bluuebunny/crossref_metadata_2025 huggingface dataset:
Colchicine-Binding Site Inhibitors from Chemistry to Clinic: A Review
Authors: McLoughlin Eavan C. , O’Boyle Niamh M.
Published: January 2020

It is over 50 years since the discovery of microtubules, and they have become one of the most important drug targets for anti-cancer therapies. Microtubules are predominantly composed of the protein tubulin, which contains a number of different binding sites for small-molecule drugs. There is continued interest in drug development for compounds targeting the colchicine-binding site of tubulin, termed colchicine-binding site inhibitors (CBSIs). This review highlights CBSIs discovered through diverse sources: from natural compounds, rational design, serendipitously and via high-throughput screening. We provide an update on CBSIs reported in the past three years and discuss the clinical status of CBSIs. It is likely that efforts will continue to develop CBSIs for a diverse set of cancers, and this review provides a timely update on recent developments.
Development of Level A In Vitro–Vivo Correlation for Electrosprayed Microspheres Containing Leuprolide: Physicochemical, Pharmacokinetic, and Pharmacodynamic Evaluation
Authors: Lee Dong-Seok , Kang Dong Wook , Choi Go-Wun , Choi Han-Gon , Cho Hea-Young
Published: January 2020

This study optimized the preparation of electrosprayed microspheres containing leuprolide and developed an in vitro–in vivo correlation (IVIVC) model that enables mutual prediction between in vitro and in vivo dissolution. The pharmacokinetic (PK) and pharmacodynamic (PD) study of leuprolide was carried out in normal rats after subcutaneous administration of electrosprayed microspheres. The parameters of the IVIVC model were estimated by fitting the PK profile of Lucrin depot® to the release compartment of the IVIVC model, thus the in vivo dissolution was predicted from the in vitro dissolution. From this correlation, the PK profile of leuprolide was predicted from the results of in vivo dissolution. The IVIVC model was validated by estimating percent prediction error (%PE) values. Among prepared microspheres, an optimal formulation was selected using the IVIVC model. The maximum plasma concentration and the area under the plasma concentration–time curve from zero to infinity from the predicted PK profile were 4.01 ng/mL and 52.52 h·ng/mL, respectively, and from the observed PK profile were 4.14 ng/mL and 56.95 h·ng/mL, respectively. The percent prediction error values of all parameters did not exceed 15%, thus the IVIVC model satisfies the validation criteria of the Food and Drug Administration (FDA) guidance. The PK/PD evaluation suggests that the efficacy of OL5 is similar to Lucrin depot®, but the formulation was improved by reducing the initial burst release.
The Complete Chloroplast Genomes of Two Lespedeza Species: Insights into Codon Usage Bias, RNA Editing Sites, and Phylogenetic Relationships in Desmodieae (Fabaceae: Papilionoideae)
Authors: Somaratne Yamuna , Guan De-Long , Wang Wen-Qiang , Zhao Liang , Xu Sheng-Quan
Published: January 2020

The genus Lespedeza (tribe: Desmodieae) consists of about 40 species that have high medicinal and economic value. However, in this genus, using morphological characters, the species identification is quite complicated, which can be solved by the analysis of the complete chloroplast genomes. As primary organelle genomes, the complete genome sequences of chloroplasts (cp) provide unique molecular information to study the divergence of species, RNA editing, and phylogeny. Therefore, to the best of our knowledge, for the first time, we sequenced the complete cp genomes of two representative Lespedeza species: Lespedeza davurica and Lespedeza cuneata. The cp genomes of both the species were found to be 149,010 bp in length, exhibiting the typical angiosperm chloroplast structure containing four regions. The Lespedeza cp genomes showed similar conserved gene contents, order, and orientations with a total GC content of 35.0%. A total of 128 genes, including 83 protein-coding genes, 37 tRNAs, and eight rRNAs, were identified from each genome. Unique molecular features of the two Lespedeza cp genome sequences were obtained by performing the analysis of repeats, sequence divergence, codon usage, and predicting the RNA editing sites in addition to phylogenetic analysis with other key genera in tribe Desmodieae. Using the two datasets, the phylogenetic relationship of Lespedeza species among Deasmodieae was discovered, suggesting that whole cp genomes provided useful information for phylogenetic studies of these species.
The Role of Major Transcription Factors in Solanaceous Food Crops under Different Stress Conditions: Current and Future Perspectives
Authors: Tolosa Lemessa Negasa , Zhang Zhengbin
Published: January 2020

