bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Mechanical Properties and Energy Absorption of Sheet-Based and Strut-Based Gyroid Cellular Structures with Graded Densities
Authors: Li Dawei , Liao Wenhe , Dai Ning , Xie Yi Min
Published: July 2019

Bio-inspired functionally graded cellular materials (FGCM) have improved performance in energy absorption compared with a uniform cellular material (UCM). In this work, sheet-based and strut-based gyroid cellular structures with graded densities are designed and manufactured by stereo-lithography (SLA). For comparison, uniform structures are also designed and manufactured, and the graded structures are generated with different gradients. The mechanical behaviors of these structures under compressive loads are investigated. Furthermore, the anisotropy and effective elastic modulus of sheet-based and strut-based unit gyroid cellular structures are estimated by a numerical homogenization method. On the one hand, it is found from the numerical results that the sheet-based gyroid tends to be isotropic, and the elastic modulus of sheet-based gyroid is larger than the strut-based gyroid at the same volume fraction. On the other hand, the graded cellular structure has novel deformation and mechanical behavior. The uniform structure exhibits overall deformation and collapse behavior, whereas the graded cellular structure shows layer-by-layer deformation and collapse behavior. Furthermore, the uniform sheet-based gyroid is not only stiffer but also better in energy absorption capacity than the uniform strut-based gyroid structure. Moreover, the graded cellular structures have better energy absorption capacity than the uniform structures. These significant findings indicate that sheet-based gyroid cellular structure with graded densities have potential applications in various industrial applications, such as in crashworthiness.
Mechanical Properties and Microstructures of Laser–TIG Welded ME21 Rare Earth Mg Alloy
Authors: Li Taotao , Song Gang , Zhang Zhaodong , Liu Liming
Published: July 2019

The microstructural and mechanical properties of laser–tungsten inert gas (TIG) hybrid welding of Mg alloy sheets for automobiles are investigated in the present work, including AZ31 and ME21, AZ31 and AZ31, ME21 and ME21, and corresponding comparisons were carried out. The results show that columnar crystals appear in the ME21/ME21 and ME21/AZ31 heat-affected zones, and no columnar crystals formed in the AZ31/AZ31 fusion zone under a constant heat ratio of arc to laser. Heat accumulation in a narrow area and the undercooling degree are the two main factors for the formation of columnar crystal. The ME21/ME21 joint has a tensile strength of up to 185.2 MPa, which is about 81.8% of that of the ME21 base metal (BM-ME21). The tensile strength of the ME21/AZ31 joint (158.8 MPa) is lower than that of the ME21/ME21 joint. The fracture of the ME21/ME21 and ME21/AZ31 joints occurs at the junction of the columnar crystal and the heat-affected zone. The microhardness of the ME21/AZ31 joint presents a low–high–low–high trend from BE-ME21 to BE-AZ31, and the distribution of the ME21/AZ31 welded joint microhardness in the cross-section presents a low–high–low trend. The ME21/ME21 weld seam is composed of an AlCe3 intermetallic compound, Mn particles, and α-Mg, and the ME21/AZ31 weld seam is composed of a α-Mg, Mg17Al12, and AlCe3 intermetallic compound.
Evolution of Power Losses in Bending Rolled Fully Finished NO Electrical Steel Treated under Unconventional Annealing Conditions
Authors: Petryshynets Ivan , Kováč František , Füzer Ján , Falat Ladislav , Puchý Viktor , Kollár Peter
Published: July 2019

Currently, the non-oriented (NO) iron-silicon steels are extensively used as the core materials in various electrical devises due to excellent combination of their mechanical and soft magnetic properties. The present study introduces a fairly innovative technological approach applicable for fully finished NO electrical steel before punching the laminations. It is based on specific mechanical processing by bending and rolling in combination with subsequent annealing under dynamic heating conditions. It has been revealed that the proposed unconventional treatment clearly led to effective improvement of the steel magnetic properties thanks to its beneficial effects involving additional grain growth with appropriate crystallographic orientation and residual stress relief. The philosophy of the proposed processing was based on employing the phenomena of selective grain growth by strain-induced grain boundary migration and a steep temperature gradient through the cross-section of heat treated specimens at dynamic heating conditions. The stored deformation energy necessary for the grain growth was provided by plastic deformation induced within the studied specimens during the bending and rolling process. The magnetic measurements clearly show that the specimens treated according to our approach exhibited more than 17% decrease in watt losses in comparison with the specimens treated by conventional heat treatment leading only to stress relief without additional grain growth.
Evaluation of the Inhibitory Potential of Casuarictin, an Ellagitannin Isolated from White Mangrove (Laguncularia racemosa) Leaves, on Snake Venom Secretory Phospholipase A2
Authors: Rodrigues Caroline Fabri Bittencourt , Ferreira Marcelo José Pena , Belchor Mariana Novo , Costa Caroline R. C. , Novaes Danielle P. , dos Santos Junior Adeilso Bispo , Tamayose Cinthia I. , Pinho Marcus Vinícius Terashima , de Oliveira Marcos Antonio , Toyama Marcos Hikari
Published: July 2019

