bluuebunny/crossref_metadata_2025 huggingface dataset:
Production and Use of Recombinant Profilins Amb a 8, Art v 4, Bet v 2, and Phl p 12 for Allergenic Sensitization Studies
Authors: Cudowska Beata , Kapingidza A. Brenda , Pawłowicz Magdalena , Pampuch Agnieszka , Hyduke Noah , Pote Swanandi , Schlachter Caleb R. , Lebensztejn Dariusz M. , Chruszcz Maksymilian , Kowal Krzysztof
Published: January 2020

Four recombinant (r) allergens (rAmb a 8.0101, rArt v 4.0101, rBet v 2.0101, and rPhl p 12.0101) were successfully produced and used for sensitization studies. The allergens belong to the profilin family which is one of the most numerous allergen families. These four proteins represent allergens originating from pollen of weeds (rAmb a 8.0101 and rArt v 4.0101), tree (rBet v 2.0101) and grass (rPhl p 12.0101). The recombinant allergens were characterized using various biochemical and biophysical methods and tested for their ability to bind patient-derived antibodies. One hundred patients aged 2 to 50 years sensitized to pollen and plant-derived food allergens (IgE > 0.35 kU/L) were included. Sensitization to individual allergen sources and components of birch and timothy pollens was evaluated using multiparameter immunoblots. The presence of IgE to pollen-derived recombinant profilins rAmb a 8.0101, rArt v 4.0101, rBet v 2.0101, and rPhl p 12.0101 in serum was evaluated using ELISA method. The presence of IgE against pollen profilins was detected in 20 out of 100 studied patients. High correlation was seen between IgE ELISA results with individual pollen profilins. In summary, it was shown that the recombinant versions of the four allergenic profilins can be used for sensitization studies and for component-resolved allergy diagnostics.
Synthesis, Crystal Structure, and Biological Activity of a Multidentate Calix[4]arene Ligand Doubly Functionalized by 2-Hydroxybenzeledene-Thiosemicarbazone
Authors: Bahojb Noruzi Ehsan , Shaabani Behrouz , Geremia Silvano , Hickey Neal , Nitti Patrizia , Kafil Hossein Samadi
Published: January 2020

The design and synthesis of a novel tert-butyl-calix[4]arene functionalized at 1, 3 positions of the lower rim with two terminal 2-hydroxybenzeledene-thiosemicarbazone moieties is reported. The new ligand with multi-dentate chelating properties was fully characterized by several techniques: ESI-Mass spectroscopy, FT-IR, 1H-NMR, and single crystal X-ray diffraction. The solid state structure confirms that the calix[4]arene macrocycle has the expected open cone conformation, with two opposite phenyl rings inclined outwards with large angles. The conformation of the two alkoxythiosemicarbazone arms produces a molecule with a C2 point group symmetry. An interesting chiral helicity is observed, with the two thiosemicarbazone groups oriented in opposite directions like a two-blade propeller. A water molecule is encapsulated in the center of the two-blade propeller through multiple H-bond coordinations. The antibacterial, antifungal, anticancer, and cytotoxic activities of the calix[4]arene-thiosemicarbazone ligand and its metal derivatives (Co2+, Ni2+, Cu2+, and Zn2+) were investigated. A considerable antibacterial activity (in particular against E. coli, MIC, and MBC = 31.25 μg/mL) was observed for the ligand and its metal derivatives. Significant antifungal activities against yeast (C. albicans) were also observed for the ligand (MIC = 31.25 μg/mL and MBC = 125 μg/mL) and for its Co2+ derivative (MIC = 62.5 μg/mL). All compounds show cytotoxicity against the tested cancerous cells. For the Saos-2 cell line, the promising anticancer activity of ligand L (IC50 < 25 μg/mL) is higher than its metal derivatives. The microscopic analysis of DAPI-stained cells shows that the treated cells change in morphology, with deformation and fragmentation of the nuclei. The hemo-compatibility study demonstrated that this class of compounds are suitable candidates for further in vivo investigations.
Nitrogen Fertilizer Levels Affect the Growth and Quality Parameters of Astragalus mongolica
Authors: Wang Lingling , Yang Lucun , Xiong Feng , Nie Xiuqing , Li Changbin , Xiao Yuanming , Zhou Guoying
Published: January 2020