Plant growth, development, and productivity are adversely affected by environmental stresses such as drought (osmotic stress), soil salinity, cold, oxidative stress, irradiation, and diverse diseases. These impacts are of increasing concern in light of climate change. Noticeably, plants have developed their adaptive mechanism to respond to environmental stresses by transcriptional activation of stress-responsive genes. Among the known transcription factors, DoF, WRKY, MYB, NAC, bZIP, ERF, ARF and HSF are those widely associated with abiotic and biotic stress response in plants. Genome-wide identification and characterization analyses of these transcription factors have been almost completed in major solanaceous food crops, emphasizing these transcription factor families which have much potential for the improvement of yield, stress tolerance, reducing marginal land and increase the water use efficiency of solanaceous crops in arid and semi-arid areas where plant demand more water. Most importantly, transcription factors are proteins that play a key role in improving crop yield under water-deficient areas and a place where the severity of pathogen is very high to withstand the ongoing climate change. Therefore, this review highlights the role of major transcription factors in solanaceous crops, current and future perspectives in improving the crop traits towards abiotic and biotic stress tolerance and beyond. We have tried to accentuate the importance of using genome editing molecular technologies like CRISPR/Cas9, Virus-induced gene silencing and some other methods to improve the plant potential in giving yield under unfavorable environmental conditions.
Flexible TiO2/PVDF/g-C3N4 Nanocomposite with Excellent Light Photocatalytic Performance
Authors: Zhou Tong-Tong , Zhao Feng-He , Cui Yu-Qian , Chen Li-Xiang , Yan Jia-Shu , Wang Xiao-Xiong , Long Yun-Ze
Published: January 2020

As the world faces water shortage and pollution crises, the development of novel visible light photocatalysts to purify water resources is urgently needed. Over the past decades, most of the reported photocatalysts have been in powder or granular forms, creating separation and recycling difficulties. To overcome these challenges, a flexible and recyclable heterostructured TiO2/polyvinylidene fluoride/graphitic carbon nitride (TiO2/PVDF/g-C3N4) composite was developed by combining electrospinning, sintering and hydrothermal methods. In the composite, PVDF was used as a support template for removing and separating the photocatalyst from solution. Compared with pure TiO2, the TiO2/PVDF/g-C3N4 composite exhibited the extended light capture range of TiO2 into the visible light region. The photogenerated carriers were efficiently transferred and separated at the contact interface between TiO2 and g-C3N4 under visible light irradiation, which consequently increased the photocatalytic activity of the photocatalyst. In addition, the flexible composites exhibited excellent self-cleaning properties, and the dye on the photocatalysts was completely degraded by the as-prepared materials. Based on the intrinsic low cost, recyclability, absorption of visible light, facile synthesis, self-cleaning properties and good photocatalytic performances of the composite, the photocatalyst is expected to be used for water treatment.
Electrically-Tunable Blue Phase Liquid Crystal Microlens Array Based on a Photoconductive Film
Authors: Huang Bing-Yau , Huang Shuan-Yu , Chuang Chia-Hsien , Kuo Chie-Tong
Published: January 2020

This paper proposes an effective approach to fabricate a blue phase liquid crystal (BPLC) microlens array based on a photoconductive film. Owing to the characteristics of photo-induced conducting polymer polyvinylcarbazole (PVK), in which conductivity depends on the irradiation of UV light, a progressive mask resulting in the variation of conductivity is adopted to produce the gradient distribution of the electric field. The reorientations of liquid crystals according to the gradient distribution of the electric field induce the variation of the refractive index. Thus, the incident light experiences the gradient distribution of the refractive index and results in the focusing phenomenon. The study investigates the dependence of lens performance on UV exposure time, the focal length of the lens, and focusing intensities with various incident polarizations. The BPLC microlens array exhibits advantages such as electrically tunability, polarization independence, and fast response time.
Phase Transition and Melt-Recrystallization Behavior of Poly(Butylene Adipate) Investigated by Simultaneous Measurements of Wide-Angle X-Ray Diffraction (WAXD) and Differential Scanning Calorimetry (DSC)
Authors: Wang Mengfan , Cao Weiyu
Published: January 2020

Simultaneous measurements of wide-angle X-ray diffraction (WAXD) and differential scanning calorimetry (DSC) were carried out to investigate the phase transition and melting behaviors of poly(butylene adipate) (PBA). Thermal expansion changes along the a and b axes of the β form unit cell are different from each other during the heating process. At the beginning of the β to αH (high-temperature α phase) phase transition, the β phase melts very fast, while the recrystallization of the αH phase is delayed and slowed. With the further increment of the temperature, the melting rate of the β phase slows down, while the recrystallization of the αH phase accelerates. The diffraction peak intensity ratios of the β(020):β(110) and αH(020):αH(110) diffraction peaks during the first heating process have similar value. However, the above value is different from the value of α(020):α(110) during the following melt-crystallization process. This difference comes from the different orientations of the crystal lattices of the α and αH(β) crystals to the substrate plane, which indicates that the αH phase inherits the orientation of the β phase during phase transition and the orientation of αH form crystals is different from the α form crystals that crystallized from the melt.
Improved Hydrophobicity and Dimensional Stability of Wood Treated with Paraffin/Acrylate Compound Emulsion through Response Surface Methodology Optimization
Authors: Jiang Jun , Chen Yupeng , Cao Jinzhen , Mei Changtong
Published: January 2020

