bluuebunny/crossref_metadata_2025 huggingface dataset:
New Method for Optimization of Polymer Powder Plasma Treatment for Composite Materials
Authors: Weberová Zuzana , Šourková Hana , Antoň Jakub , Vacková Taťána , Špatenka Petr
Published: March 2021

This paper describes a newly developed testing method for determination of the adhesivity of a film sintered from thermoplastic powder. This method is based on the modified EN 15337 standard. Application of this method enables an effective development of thermoplastic composites with enhanced adhesion between reinforcement and matrix and/or high-quality joints between plastics and dissimilar materials. The proposed method was successfully tested on a series of polyethylene powders treated in the oxygen atmosphere for 0–1200 s. Adhesion to metal and glass substrates in dependence on treatment conditions is described along with powder wettability and X-ray photoelectron spectroscopy analysis. The results show an increase in adhesion to metal by 580% and to glass by 1670% for the longest treatment time, compared to a nontreated powder. Sintering of treated powders revealed a strong influence of treatment time on the melting process. The XPS analysis confirmed the formation of new oxygen groups (C–O, C=O, O–C=O). The method reveals a specific behavior of powders based on treatment conditions, which is crucial for the optimization of plasma treatment for the improved adhesion, applicability of polymer powders, and a development of composite materials.
Modelling Stretch Blow Moulding of Poly (l-lactic acid) for the Manufacture of Bioresorbable Vascular Scaffold
Authors: Wei Huidong , Yan Shiyong , Menary Gary
Published: March 2021

Stretch blow moulding (SBM) has been employed to manufacture bioresorbable vascular scaffold (BVS) from poly (l-lactic acid) (PLLA), whilst an experience-based method is used to develop the suitable processing conditions by trial-and-error. FEA modelling can be used to predict the forming process by the scientific understanding on the mechanical behaviour of PLLA materials above the glass transition temperature (Tg). The applicability of a constitutive model, the ‘glass-rubber’ (GR) model with material parameters from biaxial stretch was examined on PLLA sheets replicating the biaxial strain history of PLLA tubes during stretch blow moulding. The different stress–strain relationship of tubes and sheets under equivalent deformation suggested the need of re-calibration of the GR model for tubes. A FEA model was developed for PLLA tubes under different operation conditions, incorporating a virtual cap and rod to capture the suppression of axial stretch. The reliability of the FEA modelling on tube blowing was validated by comparing the shape evolution, strain history and stress–strain relationship from modelling to the results from the free stretch blow test.
Tough Hydrogels Based on Maleic Anhydride, Bulk Properties Study and Microfiber Formation by Electrospinning
Authors: Bettahar Faiza , Bekkar Fadila , Pérez-Álvarez Leyre , Ferahi Mohammed Issam , Meghabar Rachid , Vilas-Vilela José Luis , Ruiz-Rubio Leire
Published: March 2021

Hydrogels present a great number of advantages, such as their swelling capacity or their capability to mimic tissues, which make them very interesting biomaterials. However, one of their main disadvantages is their lack of good mechanical properties, which could limit some of their applications. Several strategies have been carried out to develop hydrogels with enhanced mechanical properties, but many of the suggested synthetic pathways to improve this property are expensive and time consuming. In this work, we studied an easy synthetic path to produce tough hydrogels based on different maleic anhydride copolymers crosslinked with polyethylenglycol. The effect of the comonomers in the mechanical properties has been studied, their excellent mechanical properties, good swelling behavior and thermal stability being remarkable. In addition, in order to evaluate their possible applications as scaffolds or in wound healing applications, microsized fibers have been fabricated by electrospinning.
Effects of Micro-Tab on the Lift Enhancement of Airfoil S-809 with Trailing-Edge Flap
Authors: Ye Jianjun , Salem Shehab , Wang Juan , Wang Yiwen , Du Zonggang , Wang Wei
Published: March 2021

Recently, the Trailing-Edge Flap with Micro-Tab (TEF with Micro-Tab) has been exploited to enhance the performance of wind turbine blades. Moreover, it can also be used to generate more lift and delay the onset of stall. This study focused mostly on the use of TEF with Micro-Tab in wind turbine blades using NREL’s S-809 as a model airfoil. In particular, the benefits generated by TEF with Micro-Tab may be of great interest in the design of wind turbine blades. In this paper, an attempt was made to evaluate the influence of TEF with Micro-Tab on the performance of NREL’s S-809 airfoils. Firstly, a computational fluid dynamics (CFD) model for the airfoil NREL’s S-809 was established, and validated by comparison with previous studies and wind tunnel experimental data. Secondly, the effects of the flap position (H) and deflection angle (αF) on the flow behaviors were investigated. As a result, the effect of TEF on air-flow behavior was demonstrated by augmenting the pressure coefficient at the lower surface of the airfoil at flap position 80% chord length (C) and αF = 7.5°. Thirdly, the influence of TEF with Micro-Tab on the flow behaviors of the airfoil NREL’s S-809 was studied and discussed. Different Micro-Tab positions and constant TEF were examined. Finally, the effects of TEF with Micro-Tab on the aerodynamic characteristics of the S-809 with TEF were compared. The results showed that an increase in the maximum lift coefficient by 25% and a delay in the air-flow stall were accomplished due to opposite sign vortices, which was better than the standard airfoil and S-809 with TEF. Therefore, it was deduced that the benefits of TEF with Micro-Tab were apparent, especially at the lower surface of the airfoil. This particularly suggests that the developed model could be used as a new trend to modify the designs of wind turbine blades.
Applying Lean Six Sigma Methodology to a Pharmaceutical Manufacturing Facility: A Case Study
Authors: Byrne Brian , McDermott Olivia , Noonan John
Published: March 2021