Owing to overexploitation, wild resources of Astragalus mongolica, a Chinese herbal plant that is widely distributed in the arid and semi-arid areas of Northern China, have gradually become exhausted, and therefore, commercial cultivation is increasingly important to meet the growing demand for astragalus and reduce the pressure on wild populations. Nitrogen level is an important factor that affects the yield and quality of A. mongolica. However, uniform standards for fertilization among production areas have not yet been determined. In this study, the effect of nitrogen fertilizer treatment on the yield and quality of A. mongolica in the Qinghai-Tibet Plateau was explored using a control treatment (no added nitrogen, N0) and five different nutrient levels: 37.5 kg/ha (N1), 75 kg/ha (N2), 112.5 kg/ha (N3), 150 kg/ha (N4), and 187.5 kg/ha (N5). According to grey relational analysis, the optimal nitrogen fertilizer treatment was the N4 level followed by the N5 and N2 levels. Nitrogen fertilizer significantly increased the root biomass, plant height, root length, and root diameter. However, nitrogen fertilization had no significant effect on the content of Astragaloside IV and mullein isoflavone glucoside. The content of ononin and calycosin continually accumulated throughout the growing period. The results showed that the ononin and calycosin content under N4 and N2 is higher than other levels and there is not significantly different between different nitrogen fertilizer levels about them. The content of formononetin decreased gradually with the progression of the growing season. The optimal nitrogen fertilizer treatment for A. mongolica is recommended to be 150 kg/ha and the content of active compounds and yield were observed to reach the maximum in October.
Synthesis of Polyhedral Borane Cluster Fused Heterocycles via Transition Metal Catalyzed B-H Activation
Authors: Cao Ke , Zhang Cai-Yan , Xu Tao-Tao , Wu Ji , Wen Xin-Yu , Jiang Wen-Jun , Chen Mao , Yang Junxiao
Published: January 2020

Aromatic heterocycles are ubiquitous building blocks in bioactive natural products, pharmaceutical and agrochemical industries. Accordingly, the carborane-fused heterocycles would be potential candidates in drug discovery, nanomaterials, metallacarboranes, as well as photoluminescent materials. In recent years, the transition metal catalyzed B-H activation has been proved to be an effective protocol for selective functionalization of B-H bond of o-carboranes, which has been further extended for the synthesis of polyhedral borane cluster-fused heterocycles via cascade B-H functionalization/annulation process. This article summarizes the recent progress in construction of polyhedral borane cluster-fused heterocycles via B-H activation.
Substrate-Controlled Magnetism: Fe Nanowires on Vicinal Cu Surfaces
Authors: Hashemi D. , Waters M. J. , Hergert W. , Kieffer J. , Stepanyuk V. S.
Published: January 2020

Here we present a novel approach to controlling magnetic interactions between atomic-scale nanowires. Our ab initio calculations demonstrate the possibility to tune magnetic properties of Fe nanowires formed on vicinal Cu surfaces. Both intrawire and interwire magnetic exchange parameters are extracted from density functional theory (DFT) calculations. This study suggests that the effective interwire magnetic exchange parameters exhibit Ruderman–Kittel–Kasuya–Yosida-like (RKKY) oscillations as a function of Fe interwire separation. The choice of the vicinal Cu surface offers possibilities for controlling the magnetic coupling. Furthermore, an anisotropic Heisenberg model was used in Monte Carlo simulations to examine the stability of these magnetic configurations at finite temperatures. The predicted critical temperatures of the Fe nanowires on Cu(422) and Cu(533) surfaces are well above room temperature.
Energy Expenditure and Changes in Body Composition During Submarine Deployment—An Observational Study “DasBoost 2-2017”
Authors: Rietjens Gerard , Most Jasper , Joris Peter J. , Helmhout Pieter , Plasqui Guy
Published: January 2020

The present study was designed to objectively assess the effects of 3-months submarine deployment on behavioural and metabolic determinants of metabolic health. In 13 healthy, non-obese volunteers, we using stable isotope dilution, and plasma and urinary biochemistry to characterize metabolic health before and after a 3-month submarine deployment. Volunteers worked in 6-h shifts. After deployment, we observed reduced fat-free mass (mean ± SD, −4.1 ± 3.3 kg, p = 0.003) and increased adiposity (21.9 ± 3.2% fat mass to 24.4 ± 4.7%, p = 0.01). Changes in fat-free mass were positively associated with physical activity (+0.8 kg per 0.1 increase in PAL, p = 0.03). The average physical activity level was 1.64 ± 0.26 and total energy expenditure during deployment was 2937 ± 498 kcal/d, while energy intake was 3158 ± 786 kcal/d. Fasting glucose (p = 0.03), and triglycerides (p = 0.01) declined, whereas fasting free fatty acids increased (p = 0.04). Plasma vitamin D and B12 concentrations decreased (−14%, p = 0.04, and −44%, p = 0.001, respectively), and plasma calcium, and magnesium increased (+51%, p = 0.01, and +5%, p = 0.02). Haemoglobin was unchanged, but haematocrit decreased (−2.2 ± 2.1%, p = 0.005). In conclusion, submarine deployment impairs fat-free mass maintenance and promotes adiposity. High physical activity may prevent the decline in fat-free mass. Our study confirms the need to counteract Vitamin D and B12 deficiencies, and suggests impairments in erythrocyte metabolism.
Dietary Patterns and Dietary Adaptations in Women With and Without Gestational Diabetes: Evidence From the Growing Up in New Zealand Study
Authors: Lawrence Robyn L. , Wall Clare R. , Bloomfield Frank H.
Published: January 2020

