Heat shock protein 60 (HSP60) and heat shock protein 10 (HSP10) are important chaperones, which have been proven to have essential roles in mediating the correct folding of nuclear encoded proteins imported to mitochondria. Mitochondria are known as the power house of the cell, with which it produces energy and respires aerobically. In this regard, the obtained HSP60 and HSP10 have typical characteristics of the HSP60/10 family signature. Their mRNA transcripts detected were highest during the developmental phase (in April), while the lowest levels were found in the resting phase (after spawning in late July). Additionally, the strongest immunolabeling positive signals were found in the primary spermatocyte, with lower positive staining in secondary sperm cells, and a weak or absent level in the mature sperm. At the electron microscopic level, immunogold particles were localized in the mitochondrial matrix. Data indicated that HSP10 and HSP60 were inducible and functional in the Coilia nasus testis development and migration process, suggesting their essential roles in this process. The results also indicated that HSP60 may be one indicator of properly working mitochondrial import and refolding in the fish testis. This study also provides an expanded perspective on the role of heat shock protein families in spawning migration biology. Full article

Building type information is crucial to many urban studies, including fine-resolution population estimation, urban planning, and management. Although scientists have developed many methods to extract buildings via remote sensing data, only a limited number of them focus on further classification of the extracted results. This paper presents a novel building type classification scheme based on the integration of building height information from LiDAR, textural, spectral, and geometric information from high-resolution remote sensing images, and super-object information from the integrated dataset. Building height information is firstly extracted from LiDAR point clouds using a progressive morphological filter and then combined with high-resolution images for object-oriented segmentation. Multi-resolution segmentation of the combined image is performed to collect super-object information, which provides more information for classification in the next step. Finally, the segmentation results, as well as their super-object information, are inputted into the random forest classifier to obtain building type classification results. The classification scheme proposed in this study is tested through applications in two urban village areas, a type of slum-like land use characterized by dense buildings of different types, heights, and sizes, in Guangzhou, China. Segment level classification of the study area and validation area reached accuracies of 80.02% and 76.85%, respectively, while the building-level results reached accuracies of 98.15% and 87.50%, respectively. The results indicate that the proposed building type classification scheme has great potential for application in areas with multiple building types and complex backgrounds. This study also proves that both building height information and super-object information play important roles in building type classification. More accurate results could be obtained by incorporating building height information and super-object information and using the random forest classifier. Full article

Strong coupling between values at different times that exhibit properties of long range dependence, non-stationary, spiky signals cannot be processed by the conventional time series analysis. The autoregressive fractional integral moving average (ARFIMA) model, a fractional order signal processing technique, is the generalization of the conventional integer order models—autoregressive integral moving average (ARIMA) and autoregressive moving average (ARMA) model. Therefore, it has much wider applications since it could capture both short-range dependence and long range dependence. For now, several software programs have been developed to deal with ARFIMA processes. However, it is unfortunate to see that using different numerical tools for time series analysis usually gives quite different and sometimes radically different results. Users are often puzzled about which tool is suitable for a specific application. We performed a comprehensive survey and evaluation of available ARFIMA tools in the literature in the hope of benefiting researchers with different academic backgrounds. In this paper, four aspects of ARFIMA programs concerning simulation, fractional order difference filter, estimation and forecast are compared and evaluated, respectively, in various software platforms. Our informative comments can serve as useful selection guidelines. Full article