Wood treatment was conducted by paraffin/acrylate compound emulsion. Response surface methodology (RSM) was applied for modeling and to determine the relationship between hydrophobicity and influencing factors. The results showed that the paraffin emulsion concentration and acrylate emulsion percentage had significant influences on water absorption (WA) and mass percentage gain (MG). The WA decreased obviously with increasing acrylate emulsion percentage. The correlation models for WA and MG showed a good prediction due to the straight-line distribution in the normal probability plot of residuals. The optimal conditions (5.57% paraffin emulsion concentration, 20% acrylate emulsion percentage, and 10 min treatment time) provided by RSM were acceptable for predicting the MG and WA. Compared to untreated (66°) and paraffin emulsion treated wood (94°), the wood treated by compound emulsion showed the highest water contact angle (133°) and better dimensional stability. This could be ascribed to a synergistic effect (bulking effect and filling effect) provided by paraffin and acrylate, which could form a completely hydrophobic film in wood.
Enhancement of Flame Retardancy of Colorless and Transparent Semi-Alicyclic Polyimide Film from Hydrogenated-BPDA and 4,4′-oxydianiline via the Incorporation of Phosphazene Oligomer
Authors: Wu Xiao , Jiang Ganglan , Zhang Yan , Wu Lin , Jia Yanjiang , Tan Yaoyao , Liu Jingang , Zhang Xiumin
Published: January 2020

Enhancement of flame retardancy of a colorless and transparent semi-alicyclic polyimide (PI) film was carried out by the incorporation of phosphazene (PPZ) flame retardant (FR). For this purpose, PI-1 matrix was first synthesized from hydrogenated 3,3′,4,4′-biphenyltetracarboxylic dianhydride (HBPDA) and 4,4′-oxydianiline (ODA). The soluble PI-1 resin was dissolved in N,N-dimethylacetamide (DMAc) to afford the PI-1 solution, which was then physically blended with PPZ FR with the loading amounts in the range of 0–25 wt.%. The PPZ FR exhibited good miscibility with the PI-1 matrix when its proportion was lower than 10 wt.% in the composite films. PI-3 composite film with the PPZ loading of 10 wt.% showed an optical transmittance of 75% at the wavelength of 450 nm with a thickness of 50 μm. More importantly, PI-3 exhibited a flame retardancy class of UL 94 VTM-0 and reduced total heat release (THR), heat release rate (HRR), smoke production rate (SPR), and rate of smoke release (RSR) values during combustion compared with the original PI-1 film. In addition, PI-3 film had a limiting oxygen index (LOI) of 30.9%, which is much higher than that of PI-1 matrix (LOI: 20.1%). Finally, incorporation of PPZ FR decreased the thermal stability of the PI films. The 10% weight loss temperature (T10%) and the glass transition temperature (Tg) of the PI-3 film were 411.6 °C and 227.4 °C, respectively, which were lower than those of the PI-1 matrix (T10%: 487.3 °C; Tg: 260.6 °C)
Design and Implementation of a Connection between Augmented Reality and Sensors
Authors: Aguero Marlon , Maharjan Dilendra , Rodriguez Maria del Pilar , Mascarenas David Dennis Lee , Moreu Fernando
Published: January 2020

Wireless sensor networks (WSN) are used by engineers to record the behavior of structures. The sensors provide data to be used by engineers to make informed choices and prioritize decisions concerning maintenance procedures, required repairs, and potential infrastructure replacements. However, reliable data collection in the field remains a challenge. The information obtained by the sensors in the field frequently needs further processing, either at the decision-making headquarters or in the office. Although WSN allows data collection and analysis, there is often a gap between WSN data analysis results and the way decisions are made in industry. The industry depends on inspectors’ decisions, so it is of vital necessity to improve the inspectors’ access in the field to data collected from sensors. This paper presents the results of an experiment that shows the way Augmented Reality (AR) may improve the availability of WSN data to inspectors. AR is a tool which overlays the known attributes of an object with the corresponding position on the headset screen. In this way, it allows the integration of reality with a virtual representation provided by a computer in real time. These additional synthetic overlays supply data that may be unavailable otherwise, but it may also display additional contextual information. The experiment reported in this paper involves the application of a smart Strain Gauge Platform, which automatically measures strain for different applications, using a wireless sensor. In this experiment, an AR headset was used to improve actionable data visualization. The results of the reported experiment indicate that since the AR headset makes it possible to visualize information collected from the sensors in a graphic form in real time, it enables automatic, effective, reliable, and instant communication from a smart low-cost sensor strain gauge to a database. Moreover, it allows inspectors to observe augmented data and compare it across time and space, which then leads to appropriate prioritization of infrastructure management decisions based on accurate observations.
Feasibility Study of Tractor-Test Vehicle Technique for Practical Structural Condition Assessment of Beam-Like Bridge Deck
Authors: Yang Yang , Cheng Quan , Zhu Yuanhao , Wang Lilei , Jin Ruoyu
Published: January 2020