This research examines a case study on the implementation of an effective approach to advanced Lean Six Sigma problem-solving within a pharmaceutical manufacturing site which manufactures acetaminophen (paracetamol containing pain relief) tablets. Though this study was completed in a single manufacturing company, the implementation of this study delivers important application and results that can be deployed in other such manufacturing companies. The manufacturing site faced backlogs in customer orders due to increased demand. Increased demand is due to brand popularity and recognition, product efficacy and a COVID 19 pandemic that intensified the demand for pain relief tablets in an already very busy site. With increased demand, to ensure timely deliveries, customer satisfaction and minimize delays, sources of site productivity losses and wastes needed to be analyzed and reduced or eliminated. Manufacturing Packaging line downtime was identified as one area of concern. The goal of the research was to introduce a problem-solving technique to reduce downtime within a manufacturing site without affecting the production required to fulfil customer demand while increasing product quality. The research utilized an integrated LSS methodology which identifies, stratifies and effectively eliminates non-value adding (waste) activities, by following a 7-step customized problem-solving methodology which resulted in complete elimination of the issue under investigation and savings of just under half a million dollars. The learnings are being deployed and leveraged worldwide across the pharmaceutical organizations parent site and sister sites. The presented results demonstrated that Lean Six Sigma methodology and tools are effective for accurate root causing of problems and enablers of implementation of continuous improvement.
Introduction to Special Issue: Exploring Ritual Fields Today
Authors: Hoondert Martin , Post Paul
Published: March 2021

Due to the COVID-19 crisis and the related restrictive measures, many of our (daily) rituals have changed [...]
Believers, Attractiveness and Values
Authors: Khalfaoui Andrea , Burgués Ana , Duque Elena , Munté Ariadna
Published: March 2021

Societies are undergoing an intensive process of transformation, and the role that religion plays in guiding such rapid changes remains underexplored. In recent decades, postmodern discourse has hindered the attractiveness of involvement in religious affairs and reading sacred books, highlighting how “uncool” and useless these practices are in responding to current daily life challenges. Decades of research have evidenced the positive impact of reading the most precious universal literary creations. Since sacred books are considered universal texts, this study explores the potential of dialogic interreligious gatherings (DIGs) focused on sacred books to enhance the attractiveness of key values such as love, kindness, humility, and generosity. These spaces are grounded in strong principles that guarantee the freedom of participants. This context opens up a possibility of discussing sacred books in a dialogic and egalitarian space where everyone’s voice is heard. In this context, especially in times where freedom is jeopardized in many spheres, believers from different faiths and nonbelievers engage in dialogues and relate sacred book content to their personal experiences and current social challenges. The communicative analysis conducted shows that DIGs drive the attractiveness of fundamental values present in sacred books, creating possibilities to enhance their effects in spurring personal and social change.
Saints on Stage: Popular Hagiography in Post-WWII Italy
Authors: Cavallaro Daniela
Published: March 2021

This article brings to light several examples of the hagiographic plays staged in Italy during the 1950s and early 1960s in parishes, schools, and oratories. The article begins with a brief introduction to the continued tradition of staging the lives of the saints for educational purposes, which focuses on the origins, aims, and main characteristics of theatre for young people of the Salesians, the order founded by Don Bosco in 1859. Next, it offers a brief panorama of the pervasive presence of the lives of the saints in post-WWII Italy. The main discussion of the article concerns the hagiographic plays created for the Salesian educational stages in the years between 1950 and 1965, especially those regarding the lives of young saints Agnes and Domenico Savio. The article concludes that the Salesian plays on the lives of the saints, far from constituting a mere exercise in hagiography, had a definite educational goal which applied to both performers and audiences in the specific times of Italy’s reconstruction and the cold war.
Building Extraction and Number Statistics in WUI Areas Based on UNet Structure and Ensemble Learning
Authors: Chen De-Yue , Peng Ling , Li Wei-Chao , Wang Yin-Da
Published: March 2021