Degraded air quality by PM_2.5 can cause various health problems. Satellite observations provide abundant data for monitoring PM_2.5 pollution. While satellite-derived products, such as aerosol optical depth (AOD) and normalized difference vegetation index (NDVI), have been widely used in estimating PM_2.5 concentration, little research was focused on the use of remotely sensed nighttime light (NTL) imagery. This study evaluated the merits of using NTL satellite images in predicting ground-level PM_2.5 at a regional scale. Geographically weighted regression (GWR) was employed to estimate the PM_2.5 concentration and analyze its relationships with AOD, meteorological variables, and NTL data across the New England region. Observed data in 2013 were used to test the constructed GWR models for PM_2.5 prediction. The Vegetation Adjusted NTL Urban Index (VANUI), which incorporates Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI into NTL to overcome the defects of NTL data, was used as a predictor variable for final PM_2.5 prediction. Results showed that Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) NTL imagery could be an important dataset for more accurately estimating PM_2.5 exposure, especially in urbanized and densely populated areas. VANUI data could obviously improve the performance of GWR for the warm season (GWR model with VANUI performed 17% better than GWR model without NDVI and NTL data and 7.26% better than GWR model without NTL data in terms of RMSE), while its improvements were less obvious for the cold season (GWR model with VANUI performed 3.6% better than the GWR model without NDVI and NTL data and 1.83% better than the GWR model without NTL data in terms of RMSE). Moreover, the spatial distribution of the estimated PM_2.5 levels clearly revealed patterns consistent with those densely populated areas and high traffic areas, implying a close and positive correlation between VANUI and PM_2.5 concentration. In general, the DMSP/OLS NTL satellite imagery is promising for providing additional information for PM_2.5 monitoring and prediction. Full article

Quantifying vegetation fractional cover (VFC) and assessing its role in heat fluxes modeling using medium resolution remotely sensed data has received less attention than it deserves in heterogeneous urban regions. This study examined two approaches (Normalized Difference Vegetation Index (NDVI)-derived and Multiple Endmember Spectral Mixture Analysis (MESMA)-derived methods) that are commonly used to map VFC based on Landsat imagery, in modeling surface heat fluxes in urban landscape. For this purpose, two different heat flux models, Two-source energy balance (TSEB) model and Pixel Component Arranging and Comparing Algorithm (PCACA) model, were adopted for model evaluation and analysis. A comparative analysis of the NDVI-derived and MESMA-derived VFCs showed that the latter achieved more accurate estimates in complex urban regions. When the two sources of VFCs were used as inputs to both TSEB and PCACA models, MESMA-derived urban VFC produced more accurate urban heat fluxes (Bowen ratio and latent heat flux) relative to NDVI-derived urban VFC. Moreover, our study demonstrated that Landsat imagery-retrieved VFC exhibited greater uncertainty in obtaining urban heat fluxes for the TSEB model than for the PCACA model. Full article

In this paper, an analytical model is proposed to analyze and predict the characteristics of a double stator linear and rotary permanent magnet machine (DSLRPMM). In order to simplify the magnetic field calculation, the DSLRPMM is cut along the axial direction (z direction) and transferred into a planar one. Hence, an analytical model of the machine considered the orthogonal effect (OE) is proposed based on the combined solution of Maxwell’s equation, conformal mapping, and equivalent magnetic circuit model (EMCM). The magnetic field distributions of the DSLRPMM are calculated with and without considering the OE, and some important electromagnetic parameters, including the back electromotive force (EMF), detent force, cogging torque, and output torque and thrust, are also predicted and compared to the 3D finite element analysis (FEA). The results show that the errors between the proposed analytical model and the 3D FEA results are less than 0.2% and even less than 0.1% for certain parameters, that is, the results obtained from the proposed analytical model agree well with that of the FEA. Moreover, the analyzed and predicted results are also verified by the experimental results on the prototype of the DSLRPMM. Full article

Abstract: Presently, most nanofiltration membranes are prepared with non-biodegradable petrochemical materials. This process is harmful to the ecosystem and consumes a large amount of non-renewable energy. In this study, biodegradable and biocompatible antibacterial cellulose/chitosan nanofiltration membranes (BC/CS-NFMs) were fabricated and characterized for their mechanical strength, antimicrobial activity, salt and dye filtration performance, and polyethylene glycol (PEG) retention using Thermal gravimetric analysis (TGA), Field emission scanning electron microscopy(FE-SEM), Fourier transform infrared spectroscopy(FT-IR), and X-ray diffraction (XRD). The BC/CS-NFMs were obtained by the hydrolysis and carboxymethylation of dense cellulose/chitosan membranes (BC/CSMs). The tensile strength of the BC/CS-NFMs decreased as the chitosan content increased. In addition, the thermal stability and antibacterial ability of the BC/CS-NFMs improved. The pore size is less than 1 nm, and a spongy, layered structure is observed in the cross-sectional FE-SEM images. FT-IR analysis shows that a part of the hydroxyl in cellulose transforms to carboxymethyl during the hydrolysis and carboxymethylation of the BC/CSMs. No obvious changes can be observed in the cellulose and chitosan after the blend membrane formation from the XRD measurements. Based on the experimental results on the permeation and rejection of BC/CS-NFMs, different proportions of cellulose and chitosan nanofiltration membranes almost did not affect the water flux and rejection rate. The BC/CS-NFMs showed better water flux and a higher rejection rate in aqueous dye-salt solutions. Full article