Diet is a cornerstone of the management of gestational diabetes (GDM). We investigated differences in dietary patterns and dietary adaptations among pregnant women with and without GDM participating in the Growing Up in New Zealand study. Presence of GDM was determined using coded clinical data and plasma glucose results meeting the New Zealand Society for the Study of Diabetes diagnostic criteria. Women answered a food frequency questionnaire and questions regarding dietary changes and information received during pregnancy. Women with GDM had lower adherence scores than those without GDM for ‘Junk’ (mean (SD) score −0.28 (0.95) versus 0.02 (1.01) p < 0.0005) and ‘Traditional/White bread’ dietary patterns (−0.18 (0.93) versus 0.01 (1.01) p = 0.002). More women with GDM reported avoiding foods high in fat or sugar (25.3% versus 5.7%, p < 0.05) compared to women without GDM. A greater proportion of women with GDM compared with those without GDM received information from dietitians or nutritionists (27.0% versus 1.7%, p < 0.05) or obstetricians (12.6% versus 7.5%, p < 0.05). More women diagnosed before the antenatal interview received advice from dietitians or nutritionists compared with those diagnosed after (46.9% versus 6.0%, p < 0.05). Women with GDM appear to make positive changes to their diet in response to advice received from health care professionals.
Sharing is Caring: A Study of Food-Sharing Practices in Australian Early Childhood Education and Care Services
Authors: Wallace Ruth , Lombardi Karen , De Backer Charlotte , Costello Leesa , Devine Amanda
Published: January 2020

Food connects people, and can significantly impact the physical, social and emotional development of young children. Food sharing and family-style mealtimes can support healthy eating practices and psychological well-being among young children, and carersother than family members, such as Early Childhood Education and Care staff, play an important role in the provision of these practices. Despite increasing numbers of Australian children attending Early Childhood Education and Care services, there is often reluctance among staff to promote such mealtime practices, to the detriment of children’s social and emotional development. The aim of this paper was to focus on the potential role of Early Childhood Education and Care services in facilitating food sharing and family-style mealtime practices in the earliest stages of the lifespan. A qualitative, netnographic approach was used, and data was collected as part of the broader ’Supporting Nutrition for Australian Childcare’ (SNAC) study, via online conversation threads, observations and qualitative interviews. Findings demonstrated that whilst many Early Childhood Education and Care services are committed to supporting food sharing and family-style mealtime practices, a number of barriers were reported. These included the perception that babies and toddlers could not participate in these practices, concerns about food hygiene and cross contamination of allergens, and negative parental influences on food sharing. In conclusion, this paper supports the practice of food sharing in Early Childhood Education and Care settings and calls for them to become embedded in everyday operations to support the physical, social and emotional development of Australia’s future generations.
Association Between Diet, Physical Activity and Body Mass Index, Fat Mass Index and Bone Mineral Density of Soldiers of the Polish Air Cavalry Units
Authors: Anyżewska Anna , Łakomy Roman , Lepionka Tomasz , Szarska Ewa , Maculewicz Ewelina , Tomczak Andrzej , Bertrandt Jerzy
Published: January 2020

Research from recent years indicates a problem of excessive body weight among soldiers, who, due to the kind of work carried out, should possess good health and fitness levels. The aim of the study was to determine the association between diet and physical activity and the nutritional status of soldiers of the Polish Air Cavalry Units. One hundred and twenty male soldiers (aged 28 ± 5 years) completed a questionnaire (food frequency questionnaire, long-form International Physical Activity Questionnaire). Body composition was determined by bioelectrical impedance analysis, and bone calcification of the forearm was assessed by the DXA (Dual Energy X-ray Absorptiometry) densitometric method. This study confirmed the association between both the diet and physical activity and body mass index (BMI), fat mass index (FMI), and bone mineral density (BMD) expressed as T-score. Significant negative correlations were found between BMI and the frequency of consumption of cereal products, meat products and fish, and nonalcoholic beverages, between FMI and cereal products, and between BMD T-score and meat products and fish, fat, nuts, and grains, sweets and snacks, and nonalcoholic beverages. Physical activity expressed as metabolic equivalent (MET-minutes/week) negatively correlated with FMI (but not BMI) and positively correlated with the BMD T-score. This study confirmed numerous irregularities in eating behavior and in nutritional status indices; therefore, there is a need for nutritional education and further monitoring of both dietary behaviors and nutritional status of soldiers.
The Role of Vitamin D in Primary Headache–from Potential Mechanism to Treatment
Authors: Nowaczewska Magdalena , Wiciński Michał , Osiński Stanisław , Kaźmierczak Henryk
Published: January 2020

Some studies have suggested a link between vitamin D and headache; however, the underlying physiological mechanisms are unclear. We aimed to summarize the available evidence on the relationship between vitamin D and the various subtypes of primary headaches, including migraines and tension-type headaches. All articles concerning the association between primary headache and vitamin D published up to October 2019 were retrieved by searching clinical databases, including: EMBASE, MEDLINE, PubMed, Google scholar, and the Cochrane library. All types of studies (i.e., observational, cross-sectional, case-control, and clinical trials) were included. We identified 22 studies investigating serum vitamin D levels in association with headaches. Eight studies also evaluated the effect of vitamin D supplementation on the various headache parameters. Among them, 18 studies showed a link between serum vitamin D levels and headaches, with the strongest connection reported between serum vitamin D levels and migraine. Overall, there is not enough evidence to recommend vitamin D supplementation to all headache patients, but the current literature indicates that it may be beneficial in some patients suffering headaches, mainly migraineurs, to reduce the frequency of headaches, especially in those with vitamin D deficiency.
Strategic Approaches for Colon Targeted Drug Delivery: An Overview of Recent Advancements
Authors: Lee Sang Hoon , Bajracharya Rajiv , Min Jeong Youn , Han Ji-Won , Park Byeong Ju , Han Hyo-Kyung
Published: January 2020