The tractor-test vehicle technique of non-destructive testing for indirect measurement of the modal properties of a bridge deck is revisited in this paper with several improvements for possible practical application to the structural condition assessment of a beam-like bridge deck. The effect of damping of the vehicle-bridge system is considered and the modal properties from only the first vibration mode of the structure will be used for a quick and simple assessment. The two test vehicles are designed to have the same modal frequency and damping ratio but with parameters in the follower No.2 test vehicle proportional to those in the follower No.1 test vehicle. This effectively removes the effect of road surface roughness in the response of an equivalent vehicle such that the error in the subsequent condition assessment is reduced. Through data collected on-sitetransmitted to theremote computer platform, a simple technique based on the moment-curvature relationship acceptable to practical engineers is adopted for the condition assessment with improvements in the estimation of the element bending stiffness of the deck. Scenarios with different damping, vehicle speed, road surface roughness, and local damages in the bridge structure are studied with or without temperature effect in the measurement. Through numerical simulations and field tests, the tractor-test vehicle technique of non-destructive testing with the proposed modifications and improvements has been demonstrated to give consistently accurate estimates of the element bending stiffness of the bridge deck but with a small error close to the end of the deck.
Simulation Study of Moon-Based InSAR Observation for Solid Earth Tides
Authors: Wu Kai , Ji Ce , Luo Lei , Wang Xinyuan
Published: January 2020

The observation of solid earth tides (SET) provides an important basis for understanding the structure of the earth’s interior, and has long been the focus of research in geoscience. However, actually, there still exist some limitations in capturing its global-scale information only with ground stations. Remote sensing technology can realize large-scale deformation monitoring of high point density constantly. However, it is still difficult for the artificial satellite system to meet the requirements of SET monitoring in terms of field of view and temporal resolution now. In this work, the moon is hypothesized as a new platform for SET observation combined with interferometric synthetic aperture radar (InSAR) technology. Based on the tidal model and lunar ephemeris, the spatial and temporal characteristics of the SET from the lunar view were analyzed. Furthermore, the calculations demonstrate that more abundant SET information can be observed in this view. After comparing various observation modes, the single-station with repeat-pass differential InSAR was selected for this simulation. We mainly considered the restriction of observation geometry on moon-based InSAR under three signal bandwidths, thereby providing a reference for the sensor design. The results demonstrate that the moon-based platform offers the potential to become an optimal SET observation method.
A Multi-Scale and Multi-Level Spectral-Spatial Feature Fusion Network for Hyperspectral Image Classification
Authors: Mu Caihong , Guo Zhen , Liu Yi
Published: January 2020

Extracting spatial and spectral features through deep neural networks has become an effective means of classification of hyperspectral images. However, most networks rarely consider the extraction of multi-scale spatial features and cannot fully integrate spatial and spectral features. In order to solve these problems, this paper proposes a multi-scale and multi-level spectral-spatial feature fusion network (MSSN) for hyperspectral image classification. The network uses the original 3D cube as input data and does not need to use feature engineering. In the MSSN, using different scale neighborhood blocks as the input of the network, the spectral-spatial features of different scales can be effectively extracted. The proposed 3D–2D alternating residual block combines the spectral features extracted by the three-dimensional convolutional neural network (3D-CNN) with the spatial features extracted by the two-dimensional convolutional neural network (2D-CNN). It not only achieves the fusion of spectral features and spatial features but also achieves the fusion of high-level features and low-level features. Experimental results on four hyperspectral datasets show that this method is superior to several state-of-the-art classification methods for hyperspectral images.
Detecting Forest Disturbance and Recovery in Primorsky Krai, Russia, Using Annual Landsat Time Series and Multi–Source Land Cover Products
Authors: Hu Yang , Hu Yunfeng
Published: January 2020

The spatial distribution and dynamic changes of the forests in Primorsky Krai, Russia, are of great significance for regional ecological security and sustainable economic and societal development. With the support of the Google Earth Engine cloud computing platform, we first synthesized yearly Landsat surface reflectance images of the best quality of the research area and then used the random forest method to calculate the forest classification probability of the study area year by year from 1998 to 2015. Furthermore, we used a time–series segmentation algorithm to perform temporal trajectory segmentation for forest classification probability estimation, and determined the spatial and temporal distribution characteristics and change laws of the forest. We extended the existing algorithms and parameters of forest classification probability trajectory analysis, achieving a high overall accuracy (86.2%) in forest change detection in the study area. The extended method can accurately capture the time node information of the changes. In the present research we observed: (1) that from 1998 to 2015, the forest area of the whole district showed a net loss state, with a loss area of 0.56 × 106 ha, of which the cumulative forest disturbance area reached 1.12 × 106 ha, and the cumulative forest recovery area reached 0.55 × 106 ha; and (2) that more than 90% of the forest change occurred in areas with a slope of less than 18°, at a distance of less than 20 km from settlements, and at a distance of less than 10 km from roads. The forest disturbance monitoring results are consistent with the changes in official statistical results over time, but there was a 20% overestimation. The technical method we extended in this study can be used as a reference for large–scale and high–precision dynamic monitoring of the forests in Russia’s Far East and other regions of the world; it also provides a basis for estimating illegal timber harvesting and determining the appropriate amount of forest harvested.
Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data
Authors: Park Sang-Eun , Jung Yoon Taek
Published: January 2020