This study addresses the effects of the SOC (State of Charge) and the charging–discharging process on the thermal runaway of 18650 lithium-ion batteries. A series of experiments were conducted on an electric heating and testing apparatus. The experimental results indicate that 6 W is the critical heating power for 40% SOC. With a 20 W constant heating rate, the thermal runaway initial temperature of the lithium-ion battery decreases with the increasing SOC. The final thermal runaway temperature increases with the SOC when the SOC is lower than 80%. However, a contrary conclusion was obtained when the SOC was higher than 80%. Significant mass loss, accompanied by an intense exothermic reaction, took place under a higher SOC. The critical charging current, beyond which the thermal runaway occurs, was found to be 2.6 A. The thermal runaway initial temperature decreases with the increasing charging current, while the intensity of the exothermic reaction varies inversely. Mass ejection of gas and electrolytes exists during thermal runaway when the charging current is higher than 10.4 A, below which only a large amount of gas is released. The thermal runaway initial temperature of discharging is higher than that of non-discharging. Full article

Improving the estimation accuracy for the energy consumption of electric vehicles (EVs) would greatly contribute to alleviating the range anxiety of drivers and serve as a critical basis for the planning, operation, and management of charging infrastructures. To address the challenges in energy consumption estimation encountered due to sparse Global Positioning System (GPS) observations, an estimation model is proposed that considers both the kinetic characteristics from sparse GPS observations and the unique attributes of EVs: (1) work opposing the rolling resistance; (2) aerodynamic friction losses; (3) energy consumption/generation depending on the grade of the route; (4) auxiliary load consumption; and (5) additional energy losses arising from the unstable power output of the electric motor. Two quantities, the average energy consumption per kilometer and the energy consumption for an entire trip, were focused on and compared for model fitness, parameter, and effectiveness, and the latter showed a higher fitness. Based on sparse GPS observations of 68 EVs in Aichi Prefecture, Japan, the traditional linear regression approach and a multilevel mixed-effects linear regression approach were used for model calibration. The proposed model showed a high accuracy and demonstrated a great potential for application in using sparse GPS observations to predict the energy consumption of EVs. Full article

The Chinese Loess Plateau suffers from serious gully erosion induced by natural and human causes. Gully-affected areas detection is the basic work in this region for gully erosion assessment and monitoring. For the first time, an unmanned aerial vehicle (UAV) was applied to extract gully features in this region. Two typical catchments in Changwu and Ansai were selected to represent loess tableland and loess hilly regions, respectively. A high-powered quadrocopter (md4-1000) equipped with a non-metric camera was used for image acquisition. InPho and MapMatrix were applied for semi-automatic workflow including aerial triangulation and model generation. Based on the stereo-imaging and the ground control points, the highly detailed digital elevation models (DEMs) and ortho-mosaics were generated. Subsequently, an object-based approach combined with the random forest classifier was designed to detect gully-affected areas. Two experiments were conducted to investigate the influences of segmentation strategy and feature selection. Results showed that vertical and horizontal root-mean-square errors were below 0.5 and 0.2 m, respectively, which were ideal for the Loess Plateau region. The overall extraction accuracy in Changwu and Ansai achieved was 84.62% and 86.46%, respectively, which indicated the potential of the proposed workflow for extracting gully features. This study demonstrated that UAV can bridge the gap between field measurement and satellite-based remote sensing, obtaining a balance in resolution and efficiency for catchment-scale gully erosion research. Full article