Ellagitannins constitute the largest group of hydrolyzable tannins of plants, and, from this group, casuarictin (Casu) was identified in some plant species. However, to our knowledge, no investigation of secretory phospholipase A2 (sPLA2) inhibition by Casu has been performed yet. Casuarictin was isolated by chromatography n-butanol (n-BuOH) partition of Laguncularia racemosa leaves. The pharmacological and biological effects of Casu were evaluated on isolated sPLA2 from the rattlesnake (Crotalus durissus terrificus) and using a plant bacterial strain. The compound was able to form a protein complex consisting of a stable sPLA2 + Casu complex. Analyses carried out with matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF) revealed that the molecular mass of sPLA2 increased from 14,425.62 to 15,362.74 Da. The enzymatic activity of the sPLA2 + Casu complex was significantly lower than that of native sPLA2. Besides, molecular interactions of Casu with sPLA2 were able to virtually abolish the native edematogenic effect as well as myonecrosis induced by the protein when injected 10 min after sPLA2. Therefore, Casu may be considered a potential anti-inflammatory that can be used to treat edema and myonecrosis induced by serine-secreting phospholipase A2. In addition, the compound also showed great antimicrobial potential.
Study on Microstructure and Properties of a New Warm-Stamped Niobium-Alloyed Steel
Authors: Tian Peng , Liang Wen , Cui Zhennan , Zhu Guoming , Kang Yonglin , Li Baoshun , Lin Li , Liu Rendong
Published: July 2019

The warm stamping technology is a promising technology to meet the needs of car weight reduction and energy conservation. In order to compare with the mechanical properties of the traditional hot-stamped boron-alloyed steel 22MnB5, a new warm-stamped niobium-alloyed steel 22Mn3SiNb was designed and tested. The optimal heating parameters for warm forming process were explored through mechanical tests, and the process of their microstructure evolution was investigated by scanning electron microscope (SEM), transmission electron microscope (TEM) and X-ray diffraction (XRD), etc. The experimental results indicate that the optimal heating parameters for the niobium-alloyed steel 22Mn3SiNb are a heating temperature of 800 °C and a soaking time of 5 min. Compared to the hot-stamped boron-alloyed steel 22MnB5 under their respective optimal heating parameters, the properties and microstructure characteristics of 22Mn3SiNb are greatly improved, and nearly no decarburized layer is found on the surface of the niobium-alloyed steel 22Mn3SiNb. In addition, the addition of Nb produces the effects of grain refinement and precipitation strengthening due to the introduction of plenty of nano-precipitated particles and dislocations. In the end, it can be predicted that the new warm-stamped niobium-alloyed steel will replace the conventional hot-stamped boron-alloyed steel.
Visualization and Interpretation of Multivariate Associations with Disease Risk Markers and Disease Risk—The Triplot
Authors: Schillemans Tessa , Shi Lin , Liu Xin , Åkesson Agneta , Landberg Rikard , Brunius Carl
Published: July 2019

Metabolomics has emerged as a promising technique to understand relationships between environmental factors and health status. Through comprehensive profiling of small molecules in biological samples, metabolomics generates high-dimensional data objectively, reflecting exposures, endogenous responses, and health effects, thereby providing further insights into exposure-disease associations. However, the multivariate nature of metabolomics data contributes to high complexity in analysis and interpretation. Efficient visualization techniques of multivariate data that allow direct interpretation of combined exposures, metabolome, and disease risk, are currently lacking. We have therefore developed the ‘triplot’ tool, a novel algorithm that simultaneously integrates and displays metabolites through latent variable modeling (e.g., principal component analysis, partial least squares regression, or factor analysis), their correlations with exposures, and their associations with disease risk estimates or intermediate risk factors. This paper illustrates the framework of the ‘triplot’ using two synthetic datasets that explore associations between dietary intake, plasma metabolome, and incident type 2 diabetes or BMI, an intermediate risk factor for lifestyle-related diseases. Our results demonstrate advantages of triplot over conventional visualization methods in facilitating interpretation in multivariate risk modeling with high-dimensional data. Algorithms, synthetic data, and tutorials are open source and available in the R package ‘triplot’.
Speeding Up the Write Operation for Multi-Level Cell Phase Change Memory with Programmable Ramp-Down Current Pulses
Authors: Xie Chenchen , Li Xi , Chen Houpeng , Li Yang , Liu Yuanguang , Wang Qian , Ren Kun , Song Zhitang
Published: July 2019

Multi-level cell (MLC) phase change memory (PCM) can not only effectively multiply the memory capacity while maintaining the cell area, but also has infinite potential in the application of the artificial neural network. The write and verify scheme is usually adopted to reduce the impact of device-to-device variability at the expense of a greater operation time and more power consumption. This paper proposes a novel write operation for multi-level cell phase change memory: Programmable ramp-down current pulses are utilized to program the RESET initialized memory cells to the expected resistance levels. In addition, a fully differential read circuit with an optional reference current source is employed to complete the readout operation. Eventually, a 2-bit/cell phase change memory chip is presented with a more efficient write operation of a single current pulse and a read access time of 65 ns. Some experiments are implemented to demonstrate the resistance distribution and the drift.
Interactome Analysis and Docking Sites of MutS Homologs Reveal New Physiological Roles in Arabidopsis thaliana
Authors: AbdelGawwad Mohamed Ragab , Marić Aida , Al-Ghamdi Abdullah Ahmed , Hatamleh Ashraf A.
Published: July 2019