Following the advancement and progression of urbanization, management problems of the wildland–urban interface (WUI) have become increasingly serious. WUI regional governance issues involve many factors including climate, humanities, etc., and have attracted attention and research from all walks of life. Building research plays a vital part in the WUI area. Building location is closely related with the planning and management of the WUI area, and the number of buildings is related to the rescue arrangement. There are two major methods to obtain this building information: one is to obtain them from relevant agencies, which is slow and lacks timeliness, while the other approach is to extract them from high-resolution remote sensing images, which is relatively inexpensive and offers improved timeliness. Inspired by the recent successful application of deep learning, in this paper, we propose a method for extracting building information from high-resolution remote sensing images based on deep learning, which is combined with ensemble learning to extract the building location. Further, we use the idea of image anomaly detection to estimate the number of buildings. After verification on two datasets, we obtain superior semantic segmentation results and achieve better building contour extraction and number estimation.
Spatial Correlation between Ecosystem Services and Human Disturbances: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area, China
Authors: He Yeyu , Kuang Yaoqiu , Zhao Yalan , Ruan Zhu
Published: March 2021

Exploring the spatial relationship between ecosystem services (ES) and human disturbance intensity (HDI) is vital for maintaining regional ecological security. This study aims to explore the spatial correlation between ES and HDI in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) and provide meaningful implications for coastal ecological planning. Multi-source remote sensing data, remote sensing software, and geographic information system provided initial data and technical support for this research. We integrated four human pressures (population, land-use, traffic, and energy) to map the HDI in the GBA for 2018. Coastal ES were comprehensively considered and spatially visualized by extracting the ES sources. The geographically weighted Pearson correlation coefficient and bivariate local Moran were used to quantitatively reflect and spatially visualize the detailed relationship between ES and HDI. Our study presents several key findings. First, the central and southern parts of the GBA are under strong HDI, dominated by a dense population and intense land utilization. Second, the kernel density of ES sources can better manifest the spatial distribution of ES objectively in comparison to the traditional model calculation. Provisioning services mainly originate from the periphery of the central cities; cultural services are highly concentrated in the heartland of the GBA; and regulating and maintenance services have high density in the outermost regions. Third, ES and HDI have a significant correlation, and the geographically weighted Pearson correlation coefficient and local indicator of spatial association cluster maps illustrate that unlike the global findings, the local correlation is spatially nonstationary as the local scale is affected by specific human activities, natural conditions, regional development, and other local factors. Four, high-capacity regions of ES provision are mainly under high HDI. Areas with high provisioning service values are mainly affected by population and traffic pressure, whereas regulating and maintenance services and cultural services are mainly dominated by high-density populations. Regulating and maintenance services are also affected by land-use pressure. We determine that human disturbance has negative spillover effects on ES, which should be the focus in regional ecological planning.
Effects of Drought on Vegetation Productivity of Farmland Ecosystems in the Drylands of Northern China
Authors: Zhu Xiufang , Liu Ying , Xu Kun , Pan Yaozhong
Published: March 2021

Previous research on the effects of drought on vegetation productivity seldom distinguished the different responses of vegetation ecosystems to drought under different management practices and different land use systems. Studies investigating whether irrigation can buffer the negative impacts of drought on vegetation usually used discontinuous yield data in distribution. In this study, the trends in drought and vegetation productivity in farmlands in the drylands of northern China (DNC) from 2000 to 2018 were studied using the self-calibrated Palmer drought severity index (scPDSI) and enhanced vegetation index (EVI). The differences in the impact of drought on vegetation productivity in irrigated farmland, rainfed farmland, and natural vegetation areas were quantified. The results showed that the growing season scPDSI and EVI showed an increasing trend from 2000 to 2018. Significant correlations between drought anomalies and EVI anomalies were found in both arid drylands and semi-arid drylands. In addition, irrigation mitigated 59.66% of the negative impact caused by drought on irrigated farmland EVI in the growing season. The impact of drought on irrigated farmland EVI in the growing season was 19.98% lower than that on natural vegetation EVI. The impact of drought on natural vegetation EVI was 49.59% lower than that on rainfed farmland EVI. The results of this study refine the vegetation response to drought under different land management practices and land use patterns.
Digital Soil Mapping Using Multispectral Modeling with Landsat Time Series Cloud Computing Based
Authors: Novais Jean J. , Lacerda Marilusa P. C. , Sano Edson E. , Demattê José A. M. , Oliveira Manuel P.
Published: March 2021

Geotechnologies allow natural resources to be surveyed more quickly and cheaply than traditional methods. This paper aimed to produce a digital soil map (DSM) based on Landsat time series data. The study area, located in the eastern part of the Brazilian Federal District (Rio Preto hydrographic basin), comprises a representative basin of the Central Brazil plateau in terms of pedodiversity. A spectral library was produced based on the soil spectroscopy (from the visible to shortwave infrared spectral range) of 42 soil samples from 0–15 cm depth using the Fieldspec Pro equipment in a laboratory. Pearson’s correlation and principal component analysis of the soil attributes revealed that the dataset could be grouped based on the texture content. Hierarchical clustering analysis allowed for the extraction of 13 reference spectra. We interpreted the spectra morphologically and resampled them to the Landsat 5 Thematic Mapper satellite bands. Afterward, we elaborated a synthetic soil/rock image (SySI) and a soil frequency image (number of times the bare soil was captured) from the Landsat time series (1984–2020) in the Google Earth Engine platform. Multiple Endmember Spectral Mixture Analysis (MESMA) was used to model the SySI, using the endmembers as the input and generating a DSM, which was validated by the Kappa index and the confusion matrix. MESMA successfully modeled 9 of the 13 endmembers: Dystric Rhodic Ferralsol (clayic); Dystric Rhodic Ferralsol (very clayic); Dystric Haplic Ferralsol (loam-clayic); Dystric Haplic Ferralsol (clayic); Dystric Petric Plinthosol (clayic); Dystric Petric Plinthosol (very clayic); Dystric Regosol (clayic); Dystric Regosol (very clayic); and Dystric, Haplic Cambisol (clayic). The root mean squared error (RMSE) varied from 0 to 1.3%. The accuracy of DSM achieved a Kappa index of 0.74, describing the methodology’s effectiveness to differentiate the studied soils.
A New Method Based on a Multilayer Perceptron Network to Determine In-Orbit Satellite Attitude for Spacecrafts without Active ADCS Like UVSQ-SAT
Authors: Finance Adrien , Meftah Mustapha , Dufour Christophe , Boutéraon Thomas , Bekki Slimane , Hauchecorne Alain , Keckhut Philippe , Sarkissian Alain , Damé Luc , Mangin Antoine
Published: March 2021