Colon targeted drug delivery systems have gained a great deal of attention as potential carriers for the local treatment of colonic diseases with reduced systemic side effects and also for the enhanced oral delivery of various therapeutics vulnerable to acidic and enzymatic degradation in the upper gastrointestinal tract. In recent years, the global pharmaceutical market for biologics has grown, and increasing demand for a more patient-friendly drug administration system highlights the importance of colonic drug delivery as a noninvasive delivery approach for macromolecules. Colon-targeted drug delivery systems for macromolecules can provide therapeutic benefits including better patient compliance (because they are pain-free and can be self-administered) and lower costs. Therefore, to achieve more efficient colonic drug delivery for local or systemic drug effects, various strategies have been explored including pH-dependent systems, enzyme-triggered systems, receptor-mediated systems, and magnetically-driven systems. In this review, recent advancements in various approaches for designing colon targeted drug delivery systems and their pharmaceutical applications are covered with a particular emphasis on formulation technologies.
Optimization of Rifapentine-Loaded Lipid Nanoparticles Using a Quality-by-Design Strategy
Authors: Magalhães Joana , L. Chaves Luise , C. Vieira Alexandre , G. Santos Susana , Pinheiro Marina , Reis Salette
Published: January 2020

This work aims to optimize and assess the potential use of lipid nanoparticles, namely nanostructured lipid carriers (NLCs), as drug delivery systems of rifapentine (RPT) for the treatment of tuberculosis (TB). A Box–Behnken design was used to increase drug encapsulation efficiency (EE) and loading capacity (LC) of RPT-loaded NLCs. The optimized nanoparticles were fully characterized, and their effect on cell viability was assessed. The quality-by-design approach allowed the optimization of RPT-loaded NLCs with improved EE and LC using the minimum of experiments. Analyses of variance were indicative of the validity of this model to optimize this nanodelivery system. The optimized NLCs had a mean diameter of 242 ± 9 nm, polydispersity index <0.2, and a highly negative zeta potential. EE values were higher than 80%, and differential scanning calorimetry analysis enabled the confirmation of the efficient encapsulation of RPT. Transmission electron microscopy analysis showed spherical nanoparticles, uniform in shape and diameter, with no visible aggregation. Stability studies indicated that NLCs were stable over time. No toxicity was observed in primary human macrophage viability for nanoparticles up to 1000 μg mL−1. Overall, the optimized NLCs are efficient carriers of RPT and should be considered for further testing as promising drug delivery systems to be used in TB treatment.
HD-ZIP I Transcription Factor (PtHB13) Negatively Regulates Citrus Flowering through Binding to FLOWERING LOCUS C Promoter
Authors: Ma Yu-Jiao , Li Pei-Ting , Sun Lei-Ming , Zhou Huan , Zeng Ren-Fang , Ai Xiao-Yan , Zhang Jin-Zhi , Hu Chun-Gen
Published: January 2020

For floral induction in adult citrus, low temperature is one of the most important environmental factors. FLOWERING LOCUS C (FLC) plays a very important role in low-temperature-induced Arabidopsis flowering by repressed FLC expression under exposure to prolonged low-temperature conditions. However, little is known about the FLC regulation mechanism in perennial woody plants such as citrus. In this study, the functions of citrus FLC homolog (PtFLC) were investigated by ectopic expression in Arabidopsis. Transcription factor of homeodomain leucine zipper I (HD-ZIP I) as an upstream regulator of PtFLC was identified by yeast one-hybrid screen to regulate its transcription. The HD-ZIP I transcription factor was highly homologous to Arabidopsis ATHB13 and thus was named PtHB13. Ectopically expressed PtHB13 inhibited flowering in transgenic Arabidopsis. Furthermore, the expression of PtFLC and PtHB13 showed a seasonal change during the floral induction period and was also affected by low temperature. Thus, we propose that PtHB13 binds to PtFLC promoter to regulate its activity during the citrus floral induction process.
Core-Shell Graphitic Carbon Nitride/Zinc Phytate as a Novel Efficient Flame Retardant for Fire Safety and Smoke Suppression in Epoxy Resin
Authors: Zhang Weiwei , Wu Weihong , Meng Weihua , Xie Weiya , Cui Yumeng , Xu Jianzhong , Qu Hongqiang
Published: January 2020

Novel core-shell graphitic carbon nitride/zinc phytate (g-C3N4/PAZn) flame retardant was simple synthetized using two-dimensional g-C3N4 and bio-based PAZn by self-assembly and incorporated into epoxy resin (EP) for improving the fire safety. The flame retardance and smoke suppression were investigated by cone calorimetry. The results indicated that g-C3N4/PAZn-EP displayed outstanding flame retardancy and smoke suppression, for example, the peak heat release rate and peak smoke production rate decreased by 71.38% and 25%, respectively. Furthermore, the flame retardancy mechanism was further explored by char residue and thermal stability analysis. It can be predicted that g-C3N4/PAZn will provide valuable reference about bio-based flame retardant.
Short-Term Wind Power Prediction Based on Improved Grey Wolf Optimization Algorithm for Extreme Learning Machine
Authors: Ding Jiale , Chen Guochu , Yuan Kuo
Published: January 2020

