High-performance mid-wavelength InAs avalanche photodiode using AlAs013Sb087 as the multiplication layer

We report on a high-performance mid-wavelength infrared avalanche photodetector (APD) with separate absorption and multiplication regions. InAs is used as the absorber material and high-bandgap AlAs0.13Sb0.87 is used as the multiplication material. At room temperature, the APD’s peak response wavelength is 3.27 μm, and the 50% cutoff wavelength is 3.5 μm. The avalanche gain reaches 13.1 and the responsivity is 8.09 A/W at 3.27 μm when the applied reverse bias voltage is 14.6 V. The measured peak detectivit

Conservation and divergence of microRNAs and their functions in Euphorbiaceous plants

MicroRNAs (miRNAs) are ∼21 nt non-coding RNAs which regulate post-transcriptional gene expression. miRNAs are key regulators of nearly all essential biological processes. Aiming at understanding miRNA’s functions in Euphorbiaceae, a large flowering plant family, we performed a genome-scale systematic study of miRNAs in Euphorbiaceae, by combining computational prediction and experimental analysis to overcome the difficulty of lack of genomes for most Euphorbiaceous species. Specifically, we predicted 85 conserved miRNAs in 23 families in the Castor bean (Ricinus communis), and experimentally verified and characterized 58 (68.2%) of the 85 miRNAs in at least one of four Euphorbiaceous species, the Castor bean, the Cassava (Manihot esculenta), the Rubber tree (Hevea brasiliensis) and the Jatropha (Jatropha curcas) during normal seedling development. To elucidate their function in stress response, we verified and profiled 48 (56.5%) of the 85 miRNAs under cold and drought stresses as well as during the processes of stress recovery. The results revealed some species- and condition-specific miRNA expression patterns. Finally, we predicted 258 miRNA:target partners, and identified the cleavage sites of six out of ten miRNA targets by a modified 5′ RACE. This study produced the first collection of miRNAs and their targets in Euphorbiaceae. Our results revealed wide conservation of many miRNAs and diverse functions in Euphorbiaceous plants during seedling growth and in response to abiotic stresses

Estimating the Seasonal Dynamics of the Leaf Area Index Using Piecewise LAI-VI Relationships Based on Phenophases

The leaf area index (LAI) is not only an important parameter used to describe the geometry of vegetation canopy but also a key input variable for ecological models. One of the most commonly used methods for LAI estimation is to establish an empirical relationship between the LAI and the vegetation index (VI). However, the LAI-VI relationships had high seasonal variability, and they differed among phenophases and VIs. In this study, the LAI-VI relationships in different phenophases and for different VIs (i.e., the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and near-infrared reflectance of vegetation (NIRv)) were investigated based on 82 site-years of LAI observed data and the Moderate Resolution Imaging Spectroradiometer (MODIS) VI products. Significant LAI-VI relationships were observed during the vegetation growing and declining periods. There were weak LAI-VI relationships (p > 0.05) during the flourishing period. The accuracies for the LAIs estimated with the piecewise LAI-VI relationships based on different phenophases were significantly higher than those estimated based on a single LAI-VI relationship for the entire vegetation active period. The average root mean square error (RMSE) ± standard deviation (SD) value for the LAIs estimated with the piecewise LAI-VI relationships was 0.38 ± 0.13 (based on the NDVI), 0.41 ± 0.13 (based on the EVI) and 0.41 ± 0.14 (based on the NIRv), respectively. In comparison, it was 0.46 ± 0.13 (based on the NDVI), 0.55 ± 0.15 (based on the EVI) and 0.55 ± 0.15 (based on the NIRv) for those estimated with a single LAI-VI relationship. The performance of the three VIs in estimating the LAI also varied among phenophases. During the growing period, the mean RMSE ± SD value for the estimated LAIs was 0.30 ± 0.11 (LAI-NDVI relationships), 0.37 ± 0.11 (LAI-EVI relationships) and 0.36 ± 0.13 (LAI-NIRv relationships), respectively, indicating the NDVI produced significantly better LAI estimations than those from the other two VIs. In contrast, the EVI produced slightly better LAI estimations than those from the other two VIs during the declining period (p > 0.05), and the mean RMSE ± SD value for the estimated LAIs was 0.45 ± 0.16 (LAI-NDVI relationships), 0.43 ± 0.23 (LAI-EVI relationships) and 0.45 ± 0.25 (LAI-NIRv relationships), respectively. Hence, the piecewise LAI-VI relationships based on different phenophases were recommended for the estimations of the LAI instead of a single LAI-VI relationship for the entire vegetation active period. Furthermore, the optimal VI in each phenophase should be selected for the estimations of the LAI according to the characteristics of vegetation growth