Climate change is largely determined by the radiation budget imbalance at the Top Of the Atmosphere (TOA), which is generated by the increasing concentrations of greenhouse gases (GHGs). As a result, the Earth Energy Imbalance (EEI) is considered as an Essential Climate Variable (ECV) that has to be monitored continuously from space. However, accurate TOA radiation measurements remain very challenging. Ideally, EEI monitoring should be performed with a constellation of satellites in order to resolve as much as possible spatio-temporal fluctuations in EEI which contain important information on the underlying mechanisms driving climate change. The monitoring of EEI and its components (incoming solar, reflected solar, and terrestrial infrared fluxes) is the main objective of the UVSQ-SAT pathfinder nanosatellite, the first of its kind in the construction of a future constellation. UVSQ-SAT does not have an active determination system of its orientation with respect to the Sun and the Earth (i.e., the so-called attitude), a prerequisite in the calculation of EEI from the satellite radiation measurements. We present a new effective method to determine the UVSQ-SAT’s in-orbit attitude using its housekeeping and scientific sensors measurements and a well-established deep learning algorithm. One of the goals is to estimate the satellite attitude with a sufficient accuracy for retrieving the radiative fluxes (incoming solar, reflected solar, terrestrial infrared) on each face of the satellite with an uncertainty of less than ±5 Wm−2 (1σ). This new method can be extended to any other satellites with no active attitude determination or control system. To test the accuracy of the method, a ground-based calibration experiment with different attitudes is performed using the Sun as the radiative flux reference. Based on the deep learning estimation of the satellite ground-based attitude, the uncertainty on the solar flux retrieval is about ±16 Wm−2 (1σ). The quality of the retrieval is mainly limited by test conditions and the number of data samples used in training the deep learning system during the ground-based calibration. The expected increase in the number of training data samples will drastically decrease the uncertainty in the retrieved radiative fluxes. A very similar algorithm will be implemented and used in-orbit for UVSQ-SAT.
Spatial Downscaling of Land Surface Temperature Based on a Multi-Factor Geographically Weighted Machine Learning Model
Authors: Xu Saiping , Zhao Qianjun , Yin Kai , He Guojin , Zhang Zhaoming , Wang Guizhou , Wen Meiping , Zhang Ning
Published: March 2021

Land surface temperature (LST) is a critical parameter of surface energy fluxes and has become the focus of numerous studies. LST downscaling is an effective technique for supplementing the limitations of the coarse-resolution LST data. However, the relationship between LST and other land surface parameters tends to be nonlinear and spatially nonstationary, due to spatial heterogeneity. Nonlinearity and spatial nonstationarity have not been considered simultaneously in previous studies. To address this issue, we propose a multi-factor geographically weighted machine learning (MFGWML) algorithm. MFGWML utilizes three excellent machine learning (ML) algorithms, namely extreme gradient boosting (XGBoost), multivariate adaptive regression splines (MARS), and Bayesian ridge regression (BRR), as base learners to capture the nonlinear relationships. MFGWML uses geographically weighted regression (GWR), which allows for spatial nonstationarity, to fuse the three base learners’ predictions. This paper downscales the 30 m LST data retrieved from Landsat 8 images to 10 m LST data mainly based on Sentinel-2A images. The results show that MFGWML outperforms two classic algorithms, namely thermal image sharpening (TsHARP) and the high-resolution urban thermal sharpener (HUTS). We conclude that MFGWML combines the advantages of multiple regression, ML, and GWR, to capture the local heterogeneity and obtain reliable and robust downscaled LST data.
Forest Fuel Loads Estimation from Landsat ETM+ and ALOS PALSAR Data
Authors: Li Yanxi , Quan Xingwen , Liao Zhanmang , He Binbin
Published: March 2021