The internal defects of cable joints always accelerate the deterioration of insulation, until finally accidents can arise due to the explosion of the joints. The formation process of this damage often involves changes in the electromagnetic, temperature and stress distribution of the cable joint, therefore, it is necessary to analyze the electromagnetic-thermal-mechanical distribution of cable joints. Aiming at solving this problem, the paper sets up a 3-D electromagnetic-thermal-mechanical coupling model of cable joints under crimping process defects. Based on the model, the electromagnetic losses distribution, temperature distribution and stress distribution of a cable joint and body are calculated. Then, the coupling fields characteristics in different contact coefficient k, ambient temperature T_amb and load current I were analyzed, and according to the thermal-mechanical characteristics of a cable joint under internal defects, the temperature difference ΔT_f and stress difference Δσ_f of cable surface are applied to evaluate the internal cable joint defects. Finally, a simplified model of the cable joint is set up to verify the accuracy of the coupling field model proposed in this paper, which indicates that the model can be used to analyze the coupling fields characteristics of cable joints and the method can be applied to evaluate crimping process defects of cable joints. Full article

In wireless sensor networks, in order to satisfy the requirement of long working time of energy-limited nodes, we need to design an energy-efficient and lifetime-extended medium access control (MAC) protocol. In this paper, a node cooperation mechanism that one or multiple nodes with higher channel gain and sufficient residual energy help a sender relay its data packets to its recipient is employed to achieve this objective. We first propose a transmission power optimization algorithm to prolong network lifetime by optimizing the transmission powers of the sender and its cooperative nodes to maximize their minimum residual energy after their data packet transmissions. Based on it, we propose a corresponding power-optimized cooperative MAC protocol. A cooperative node contention mechanism is designed to ensure that the sender can effectively select a group of cooperative nodes with the lowest energy consumption and the best channel quality for cooperative transmissions, thus further improving the energy efficiency. Simulation results show that compared to typical MAC protocol with direct transmissions and energy-efficient cooperative MAC protocol, the proposed cooperative MAC protocol can efficiently improve the energy efficiency and extend the network lifetime. Full article

Efficient processing of big geospatial data is crucial for tackling global and regional challenges such as climate change and natural disasters, but it is challenging not only due to the massive data volume but also due to the intrinsic complexity and high dimensions of the geospatial datasets. While traditional computing infrastructure does not scale well with the rapidly increasing data volume, Hadoop has attracted increasing attention in geoscience communities for handling big geospatial data. Recently, many studies were carried out to investigate adopting Hadoop for processing big geospatial data, but how to adjust the computing resources to efficiently handle the dynamic geoprocessing workload was barely explored. To bridge this gap, we propose a novel framework to automatically scale the Hadoop cluster in the cloud environment to allocate the right amount of computing resources based on the dynamic geoprocessing workload. The framework and auto-scaling algorithms are introduced, and a prototype system was developed to demonstrate the feasibility and efficiency of the proposed scaling mechanism using Digital Elevation Model (DEM) interpolation as an example. Experimental results show that this auto-scaling framework could (1) significantly reduce the computing resource utilization (by 80% in our example) while delivering similar performance as a full-powered cluster; and (2) effectively handle the spike processing workload by automatically increasing the computing resources to ensure the processing is finished within an acceptable time. Such an auto-scaling approach provides a valuable reference to optimize the performance of geospatial applications to address data- and computational-intensity challenges in GIScience in a more cost-efficient manner. Full article

Objective: Postnatal tissue accretion in preterm infants differs from those in utero, affecting body composition (BC) and lifelong morbidity. Length normalized BC data allows infants with different body lengths to be compared and followed longitudinally. This study aims to analyze BC of preterm and term infants during the first six months of life. Methods: The BC data, measured using dual energy X-ray absorptiometry, of 389 preterm and 132 term infants from four longitudinal studies were combined. Fat-mass/length² (FMI) and fat-free mass/length² (FFMI) for postmenstrual age were calculated after reaching full enteral feeding, at term and two further time points up to six months corrected age. Results: Median FMI (preterm) increased from 0.4 kg/m² at 30 weeks to 2.5, 4.3, and 4.8 kg/m² compared to 1.7, 4.7, and 6 kg/m² in term infants at 40, 52, and 64 weeks, respectively. Median FFMI (preterm) increased from 8.5 kg/m² (30 weeks) to 11.4 kg/m² (45 weeks) and remained constant thereafter, whereas term FFMI remained constant at 11 kg/m² throughout the tested time points. Conclusion: The study provides a large dataset of length normalized BC indices. Followed longitudinally, term and preterm infants differ considerably during early infancy in the pattern of change in FMI and FFMI for age. Full article