In order to improve the accuracy of wind power prediction and ensure the effective utilization of wind energy, a short-term wind power prediction model based on variational mode decomposition (VMD) and an extreme learning machine (ELM) optimized by an improved grey wolf optimization (GWO) algorithm is proposed. The original wind power sequence is decomposed into series of modal components with different center frequencies by the VMD method and some new sequences are obtained by phase space reconstruction (PSR). Then, the ELM model is established for different new time series, and the improved GWO algorithm is used to optimize its parameters. Finally, the output results are weighted and merged as the final predicted value of wind power. The root-mean-square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of the proposed VMD-improved GWO-ELM prediction model in the paper are 5.9113%, 4.6219%, and 13.01% respectively, which are better than these of ELM, back propagation (BP), and the improved GWO-ELM model. The simulation results show that the proposed model has higher prediction accuracy than other models in short-term wind power prediction.
Research on Green Power Dispatching Based on an Emergy-Based Life Cycle Assessment
Authors: Li Tao , Song Yi Miao , Li Ang , Shen Jing , Liang Chao , Gao Ming
Published: January 2020

Environmental protection pressures and green energy strategies have created major challenges for a cleaner production of China’s coal-fired power generation. Although China’s electric power dispatching department has tried to prioritize clean energy, the current dispatching models lack environmental indicators related to coal-fired power generation. The main purpose of this paper is to provide a comprehensive environmental indicator for the cleanliness evaluation of coal-fired power plants. In this paper, the (Emergy-based Life Cycle Assessment) Em-LCA method is used to measure and analyze environmental related resource consumption, socio-economic investment, and emissions in the whole life cycle of coal-fired power plants. At the same time, based on the above three environmental impacts in the whole life cycle, this paper constructs the (Em-LCA based Cleaner Production Comprehensive Evaluation) ECPCE index to guide a green dispatching plan. By comparing the calculation results of the index, this paper finds that there are differences in the environmental advantages of different generating units in green dispatching, which are closely related to the process management of coal-fired power plants in production and the environment.
Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation
Authors: Sekertekin Aliihsan , Bonafoni Stefania
Published: January 2020

Land Surface Temperature (LST) is an important parameter for many scientific disciplines since it affects the interaction between the land and the atmosphere. Many LST retrieval algorithms based on remotely sensed images have been introduced so far, where the Land Surface Emissivity (LSE) is one of the main factors affecting the accuracy of the LST estimation. The aim of this study is to evaluate the performance of LST retrieval methods using different LSE models and data of old and current Landsat missions. Mono Window Algorithm (MWA), Radiative Transfer Equation (RTE) method, Single Channel Algorithm (SCA) and Split Window Algorithm (SWA) were assessed as LST retrieval methods processing data of Landsat missions (Landsat 5, 7 and 8) over rural pixels. Considering the LSE models introduced in the literature, different Normalized Difference Vegetation Index (NDVI)-based LSE models were investigated in this study. Specifically, three LSE models were considered for the LST estimation from Landsat 5 Thematic Mapper (TM) and seven Enhanced Thematic Mapper Plus (ETM+), and six for Landsat 8. For the accurate evaluation of the estimated LST, in-situ LST data were obtained from the Surface Radiation Budget Network (SURFRAD) stations. In total, forty-five daytime Landsat images; fifteen images for each Landsat mission, acquired in the Spring-Summer-Autumn period in the mid-latitude region in the Northern Hemisphere were acquired over five SURFRAD rural sites. After determining the best LSE model for the study case, firstly, the LST retrieval accuracy was evaluated considering the sensor type: when using Landsat 5 TM, 7 ETM+, and 8 Operational Land Imager (OLI), and Thermal Infrared Sensor (TIRS) data separately, RTE, MWA, and MWA presented the best results, respectively. Then, the performance was evaluated independently of the sensor types. In this case, all LST methods provided satisfying results, with MWA having a slightly better accuracy with a Root Mean Square Error (RMSE) equals to 2.39 K and a lower bias error. In addition, the spatio-temporal and seasonal analyses indicated that RTE and SCA presented similar results regardless of the season, while MWA differed from RTE and SCA for all seasons, especially in summer. To efficiently perform this work, an ArcGIS toolbox, including all the methods and models analyzed here, was implemented and provided as a user facility for the LST retrieval from Landsat data.
Comparison of Different Machine Learning Methods for Debris Flow Susceptibility Mapping: A Case Study in the Sichuan Province, China
Authors: Xiong Ke , Adhikari Basanta Raj , Stamatopoulos Constantine A. , Zhan Yu , Wu Shaolin , Dong Zhongtao , Di Baofeng
Published: January 2020