Enhancement of Photocatalytic Activity under Visible Light Irradiation via the AgI@TCNQ Core-Shell Structure

In this paper, a AgI@TCNQ photocatalyst with a core-shell structure was reported. A two-dimensional TCNQ (7,7,8,8-Tetracyanoquinodimethane) nanosheet, with a π-π conjugate structure, was used as a shell layer to realize the flexible coating on the surface of AgI nanoparticles. These special core-shell structure composites solve the key problems of the small interface of the bulk composites and the lesser charge transfer paths, which could accelerate the migration of photogenerated carriers. Thus, the AgI@TCNQ photocatalysts showed the better photodegradation performance for the methylene blue (MB) solution, and the degradation rate of AgI@TCNQ (1 wt.%) composite was 1.8 times than AgI under irradiation. The reactive species trapping experiments demonstrated that ·O2−, h+, and ·OH all participated in the MB degradation process. The photocatalytic mechanism of AgI@TCNQ composites could be rationally explained by considering the Z-scheme structure, resulting in a higher redox potential and more efficient separation of charge carriers. At the same time, the unique core-shell structure provides a larger contact area, expands the charge transport channel, and increases the surface active sites, which are beneficial for improving photocatalytic performance

Research Progress of High-Salinity Wastewater Treatment Technology

With the continuous expansion of industrial enterprises, a large amount of high-salt wastewater with complex components is produced. Direct discharge will cause great harm to the ecosystem and waste a large amount of potential salt resources. This paper summarizes the source, water quality characteristics, and environmental impact of high-salinity wastewater, and introduces the desalination and treatment technologies of high-salinity wastewater. The desalination technology of high-salinity wastewater mainly includes two processes: concentration and crystallization, obtaining concentrated solution through membrane concentration or thermal concentration and then carrying out crystallization treatment on the concentrated solution, thereby realizing the recovery of salt. The advanced treatment technologies of high-salinity wastewater were analyzed, including physicochemical treatment, biological treatment, and coupling treatment. Catalytic ozonation is one of the most widely used physicochemical technologies for the advanced treatment of high-salinity wastewater. Biological treatment processes operating in the presence of halotolerant bacteria show excellent performance at high salinity. High salinity has a negative impact on the performance of various physicochemical processes and biological treatment technologies. However, high salinity has little effect on the performance of a coupled system designed to treat high-salinity wastewater. In this review, the effect of salinity on the scaling and corrosion of equipment is also illustrated. It is suggested that the research direction of high-salinity wastewater should be to develop new membrane materials and catalysts, develop salt-tolerant microorganisms, explore high-efficiency and energy-saving physico–chemical–biochemical combination processes, improve the treatment efficiency of high-salinity organic wastewater, and reduce treatment costs

Preparation of Mn/Zn@PG Catalyst for Catalytic Oxidation Treatment of Coal Chemical Wastewater

In this study, Mn/Zn@palygorskite (PG) catalysts with developed pores and good salt tolerance were prepared and applied to the treatment of coal chemical wastewater. A doping ratio of metal elements, calcination temperature, and calcination time was used to optimize the preparation conditions and determine the optimal preparation conditions of the Mn/Zn@PG catalysts. The catalysts, obtained under various preparation conditions, were characterized and analyzed by XRD, SEM, EDS, BET, XRF, XPS, and other techniques. Results showed that the Zn and Mn elements in the Mn/Zn@PG catalyst existed as ZnO and MnO2, respectively. The optimal working conditions of the Mn/Zn@PG catalyst for catalytic oxidation treatment of coal chemical wastewater, obtained through the optimization of working conditions, are the following: reaction time 60 min, wastewater pH = 9.28, ozone ventilation rate 0.2 L/min, catalyst filling ratio 20%. The height-to-diameter ratio of the tower was 6:1. The abrasion resistance and catalytic performance of the Mn/Zn@PG catalyst after repeated use were investigated, and the mechanism of the loss of active components of the Mn/Zn@PG catalyst was explored. The coal chemical wastewater, before and after treatment, was analyzed by UV–vis spectroscopy and 3D fluorescence spectroscopy. The hierarchical–principal component comprehensive evaluation system (AHP–PCA) was established to evaluate the catalytic ozonation process of coal chemical wastewater, so that the overall evaluation of the process performance can be achieved