Remote sensing, particularly using synthetic aperture radar (SAR) systems, can be an effective tool in detecting and assessing the area and amount of building damages caused by earthquake or tsunami. Several studies have provided experimental evidence for the importance of polarimetric SAR observations in building damage detection and assessment, particularly caused by a tsunami. This study aims to evaluate the practical applicability of the polarimetric SAR observations to building damage caused by the direct ground-shaking of an earthquake. The urban areas heavily damaged by the 2016 Kumamoto earthquake in Japan have been investigated by using the polarimetric PALSAR-2 data acquired in pre- and post-earthquake conditions. Several polarimetric change detection approaches, such as the changes of polarimetric scattering powers, the matrix dissimilarity measures, and changes of the radar scattering mechanisms, were examined. Optimal damage indicators in the presence of significant natural changes, and a novel change detection method by the fuzzy-based fusion of polarimetric damage indicators are proposed. The accuracy analysis results show that the proposed automatic classification method can successfully detect the selected damaged areas with a detection rate of 90.9% and false-alarm rate of 1.3%.
Generating High Resolution LAI Based on a Modified FSDAF Model
Authors: Zhai Huan , Huang Fang , Qi Hang
Published: January 2020

Leaf area index (LAI) is an important parameter for monitoring the physical and biological processes of vegetation canopy. Due to the constraints of cloud contamination, snowfall, and instrument conditions, most of the current satellite remote sensing LAI products have lower resolution that cannot satisfy the needs of vegetation remote sensing application in areas of high heterogeneity. We proposed a new model to generate high resolution LAI, by combining linear pixel unmixing and the Flexible Spatiotemporal Data Fusion (FSDAF) method. This method derived the input data of FSDAF by downscaling the MODIS (Moderate Resolution Imaging Spectroradiometer) data with a linear spectral mixture model. Through the improved input parameters of the algorithm, the fusion of MODIS LAI and LAI at Landsat spatial resolution estimated by Support Vector Regression model was realized. The fusion accuracy of generated LAI data was validated based on Sentinel-2 LAI products. The results showed that strong correlation between predicted LAI and Sentinel-2 LAI in sample sites was observed with higher correlation coefficients and lower Root Mean Square Error. Compared to the simulation results of FSDAF, the modified FSDAF model showed higher accuracy and reflected more spatial details in the boundary areas of different land cover types.
Integration of Time Series Sentinel-1 and Sentinel-2 Imagery for Crop Type Mapping over Oasis Agricultural Areas
Authors: Sun Luyi , Chen Jinsong , Guo Shanxin , Deng Xinping , Han Yu
Published: January 2020

Timely and accurate crop type mapping is a critical prerequisite for the estimation of water availability and environmental carrying capacity. This research proposed a method to integrate time series Sentinel-1 (S1) and Sentinel-2 (S2) data for crop type mapping over oasis agricultural areas through a case study in Northwest China. Previous studies using synthetic aperture radar (SAR) data alone often yield quite limited accuracy in crop type identification due to speckles. To improve the quality of SAR features, we adopted a statistically homogeneous pixel (SHP) distributed scatterer interferometry (DSI) algorithm, originally proposed in the interferometric SAR (InSAR) community for distributed scatters (DSs) extraction, to identify statistically homogeneous pixel subsets (SHPs). On the basis of this algorithm, the SAR backscatter intensity was de-speckled, and the bias of coherence was mitigated. In addition to backscatter intensity, several InSAR products were extracted for crop type classification, including the interferometric coherence, master versus slave intensity ratio, and amplitude dispersion derived from SAR data. To explore the role of red-edge wavelengths in oasis crop type discrimination, we derived 11 red-edge indices and three red-edge bands from Sentinel-2 images, together with the conventional optical features, to serve as input features for classification. To deal with the high dimension of combined SAR and optical features, an automated feature selection method, i.e., recursive feature increment, was developed to obtain the optimal combination of S1 and S2 features to achieve the highest mapping accuracy. Using a random forest classifier, a distribution map of five major crop types was produced with an overall accuracy of 83.22% and kappa coefficient of 0.77. The contribution of SAR and optical features were investigated. SAR intensity in VH polarization was proved to be most important for crop type identification among all the microwave and optical features employed in this study. Some of the InSAR products, i.e., the amplitude dispersion, master versus slave intensity ratio, and coherence, were found to be beneficial for oasis crop type mapping. It was proved the inclusion of red-edge wavelengths improved the overall accuracy (OA) of crop type mapping by 1.84% compared with only using conventional optical features. In comparison, it was demonstrated that the synergistic use of time series Sentinel-1 and Sentinel-2 data achieved the best performance in the oasis crop type discrimination.
Spectral Analysis of Satellite Altimeter and Tide Gauge Data around the Northern Australian Coast
Authors: Gharineiat Zahra , Deng Xiaoli
Published: January 2020