Debris flow susceptibility mapping is considered to be useful for hazard prevention and mitigation. As a frequent debris flow area, many hazardous events have occurred annually and caused a lot of damage in the Sichuan Province, China. Therefore, this study attempted to evaluate and compare the performance of four state-of-the-art machine-learning methods, namely Logistic Regression (LR), Support Vector Machines (SVM), Random Forest (RF), and Boosted Regression Trees (BRT), for debris flow susceptibility mapping in this region. Four models were constructed based on the debris flow inventory and a range of causal factors. A variety of datasets was obtained through the combined application of remote sensing (RS) and geographic information system (GIS). The mean altitude, altitude difference, aridity index, and groove gradient played the most important role in the assessment. The performance of these modes was evaluated using predictive accuracy (ACC) and the area under the receiver operating characteristic curve (AUC). The results of this study showed that all four models were capable of producing accurate and robust debris flow susceptibility maps (ACC and AUC values were well above 0.75 and 0.80 separately). With an excellent spatial prediction capability and strong robustness, the BRT model (ACC = 0.781, AUC = 0.852) outperformed other models and was the ideal choice. Our results also exhibited the importance of selecting suitable mapping units and optimal predictors. Furthermore, the debris flow susceptibility maps of the Sichuan Province were produced, which can provide helpful data for assessing and mitigating debris flow hazards.
Quantifying Understory and Overstory Vegetation Cover Using UAV-Based RGB Imagery in Forest Plantation
Authors: Li Linyuan , Chen Jun , Mu Xihan , Li Weihua , Yan Guangjian , Xie Donghui , Zhang Wuming
Published: January 2020

Vegetation cover estimation for overstory and understory layers provides valuable information for modeling forest carbon and water cycles and refining forest ecosystem function assessment. Although previous studies demonstrated the capability of light detection and ranging (LiDAR) in the three-dimensional (3D) characterization of forest overstory and understory communities, the high cost inhibits its application in frequent and successive survey tasks. Low-cost commercial red–green–blue (RGB) cameras mounted on unmanned aerial vehicles (UAVs), as LiDAR alternatives, provide operational systems for simultaneously quantifying overstory crown cover (OCC) and understory vegetation cover (UVC). We developed an effective method named back-projection of 3D point cloud onto superpixel-segmented image (BAPS) to extract overstory and forest floor pixels using 3D structure-from-motion (SfM) point clouds and two-dimensional (2D) superpixel segmentation. The OCC was estimated from the extracted overstory crown pixels. A reported method, called half-Gaussian fitting (HAGFVC), was used to segement green vegetation and non-vegetation pixels from the extracted forest floor pixels and derive UVC. The UAV-based RGB imagery and field validation data were collected from eight forest plots in Saihanba National Forest Park (SNFP) plantation in northern China. The consistency of the OCC estimates between BAPS and canopy height model (CHM)-based methods (coefficient of determination: 0.7171) demonstrated the capability of the BAPS method in the estimation of OCC. The segmentation of understory vegetation was verified by the supervised classification (SC) method. The validation results showed that the OCC and UVC estimates were in good agreement with reference values, where the root-mean-square error (RMSE) of OCC (unitless) and UVC (unitless) reached 0.0704 and 0.1144, respectively. The low-cost UAV-based observation system and the newly developed method are expected to improve the understanding of ecosystem functioning and facilitate ecological process modeling.
RETRACTED: Chen et al. The Novel Sensor Network Structure for Classification Processing Based on the Machine Learning Method of the ACGAN. Sensors 2019, 19, 3145
Authors:   Sensors Editorial Office
Published: January 2020

It has been brought to our attention that the majority of the text, figures, structures, and references in the title paper [...]
Optimal Energy Resources Allocation Method of Wireless Sensor Networks for Intelligent Railway Systems
Authors: Bin Sheng , Sun Gengxin
Published: January 2020

The rapid increase of train speed has brought greater challenges to the safety and reliability of railway systems. Therefore, it is necessary to monitor the operation status of trains, infrastructure, and their operating environment in real time. Because the operation environment of railway systems is complex, the construction cost of wired monitoring systems is high, and it is difficult to achieve full coverage in the operation area of harsh environments, so wireless sensor networks are suitable for the status monitoring of railway systems. Energy resources of nodes are the basis of ensuring the lifecycle of wireless sensor networks, but severely restrict the sustainability of wireless sensor networks. A construction method of special wireless sensor networks for railway status monitoring, and an optimal energy resources allocation method of wireless sensor networks for intelligent railway systems are proposed in this paper. Through cluster head selection and rotating probability model, clustering generation and optimization model, and partial coverage model, the energy consumption of nodes can be minimized and balanced. The result of simulation experiment proved that the lifetime of wireless sensor networks can be maximized by the optimal energy resources allocation method based on clustering optimization and partial coverage model, based on polynomial time algorithm.
Distributed Multi-Robot Information Gathering under Spatio-Temporal Inter-Robot Constraints
Authors: Viseras Alberto , Xu Zhe , Merino Luis
Published: January 2020