Background: Drug resistance is one of the bottlenecks of cancer chemotherapy in the clinic. Polymeric nanomedicine is one of the most promising strategies for overcoming poor chemotherapy responses due to the multidrug resistance (MDR). Methods: In this study, a new polymer-based drug delivery system, poly (l-γ-glutamylglutamine)-doxorubicin (PGG-Dox) conjugate, was studied in both drug-induced resistant human breast cancer MDA-MB-231/MDR cells and their parent human breast cancer MDA-MB-231 cells. The effect of PGG on facilitating the growth inhibition of Dox against multidrug resistant cells were investigated by evaluating the cytotoxicity of PGG-Dox conjugate, PGG/Dox unconjugated complex and free Dox on both cells. The underlying mechanisms in resistant cells were further studied via the intracellular traffic studies. Results: Both conjugated and unconjugated PGG significantly increased Dox uptake, prolonged Dox retention and reduced Dox efflux in the MDA-MB-231/MDR cells. The PGG-Dox conjugate is taken up by tumor cells mainly by pinocytosis pathway, in which PGG-Dox conjugate-containing vesicles are formed and enter the cells. Conclusions: This study indicated that both polymer-drug conjugate and unconjugated complex are promising strategies of overcoming resistance of anti-tumor drugs. Full article

The successful launch of the Chinese high spatial resolution hyperspectral satellite TianGong-1 (TG-1) opens up new possibilities for applications of remotely-sensed satellite imagery. One of the main goals of the TG-1 mission is to provide observations of surface attributes at local and landscape spatial scales to map urban land cover accurately using the hyperspectral technique. This study attempted to evaluate the TG-1 datasets for urban feature analysis, using existing data over Beijing, China, by comparing the TG-1 (with a spatial resolution of 10 m) to EO-1 Hyperion (with a spatial resolution of 30 m). The spectral feature of TG-1 was first analyzed and, thus, finding out optimal hyperspectral wavebands useful for the discrimination of urban areas. Based on this, the pixel-based maximum likelihood classifier (PMLC), pixel-based support vector machine (PSVM), hybrid maximum likelihood classifier (HMLC), and hybrid support vector machine (HSVM) were implemented, as well as compared in the application of mapping urban land cover types. The hybrid classifier approach, which integrates the pixel-based classifier and the object-based segmentation approach, was demonstrated as an effective alternative to the conventional pixel-based classifiers for processing the satellite hyperspectral data, especially the fine spatial resolution data. For TG-1 imagery, the pixel-based urban classification was obtained with an average overall accuracy of 89.1%, whereas the hybrid urban classification was obtained with an average overall accuracy of 91.8%. For Hyperion imagery, the pixel-based urban classification was obtained with an average overall accuracy of 85.9%, whereas the hybrid urban classification was obtained with an average overall accuracy of 86.7%. Overall, it can be concluded that the fine spatial resolution satellite hyperspectral data TG-1 is promising in delineating complex urban scenes, especially when using an appropriate classifier, such as the hybrid classifier. Full article

We have recently developed a bivalent strategy to provide novel compounds that potentially target multiple risk factors involved in the development of Alzheimer’s disease (AD). Our previous studies employing a bivalent compound with a shorter spacer (17MN) implicated that this compound can localize into mitochondria and endoplasmic reticulum (ER), thus interfering with the change of mitochondria membrane potential (MMP) and Ca²⁺ levels in MC65 cells upon removal of tetracycline (TC). In this report, we examined the effects by a bivalent compound with a longer spacer (21MO) in MC65 cells. Our results demonstrated that 21MO suppressed the change of MMP, possibly via interaction with the mitochondrial complex I in MC65 cells. Interestingly, 21MO did not show any effects on the Ca²⁺ level upon TC removal in MC65 cells. Our previous studies suggested that the mobilization of Ca²⁺ in MC65 cells, upon withdraw of TC, originated from ER, so the results implicated that 21MO may preferentially interact with mitochondria in MC65 cells under the current experimental conditions. Collectively, the results suggest that bivalent compounds with varied spacer length and cell membrane anchor moiety may exhibit neuroprotective activities via different mechanisms of action. Full article