The north of Australia is known for its complex tidal system, where the highest astronomical tides (HATs) reach 12 m. This paper investigates the tidal behaviour in this region by developing spectral climatology for tide gauge and altimetry data. Power spectral density analysis is applied to detect the magnitude of ocean tides in 20 years of sea-level data from multimission satellite altimeters and tide gauges. The spectra of altimetry sea level anomaly (SLA) time series have their strongest peaks centred at approximately 2.11, 5.88, and 7.99 cycles per year (cpy), corresponding to the diurnal and semidiurnal tidal constituents K1, M2, and O1, respectively. Closer to the coastline, the spectra peak at high-frequency overtide and shallow-water constituents such as M4, MK4, and MK3. There have been many large, high-frequency spectral peaks near the coastline, indicating the difficulty of predicting tidal signals by coastal altimetry. Similar to altimetry observations, there are dominant semidiurnal and diurnal tidal peaks in tide gauge SLA time series accompanying a number of overtides. The semidiurnal and diurnal peaks are mostly higher on the northwest coast of Australia compared with the north and northeast coast. The results from both altimetry and tide gauges indicate that tidal range increases with increasing continental shelf.
Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China
Authors: Yao Wutao , Ma Yong , Chen Fu , Xiao Zhishu , Shu Zufei , Chen Lijun , Xiao Wenhong , Liu Jianbo , Jiang Liyuan , Zhang Shuyan
Published: January 2020

Ice storms greatly affect the structure, dynamics, and functioning of forest ecosystems. Studies on the impact of such disasters, as well as the post-disaster recovery of forests, are important contents in forest biology, ecology, and geography. Remote-sensing technology provides data and methods that can support the study of disasters at the large-to-medium scale and over long time periods. This study took Chebaling National Nature Reserve in Guangdong Province, China, as the study area. First, field-survey data and remote-sensing data were comprehensively analyzed to demonstrate the feasibility of replacing the forest stock volume with the mean annual value of the Enhanced Vegetation Index (EVI), to study forest growth and change. We then used the EVI from 2007 to 2017, together with a variety of other remote-sensing and forest sub-compartment data, to analyze the impact of the 2008 ice storm and the subsequent post-disaster recovery of the forest. Finally, we drew the following conclusions: (1) Topography had a considerable effect on disaster impact and forest recovery in Chebaling. The forest at high altitudes (700–1000 m) and on steep slopes (25–40°) was seriously affected by this disaster but had a stronger post-disaster recovery ability. Meanwhile, the hardest-hit area for coniferous forest was higher and steeper than that for broad-leaved forest. (2) In the same terrain conditions, coniferous forests were less affected by the disaster than broad-leaved forests and showed less variation during the post-disaster recovery process. Nevertheless, broad-leaved forests had faster recovery rates and higher recovery degrees; (3) Under the influence of human activities, the recovery and fluctuation degree for planted forest in the post-disaster recovery process was significantly higher than that for natural forest. The study suggests that forest has high disaster resistance and self-recovery ability after the ice storm, and this ability has a strong correlation with the type of forest and the topographic factors such as elevation and slope. At the same time, human intervention can speed up the recovery of forests after disasters.
A Sensitivity Study of the 4.8 µm Carbon Dioxide Absorption Band in the MWIR Spectral Range
Authors: Romaniello Vito , Spinetti Claudia , Silvestri Malvina , Buongiorno Maria Fabrizia
Published: January 2020

The measurements of gas concentrations in the atmosphere are recently developed thanks to the availability of gases absorbing spectral channels in space sensors and strictly depending on the instrument performances. In particular, measuring the sources of carbon dioxide is of high interest to know the distribution, both spatial and vertical, of this greenhouse gas and quantify the natural/anthropogenic sources. The present study aims to understand the sensitivity of the CO2 absorption band at 4.8 µm to possibly detect and measure the spatial distribution of emissions from point sources (i.e., degassing volcanic plumes, fires, and industrial emissions). With the aim to define the characteristics of future multispectral imaging space radiometers, the performance of the CO2 4.8 µm absorption band was investigated. Simulations of the “Top of Atmosphere” (TOA) radiance have been performed by using real input data to reproduce realistic scenarios on a volcanic high elevation point source (>2 km): actual atmospheric background of CO2 (~400 ppm) and vertical atmospheric profiles of pressure, temperature, and humidity obtained from probe balloons. The sensitivity of the channel to the CO2 concentration has been analyzed also varying surface temperatures as environmental conditions from standard to high temperature. Furthermore, response functions of operational imaging sensors in the middle wave infrared spectral region were used. The channel width values of 0.15 µm and 0.30 µm were tested in order to find changes in the gas concentration. Simulations provide results about the sensitivity necessary to appreciate carbon dioxide concentration changes considering a target variation of 10 ppm in gas column concentration. Moreover, the results show the strong dependence of at-sensor radiance on the surface temperature: radiances sharply increase, from 1 Wm−2sr−1µm−1 (in the “standard condition”) to >1200 Wm−2sr−1µm−1 (in the warmest case) when temperatures increase from 300 to 1000 K. The highest sensitivity has been obtained considering the channel width equal to 0.15 µm with noise equivalent delta temperature (NEDT) values in the range from 0.045 to 0.56 K at surface temperatures ranging from 300 to 1000 K.
Accurate Simulation of Ice and Snow Runoff for the Mountainous Terrain of the Kunlun Mountains, China
Authors: Duan Yongchao , Liu Tie , Meng Fanhao , Yuan Ye , Luo Min , Huang Yue , Xing Wei , Nzabarinda Vincent , De Maeyer Philippe
Published: January 2020