Information gathering (IG) algorithms aim to intelligently select the mobile robotic sensor actions required to efficiently obtain an accurate reconstruction of a physical process, such as an occupancy map, a wind field, or a magnetic field. Recently, multiple IG algorithms that benefit from multi-robot cooperation have been proposed in the literature. Most of these algorithms employ discretization of the state and action spaces, which makes them computationally intractable for robotic systems with complex dynamics. Moreover, they cannot deal with inter-robot restrictions such as collision avoidance or communication constraints. This paper presents a novel approach for multi-robot information gathering (MR-IG) that tackles the two aforementioned restrictions: (i) discretization of robot’s state space, and (ii) dealing with inter-robot constraints. Here we propose an algorithm that employs: (i) an underlying model of the physical process of interest, (ii) sampling-based planners to plan paths in a continuous domain, and (iii) a distributed decision-making algorithm to enable multi-robot coordination. In particular, we use the max-sum algorithm for distributed decision-making by defining an information-theoretic utility function. This function maximizes IG, while fulfilling inter-robot communication and collision avoidance constraints. We validate our proposed approach in simulations, and in a field experiment where three quadcopters explore a simulated wind field. Results demonstrate the effectiveness and scalability with respect to the number of robots of our approach.
A New DGNSS Positioning Infrastructure for Android Smartphones
Authors: Weng Duojie , Gan Xingli , Chen Wu , Ji Shengyue , Lu Yangwei
Published: January 2020

One’s position has become an important piece of information for our everyday lives in a smart city. Currently, a position can be obtained easily using smartphones that is equipped with low-cost Global Navigation Satellite System (GNSS) chipsets with accuracy varying from 5 m to 10 m. Differential GNSS (DGNSS) is an efficient technology that removes the majority of GNSS errors with the aid of reference stations installed at known locations. The sub-meter accuracy can be achieved when applying the DGNSS technology on the advanced receivers. In 2016, Android has opened the accesses of raw GNSS measurements to developers. However, most of the mid and low-end smartphones only provide the data using the National Marine Electronics Association (NMEA) protocol. They do not provide the raw measurements, and thus do not support the DGNSS operation either. We proposed a DGNSS infrastructure that correct the standalone GNSS position of smartphones using the corrections from the reference station. In the infrastructure, the position correction is generated considering the GNSS satellite IDs that contribute to the standalone solution in smartphones, and the position obtained is equivalent to the solution of using the range-domain correction directly. To serve a large number of smartphone users, a Client/Server architecture is developed to cope with a mass of DGNSS positioning requests efficiently. The comparison of the proposed infrastructure against the ground truth, for all field tests in open areas, showed that the infrastructure achieves the horizontal positioning accuracy better than 2 m. The improvement in accuracy can reach more than 50% for the test in the afternoon. The infrastructure brings benefits to applications that require more accuracy without requiring any hardware modifications.
Application of UAV in Topographic Modelling and Structural Geological Mapping of Quarries and Their Surroundings—Delineation of Fault-Bordered Raw Material Reserves
Authors: Török Ákos , Bögöly Gyula , Somogyi Árpád , Lovas Tamás
Published: January 2020

A 3D surface model of an active limestone quarry and a vegetation-covered plateau was created using unmanned aerial vehicle (UAV) technique in combination with terrestrial laser scanning (TLS). The aim of the research was to identify major fault zones that dissect the inaccessible quarry faces and to prepare a model that shows the location of these fault zones at the entire study area. An additional purpose was to calculate reserves of the four identified lithological units. It was only possible to measure faults at the lowermost two meters of the quarry faces. At the upper parts of the quarry and on the vegetation-covered plateau where no field geological information was available, remote sensing was used. Former logs of core drillings were obtained for the modelling of the spatial distribution of four lithological units representing cover beds and various quality of limestone reserves. With the comparison of core data, field measurements and remote sensing, it was possible to depict major faults. Waste material volumes and limestone reserves were calculated for five blocks that are surrounded by these faults. The paper demonstrates that, with remote sensing and with localised control field measurements, it is possible: (a) to provide all geometric data of faults and (b) to create a 3D model with fault planes even at no exposure or at hardly accessible areas. The surface model with detected faults serves as a basis for calculating geological reserves.
Autonomous Exploration and Map Construction of a Mobile Robot Based on the TGHM Algorithm
Authors: Liu Shuang , Li Shenghao , Pang Luchao , Hu Jiahao , Chen Haoyao , Zhang Xiancheng
Published: January 2020

An a priori map is often unavailable for a mobile robot in a new environment. In a large-scale environment, relying on manual guidance to construct an environment map will result in a huge workload. Hence, an autonomous exploration algorithm is necessary for the mobile robot to complete the exploration actively. This study proposes an autonomous exploration and mapping method based on an incremental caching topology–grid hybrid map (TGHM). Such an algorithm can accomplish the exploration task with high efficiency and high coverage of the established map. The TGHM is a fusion of a topology map, containing the information gain and motion cost for exploration, and a grid map, representing the established map for navigation and localization. At the beginning of one exploration round, the method of candidate target point generation based on geometry rules are applied to extract the candidates quickly. Then, a TGHM is established, and the information gain is evaluated for each candidate topology node on it. Finally, the node with the best evaluation value is selected as the next target point and the topology map is updated after each motion towards it as the end of this round. Simulations and experiments were performed to benchmark the proposed algorithm in robot autonomous exploration and map construction.
Current Measurement Transducer Based on Current-To-Voltage-To-Frequency Converting Ring Oscillator with Cascade Bias Circuit
Authors: Park Jongha , Park Jung-Hyun , Jung Seong-Ook
Published: January 2020