Fuel load is the key factor driving fire ignition, spread and intensity. The current literature reports the light detection and ranging (LiDAR), optical and airborne synthetic aperture radar (SAR) data for fuel load estimation, but the optical and SAR data are generally individually explored. Optical and SAR data are expected to be sensitive to different types of fuel loads because of their different imaging mechanisms. Optical data mainly captures the characteristics of leaf and forest canopy, while the latter is more sensitive to forest vertical structures due to its strong penetrability. This study aims to explore the performance of Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) data as well as their combination on estimating three different types of fuel load—stem fuel load (SFL), branch fuel load (BFL) and foliage fuel load (FFL). We first analyzed the correlation between the three types of fuel load and optical and SAR data. Then, the partial least squares regression (PLSR) was used to build the fuel load estimation models based on the fuel load measurements from Vindeln, Sweden, and variables derived from optical and SAR data. Based on the leave-one-out cross-validation (LOOCV) method, results show that L-band SAR data performed well on all three types of fuel load (R2 = 0.72, 0.70, 0.72). The optical data performed best for FFL estimation (R2 = 0.66), followed by BFL (R2 = 0.56) and SFL (R2 = 0.37). Further improvements were found for the SFL, BFL and FFL estimation when integrating optical and SAR data (R2 = 0.76, 0.81, 0.82), highlighting the importance of data selection and combination for fuel load estimation.
Increasing Spatio-Temporal Resolution for Monitoring Alpine Solifluction Using Terrestrial Laser Scanners and 3D Vector Fields
Authors: Holst Christoph , Janßen Jannik , Schmitz Berit , Blome Martin , Dercks Malte , Schoch-Baumann Anna , Blöthe Jan , Schrott Lothar , Kuhlmann Heiner , Medic Tomislav
Published: March 2021

This article investigates the usage of terrestrial laser scanner (TLS) point clouds for monitoring the gradual movements of soil masses due to freeze–thaw activity and water saturation, commonly referred to as solifluction. Solifluction is a geomorphic process which is characteristic for hillslopes in (high-)mountain areas, primarily alpine periglacial areas and the arctic. The movement can reach millimetre-to-centimetre per year velocities, remaining well below the typical displacement mangitudes of other frequently monitored natural objects, such as landslides and glaciers. Hence, a better understanding of solifluction processes requires increased spatial and temporal resolution with relatively high measurement accuracy. To that end, we developed a workflow for TLS point cloud processing, providing a 3D vector field that can capture soil mass displacement due to solifluction with high fidelity. This is based on the common image-processing techniques of feature detection and tracking. The developed workflow is tested on a study area placed in Hohe Tauern range of the Austrian Alps with a prominent assemblage of solifluction lobes. The derived displacements were compared with the established geomonitoring approach with total station and signalized markers and point cloud deformation monitoring approaches. The comparison indicated that the achieved results were in the same accuracy range as the established methods, with an advantage of notably higher spatial resolution. This improvement allowed for new insights considering the solifluction processes.
Application of Support Vector Regression and Metaheuristic Optimization Algorithms for Groundwater Potential Mapping in Gangneung-si, South Korea
Authors: Fadhillah Muhammad Fulki , Lee Saro , Lee Chang-Wook , Park Yu-Chul
Published: March 2021

The availability of groundwater is of concern. The demand for groundwater in Korea increased by more than 100% during the period 1994–2014. This problem will increase with population growth. Thus, a reliable groundwater analysis model for regional scale studies is needed. This study used the geographical information system (GIS) data and machine learning to map groundwater potential in Gangneung-si, South Korea. A spatial correlation performed using the frequency ratio was applied to determine the relationships between groundwater productivity (transmissivity data from 285 wells) and various factors. This study used four topography factors, four hydrological factors, and three geological factors, along with the normalized difference wetness index and land use and soil type. Support vector regression (SVR) and metaheuristic optimization algorithms—namely, grey wolf optimization (GWO), and particle swarm optimization (PSO), were used in the construction of the groundwater potential map. Model validation based on the area under the receiver operating curve (AUC) was used to determine model accuracy. The AUC values of groundwater potential maps made using the SVR, SVR_GWO, and SVR_PSO algorithms were 0.803, 0.878, and 0.814, respectively. Thus, the application of optimization algorithms increased model accuracy compared to the standard SVR algorithm. The findings of this study improve our understanding of groundwater potential in a given area and could be useful for policymakers aiming to manage water resources in the future.
Similarity Index Based Approach for Identifying Similar Grotto Statues to Support Virtual Restoration
Authors: Hua Wei , Hou Miaole , Qiao Yunfei , Zhao Xuesheng , Xu Shishuo , Li Songnian
Published: March 2021

