A general and simple automated impervious surface mapping approach based on three-dimensional texture features (3DTF) using fine spatial resolution remotely sensed imagery.

The mapping of impervious surfaces using remote sensing techniques offer essential technical support for sustainable development objectives and safeguard the environment. In this study, we developed an automated method without training samples for mapping impervious surfaces using texture features. The different aggregated impervious surface patterns and distributions in study areas of Site A-C in China (Beijing, Huainan, Jinhua) were considered. The Site D-E in Dubai and Tehran, surrounded with deserts in arid areas. They were selected to develop and evaluate the performance of the proposed automated method. The texture features of the Contrast, Gabor wavelets, and secondary texture extraction (Con_Gabor) derived from Sentinel-2 images at each site were used to construct the three-dimensional texture features (3DTF) of impervious surfaces. The 3DTF-combined K-means classifier was used to automatically map the impervious surfaces. The results showed that the overall accuracies of mapping impervious surface were 91.15 %, 89.75 %, and 91.90 % in Site A-C. The overall accuracies of mapping impervious surface were 90.95 %, 91.45 % and 88.23 % in rural areas. The distributions of impervious surface on automated method, GHS-BUILT-S and ESA WorldCover were similar in study areas. The automated method for mapping impervious surfaces performed as well as the artificial neural network (ANN) and Random Forest (RF), and the advantage of not requiring training samples. The automated method was tested in the in Dubai and Tehran. The overall accuracies of the automatic method for mapping impervious surfaces >89 % at Site D-E, and >88 % at rural area. In addition, the 3DTF was proved as the simplest and most effective feature combination to map impervious surfaces. The impervious surface mapped using the automated method was robust across bands, seasons and sensors. However, further evaluation is necessary to assess the effectiveness of automated methods using high spatial resolution images for mapping impervious surface in complex areas.

A new assessment framework to forecast land use and carbon storage under different SSP-RCP scenarios in China.

The vision of achieving "carbon neutrality" has created new requirements for the projection of land use and land cover (LULC), as well as the carbon storage (CS) of terrestrial ecosystem. Global-scale LULC scenario assessments with coarser resolution introduces uncertainties to national and regional-scale studies, which in turn has a negative impact on CS analysis based on land use perspective. Therefore, we proposed a new framework for scenario-based assessment that integrates the global-scale Land Use Harmonization (LUH2) dataset, Patch-generating Land Use Simulation (PLUS) model, and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, which we called LUH2-PLUS-InVEST (LPI) model. Our aim is to investigate the potential impacts of the combinations of Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) on China's future LULC and CS. By calibrating the demands, we generated structural predictions that were consistent with the actual land use. Furthermore, we explored the spatial heterogeneity of potential land use changes using 500 m × 500 m downscale simulations. Additionally, we developed a quantitative evaluation of CS from a spatiotemporal perspective and made recommendations on potential ecological threats. Our findings indicate that the basic characteristics of LULC and CS are determined by the natural context and that the prospects of land use distribution and carbon sequestration capacity are influenced by global emission pressure, regional competition, and China's unique development pattern. The results demonstrate that the LUH2-PLUS-INVEST model can provide an effective method for modeling the feedbacks of LULC and CS to the climate-society system.

Land use and habitat quality change in the Yellow River Basin: A perspective with different CMIP6-based scenarios and multiple scales.

Studying the spatial distribution of land use/land cover (LULC) and habitat quality (HQ), influenced by both climate change and socio-economic factors, holds immense importance for fostering ecological sustainability. The previous scale setting was based on changes in granularity and division of spatial ranges, without considering the differences in land quantity structure and spatial expansion under different spatial ranges. Therefore, this study is based on climate and economic data at different spatial scales to determine the various land demands of provinces (YRB-P) and integration of provinces (YRB-I) in the Yellow River Basin, and to limit the expansion of LULC in corresponding regions. At the same time, we have also established three future scenarios representing different development speeds based on the latest path of shared socio-economic development in CMIP6. We found exhibit significant characteristics in ecological responses under combinations of different scales and scenarios. Shandong and Henan Provinces are the main gathering (38.7-41.7%, 24.1-26.5%) and expansion (68.54-85.99 × 102km2, 18.89-34.12 × 102km2) provinces of built-up land under the YRB-P scale, and their HQ (0.260-0.397) are significantly lower than the average HQ (0.619-0.654). Forest land, grassland, and high value regions of HQ show "45°" distribution at two scales, with high and low values clearly clustered (Moran's I is 0.5440-0.580). The HQ evolution region is larger and more dispersed at the YRB-P scale, but accumulates in local areas at the YRB-I scale. In addition, the highest and lowest HQ mean values appear under the low speed development scenario at the YRB-P scale (0.721) and the rapid development scenario at the YRB-I scale (0.689), respectively. This study helps decision-makers control different scales and development scenarios to improve the ecological level of the study area.