Due to their sedentary lifestyle, plants are constantly exposed to different stress stimuli. Stress comes in variety of forms where factors like radiation, free radicals, “replication errors, polymerase slippage”, and chemical mutagens result in genotoxic or cytotoxic damage. In order to face “the base oxidation or DNA replication stress”, plants have developed many sophisticated mechanisms. One of them is the DNA mismatch repair (MMR) pathway. The main part of the MMR is the MutS homologue (MSH) protein family. The genome of Arabidopsis thaliana encodes at least seven homologues of the MSH family: AtMSH1, AtMSH2, AtMSH3, AtMSH4, AtMSH5, AtMSH6, and AtMSH7. Despite their importance, the functions of AtMSH homologs have not been investigated. In this work, bioinformatics tools were used to obtain a better understanding of MSH-mediated DNA repair mechanisms in Arabidopsis thaliana and to understand the additional biological roles of AtMSH family members. In silico analysis, including phylogeny tracking, prediction of 3D structure, interactome analysis, and docking site prediction, suggested interactions with proteins were important for physiological development of A. thaliana. The MSH homologs extensively interacted with both TIL1 and TIL2 (DNA polymerase epsilon catalytic subunit), proteins involved in cell fate determination during plant embryogenesis and involved in flowering time repression. Additionally, interactions with the RECQ protein family (helicase enzymes) and proteins of nucleotide excision repair pathway were detected. Taken together, the results presented here confirm the important role of AtMSH proteins in mismatch repair and suggest important new physiological roles.
Genetic Permissiveness and Dietary Glycemic Load Interact to Predict Type-II Diabetes in the Nile rat (Arvicanthis niloticus)
Authors: Subramaniam Avinaash , Landstrom Michelle , Hayes K. C.
Published: July 2019

Objective: The Nile rat (Arvicanthis niloticus) is a superior model for Type-II Diabetes Mellitus (T2DM) induced by diets with a high glycemic index (GI) and glycemic load (GLoad). To better define the age and gender attributes of diabetes in early stages of progression, weanling rats were fed a high carbohydrate (hiCHO) diet for between 2 to 10 weeks. Methods: Data from four experiments compared two diabetogenic semipurified diets (Diet 133 (60:20:20, as % energy from CHO, fat, protein with a high glycemic load (GLoad) of 224 per 2000 kcal) versus Diets 73 MBS or 73 MB (70:10:20 with or without sucrose and higher GLoads of 259 or 295, respectively). An epidemiological technique was used to stratify the diabetes into quintiles of blood glucose (Q1 to Q5), after 2–10 weeks of dietary induction in 654 rats. The related metagenetic physiological growth and metabolic outcomes were related to the degree of diabetes based on fasting blood glucose (FBG), random blood glucose (RBG), and oral glucose tolerance test (OGTT) at 30 min and 60 min. Results: Experiment 1 (Diet 73MBS) demonstrated that the diabetes begins aggressively in weanlings during the first 2 weeks of a hiCHO challenge, linking genetic permissiveness to diabetes susceptibility or resistance from an early age. In Experiment 2, ninety male Nile rats fed Diet 133 (60:20:20) for 10 weeks identified two quintiles of resistant rats (Q1,Q2) that lowered their RBG between 6 weeks and 10 weeks on diet, whereas Q3–Q5 became progressively more diabetic, suggesting an ongoing struggle for control over glucose metabolism, which either stabilized or not, depending on genetic permissiveness. Experiment 3 (32 males fed 70:10:20) and Experiment 4 (30 females fed 60:20:20) lasted 8 weeks and 3 weeks respectively, for gender and time comparisons. The most telling link between a quintile rank and diabetes risk was telegraphed by energy intake (kcal/day) that established the cumulative GLoad per rat for the entire trial, which was apparent from the first week of feeding. This genetic permissiveness associated with hyperphagia across quintiles was maintained throughout the study and was mirrored in body weight gain without appreciable differences in feed efficiency. This suggests that appetite and greater growth rate linked to a fiber-free high GLoad diet were the dominant factors driving the diabetes. Male rats fed the highest GLoad diet (Diet 73MB 70:10:20, GLoad 295 per 2000 kcal for 8 weeks in Experiment 3], ate more calories and developed diabetes even more aggressively, again emphasizing the Cumulative GLoad as a primary stressor for expressing the genetic permissiveness underlying the diabetes. Conclusion: Thus, the Nile rat model, unlike other rodents but similar to humans, represents a superior model for high GLoad, low-fiber diets that induce diabetes from an early age in a manner similar to the dietary paradigm underlying T2DM in humans, most likely originating in childhood.
Of Mice and Men—The Physiology, Psychology, and Pathology of Overhydration
Authors: Hew-Butler Tamara , Smith-Hale Valerie , Pollard-McGrandy Alyssa , VanSumeren Matthew
Published: July 2019