Seasonal differences in relationships between changes in spring phenology and dynamics of carbon cycle in grasslands

Abstract Global warming is dramatically altering the plant phenology of terrestrial ecosystem and thus has caused significant effects on the terrestrial carbon cycle. Many studies have investigated the relationships between the spring phenological changes and the dynamics of carbon cycle, but the seasonal differences in these relationships are still unclear. This study used eddy covariance measurements of grassland net ecosystem productivity (NEP) from nine FLUXNET sites (73 site‐years of data) to investigate the relationships between the spring phenological changes (i.e., early green‐up, EGU; middle green‐up, MGU; and late green‐up, LGU) and the dynamics of carbon cycle (including NEP; ecosystem respiration, ER; and gross ecosystem production, GEP) at a ten‐day scale. Weak relationships were found between the spring phenological changes and the dynamics of ER at all sites. The advance of spring phenology mainly caused significant increases in GEP (or NEP) during the initial 20–50 d after the green‐up date at most sites. With an advancement of 1 d in EGU (MGU and LGU), GEP and NEP were increased by 1.5–6.0 (3.5–7.1 and 2.4–4.7) and 0.7–3.6 (1.5–3.9 and 1.9–4.7) g C/m2 during the early growing season (EGS), respectively. The advance of spring phenology did not have significant impacts on GEP (or NEP) during the middle and late growing season (MGS and LGS) at most sites, but yielded a significant decrease in GEP (or NEP) during MGS at a few sites. As the grasslands turning green, the duration of the impact of the changes in EGU, MGU, and LGU on GEP (or NEP) was reduced, whereas the magnitude of the impact of the changes on the ten‐day cumulative GEP (or NEP) was increased at most sites. Thus, there were two possible impact models for the spring phenological changes on the dynamics of carbon cycle for grasslands: The advance of spring phenology only increases the GEP (or NEP) during EGS, and the advance of spring phenology only decreases the GEP (or NEP) during MGS. These results could be helpful in further understanding the influences of spring phenological changes on the dynamics of carbon cycle for grasslands

Reconstruction of Vegetation Index Time Series Based on Self-Weighting Function Fitting from Curve Features

Vegetation index (VI) time series derived from satellite sensors have been widely used in the estimation of vegetation parameters, but the quality of VI time series is easily affected by clouds and poor atmospheric conditions. The function fitting method is a widely used effective noise reduction technique for VI time series, but it is vulnerable to noise. Thus, ancillary data about VI quality are utilized to alleviate the interference of noise. However, this approach is limited by the availability, accuracy, and application rules of ancillary data. In this paper, we aimed to develop a new reconstruction method that does not require ancillary data. Based on the assumptions that VI time series follow the gradual growth and decline pattern of vegetation dynamics, and that clouds or poor atmospheric conditions usually depress VI values, we proposed a reconstruction method for VI time series based on self-weighting function fitting from curve features (SWCF). SWCF consists of two major procedures: (1) determining a fitting weight for each VI point based on the curve features of the VI time series and (2) implementing the weighted function fitting to reconstruct the VI time series. The double logistic function, double Gaussian function, and polynomial function were tested in SWCF based on a simulated dataset. The results indicate that the weighted function fitting with SWCF outperformed the corresponding unweighted function fitting with the root-mean-square error (RMSE) significantly reduced by 26.82–52.44% (p p < 0.05) for 270 sample points selected in mid-high latitudes of the Northern Hemisphere. Moreover, SWCF showed excellent robustness and applicability in regional applications