Modular Robotic Limbs for Astronaut Activities Assistance.

In order to meet the assist requirements of extravehicular activity (EVA) for astronauts, such as moving outside the international space station (ISS) or performing on-orbit tasks by a single astronaut, this paper proposes an astronaut robotic limbs system (AstroLimbs) for extravehicular activities assistance. This system has two robotic limbs that can be fixed on the backpack of the astronaut. Each limb is composed of several basic module units with identical structure and function, which makes it modularized and reconfigurable. The robotic limbs can work as extra arms of the astronaut to assist them outside the space station cabin. In this paper, the robotic limbs are designed and developed. The reinforcement learning method is introduced to achieve autonomous motion planning capacity for the robot, which makes the robot intelligent enough to assist the astronaut in unstructured environment. In the meantime, the movement of the robot is also planned to make it move smoothly. The structure scene of the ISS for extravehicular activities is modeled in a simulation environment, which verified the effectiveness of the proposed method.

Exploiting singlet excited state conformation for rational design of highly efficient photoinduced electron transfer molecules.

In spite of the pivotal role of excited state electronic structures as regulation of photoinduced electron transfer (PET) process, the effect of excited state conformation on PET remains elusive. Here we exploit distinguishable emission characters of trans and cis singlet excited states of donor-acceptor-donor ensemble MTPAAZO to reveal that its PET efficiency and rate are closely depended on its singlet excited state conformation. The PET process occurs solely in cis conformation of MTPAAZO singlet excited states. Novel molecule (MTPA)2Ab as-designed with similar structure of MTPAAZO cis singlet excited states shows high PET efficacy and rate, leading to long-lived CS states. Our findings enable the rational design of the novel molecules with highly efficient PET process suitable for charge separation applications.

Draft Genome Sequence of Bacillus subtilis Strain S1-4, Which Degrades Feathers Efficiently.

Bacillus subtilis strain S1-4, with the capacity to efficiently degrade feathers, was isolated from chicken feathers. Sequencing showed that the genome of strain S1-4 differs from that of other B. subtilis strains, with limited insertions and deletions. The genome encodes multiple extracellular proteases and keratinases.

Draft genome sequence of Enterobacter cloacae subsp. cloacae strain 08XA1, a fecal bacterium of giant pandas.

Enterobacter cloacae, a common pathogenic bacterium, is a Gram-negative bacillus. We analyzed the draft genome of Enterobacter cloacae subsp. cloacae strain 08XA1 from the feces of a giant panda in China. Genes encoding a ß-lactamase and efflux pumps, as well as other factors, have been found in the genome.

Draft genome sequence of Bacillus pumilus BA06, a producer of alkaline serine protease with leather-dehairing function.

Bacillus pumilus BA06 was isolated from the proteinaceous soil and produced an extracellular alkaline protease with leather-dehairing function. The genome of BA06 was sequenced. The comparative genome analysis indicated that strain BA06 is different in genome from the other B. pumilus strains, with limited insertions, deletions, and rearrangements.

Digital gene expression analysis based on integrated de novo transcriptome assembly of sweet potato [Ipomoea batatas (L.) Lam].

BACKGROUND: Sweet potato (Ipomoea batatas L. [Lam.]) ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. METHODOLOGY/PRINCIPAL FINDINGS: Illumina paired-end (PE) RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts (≥ 100 bp), which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE) tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified. CONCLUSIONS/SIGNIFICANCE: The combined de novo transcriptome assembly strategy can be applied to other organisms whose reference genomes are not available. The data provided here represent the most comprehensive and integrated genomic resources for cloning and identifying genes of interest in sweet potato. Characterization of sweet potato transcriptome provides an effective tool for better understanding the molecular mechanisms of cellular processes including development of leaves and storage roots, tissue-specific gene expression, potential biotic and abiotic stress response in sweet potato.