The detrimental effects of dehydration, to both mental and physical health, are well-described. The potential adverse consequences of overhydration, however, are less understood. The difficulty for most humans to routinely ingest ≥2 liters (L)—or “eight glasses”—of water per day highlights the likely presence of an inhibitory neural circuit which limits the deleterious consequences of overdrinking in mammals but can be consciously overridden in humans. This review summarizes the existing data obtained from both animal (mostly rodent) and human studies regarding the physiology, psychology, and pathology of overhydration. The physiology section will highlight the molecular strength and significance of aquaporin-2 (AQP2) water channel downregulation, in response to chronic anti-diuretic hormone suppression. Absence of the anti-diuretic hormone, arginine vasopressin (AVP), facilitates copious free water urinary excretion (polyuria) in equal volumes to polydipsia to maintain plasma tonicity within normal physiological limits. The psychology section will highlight reasons why humans and rodents may volitionally overdrink, likely in response to anxiety or social isolation whereas polydipsia triggers mesolimbic reward pathways. Lastly, the potential acute (water intoxication) and chronic (urinary bladder distension, ureter dilation and hydronephrosis) pathologies associated with overhydration will be examined largely from the perspective of human case reports and early animal trials.
A Review on Porous Polymeric Membrane Preparation. Part I: Production Techniques with Polysulfone and Poly (Vinylidene Fluoride)
Authors: Tan XueMei , Rodrigue Denis
Published: July 2019

Porous polymeric membranes have emerged as the core technology in the field of separation. But some challenges remain for several methods used for membrane fabrication, suggesting the need for a critical review of the literature. We present here an overview on porous polymeric membrane preparation and characterization for two commonly used polymers: polysulfone and poly (vinylidene fluoride). Five different methods for membrane fabrication are introduced: non-solvent induced phase separation, vapor-induced phase separation, electrospinning, track etching and sintering. The key factors of each method are discussed, including the solvent and non-solvent system type and composition, the polymer solution composition and concentration, the processing parameters, and the ambient conditions. To evaluate these methods, a brief description on membrane characterization is given related to morphology and performance. One objective of this review is to present the basics for selecting an appropriate method and membrane fabrication systems with appropriate processing conditions to produce membranes with the desired morphology, performance and stability, as well as to select the best methods to determine these properties.
Enhanced In-Vitro Hemozoin Polymerization by Optimized Process using Histidine-Rich Protein II (HRPII)
Authors: Lee Ju Hun , Kim Hyeong Ryeol , Lee Ja Hyun , Lee Soo Kweon , Chun Youngsang , Han Sung Ok , Yoo Hah Young , Park Chulhwan , Kim Seung Wook
Published: July 2019

Conductive biopolymers, an important class of functional materials, have received attention in various fields because of their unique electrical, optical, and physical properties. In this study, the polymerization of heme into hemozoin was carried out in an in vitro system by the newly developed heme polymerase (histidine-rich protein 2 (HRP-II)). The HRP-II was produced by recombinant E. coli BL21 from the Plasmodium falciparum gene. To improve the hemozoin production, the reaction conditions on the polymerization were investigated and the maximum production was achieved after about 790 μM at 34 °C with 200 rpm for 24 h. As a result, the production was improved about two-fold according to the stepwise optimization in an in vitro system. The produced hemozoin was qualitatively analyzed using the Fourier transform infrared (FTIR) spectroscopy, energy dispersive X-ray spectroscopy (EDS), and scanning electron microscopy (SEM). Finally, it was confirmed that the enzymatically polymerized hemozoin had similar physical properties to chemically synthesized hemozoin. These results could represent a significant potential for nano-biotechnology applications, and also provide guidance in research related to hemozoin utilization.
On the Para/Ortho Reactivity of Isocyanate Groups during the Carbamation of Cellulose Nanocrystals Using 2,4-Toluene Diisocyanate
Authors: Abushammala Hatem
Published: July 2019

2,4-toluene diisocyanate (TDI) has been commonly used to bind molecules and polymers onto the surface of cellulose nanocrystals (CNCs). Such a process usually involves two steps: (1) the more reactive para-isocyanates (p-NCOs) of TDI are reacted with the surface hydroxyl groups of CNCs then (2) the ortho-isocyanates (o-NCOs) are reacted with certain desired molecules. During the first reaction, an ideal para/ortho selectivity could be impossible to achieve, as o-NCOs are not fully unreactive. Therefore, there is a need to better understand the reaction between CNCs and TDI towards a maximum para/ortho selectivity. For that goal, CNCs were reacted with TDI under varying temperatures (35–75 °C) and TDI/CNCs molar ratios (1–5). The amount of the reacted TDI was estimated using elemental analysis while the free o-NCO groups were quantified following the hydrolysis method of Abushammala. The results showed that temperature had a negative impact on para/ortho selectivity while TDI/CNCs molar ratio improved it. A maximum selectivity of 93% was achieved using a temperature of 35 °C and a molar ratio of 3. This is a three-fold improvement to that using the traditional reaction conditions (75 °C and molar ratio of 1).
Pixel Size and Revisit Rate Requirements for Monitoring Power Plant CO2 Emissions from Space
Authors: Hill Tim , Nassar Ray
Published: July 2019