Urban surface energy fluxes are closely associated with land-cover types (LCTs) and critical biophysical compositions. This study aims to assess the contribution of LCTs, vegetation fractional coverage (VFC) and percentage of impervious surface area (ISA%) to urban surface energy fluxes using remote sensing. An advanced urban surface energy flux algorithm was used to combine satellite imagery and meteorological station data to investigate the thermal environments in the city of Suzhou, China. The land cover abundances retrieved by multiple endmember spectral unmixing analysis (MESMA) were used to retrieve the per-pixel sensible heat flux (H) and latent heat flux (LE). The resultant heat fluxes were assessed using evaporation pan data collected from meteorological stations and ratios of the heat fluxes to the net radiation (Rn). Furthermore, spatial patterns of urban heat energy were investigated using an integrated analysis among land surface temperature (LST), heat fluxes, LCTs, VFC and ISA%. The high values of H and LST were found over the urbanized areas, which also had low values of LE. Conversely, the vegetated area was characterized with high LEs, as well as low LSTs and Hs. Moreover, a statistically-significant correlation (p < 0.05; R² = 0.88) was observed between LE and VFC at the zonal level, and a statistically-significant correlation (p < 0.05; R² = 0.90) was exhibited between H and ISA%. It is concluded that VFC, ISA% and LCTs are promising for delineating urban heat fluxes. Overall, this study indicates that remote sensing techniques can be used to quantify urban thermal environments. Full article

Heat shock proteins play essential roles in basic cellular events. Spawning migration is a complex process, with significant structural and biochemical changes taking place in the adult gonad. To date, the molecular mechanisms underlying migration reproductive biology remain undetermined. In this regard, a full length HSP90AA1 comprising 2608 nucleotides from the anadromous fish Coilia nasus was characterized, encoding 742 amino acid (aa) residues with potential phosphorylation sites. HSP90AA1 mRNA transcripts were detected in all organs, especially in the gonad. Furthermore, the greatest transcript levels were found during the developmental phase, while the lowest levels were found during the resting phase. In addition, the strongest immunolabeling positive signal was found in the primary spermatocyte and oocyte, with lower positive staining in secondary germ cells, and a weak or absent level in the mature sperm and oocyte. Interestingly, HSP90AA1 was mainly located in the cytoplasm of germ cells. These results are important for understanding the molecular mechanism of anadromous migration reproductive biology. In combination with data from other fish species, the result of this present study may facilitate further investigations on the spawning migration mechanism. Full article

Here, a novel model of loop-mediated isothermal amplification (LAMP), termed multiple inner primers-LAMP (MIP-LAMP), was devised and successfully applied to detect Listeria monocytogenes. A set of 10 specific MIP-LAMP primers, which recognized 14 different regions of target gene, was designed to target a sequence in the hlyA gene. The MIP-LAMP assay efficiently amplified the target element within 35 min at 63 °C and was evaluated for sensitivity and specificity. The templates were specially amplified in the presence of the genomic DNA from L. monocytogenes. The limit of detection (LoD) of MIP-LAMP assay was 62.5 fg/reaction using purified L. monocytogenes DNA. The LoD for DNA isolated from serial dilutions of L. monocytogenes cells in buffer and in milk corresponded to 2.4 CFU and 24 CFU, respectively. The amplified products were analyzed by real-time monitoring of changes in turbidity, and visualized by adding Loop Fluorescent Detection Reagent (FD), or as a ladder-like banding pattern on gel electrophoresis. A total of 48 pork samples were investigated for L. monocytogenes by the novel MIP-LAMP method, and the diagnostic accuracy was shown to be 100% when compared to the culture-biotechnical method. In conclusion, the MIP-LAMP methodology was demonstrated to be a reliable, sensitive and specific tool for rapid detection of L. monocytogenes strains. Full article