Grottoes, with caves and statues, are an important part of immovable heritage. Statues in a particular grotto setting are often similar in geometric form and artistic style, and identifying the similarity between these statues can help provide important references for value recognition, condition assessment, repair, and the virtual restoration of statues. Traditionally, such reference information mainly depended on expert empirical judgment, which is highly subjective, lacks quantitative analysis, and cannot provide effective scientific support for the virtual restoration of grotto statues. This paper presents a similarity index based approach for identifying similarities between grotto statues by studying 11 small Buddhist statues carved on the 18th cave in the Yungang Grottoes, located in Datong, China. The similarity index is determined according to the hash values calculated based on the pHash method using the orthophoto images of Buddhist statues to identify similar statues. Similar feature points between the identified statues are then matched using the Scale Invariant Feature Transform (SIFT) operator to support the repair and reconstruction of damaged statues. The experimental results show that the variation of similarity index values confirms the visual inspection of the statues’ appearance in the orthophotos. The additional analysis of three-dimensional (3D) point clouds also confirms that the similarity index based approach is accurate in the initial screening of similar grotto statues.
Evaluating the Vertical Accuracy of DEM Generated from ZiYuan-3 Stereo Images in Understanding the Tectonic Morphology of the Qianhe Basin, China
Authors: Liu Zhiheng , Han Ling , Yang Zhaohui , Cao Hongye , Guo Fengcheng , Guo Jianhua , Ji Yiqi
Published: March 2021

Currently available high-resolution digital elevation model (DEM) is not particularly useful to geologists for understanding the long-term changes in fluvial landforms induced by tectonic uplift, although DEMs that are generated from satellite stereo images such as the ZiYuan-3 (ZY3) satellite include characteristics with significant coverage and rapid acquisition. Since an ongoing analysis of fluvial systems is lacking, the ZY3 DEM was generated from block adjustment to describe the mountainous area of the Qianhe Basin that have been induced by tectonic uplift. Moreover, we evaluated the overall elevation difference in ZY3 DEM, Shuttle Radar Topography Mission (1″ × 1″) (SRTM1), and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) by using the Ice Cloud and Land Elevation Satellite/Geoscience Laser Altimeter (ICESat/GLAH14) point cloud and a DEM of 1:50,000 scale. The values of the root mean square error (RMSE) of the elevation difference for ZY3 DEM were 9.31 and 9.71 m, respectively, and are in good agreement with SRTM1. The river long profiles and terrace heights were also extracted to compare the differences in channel steepness and the incision rates with SRTM1 and ASTER GDEM. Our results prove that ZY3 DEM would be a good alternative to SRTM1 in achieving the 1:50,000 scale for DEM products in China, while ASTER GDEM is unsuitable for extracting river longitudinal profiles. In addition, the northern and southern river incision rates were estimated using the ages and heights of river terraces, demonstrating a range from 0.12–0.45 to 0.10–0.33 m/kyr, respectively. Collectively, these findings suggest that ZY3 DEM is capable of estimating tectonic geomorphological features and has the potential for analyzing the continuous evolutionary response of a landscape to changes in climate and tectonics.
Analysis and Validation of a Hybrid Forward-Looking Down-Looking Ground Penetrating Radar Architecture
Authors: García-Fernández María , Álvarez-Narciandi Guillermo , Álvarez López Yuri , Las-Heras Andrés Fernando
Published: March 2021

Ground Penetrating Radar (GPR) has proved to be a successful technique for the detection of landmines and Improvised Explosive Devices (IEDs) buried in the ground. In the last years, novel architectures for safe and fast detection, such as those based on GPR systems onboard Unmanned Aerial Vehicles (UAVs), have been proposed. Furthermore, improvements in GPR hardware and signal processing techniques have resulted in a more efficient detection. This contribution presents an experimental validation of a hybrid Forward-Looking–Down-Looking GPR architecture. The main goal of this architecture is to combine advantages of both GPR architectures: reduction of clutter coming from the ground surface in the case of Forward-Looking GPR (FLGPR), and greater dynamic range in the case of Down-Looking GPR (DLGPR). Compact radar modules working in the lower SHF frequency band have been used for the validation of the hybrid architecture, which involved realistic targets.
Multiple RFI Sources Location Method Combining Two-Dimensional ESPRIT DOA Estimation and Particle Swarm Optimization for Spaceborne SAR
Authors: Yu Junfei , Li Jingwen , Sun Bing , Jiang Yuming , Xu Liying
Published: March 2021

Synthetic aperture radar (SAR) systems are susceptible to radio frequency interference (RFI). The existence of RFI will cause serious degradation of SAR image quality and a huge risk of target misjudgment, which makes the research on RFI suppression methods receive widespread attention. Since the location of the RFI source is one of the most vital information for achieving RFI spatial filtering, this paper presents a novel location method of multiple independent RFI sources based on direction-of-arrival (DOA) estimation and the non-convex optimization algorithm. It deploys an L-shaped multi-channel array on the SAR system to receive echo signals, and utilizes the two-dimensional estimating signal parameter via rotational invariance techniques (2D-ESPRIT) algorithm to estimate the positional relationship between the RFI source and the SAR system, ultimately combines the DOA estimation results of multiple azimuth time to calculate the geographic location of RFI sources through the particle swarm optimization (PSO) algorithm. Results on simulation experiments prove the effectiveness of the proposed method.
A Comprehensive Evaluation of Latest GPM IMERG V06 Early, Late and Final Precipitation Products across China
Authors: Yu Linfei , Leng Guoyong , Python Andre , Peng Jian
Published: March 2021