The observational requirements for space-based quantification of anthropogenic CO 2 emissions are of interest to space agencies and related organizations that may contribute to a possible satellite constellation to support emission monitoring in the future. We assess two key observing characteristics for space-based monitoring of CO2 emissions: pixel size and revisit rate, and we introduce a new method utilizing multiple images simultaneously to significantly improve emission estimates. The impact of pixel size ranging from 2–10 km for space-based imaging spectrometers is investigated using plume model simulations, accounting for biases in the observations. Performance of rectangular pixels is compared to square pixels of equal area. The findings confirm the advantage of the smallest pixels in this range and the advantage of square pixels over rectangular pixels. A method of averaging multiple images is introduced and demonstrated to be able to estimate emissions from small sources when the individual images are unable to distinguish the plume. Due to variability in power plant emissions, results from a single overpass cannot be directly extrapolated to annual emissions, the most desired timescale for regulatory purposes. We investigate the number of overpasses required to quantify annual emissions with a given accuracy, based on the mean variability from the 50 highest emitting US power plants. Although the results of this work alone are not sufficient to define the full architecture of a future CO 2 monitoring constellation, when considered along with other studies, they may assist in informing the design of a space-based system to support anthropogenic CO 2 emission monitoring.
The Inter-Calibration of the DSCOVR EPIC Imager with Aqua-MODIS and NPP-VIIRS
Authors: Doelling David , Haney Conor , Bhatt Rajendra , Scarino Benjamin , Gopalan Arun
Published: July 2019

The Deep Space Climate Observatory (DSCOVR) through the earth polychromatic imaging camera (EPIC) continuously observes the illuminated disk from the Lagrange-1 point. The EPIC sensor was designed to monitor the diurnal variation of ozone, clouds, aerosols, and vegetation, especially those features that benefit from observation near-backscatter conditions. The EPIC sensor does not contain any onboard calibration systems. This study describes the inter-calibration of EPIC channels 5 (0.44 µm), 6 (0.55 µm), 7 (0.68 µm), and 10 (0.78 µm) with respect to Aqua-MODIS and NPP-VIIRS. The calibration is transferred using coincident ray-matched reflectance pairs over all-sky tropical ocean (ATO) and deep convective cloud (DCC) targets. A robust and automated image-alignment technique based on feature matching was formulated to improve the navigation quality of the EPIC images. The EPIC V02 dataset exhibits improved navigation over V01. As the visible channels display similar spatial features, a single visible channel can be used to co-register the remaining visible bands. The VIIRS-referenced EPIC ATO and DCC ray-matched calibration coefficients are within 0.3%. The EPIC four-year calibration trends based on VIIRS are within 0.15%/year. The MODIS-based EPIC calibration coefficients were compared against the Geogdzhayev and Marshak 2018 published calibration coefficients and were found to be within 1.6%.
Optimal Cyanobacterial Pigment Retrieval from Ocean Colour Sensors in a Highly Turbid, Optically Complex Lake
Authors: Riddick Caitlin A.L. , Hunter Peter D. , Domínguez Gómez José Antonio , Martinez-Vicente Victor , Présing Mátyás , Horváth Hajnalka , Kovács Attila W. , Vörös Lajos , Zsigmond Eszter , Tyler Andrew N.
Published: July 2019

To date, several algorithms for the retrieval of cyanobacterial phycocyanin (PC) from ocean colour sensors have been presented for inland waters, all of which claim to be robust models. To address this, we conducted a comprehensive comparison to identify the optimal algorithm for retrieval of PC concentrations in the highly optically complex waters of Lake Balaton (Hungary). MEdium Resolution Imaging Spectrometer (MERIS) top-of-atmosphere radiances were first atmospherically corrected using the Self-Contained Atmospheric Parameters Estimation for MERIS data v.B2 (SCAPE-M_B2). Overall, the Simis05 semi-analytical algorithm outperformed more complex inversion algorithms, providing accurate estimates of PC up to ±7 days from the time of satellite overpass during summer cyanobacteria blooms (RMSElog < 0.33). Same-day retrieval of PC also showed good agreement with cyanobacteria biomass (R2 > 0.66, p < 0.001). In-depth analysis of the Simis05 algorithm using in situ measurements of inherent optical properties (IOPs) revealed that the Simis05 model overestimated the phytoplankton absorption coefficient [aph(λ)] by a factor of ~2. However, these errors were compensated for by underestimation of the mass-specific chlorophyll absorption coefficient [a*chla(λ)]. This study reinforces the need for further validation of algorithms over a range of optical water types in the context of the recently launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3.
Assimilating Soil Moisture Retrieved from Sentinel-1 and Sentinel-2 Data into WOFOST Model to Improve Winter Wheat Yield Estimation
Authors: Zhuo Wen , Huang Jianxi , Li Li , Zhang Xiaodong , Ma Hongyuan , Gao Xinran , Huang Hai , Xu Baodong , Xiao Xiangming
Published: July 2019

