Transformation behaviors and environmental risk assessment of heavy metals during resource recovery from Sedum plumbizincicola via hydrothermal liquefaction

Environmentally sound disposal of hyperaccumulator harvests is of critical importance to industrialization of phytoremediation. Herein, transformation behaviors and environmental risk of heavy metals were comprehensively examined during subcritical hydrothermal liquefaction of Sedum plumbizincicola. It is concluded that low temperature liquefaction favored resource recovery of heavy oil and hydrochars in terms of higher energy density, improved carbon sequestration and less energy consumption. Heavy metals were mainly distributed into hydrochars and water soluble phase with less than 10% in heavy oil. All metal elements except As could be accumulated in hydrochars by extending reaction time, whereas more than 96% of As was redistributed into water soluble phase. Prolonged liquefaction time facilitated immobilization of Cd, Cr and As in hydrochars, but fast liquefaction favored Pb stabilization. Liquefaction significantly reduced environmental risk level of Cd, Zn and As, but may mobilize Pb and Mn, especially for Mn to very high risk level at 240 ºC. High temperature with long reaction time tended to inhibit leaching rate of Mn, whereas low liquefaction temperature with short reaction time prevented the leaching of Zn and As from hydrochars. Overall, these findings are essential for downstream upgrading of heavy oil and metals recovery from hydrochars.acceptedVersionPeer reviewe

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Hydrogeochemical Characteristics and Groundwater Quality in a Coastal Urbanized Area, South China: Impact of Land Use

Land use transformation accompanied with various human activities affects groundwater chemistry and quality globally, especially in coastal urbanized areas because of complex human activities. This study investigated the impact of land use on groundwater chemistry and quality in a coastal alluvial aquifer (CAA) of the Pearl River Delta where urbanization continues. A fuzzy synthetic evaluation method was used to evaluate the groundwater quality. Besides, factors controlling groundwater chemistry and quality in the CAA were discussed by using a principal components analysis (PCA). Nearly 150 groundwater samples were collected. All samples were filtered on-site and stored at 4 °C until the laboratory procedures could be performed. Nineteen chemical parameters including pH, dissolved oxygen, redox potential, total dissolved solids, K+, Na+, Ca2+, Mg2+, NH4+, HCO3−, NO3−, SO42−, Cl−, I−, NO2−, Pb, Mn, Fe, and As were analyzed. Results show that groundwater chemistry in the CAA was dominated by Ca-HCO3 and Ca·Na-HCO3 facies. In addition, groundwater with NO3 facies was also present because of more intensive human activities. In the CAA, 61.8% of groundwaters were fit for drinking, and 10.7% of groundwaters were undrinkable but fit for irrigation, whereas 27.5% of groundwaters were unfit for any purpose. Poor-quality groundwaters in urban and agricultural areas were 1.1–1.2 times those in peri-urban areas, but absent in the remaining area. Groundwater chemistry and quality in the CAA was mainly controlled by five factors according to the PCA. Factor 1 is the release of salt and NH4+ from marine sediments, and the infiltration of domestic and septic sewage. Factor 2 is agricultural activities related to the irrigation of river water, and the use of chemical fertilizers. Factor 3 is the industrial pollution related to heavy metals and acid deposition. Factor 4 is the input of anthropogenic reducing sewage inducing the reductive dissolution of As-loaded Fe minerals and denitrification. Factor 5 is the I− contamination from both of geogenic and anthropogenic sources. Therefore, in order to protect groundwater quality in coastal urbanized areas, repairing old sewer systems in urban areas, building sewer systems in peri-urban areas, limiting sewage irrigation and the amount of chemical fertilizers application in agricultural areas, as well as strengthening the supervision of the industrial exhaust gas discharge in urban and peri-urban areas are recommended

A surface graph based deep learning framework for large-scale urban mesh semantic segmentation

