale.
Gender and Age Association with Physical Activity and Mood States of Children and Adolescents in Social Isolation during the COVID-19 Pandemic
Authors: He Junliang , Qiu Longkun
Published: November 2022

Background: The outbreak of COVID-19 had a huge impact on daily life. It greatly reduced our physical activity (PA) and caused an increase in negative emotions. The emotions of different ages and sexes were impacted during the pandemic but the most severely influenced were adolescents. Therefore, the study’s main purpose was to explore the influence of age and gender on adolescent physical activity and emotions during the pandemic. Methods: The subjects of the present study were 14,045 adolescents aged 10–18 years from the Yan’an Shaanxi province. The International Physical Activity Questionnaire Short Form (IPAQ-SF) was used to investigate the PA and Profile of Mood States (POMS) was used to investigate adolescents’ mood states. Results: we found that girls and boys have significant differences in total PA and moderate PA (p < 0.01). The adolescents’ PA levels of different ages had significant differences (p < 0.01). Meanwhile, boys had higher negative emotion scores (anger, fatigue, depression, confusion) than girls. Girls, in contrast, had higher positive emotion scores (self-esteem, vigor) (p < 0.01). With increasing age, the increase in emotional states seems to diminish (p < 0.01). Conclusions: Results show long-term social isolation causes reduced PA and increased negative mood states. Girls’ PA was higher than boys, and boys had higher levels of mood disturbances. PA and levels of mood disturbances were significantly associated with age from 10 to 18 years old. This research study aimed to help the correlation department understand the relationship between PA and mood states of adolescents of different ages and sexes during COVID-19. Providing health promotion and preventative advice for different sex and age groups has expanded globally.
Variations in Permeability and Mechanical Properties of Basaltic Rocks Induced by Carbon Mineralization
Authors: Ye Zhenni , Liu Xiaoli , Sun Huan , Dong Qinxi , Du Weisheng , Long Qijian
Published: November 2022

Carbon capture, utilization, and storage (CCUS/CCS) is a strategic choice for ensuring energy security and reducing carbon dioxide emissions across the globe. The injection of CO2 into the basaltic reservoir is one strategy for the permanent disposal of carbon emissions. Basaltic rocks, which are widely distributed in Hainan Island, are capable of CO2 geological sequestration. In this study, the reaction of CO2-NaOH/Ca(OH)2-basaltic rocks under conditions of 6.0 M Pa and 30 °C was performed using basaltic samples collected from the Fushan area of the Hainan Province to evaluate the sequestration of CO2 in basalt by mineralization. Then, the effect of CO2 mineralization on the permeability and mechanical properties of basaltic rocks was evaluated using X-ray computer tomography and triaxial compression testing at 21.0 MPa. In addition, microwave technology was used to irradiate the basaltic rocks before mineralization. Changes in the permeability of basalt before and after mineralization and microwave irradiation were simulated numerically, and their effects on the mechanical strength deterioration of basalt were analyzed according to the rock mechanics using triaxial testing. Based on these results, a new method for the induction of basalt deterioration, mineralization, CO2 injectivity, and storage capacity using microwave irradiation is proposed for use in CCUS/CCS engineering.