This study evaluated the performance of the early, late and final runs of IMERG version 06 precipitation products at various spatial and temporal scales in China from 2008 to 2017, against observations from 696 rain gauges. The results suggest that the three IMERG products can well reproduce the spatial patterns of precipitation, but exhibit a gradual decrease in the accuracy from the southeast to the northwest of China. Overall, the three runs show better performances in the eastern humid basins than the western arid basins. Compared to the early and late runs, the final run shows an improvement in the performance of precipitation estimation in terms of correlation coefficient, Kling–Gupta Efficiency and root mean square error at both daily and monthly scales. The three runs show similar daily precipitation detection capability over China. The biases of the three runs show a significantly positive (p < 0.01) correlation with elevation, with higher accuracy observed with an increase in elevation. However, the categorical metrics exhibit low levels of dependency on elevation, except for the probability of detection. Over China and major river basins, the three products underestimate the frequency of no/tiny rain events (P < 0.1 mm/day) but overestimate the frequency of light rain events (0.1 ≤ P < 10 mm/day). The three products converge with ground-based observation with regard to the frequency of rainstorm (P ≥ 50 mm/day) in the southern part of China. The revealed uncertainties associated with the IMERG products suggests that sustaining efforts are needed to improve their retrieval algorithms in the future.
The Effect of Inspiratory Muscle Warm-Up on VO2 Kinetics during Submaximal Rowing
Authors: Arend Mati , Kivastik Jana , Talts Jaak , Mäestu Jarek
Published: March 2021

The aim of the study was to investigate the effect of an inspiratory muscle warm-up on the VO2 kinetics during submaximal intensity ergometer rowing. Ten competitive male rowers (age 23.1 ± 3.8 years; height 188.1 ± 6.3 cm; body mass 85.6 ± 6.6 kg) took part in this investigation. A submaximal constant intensity (90% PVO2max) rowing test to volitional exhaustion was carried out twice with the standard rowing warm-up (Test 1) and with the standard rowing warm-up with additional specific inspiratory muscle warm-up of two sets of 30 repetitions at 40% maximal inspiratory pressure (Test 2). We found a significant correlation between time constant (τ1) and the VO2 value at 400 s in Test 1 (r = 0.78; p < 0.05); however, no correlation was found between those parameters in Test 2. In addition, we found a positive association between VO2max from the incremental rowing test and τ1 from Test 1 (r = 0.71; p < 0.05), whereas VO2 did not correlate with τ1 from Test 2. Adding inspiratory muscle warm-up of 40% maximal inspiratory pressure to regular rowing warm-up had no significant effect on oxygen consumption kinetics during submaximal rowing tests.
AMPK Is the Crucial Target for the CDK4/6 Inhibitors Mediated Therapeutic Responses in PANC-1 and MIA PaCa-2 Pancreatic Cancer Cell Lines
Authors: Sevgin Bortecine , Coban Merve , Rencuzogullari Özge , Coker-Gurkan Ajda , Obakan-Yerlikaya Pinar , Uysal Onganer Pinar , Arisan Elif
Published: March 2021

The survival rate of pancreatic ductal adenocarcinoma (PDAC) patients is short, and PDAC is a cancer type that ranks fourth in the statistics regarding death due to cancer. Mutation in the KRAS gene, which plays a role in pancreatic cancer development, activates the PI3K/AKT/mTOR signaling pathway. The activity of the AMPK as a cellular energy sensor is one of the fundamental mechanisms that can induce effective therapeutic responses against CDK4/6 inhibitors via adjusting the cellular and tumor microenvironment stress management. The phosphorylation of AMPKα at the different phosphorylation residues such as Thr172 and Ser 377 causes metabolic differentiation in the cells following CDK4/6 inhibitor treatment in accordance with an increased cell cycle arrest and senescence under the control of different cellular players. In this study, we examined the competencies of the CDK4/6 inhibitors LY2835219 and PD-0332991 on the mechanism of cell survival and death based on AMPK signaling. Both CDK4/6 inhibitors LY2835219 and PD-0332991 modulated different molecular players on the PI3K/AKT/mTOR and AMPK signaling axis in different ways to reduce cell survival in a cell type dependent manner. These drugs are potential inducers of apoptosis and senescence that can alter the therapeutic efficacy cells.
The Effectiveness of Different Incentive Programs to Encourage Safe Driving
Authors: Elias Wafa
Published: March 2021

This study examined the effectiveness of various financial incentive schemes for improving drivers’ safety performance, specifically in regard to speeding, tailgating, and frequent lane changing without signaling. The study examined the hypothesis that, with regard to modifying unsafe driving behavior in a sample of professional bus drivers in Israel, small yet reliable rewards are more effective than rewards that are large but rarely obtained. While this hypothesis has been tested and partially supported in laboratory studies, the current study is the first to test it in real-world conditions. This study demonstrates that a combination of surveillance, rewards (monetary compensation), and informing the drivers about their driving performance in real time produces a lasting and significant decline in traffic violations. The results show that financial incentives are effective for encouraging safe driving behavior. Simultaneously, the results show some indications that small yet probable rewards may be more effective than large but uncertain ones. This study also demonstrates that the improvement in behavior continued during the period immediately after the experiment.
Comparative Cradle-to-Grave Life Cycle Assessment of Low and Mid-Rise Mass Timber Buildings with Equivalent Structural Steel Alternatives
Authors: Allan Kevin , Phillips Adam R.
Published: March 2021