The acquisition of large-scale 3D urban scene by photogrammetry and remote sensing is becoming faster and easier in recent years. As one of the important steps to help machines understand scenarios, mesh semantic segmentation has received extensive attention. Aiming at the 3D urban scene, a surface graph based deep learning framework is proposed, which combines the merits of simple representation of point cloud and expresses complex surface topography and texture of mesh. The proposed model employs COG graph to represent surface topography of the mesh. Then novel mesh abstraction and neighborhood definition are conducted on the COG graph. In addition, we propose a texture convolution to extract textual features for individual facets. A hierarchical network architecture is adopted on the prebuilt abstraction and neighborhood data. The experiments on the self-made Wuhan dataset verify the effectiveness of the introduction of surface topography and texture convolution. Additionally, our model increases performance to 94.1% (OA), 71.5% (mIoU) and 79.4% (mF1) in comparative experiments on the SUM dataset that proves its strong competitiveness in semantic segmentation of urban scenes

A Texture Integrated Deep Neural Network for Semantic Segmentation of Urban Meshes

3-D geo-information is essential for many urban related applications. Point cloud and mesh are two common representations of the 3-D urban surface. Compared to point cloud data, mesh possesses indispensable advantages, such as high-resolution image texture and sharp geometry representation. Semantic segmentation, as an important way to obtain 3-D geo-information, however, is mainly performed on the point cloud data. Due to the complex geometry representation and lack of efficient utilizing of image texture information, the semantic segmentation of the mesh is still a challenging task for urban 3-D geo-information acquisition. In this article, we propose a texture and geometry integrated deep learning method for the mesh segmentation task. A novel texture convolution module is introduced to capture image texture features. The texture features are concatenate with nontexture features on a point cloud that represents by the center of gravity (COG) of the mesh triangles. A hierarchical deep network is employed to segment the COG point cloud. Our experimental results show that the proposed network significantly improves the accuracy with the introduced texture convolution module (1.9% for overall accuracy and 4.0% for average F1 score). It also compares with other state-of-the-art methods on the public SUM-Helsinki dataset and achieves considerable results

Transplantation of Stem Cells from Human Exfoliated Deciduous Teeth Decreases Cognitive Impairment from Chronic Cerebral Ischemia by Reducing Neuronal Apoptosis in Rats

Stem cells from human exfoliated deciduous teeth (SHED) are a unique postnatal stem cell population with high self-renewal ability that originates from the cranial neural crest. Since SHED are homologous to the central nervous system, they possess superior capacity to differentiate into neural cells. However, whether and how SHED ameliorate degenerative central nervous disease are unclear. Chronic cerebral ischemia (CCI) is a kind of neurological disease caused by long-term cerebral circulation insufficiency and is characterized by progressive cognitive and behavioral deterioration. In this study, we showed that either systemic transplantation of SHED or SHED infusion into the hippocampus ameliorated cognitive impairment of CCI rats in four weeks after SHED treatment by rescuing the number of neurons in the hippocampus area. Mechanistically, SHED transplantation decreased the apoptosis of neuronal cells in the hippocampus area of CCI rats through downregulation of cleaved caspase-3. In summary, SHED transplantation protected the neuronal function and reduced neuronal apoptosis, resulting in amelioration of cognitive impairment from CCI. Our findings suggest that SHED are a promising stem cell source for cell therapy of neurological diseases in the clinic

Differential Effects of Senescence on the Phloem Exports of Cadmium and Zinc from Leaves to Grains in Rice during Grain Filling