While mountain runoff provides great potential for the development and life quality of downstream populations, it also frequently causes seasonal disasters. The accurate modeling of hydrological processes in mountainous areas, as well as the amount of meltwater from ice and snow, is of great significance for the local sustainable development, hydropower regulations, and disaster prevention. In this study, an improved model, the Soil Water Assessment Tool with added ice-melt module (SWATAI) was developed based on the Soil Water Assessment Tool (SWAT), a semi-distributed hydrological model, to simulate ice and snow runoff. A temperature condition used to determine precipitation types has been added in the SWATAI model, along with an elevation threshold and an accumulative daily temperature threshold for ice melt, making it more consistent with the runoff process of ice and snow. As a supplementary reference, the comparison between the normalized difference vegetation index (NDVI) and the quantity of meltwater were conducted to verify the simulation results and assess the impact of meltwater on the ecology. Through these modifications, the accuracy of the daily flow simulation results has been considerably improved, and the contribution rate of ice and snow melt to the river discharge calculated by the model increased by 18.73%. The simulation comparison of the flooding process revealed that the accuracy of the simulated peak flood value by the SWATAI was 77.65% higher than that of the SWAT, and the temporal accuracy was 82.93% higher. The correlation between the meltwater calculated by the SWATAI and the NDVI has also improved significantly. This improved model could simulate the flooding processes with high temporal resolution in alpine regions. The simulation results could provide technical support for economic benefits and reasonable reference for flood prevention.
Renewable Energy and Land Use in India: A Vision to Facilitate Sustainable Development
Authors: Kiesecker Joseph , Baruch-Mordo Sharon , Heiner Mike , Negandhi Dhaval , Oakleaf James , Kennedy Christina , Chauhan Pareexit
Published: January 2020

India has committed to reduce emissions with a goal to increase renewable energy production to 175 gigawatts (GW) by 2022. Achieving this objective will involve rapidly increasing the deployment of solar and wind energy, while at the same time addressing the related challenges of the financing requirements, environment impacts, and power grid integration. Developing energy on lands degraded by human activities rather than placing new infrastructure within natural habitats or areas of high production agriculture would reduce cumulative impacts and minimize land use conflicts. We estimated that converted lands have the potential capacity of 1789 GW across India, which is >10 times the 2022 goals. At the same time, the total land footprint needed to meet India’s 2022 renewable energy target is large, ranging from ~55,000 to 125,000 km2, which is roughly the size of Himachal Pradesh or Chhattisgarh, respectively. If renewable energy is advanced with the singular aim of maximizing resource potential, approximately 6700–11,900 km2 of forest land and 24,100–55,700 km2 of agricultural land could be impacted. Subsidies and incentive programs aimed at promoting low-impact renewable energy deployment and establishing mitigation obligations that raise costs for projects that create land-impacts could improve the public support for renewable energy.
Stakeholder Legitimization of the Provision of Emergency Centralized Accommodations to Displaced Persons
Authors: Faure Julie C. , Faust Kasey M. , Kaminsky Jessica
Published: January 2020

Sudden population influxes into cities—such as those seen during post-disaster migration—place unexpected demands on the urban housing system. Decisions made during these influxes are often controversial, potentially hindering the ability of the organizations involved to respond. This study’s objective was to explore strategies (e.g., types of information shared and types of accommodation chosen) that can be used during decision-making processes when providing emergency accommodations to increase stakeholder acceptance, and thus lead to sustainable institutional responses. This study specifically sought to shed light on how, during the Refugee Crisis in Germany of 2015 and 2016, stakeholders legitimized decisions made to provide centralized emergency accommodations to displaced persons. Making this study possible were 25 semi-structured interviews with utility, government, nonprofit, and company employees involved in the provision of centralized accommodations for displaced persons. Interviews were conducted in 2016 and underwent a qualitative analysis. Results indicate that stakeholders primarily legitimized the provision of centralized accommodations based on convictions of right and wrong (moral legitimacy), while they legitimized decisions to not provide such accommodations based on their understanding and experience of practical barriers (cultural-cognitive legitimacy). Recommendations arising from this study include the following: provide information to stakeholders about accommodations’ livability (to gain consequential legitimacy) and past successes (to gain comprehensibility legitimacy), adapt regulations to help stakeholders use procedural legitimacy, and prefer fully renovated buildings or modular housing to buildings with no major renovations or container housing (to gain consequential rather than procedural legitimacy).
The Displacement of Santiago de Chile’s Downtown during 1990–2015: Travel Time Effects on Eradicated Population
Authors: Suazo-Vecino Gonzalo , Muñoz Juan Carlos , Fuentes Arce Luis
Published: January 2020

