Speolabeo hokhanhi, a new cavefish from Central Vietnam (Teleostei: Cyprinidae)

Cao, Nguyen Dinh Tao Liang, Deng, Shuqing (2018): Speolabeo hokhanhi, a new cavefish from Central Vietnam (Teleostei: Cyprinidae). Zootaxa 4476 (1): 109-117, DOI: https://doi.org/10.11646/zootaxa.4476.1.1

Speolabeo hokhanhi, a new cavefish from Central Vietnam (Teleostei: Cyprinidae)

Speolabeo hokhanhi, new species, is here described from Hang Va Cave in Phong Nha-Ke Bang National Park (Son River basin) in Central Vietnam. It can be distinguished from S. musaei by having no papillae on the lower lip, no hump immediately behind the head, a duckbilled snout, a shorter caudal peduncle (length 16.8-18.6% SL), and the pelvic fin inserted closer to the snout tip than to the caudal-fin base

Estimating Maize Maturity by Using UAV Multi-Spectral Images Combined with a CCC-Based Model

Measuring maize grain moisture content (GMC) variability at maturity provides an essential piece of information for the formulation of maize harvesting sequences and the applications of precision agriculture. Canopy chlorophyll content (CCC) is an important parameter that describes crop growth, photosynthetic rate, health, and senescence. The main goal of this study was to estimate maize GMC at maturity through CCC retrieved from multi-spectral UAV images using a PROSAIL model inversion and compare its performance with GMC estimation through simple vegetation indices (VIs) approaches. This study was conducted in two separate maize fields of 50.3 and 56 ha located in Hailun County, Heilongjiang Province, China. Each of the fields was cultivated with two maize varieties. One field was used as reference data for constructing the model, and the other field was applied to validate. The leaf chlorophyll content (LCC) and leaf area index (LAI) of maize were collected at three critical stages of crop growth, and meanwhile, the GMC of maize at maturity was also obtained. During the collection of field data, a UAV flight campaign was performed to obtain multi-spectral images from two fields at three main crop growth stages. In order to calibrate and evaluate the PROSAIL model for obtaining maize CCC, crop canopy spectral reflectance was simulated using crop-specific parameters. In addition, various VIs were computed from multi-spectral images to estimate maize GMC at maturity and compare the results with CCC estimations. When the CCC-retrieved results were compared to measured data, the R2 value was 0.704, the RMSE was 34.58 μg/cm2, and the MAE was 26.27 μg/cm2. The estimation accuracy of the maize GMC based on the normalized red edge index (NDRE) was demonstrated to be the greatest among the selected VIs in both fields, with R2 values of 0.6 and 0.619, respectively. Although the VIs of UAV inversion GMC accuracy are lower than those of CCC, their rapid acquisition, high spatial and temporal resolution, suitability for empirical models, and capture of growth differences within the field are still helpful techniques for field-scale crop monitoring. We found that maize varieties are the main reason for the maturity variation of maize under the same geographical and environmental conditions. The method described in this article enables precision agriculture based on UAV remote sensing by giving growers a spatial reference for crop maturity at the field scale

DFR1-Mediated Inhibition of Proline Degradation Pathway Regulates Drought and Freezing Tolerance in Arabidopsis

Summary: Proline accumulation is one of the most important adaptation mechanisms for plants to cope with environmental stresses, such as drought and freezing. However, the molecular mechanism of proline homeostasis under these stresses is largely unknown. Here, we identified a mitochondrial protein, DFR1, involved in the inhibition of proline degradation in Arabidopsis. DFR1 was strongly induced by drought and cold stresses. The dfr1 knockdown mutants showed hypersensitivity to drought and freezing stresses, whereas the DFR1 overexpression plants exhibited enhanced tolerance, which was positively correlated with proline levels. DFR1 interacts with proline degradation enzymes PDH1/2 and P5CDH and compromises their activities. Genetic analysis showed that DFR1 acts upstream of PDH1/2 and P5CDH to positively regulate proline accumulation. Our results demonstrate a regulatory mechanism by which, under drought and freezing stresses, DFR1 interacts with PDH1/2 and P5CDH to abrogate their activities to maintain proline homeostasis, thereby conferring drought and freezing tolerance. : Proline accumulation is very important for plants to cope with drought and freezing stresses. Ren et al. show that, in response to drought and freezing stresses, a mitochondrial protein DFR1 interacts with PDH1/2 and P5CDH to abrogate their activities to maintain proline homeostasis, thereby conferring drought and freezing tolerance. Keywords: Arabidopsis, DFR1, drought, freezing, proline degradation, PDH1, PDH2, P5CD

An Integrated Cyber-Physical Simulation Environment for Smart Grid Applications 143 Yuxin Wan is currently a PhD candidate of

Abstract: The concept of Cyber-Physical Systems (CPSs), which combine computation, networking, and physical processes, is considered to be beneficial to smart grid applications. This study presents an integrated simulation environment to provide a unified platform for the investigation of smart grid applications involving power grid monitoring, communication, and control. In contrast to the existing approaches, this environment allows the network simulator to operate independently, importing its results to the power system simulation. This resolves conflicts between discrete event simulation and continuous simulation. In addition, several data compensation methods are proposed and investigated under different network delay conditions. A case study of wide-area monitoring and control is provided, and the efficiency of the proposed simulation framework has been evaluated based on the experimental results