The objective of this paper was to quantify and compare the environmental impacts associated with alternative designs of typical North American low and mid-rise buildings. Two scenarios were considered: a traditional structural steel frame or an all-wood mass timber design, utilizing engineered wood products for both gravity and lateral load resistance. The boundary of the quantitative analysis was cradle-to-grave with considerations taken to discuss end-of-life and material reuse scenarios. The TRACI methodology was followed to conduct a Life Cycle Impact Assessment (LCIA) analysis that translates building quantities to environmental impact indicators using the Athena Impact Estimator for Buildings Life Cycle analysis software tool and Athena’s Life Cycle Inventory database. The results of the analysis show that mass timber buildings have an advantage with respect to several environmental impact categories, including eutrophication potential, human health particulate, and global warming potential where a 31% to 41% reduction was found from mass timber to steel designs, neglecting potential carbon sequestration benefits from the timber products. However, it was also found that the steel buildings have a lower impact with respect to the environmental impact categories of smog potential, acidification potential, and ozone depletion potential, where a 48% to 58% reduction was found from the steel to the mass timber building designs.
Influencing Factors and Social Media Reflections of Bakery Products Consumption in Romania
Authors: Lădaru Georgiana-Raluca , Siminică Marian , Diaconeasa Maria Claudia , Ilie Diana Maria , Dobrotă Carmen-Elena , Motofeanu Marian
Published: March 2021

Bakery products, and bread specifically, represent an important part of the Romanian diet. Whether this situation is motivated by quality factors or by quantitative factors is an important aspect that needs to be investigated. In addition, the relation between peoples’ interest in a particular product such as bread during a crisis period should point out important characteristics of that population. Aiming at determining both the influencing factors of bakery product consumption and the importance given to this type of product in the media during a crisis, this empirical study highlights the profound connections between income level and the fear of not having food security for the people of a less developed country such as Romania. The study considers the use of both qualitative and quantitative methods to reach its objectives. The results point to a strong reliance of the respondents on cheap white-flour bakery products in their regular diet, and a significant increase in interest in bakery products during the COVID-19 pandemic.
Crowdsourcing in Nursing Education: A Possibility of Creating a Personalized Online Learning Environment for Student Nurses in the Post-COVID Era
Authors: Geng Ying , Huang Po-Sen , Huang Yeuh-Min
Published: March 2021

The widespread COVID-19 pandemic has not only posed a major health threat in Taiwan but also has challenged the nursing pedagogy. Both academia and the education industry are calling for a radical change of nursing pedagogy. Under such a call, the present study investigates an online collaborative knowledge co-construction mechanism—Crowdsourcing Collaborative Learning Strategy (CCLS)—to help student nurses acquire and practice functional knowledge on clinical operations targeted to the Objective Structured Clinical Examination (OSCE) at anytime and anywhere via the internet service. A t-test on the pre-and-post test between the control and experimental group explained the effectiveness of the CCLS online platform. Two questionnaires were used to explore students’ perception of the effectiveness and the usefulness of the CCLS online platform. The findings suggested the CCLS online platform can help students to revisit their clinical performance via the recorded videos, facilitate student nurses’ self-reflection on their performance, and help student nurses to minimize the academic-practice gap. Participants in this study scored the CCLS online platform as helpful and easy to use during the learning process.
Economic Calculation and Operations Research in Terms of LNG Carriage by Water Transport: A Case Study of the Port of Bratislava
Authors: Jurkovič Martin , Kalina Tomáš , Stopka Ondrej , Gorzelanczyk Piotr , Abramović Borna
Published: March 2021

The presented manuscript discusses a specific research study examining several variants of liquefied natural gas (LNG) carriage from chosen seaports to the port of Bratislava using the Danube waterway, assessing them using chosen multi-criteria analysis techniques. Two ports in Turkey and one port in Georgia are deemed export terminals. A total of twelve variants are compared, whereby the comparison is carried out based on multiple evaluation criteria defined by a panel of experts who laid particular stress on their importance. An economic calculation is performed in the first phase to assess LNG carriage in all the variants. This represents the very foundation for the multi-criteria evaluation, which is conducted using Multi-Criteria Decision Analysis (MCDA) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The evaluated variants differ not only in terms of export port location, but also in relation to transport technology. As for the second phase, four distinct technologies in three different scenarios are assessed—specifically, Small-Scale (SS) LNG-C tankers—while two modes of operation (i.e., time-charter, own tanker) and a river-sea LNG tanker with an LNG barge in two versions are considered. The first version considers the use of Marine Gasoil (MGO) fuel, while the second one considers LNG use. The results obtained provide interesting findings, wherein two out of three applied methods prefer the same transport option. Thus, it can be stated that our study presents a unique approach by comparing different scenarios of LNG distribution as a commodity inland along the river Danube, specifically to Central Europe, from a variety of standpoints. The manuscript evaluates carriage using traditional MGO fuels as well as alternative LNG fuels, and also brings a comparison from a technological point of view.