Crop yield estimation at a regional scale over a long period of time is of great significance to food security. In past decades, the integration of remote sensing observations and crop growth models has been recognized as a promising approach for crop growth monitoring and yield estimation. Optical remote sensing data are susceptible to cloud and rain, while synthetic aperture radar (SAR) can penetrate through clouds and has all-weather capabilities. This allows for more reliable and consistent crop monitoring and yield estimation in terms of radar sensor data. The aim of this study is to improve the accuracy for winter wheat yield estimation by assimilating time series soil moisture images, which are retrieved by a water cloud model using SAR and optical data as input, into the crop model. In this study, SAR images were acquired by C-band SAR sensors boarded on Sentinel-1 satellites and optical images were obtained from a Sentinel-2 multi-spectral instrument (MSI) for Hengshui city of Hebei province in China. Remote sensing data and ground data were all collected during the main growing season of winter wheat. Both the normalized difference vegetation index (NDVI), derived from Sentinel-2, and backscattering coefficients and polarimetric indicators, computed from Sentinel-1, were used in the water cloud model to derive time series soil moisture (SM) images. To improve the prediction of crop yields at the field scale, we incorporated remotely sensed soil moisture into the World Food Studies (WOFOST) model using the Ensemble Kalman Filter (EnKF) algorithm. In general, the trend of soil moisture inversion was consistent with the ground measurements, with the coefficient of determination (R2) equal to 0.45, 0.53, and 0.49, respectively, and RMSE was 9.16%, 7.43%, and 8.53%, respectively, for three observation dates. The winter wheat yield estimation results showed that the assimilation of remotely sensed soil moisture improved the correlation of observed and simulated yields (R2 = 0.35; RMSE =934 kg/ha) compared to the situation without data assimilation (R2 = 0.21; RMSE = 1330 kg/ha). Consequently, the results of this study demonstrated the potential and usefulness of assimilating SM retrieved from both Sentinel-1 C-band SAR and Sentinel-2 MSI optical remote sensing data into WOFOST model for winter wheat yield estimation and could also provide a reference for crop yield estimation with data assimilation for other crop types.
An Effectiveness Evaluation Model for Satellite Observation and Data-Downlink Scheduling Considering Weather Uncertainties
Authors: Zhang Siyue , Xiao Yiyong , Yang Pei , Liu Yinglai , Chang Wenbing , Zhou Shenghan
Published: July 2019

Low Earth orbit (LEO) satellites play an important role in human space activities, and market demands for commercial uses of LEO satellites have been increasing rapidly in recent years. LEO satellites mainly consist of Earth observation satellites (EOSs), the major commercial applications of which are various sorts of Earth observations, such as map making, crop growth assessment, and disaster surveillance. However, the success rates of observation tasks are influenced considerably by uncertainties in local weather conditions, inadequate sunlight, observation dip angle, and other practical factors. The available time windows (ATWs) suitable for observing given types of targets and for transmitting data back to ground receiver stations are relatively narrow. In order to utilize limited satellite resources efficiently and maximize their commercial benefits, it is necessary to evaluate the overall effectiveness of satellites and planned tasks considering various factors. In this paper, we propose a method for determining the ATWs considering the influence of sunlight angle, elevation angle, and the type of sensor equipped on the satellite. After that, we develop a satellite effectiveness evaluation (SEE) model for satellite observation and data-downlink scheduling (SODS) based on the Availability–Capacity–Profitability (ACP) framework, which is designed to evaluate the overall performance of satellites from the perspective of time resource utilization, the success rate of tasks, and profit return. The effects of weather uncertainties on the tasks’ success are considered in the SEE model, and the model can be applied to support the decision-makers on optimizing and improving task arrangements for EOSs. Finally, a case study is presented to demonstrate the effectiveness of the proposed method and verify the ACP-based SEE model. The obtained ATWs by the proposed method are compared with those by the Systems Tool Kit (STK), and the correctness of the method is thus validated.
A Cancelable Iris- and Steganography-Based User Authentication System for the Internet of Things
Authors: Yang Wencheng , Wang Song , Hu Jiankun , Ibrahim Ahmed , Zheng Guanglou , Macedo Marcelo Jose , Johnstone Michael N. , Valli Craig
Published: July 2019

Remote user authentication for Internet of Things (IoT) devices is critical to IoT security, as it helps prevent unauthorized access to IoT networks. Biometrics is an appealing authentication technique due to its advantages over traditional password-based authentication. However, the protection of biometric data itself is also important, as original biometric data cannot be replaced or reissued if compromised. In this paper, we propose a cancelable iris- and steganography-based user authentication system to provide user authentication and secure the original iris data. Most of the existing cancelable iris biometric systems need a user-specific key to guide feature transformation, e.g., permutation or random projection, which is also known as key-dependent transformation. One issue associated with key-dependent transformations is that if the user-specific key is compromised, some useful information can be leaked and exploited by adversaries to restore the original iris feature data. To mitigate this risk, the proposed scheme enhances system security by integrating an effective information-hiding technique—steganography. By concealing the user-specific key, the threat of key exposure-related attacks, e.g., attacks via record multiplicity, can be defused, thus heightening the overall system security and complementing the protection offered by cancelable biometric techniques.
Estimation of Chlorophyll Fluorescence at Different Scales: A Review
Authors: Ni Zhuoya , Lu Qifeng , Huo Hongyuan , Zhang Huili
Published: July 2019