The center of activities of Santiago de Chile has been continuously evolving towards the eastern part of the city, where the most affluent residents live. This paper characterizes the direction and magnitude of this evolution through an indicator stating how much the built surface area for service purposes grows in different areas in the city. To identify the impact of this evolution, we compare residents’ travel-time distributions from different sectors in the city to the central area. This travel-time comparison is focused on the sectors where informal settlements were massively eradicated between 1978–1985 and those areas where the settlements were relocated. This analysis show that this policy and the consequent evolution of the city were detrimental to the affected families, significantly increasing average travel time to the extended center of the city and inequality among different socioeconomic groups in the city. Although the phenomenon is quite visible to everyone, it has not received any policy reaction from the authority. These findings suggest that middle and low-income sectors would benefit if policies driving the evolution of the center of activities towards them were implemented.
Detecting and Understanding Synergies and Co-Benefits of Low Carbon Development in the Electric Power Industry in China
Authors: Jiang Ping , Alimujiang Adila , Dong Hongjia , Yan Xiaoyu
Published: January 2020

China’s electric power industry contributes a significant amount of carbon emissions as well as air pollutants such as SO2, NOx, and fine particles. In order to detect co-benefits of carbon reduction and air pollution control, this study analyzed the emission reduction, emission reduction factors, and synergistic effect factors of technical and structural emission reduction measures in the electric power industry in the Jiangsu, Zhejiang, and Yunnan provinces and Shanghai City. The main findings are: (1) the structural emission reduction measures in all four regions had positive co-control effects. Therefore, promoting renewables can achieve remarkable co-benefits; (2) the result demonstrated that the direct removal ability of pollutants by technical emission reduction measures was better than the structural emission reduction measures in all four case studies. However, there were no or few carbon reduction co-benefits associated with their utilization; (3) in all cases, CO2 had the highest emission factor value, which means that there is still room for synergistic carbon reduction; (4) air pollutants and CO2 emission intensity from the Yunnan power plants were much higher than that of the other three regions. In order to achieve the overall co-benefits, co-control measures should be promoted and strengthened in western areas such as Yunnan.
An Analytical Model for the Many-to-One Demand Responsive Transit Systems
Authors: Huang Di , Tong Weiping , Wang Lumeng , Yang Xun
Published: January 2020

The demand-responsive transit (DRT) service is an emerging and flexible transit mode to enhance the mobility of the urban transit system by providing personalized services. Passengers can make advanced appointments through smartphone applications. In this paper, an analytical model is proposed for the many-to-one DRT system. The agency and user costs are approximated by closed-form expressions. The agency cost, which is also the operation cost, is approximated by the continuum approximation technique. A nearest-neighbor routing strategy is applied, whereby the vehicle always collects the nearest passenger waiting in the system. The Vickrey queueing theory is adopted as the basis for approximating each component of the user cost, which is composed of the out-of-vehicle and in-vehicle waiting times and schedule deviations, which also depend on the service quality of the DRT system. The results of the numerical experiment show that (1) the agency and user costs are influenced significantly by the demand density, and (2) the DRT operator cannot further decrease the operating cost by solely deploying larger vehicles.
Social Innovation for Sustainability Challenges
Authors: Repo Petteri , Matschoss Kaisa
Published: January 2020

Social innovation is concerned with social mobilization and impact, and is increasingly seen as an option to address sustainability challenges. Nevertheless, the concept of social innovation is quite open in character and requires empirical accommodation to establish how it differs from other types of innovation in this setting. This article contributes empirically to the concept of social innovation as it reviews categories of success factors of social innovation against those of five other innovation types (product, service, governmental, organizational, system) in 202 innovation cases that focus on climate action, environment, resource efficiency and raw materials. Statistical analysis with contingency tables is applied to examine the distribution of five kinds of success factors across the innovation types: economic, environmental, political, social, and technological. The results confirm empirically that social innovation is indeed a distinct type of innovation. There are statistically significant differences in the distribution of categories of success factors between social innovation on the one hand and product, service and governance innovation on the other. In addition to the prevalence of social success factors, social innovation is characterized by a lesser emphasis on political and technological success factors.
Strategy Orientation, Innovation Capacity Endowment, and International R&D Intensity of Listed Companies in China
Authors: He Jianhong , Chen Hongmin , Tsai Fu-Sheng
Published: January 2020

Based on the endogenous factors which can affect the strategy of international R&D of China’s enterprises, an analysis is carried out on the relationship between market- and technology-orientation of the strategy and the intensity of international R&D. In addition, the mediation effects of innovation capacity endowment are discussed. On this basis, 254 listed enterprises with overseas R&D institutions approved by the Ministry of Commerce of China were taken as the sample for survey administration. The poisson regression method was adopted to test the hypotheses. Additionally, we utilized the Bootstrap method to confirm the robustness of the regression models. Results show that for Chinese enterprises with significant international R&D strategy intentions, market orientation has a significant inhibitory effect on their international R&D intensity, while the technology orientation has a significant stimulating effect on international R&D. In addition, innovation capacity has a significant positive impact on the intensity of international R&D, and plays a partial mediating role in the relationship between technology orientation and international R&D. Therefore, to promote international R&D strategies in the era of high-quality economic development, Chinese enterprises are suggested to establish an innovation-oriented strategy orientation to promote innovation cultural heritage, and to strengthen the accumulation of innovative resources and capabilities.