Previous research studies have demonstrated that the relationship between remote sensing-derived parameters and aboveground biomass (AGB) could vary across different species types. However, there are few studies that calibrate reliable statistical models for mangrove AGB. This study quantifies the differences of accuracy in AGB estimation between the results obtained with and without the consideration of species types using Worldview-2 images and field surveys. A Back Propagation Artificial Neural Network (BP ANN) based model is developed for the accurate estimation of uneven-aged and dense mangrove forest biomass. The contributions of the input variables are further quantified using a “Weights” method based on BP ANN model. Two types of mangrove species, Sonneratia apetala (S. apetala) and Kandelia candel (K. candel), are examined in this study. Results show that the species type information is the most important variable for AGB estimation, and the red edge band and the associated vegetation indices from WorldView-2 images are more sensitive to mangrove AGB than other bands and vegetation indices. The RMSE of biomass estimation at the incorporation of species as a dummy variable is 19.17% lower than that of the mixed species level. The results demonstrate that species type information obtained from the WorldView-2 images can significantly improve of the accuracy of the biomass estimation. Full article

The urban heat island (UHI) effect resulting from rapid urbanization generally has a negative impact on urban residents. Shijiazhuang, the capital of Hebei Province in China, was selected to assess surface thermal patterns and its correlation with Land Cover Types (LCTs). This study was conducted using Landsat TM images on the mesoscale level and airborne hyperspectral thermal images on the microscale level. Land surface temperature (LST) was retrieved from four scenes of Landsat TM data in the summer days to analyze the thermal spatial patterns and intensity of surface UHI (SUHI). Surface thermal characteristics were further examined by relating LST to percentage of imperious surface area (ISA%) and four remote sensing indices (RSIs), the Normalized Difference Vegetation Index (NDVI), Universal Pattern Decomposition method (VIUPD), Normalized Difference Built-up Index (NDBI) and Biophysical Composition Index (BCI). On the other hand, fives scenes of airborne TASI (Thermal Airborne Spectrographic Imager sensor) images were utilized to describe more detailed urban thermal characteristics of the downtown of Shijiazhuang city. Our results show that an obvious surface heat island effect existed in the study area during summer days, with a SUHI intensity of 2–4 °C. The analyses reveal that ISA% can provide an additional metric for the study of SUHI, yet its association with LST is not straightforward and this should a focus in future work. It was also found that two physically based indices, VIUPD and BCI, have the potential to account for the variation in urban LST. The results concerning on TASI indicate that diversity of impervious surfaces (rooftops, concrete, and mixed asphalt) contribute most to the SUHI, among all of the land cover features. Moreover, the effect of impervious surfaces on LST is complicated, and the composition and arrangement of land cover features may play an important role in determining the magnitude and intensity of SUHI. Overall, the analysis of urban thermal signatures at two spatial scales complement each other and the use of airborne imagery data with higher spatial resolution is helpful in revealing more details for understanding urban thermal environments. Full article

A facile synthetic route of rivaroxaban has been developed. Using commercially available (R)-epichlorohydrin and bromobenzene as the starting materials, rivaroxaban was obtained in 39% overall yield using a Goldberg coupling as the key step. The synthetic route represents a convenient procedure for the production of rivaroxaban. Full article

The extensive usage of wireless sensor networks (WSNs) has led to the development of many power- and energy-efficient routing protocols. Cooperative routing in WSNs can improve performance in these types of networks. In this paper we discuss the existing proposals and we propose a routing algorithm for wireless sensor networks called Power Efficient Location-based Cooperative Routing with Transmission Power-upper-limit (PELCR-TP). The algorithm is based on the principle of minimum link power and aims to take advantage of nodes cooperation to make the link work well in WSNs with a low transmission power. In the proposed scheme, with a determined transmission power upper limit, nodes find the most appropriate next nodes and single-relay nodes with the proposed algorithm. Moreover, this proposal subtly avoids non-working nodes, because we add a Bad nodes Avoidance Strategy (BAS). Simulation results show that the proposed algorithm with BAS can significantly improve the performance in reducing the overall link power, enhancing the transmission success rate and decreasing the retransmission rate. Full article