Measuring chlorophyll fluorescence is a direct and non-destructive way to monitor vegetation. In this paper, the fluorescence retrieval methods from multiple scales, ranging from near the ground to the use of space-borne sensors, are analyzed and summarized in detail. At the leaf-scale, the chlorophyll fluorescence is measured using active and passive technology. Active remote sensing technology uses a fluorimeter to measure the chlorophyll fluorescence, and passive remote sensing technology mainly depends on the sun-induced chlorophyll fluorescence filling in the Fraunhofer lines or oxygen absorptions bands. Based on these retrieval principles, many retrieval methods have been developed, including the radiance-based methods and the reflectance-based methods near the ground, as well as physically and statistically-based methods that make use of satellite data. The advantages and disadvantages of different approaches for sun-induced chlorophyll fluorescence retrieval are compared and the key issues of the current sun-induced chlorophyll fluorescence retrieval algorithms are discussed. Finally, conclusions and key problems are proposed for the future research.
A Blood Flow Volume Linear Inversion Model Based on Electromagnetic Sensor for Predicting the Rate of Arterial Stenosis
Authors: Yang Dan , Liu Yan-jun , Xu Bin , Duo Yun-hui
Published: July 2019

This paper presents a mathematical model of measuring blood flow based on electromagnetic induction for predicting the rate of arterial stenosis. Firstly, an electrode sensor was used to collect the induced potential differences from human skin surface in a uniform magnetic field. Then, the inversion matrix was constructed by the weight function theory and finite element method. Next, the blood flow volume inversion model was constructed by combining the induction potential differences and inversion matrix. Finally, the rate of arterial stenosis was predicted based on mathematical relationship between blood flow and the area of arterial stenosis. To verify the accuracy of the model, a uniform magnetic field distribution of Helmholtz coil and a 3D geometric model of the ulnar artery of the forearm with different rates of stenosis were established in COMSOL, a finite element analysis software. Simulation results showed that the inversion model had high accuracy in the measurement of blood flow and the prediction of rate of stenosis, and is of great significance for the early diagnosis of arterial stenosis and other vessel diseases.
A Novel Chiller Sensors Fault Diagnosis Method Based on Virtual Sensors
Authors: Gao Long , Li Donghui , Li Ding , Yao Lele , Liang Limei , Gao Yanan
Published: July 2019

Sensor fault detection and diagnosis (FDD) has great significance for ensuring the energy saving and normal operation of the air conditioning system. Chiller systems serving as an important part of central air conditioning systems are the major energy consumer in commercial and industrial buildings. In order to ensure the normal operation of the chiller system, virtual sensors have been proposed to detect and diagnose sensor faults. However, the performance of virtual sensors could be easily impacted by abnormal data. To solve this problem, virtual sensors combined with the maximal information coefficient (MIC) and a long short-term memory (LSTM) network is proposed for chiller sensor fault diagnosis. Firstly, MIC, which has the ability to quantify the degree of relevance in a data set, is applied to examine all potentially interesting relationships between sensors. Subsequently, sensors with high correlation are divided into several groups by the grouping thresholds. Two virtual sensors, which are constructed in each group by LSTM with different input sensors and corresponding to the same physical sensor, could have the ability to predict the value of physical sensors. High correlation sensors in each group improve the fitting effect of virtual sensors. Finally, sensor faults can be diagnosed by the absolute deviation which is generated by comparing the virtual sensors’ output with the actual value measured from the air-cooled chiller. The performance of the proposed method is evaluated by using a real data set. Experimental results indicate that virtual sensors can be well constructed and the proposed method achieves a significant performance along with a low false alarm rate.
Integration in the Shadow of Austerity—Refugees in Newcastle upon Tyne
Authors: Flug Matthias , Hussein Jason
Published: July 2019

Newcastle upon Tyne, a post-industrial city in the North East of England, has long been committed to hosting refugees. Although the city has suffered drastic cuts in government funding and faces high levels of deprivation, Newcastle declared itself a city of sanctuary and participates in several dispersal schemes for asylum seekers and refugees. This paper shows how political support as well as the self-motivating ambition to be a city of sanctuary are driving forces behind the city’s commitment to hosting refugees. This study then proceeds to explore the integration experiences of refugees in Newcastle, with a focus on housing, employment and the relations between refugees and local residents. While an overall positive picture emerges across these areas, language barriers, the refusal to accept refugees’ previous qualifications and experiences of racism remain major obstacles to integration. Moreover, the gulf in funding and support between resettled refugees and former asylum seekers greatly aggravates the latter’s access to housing and employment and contributes to a lower feeling of safety among this group.
Rapid Intensification of Typhoon Hato (2017) over Shallow Water
Authors: Pun Iam-Fei , Chan Johnny , Lin I.-I. , Chan Kelvin , Price James , Ko Dong , Lien Chun-Chi , Wu Yu-Lun , Huang Hsiao-Ching
Published: July 2019

On 23 August, 2017, Typhoon Hato rapidly intensified by 10 kt within 3 h just prior to landfall in the city of Macau along the South China coast. Hato’s surface winds in excess of 50 m s−1 devastated the city, causing unprecedented damage and social impact. This study reveals that anomalously warm ocean conditions in the nearshore shallow water (depth < 30 m) likely played a key role in Hato’s fast intensification. In particular, cooling of the sea surface temperature (SST) generated by Hato at the critical landfall point was estimated to be only 0.1–0.5 °C. The results from both a simple ocean mixing scheme and full dynamical ocean model indicate that SST cooling was minimized in the shallow coastal waters due to a lack of cool water at depth. Given the nearly invariant SST in the coastal waters, we estimate a large amount of heat flux, i.e., 1.9k W m−2, during the landfall period. Experiments indicate that in the absence of shallow bathymetry, and thus, if nominal cool water had been available for vertical mixing, the SST cooling would have been enhanced from 0.1 °C to 1.4 °C, and sea to air heat flux reduced by about a quarter. Numerical simulations with an atmospheric model suggest that the intensity of Hato was very sensitive to air-sea heat flux in the coastal region, indicating the critical importance of coastal ocean hydrography.
Developing a Mobile Mapping System for 3D GIS and Smart City Planning
Authors: Yang Byungyun
Published: July 2019