We propose a ring oscillator (RO) based current-to-voltage-to-frequency (I–V–F) converting current transducer with a cascade bias circuit. The I–V–F converting scheme guarantees highly stable biasing against RO, with a rail-to-rail output operation. This device was fabricated using National NanoFab Center (NNFC) 180 nm complementary metal-oxide-semiconductor (CMOS) technology, which achieves a current resolution of 1 nA in a measurement range up to 200 nA. A noise floor of 11.8 pA/√Hz, maximum differential nonlinearity (DNL) of 0.15 in 1 nA steps, and rail-to-rail output with a 1.8 V power supply is achieved. The proposed transducer can be effectively applied to bio-sensing devices requiring a compact area and low power consumption with a low current output. The fabricated structure can be applied to monolithic-three-dimensional integration with a bio-sensing device.
An Investigation of Various Machine and Deep Learning Techniques Applied in Automatic Fear Level Detection and Acrophobia Virtual Therapy
Authors: Bălan Oana , Moise Gabriela , Moldoveanu Alin , Leordeanu Marius , Moldoveanu Florica
Published: January 2020

In this paper, we investigate various machine learning classifiers used in our Virtual Reality (VR) system for treating acrophobia. The system automatically estimates fear level based on multimodal sensory data and a self-reported emotion assessment. There are two modalities of expressing fear ratings: the 2-choice scale, where 0 represents relaxation and 1 stands for fear; and the 4-choice scale, with the following correspondence: 0—relaxation, 1—low fear, 2—medium fear and 3—high fear. A set of features was extracted from the sensory signals using various metrics that quantify brain (electroencephalogram—EEG) and physiological linear and non-linear dynamics (Heart Rate—HR and Galvanic Skin Response—GSR). The novelty consists in the automatic adaptation of exposure scenario according to the subject’s affective state. We acquired data from acrophobic subjects who had undergone an in vivo pre-therapy exposure session, followed by a Virtual Reality therapy and an in vivo evaluation procedure. Various machine and deep learning classifiers were implemented and tested, with and without feature selection, in both a user-dependent and user-independent fashion. The results showed a very high cross-validation accuracy on the training set and good test accuracies, ranging from 42.5% to 89.5%. The most important features of fear level classification were GSR, HR and the values of the EEG in the beta frequency range. For determining the next exposure scenario, a dominant role was played by the target fear level, a parameter computed by taking into account the patient’s estimated fear level.
Sensor-Based Daily Physical Activity: Towards Prediction of the Level of Concern about Falling in Peripheral Neuropathy
Authors: Kang Gu Eon , Najafi Bijan
Published: January 2020

Concern about falling is prevalent and increases the risk of falling in people with peripheral neuropathy (PN). However, the assessment of concern about falling relies on self-report surveys, and thus continuous monitoring has not been possible. We investigated the influence of concern about falling on sensor-based daily physical activity among people with PN. Forty-nine people with PN and various levels of concern about falling participated in this study. Physical activity outcomes were measured over a period of 48 hours using a validated chest-worn sensor. The level of concern about falling was assessed using the falls efficacy scale-international (FES-I). The low concern group spent approximately 80 min more in walking and approximately 100 min less in sitting/lying compared to the high concern group. In addition, the low concern group had approximately 50% more walking bouts and step counts compared to the high concern group. Across all participants, the duration of walking bouts and total step counts was significantly correlated with FES-I scores. The duration of walking bouts and total step counts may serve as eHealth targets and strategies for fall risk assessment among people with PN.
A Green Triboelectric Nano-Generator Composite of Degradable Cellulose, Piezoelectric Polymers of PVDF/PA6, and Nanoparticles of BaTiO3
Authors: Sun Zhuangzhi , Yang Lu , Liu Sicheng , Zhao Jintao , Hu Zhiwei , Song Wenlong
Published: January 2020

In this paper, a kind of green triboelectric nano-generator based on natural degradable cellulose is proposed. Different kinds of regenerated cellulose composite layers are prepared by a blending doping method, and then assembled with poly(tetrafluoroethylene) (PTFE) thin films to form tribioelectric nanogenerator (TENG). The results show that the open circuit output voltage and the short circuit output current using a pure cellulose membrane is 7.925 V and 1.095 μA. After adding a certain amount of polyamide (PA6)/polyvinylidene fluoride (PVDF)/barium titanate (BaTiO3), the open circuit output voltage peak and the peak short circuit output current increases by 254.43% (to 20.155 V) and 548.04% (to 6.001 μA). The surface morphology, elemental composition and functional group of different cellulose layers are characterized by Scanning Electronic Microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and tested by the electrochemical analyze. Moreover, after multiple assembly and rectification processing, the electrical output performance shows that the peak value of open-circuit output voltage and the peak value of short circuit output current increases by 132.06% and 116.13%. Within 500 s of the charge-discharge test, the single peak charge reached 3.114 V, and the two peak charges reached 3.840 V. The results demonstrate that the nano-generator based on cellulose showed good stability and reliability, and the application and development of natural biomaterials represented by cellulose are greatly promoted in miniature electronic sensing area.