In rice, non-essential toxic cadmium (Cd) and the essential nutrient zinc (Zn) share similar transport pathways, which makes it challenging to differentially regulate the allocation of these elements to the grain. The phloem is the main pathway for the loading of these elements into rice grains. It has long been accepted that tissue senescence makes the nutrients (e.g., Zn) stored in leaves available for further phloem export toward the grain. Whether senescence could drive the phloem export of Cd remains unclear. To this end, the stable isotopes 111Cd and 67Zn were used to trace the phloem export and the subsequent allocation of Cd and Zn from the flag leaves, where senescence was accelerated by spraying abscisic acid. Furthermore, changes upon senescence in the distribution of these elements among the leaf subcellular fractions and in the expression of key transporter genes were investigated. Abscisic acid-induced senescence enhanced the phloem export of Zn but had no impact on that of Cd, which was explained by the significant release of Zn from the chloroplast and cytosol fractions (concentrations decreased by ~50%) but a strong allocation of Cd to the cell wall fraction (concentration increased by ~90%) during senescence. Nevertheless, neither Zn nor Cd concentrations in the grain were affected, since senescence strengthened the sequestration of phloem-exported Zn in the uppermost node, but did not impact that of phloem-exported Cd. This study suggests that the agronomic strategies affecting tissue senescence could be utilized to differentially regulate Cd and Zn allocation in rice during grain filling

An Adaptive Chaotic Sine Cosine Algorithm for Constrained and Unconstrained Optimization

Sine cosine algorithm (SCA) is a new meta-heuristic approach suggested in recent years, which repeats some random steps by choosing the sine or cosine functions to find the global optimum. SCA has shown strong patterns of randomness in its searching styles. At the later stage of the algorithm, the drop of diversity of the population leads to locally oriented optimization and lazy convergence when dealing with complex problems. Therefore, this paper proposes an enriched SCA (ASCA) based on the adaptive parameters and chaotic exploitative strategy to alleviate these shortcomings. Two mechanisms are introduced into the original SCA. First, an adaptive transformation parameter is proposed to make transformation more flexible between global search and local exploitation. Then, the chaotic local search is added to augment the local searching patterns of the algorithm. The effectiveness of the ASCA is validated on a set of benchmark functions, including unimodal, multimodal, and composition functions by comparing it with several well-known and advanced meta-heuristics. Simulation results have demonstrated the significant superiority of the ASCA over other peers. Moreover, three engineering design cases are employed to study the advantage of ASCA when solving constrained optimization tasks. The experimental results have shown that the improvement of ASCA is beneficial and performs better than other methods in solving these types of problems

Formation and Characterization of Dendritic Interfacial Electrodes inside an Ionomer

Formation of dendritic interfacial electrodes (DIEs) between metal/polymer interfaces has high demands in a variety of areas. By combining impregnation electroplating (IEP) step with impregnation–reduction (IR) step under straightforward conditions, we report a novel method of preparation of dendritic interfacial metal electrodes of palladium, platinum, silver and copper inside an ionomer for ionic polymer–metal composites (IPMC) application. The depth of palladium DIEs can be controlled by adjusting the reaction time, and the maximum depth can almost reach up to contact from the both sides of ionomer with a total thickness of 200 μm. The capacitance and actuation performance of IPMC was dramatically enhanced because of the presence of DIEs

A Scalable Heat Pump Film with Zero Energy Consumption

Radiative cooling is an effective technology with zero energy consumption to alleviate climate warming and combat the urban heat island effect. At present, researchers often use foam boxes to isolate non-radiant heat exchange between the cooler and the environment through experiments, so as to achieve maximum cooling power. In practice, however, there are challenges in setting up foam boxes on a large scale, resulting in coolers that can be cooled below ambient only under low convection conditions. Based on polymer materials and nano-zinc oxide (nano-ZnO, refractive index > 2, the peak equivalent spherical diameter 500 nm), the manufacturing process of heat pump film (HPF) was proposed. The HPF (4.1 mm thick) consists of polyethylene (PE) bubble film (heat transfer coefficient 0.04 W/m/K, 4 mm thick) and Ethylene-1-octene copolymer (POE) cured nano-ZnO (solar reflectance ≈94% at 0.075 mm thick). Covering with HPF, the object achieves 7.15 °C decreasing in normal natural environment and 3.68 °C even under certain circumstances with high surface convective heat transfer (56.9 W/m2/K). HPF has advantages of cooling the covered object, certain strength (1.45 Mpa), scalable manufacturing with low cost, hydrophobic characteristics (the water contact angle, 150.6°), and meeting the basic requirements of various application scenarios