The creation of augmented reality-related geographic information system (GIS) mapping applications has witnessed considerable advances in the technology of urban modeling; however, there are limitations to the technology that is currently used to create similar resources. The cost of the creation of the vehicle is an obstacle, and the rendering of textures of buildings is often lacking because of the distortion caused by the types of lenses that have been used. Generally, mobile mapping systems (MMSs) can extract detailed three-dimensional (3D) data with high quality texture information of the 3D building model. However, mapping urban areas by MMSs is expensive and requires advanced mathematical approaches with complicated steps. In particular, commercial MMS, which generally includes two GPS receivers, is an expensive device, costing ~$1 million. Thus, this research is aimed at developing a new MMS that semi-automatically produces high-quality texture information of 3D building models proposes a 3D urban model by hybrid approaches. Eventually, this study can support urban planners and people to improve their spatial perception and awareness of urban area for Smart City Planning.
Research on the Literature of Green Building Based on the Web of Science: A Scientometric Analysis in CiteSpace (2002–2018)
Authors: Shi Yingling , Liu Xinping
Published: July 2019

Since the 21st century, the concept of green building has been gradually popularized and implemented in more countries, which has become a popular direction in the area of sustainability in the building industry. Over the past few decades, many scholars and experts have done extensive research on green building. The purpose of this paper is to systematically analyze and visualize the status quo of green building. Therefore, based on Web of Science (WoS), this paper analyzed the existing knowledge system of green building using CiteSpace, identified keywords related to green building and their frequency of occurrence using the function of keyword co-occurrence analysis, recognized five clusters using the function of cluster analysis, and explored the knowledge evolution pattern of green building using citation bursts analysis in order to reveal how research related to green building has evolved over time. On the basis of aforementioned keywords, clusters, and citation bursts analysis, this paper has built a knowledge graph for green building. This paper can help readers to better understand the status quo and development trend of green building and to easier recognize the shortcomings in the development of green building, so as to provide a promising direction for future research.
Estimating Lifetimes and Stock Turnover Dynamics of Urban Residential Buildings in China
Authors: Zhou Wei , Moncaster Alice , Reiner David M , Guthrie Peter
Published: July 2019

Building lifetime and stock turnover are both key determinants in modelling building energy and carbon. However in China, aside from anecdotal claims that urban residential buildings are generally short-lived, there are no recent official statistics, and empirical data are extremely limited. We present a system dynamics model where survival analysis is used to characterise the dynamic interplay between new construction, aging, and demolition of residential buildings in urban China. The uncertainties associated with building lifetime were represented using a Weibull distribution, whose shape and scale parameters were calibrated based on official statistics on floor area up to 2006. The calibrated Weibull lifetime distribution allowed us to estimate the dynamic stock turnover of Chinese urban residential buildings for 2007 to 2017. We find that the average lifetime of urban residential buildings was around 34 years, and the overall residential stock size reached 23.7 billion m2 in 2017. The resultant age-specific sub-stocks provide a baseline for the overall stock, which—along with the calibrated Weibull lifetime distribution—can be used in further modelling and for analysis of policies to reduce the whole-life embodied and operational energy and CO2 emissions in Chinese residential buildings.
Financial Structure and Systemic Risk of Banks: Evidence from Chinese Reform
Authors: Ji Guseon , Kim Daniel Sungyeon , Ahn Kwangwon
Published: July 2019

Using Chinese data from 2006 to 2014, we find that a shift in the financial structure towards a more market-based structure can reduce the systemic risk of the banking sector. One transmission channel through which this occurs is the improvement in an individual firm’s debt repaying capacity, which is positively influenced by the development of stock markets. Another channel is the enhanced credit monitoring of borrowers by banks, owing to their slower credit growth. Our results imply that the shift toward market-based financial structure could lead to the development of financial market as well as the enhancement of the stability of an economy.
The Benefits of Randomly Delayed Charging of Electric Vehicles
Authors: Jäger Georg , Hofer Christian , Füllsack Manfred
Published: July 2019

The increasing use of electric vehicles, combined with the trend of higher charging currents, puts a significant strain on the electrical grid. Many solutions to this problem are being discussed, some relying on some form of smart grid, others proposing stricter regulations concerning charging electric vehicles. In this study, a different approach, called randomly delayed charging, is explored. The main idea is to charge a battery over night, but instead of starting the charging process as soon as possible, introduce a random delay, satisfying the boundary condition that the battery is sufficiently charged in the morning. Benefits of this technique are investigated by using an agent-based simulation that simulates commuters and calculates the electricity demand with temporal resolution. Results suggest that randomly delayed charging can have a significant effect on peak load caused by charging and that this benefit increases the higher the used charging current is. Randomly delayed charging can be a viable option for reducing the peak electricity demand that is caused by charging electric vehicles.