Microencapsulation of paraffin with poly (urea methacrylate) shell for solar water heater

Previous research has demonstred that microencapsulated phase change materials (MEPCMs) could significantly increase the energy storage density of solar thermal energy storage (TES) systems. Compared with traditional phase change materials (PCMs), MEPCMs have many advantages since they can limit their exposure to the surrounding environment, enlarge the heat transfer area, and maintain the volume as the phase change occurs. In this study, a new MEPCM for solar TES systems is developed by encapsulation of paraffin wax with poly (urea formaldehyde) (PUF). The experimental results revealed that agglomeration of MEPCM particles occurred during the encapsulation process which affected the uniformity of the particle size distribution profile when sodium dodecyl sulfate was used as an emulsifier. The differential scanning calorimetric (DSC) analysis results showed that the melting temperatures were slightly increased by 0.14-0.72 ◦C after encapsulation. A thermogravimetric (TG) test showed that the sample weight decreased while the weight loss starting temperature was slightly increased after encapsulation. Overall, the sample UF-2, fabricated with the binary emulsifiers of Brij 35 and Brij 30 and 5% nucleating agent, resulted in good particle dispersion and shell integrity, higher core material content and encapsulation efficiency, as well as improved thermal stability

Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization

Instance segmentation on point clouds is crucially important for 3D scene understanding. Distance clustering is commonly used in state-of-the-art methods (SOTAs), which is typically effective but does not perform well in segmenting adjacent objects with the same semantic label (especially when they share neighboring points). Due to the uneven distribution of offset points, these existing methods can hardly cluster all instance points. To this end, we design a novel divide and conquer strategy and propose an end-to-end network named PBNet that binarizes each point and clusters them separately to segment instances. PBNet divides offset instance points into two categories: high and low density points (HPs vs.LPs), which are then conquered separately. Adjacent objects can be clearly separated by removing LPs, and then be completed and refined by assigning LPs via a neighbor voting method. To further reduce clustering errors, we develop an iterative merging algorithm based on mean size to aggregate fragment instances. Experiments on ScanNetV2 and S3DIS datasets indicate the superiority of our model. In particular, PBNet achieves so far the best AP50 and AP25 on the ScanNetV2 official benchmark challenge (Validation Set) while demonstrating high efficiency

From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion

We consider the problem of Multi-view 3D Face Reconstruction (MVR) with weakly supervised learning that leverages a limited number of 2D face images (e.g. 3) to generate a high-quality 3D face model with very light annotation. Despite their encouraging performance, present MVR methods simply concatenate multi-view image features and pay less attention to critical areas (e.g. eye, brow, nose and mouth). To this end, we propose a novel model called Deep Fusion MVR (DF-MVR) and design a multi-view encoding to a single decoding framework with skip connections, able to extract, integrate, and compensate deep features with attention from multi-view images. In addition, we develop a multi-view face parse network to learn, identify, and emphasize the critical common face area. Finally, though our model is trained with a few 2D images, it can reconstruct an accurate 3D model even if one single 2D image is input. We conduct extensive experiments to evaluate various multi-view 3D face reconstruction methods. Our proposed model attains superior performance, leading to 11.4% RMSE improvement over the existing best weakly supervised MVRs. Source codes are available in the supplementary materials

Low dose triptolide reverses chemoresistance in adult acute lymphoblastic leukemia cells via reactive oxygen species generation and DNA damage response disruption

Chemoresistance represents a major challenge for treatment of acute lymphoblastic leukemia (ALL). Thus, new drugs to overcome chemoresistance in ALL are urgently needed. To this end, we established a cytarabine (araC)-resistant ALL cell line (NALM-6/R), which interestingly displayed cross-resistance towards doxorubicin (ADM). Here we report that low dose of triptolide (TPL), a natural product used for treating inflammatory diseases such as arthritis, could reverse araC and ADM resistance and in NALM-6/R cells as well as primary cells from patients with relapsed or refractory (R/R) ALL, reflected by inhibition of cell proliferation and induction of apoptosis in vitro, and repression of tumor growth in vivo in a mouse xenograft model. Mechanistically, these events were associated with impaired mitochondrial membrane potential and increased reactive oxygen species (ROS) production. Co-treatment with TPL and araC or ADM upregulated pro-apoptotic caspase-9 protein, inhibited checkpoint kinase 1 (Chk1) and 2 (Chk2) phosphorylation, and induced γH2A.X (a DNA damage marker). Notably, the combination regimen of TPL and conventional chemotherapeutics also rapidly diminished tumor burden in a patient with R/R ALL. Together, these findings provide preclinical evidence for repurposing use of TPL in combination with chemotherapeutic agents to treat R/R ALL as an alternative salvage regimen

Development of Omni InDel and supporting database for maize

Insertions–deletions (InDels) are the second most abundant molecular marker in the genome and have been widely used in molecular biology research along with simple sequence repeats (SSR) and single-nucleotide polymorphisms (SNP). However, InDel variant mining and marker development usually focuses on a single type of dimorphic InDel, which does not reflect the overall InDel diversity across the genome. Here, we developed Omni InDels for maize, soybean, and rice based on sequencing data and genome assembly that included InDel variants with base lengths from 1 bp to several Mb, and we conducted a detailed classification of Omni InDels. Moreover, we screened a set of InDels that are easily detected and typed (Perfect InDels) from the Omni InDels, verified the site authenticity using 3,587 germplasm resources from 11 groups, and analyzed the germplasm resources. Furthermore, we developed a Multi-InDel set based on the Omni InDels; each Multi-InDel contains multiple InDels, which greatly increases site polymorphism, they can be detected in multiple platforms such as fluorescent capillary electrophoresis and sequencing. Finally, we developed an online database website to make Omni InDels easy to use and share and developed a visual browsing function called “Variant viewer” for all Omni InDel sites to better display the variant distribution

Both NaCl and H2O2 Long-Term Stresses Affect Basal Cytosolic Ca2+ Levels but Only NaCl Alters Cytosolic Ca2+ Signatures in Arabidopsis

Salinity is one of the formidable environmental factors that affect plant growth and development and constrain agricultural productivity. Experimentally imposed short-term NaCl treatment triggers a transient increase in cytosolic free Ca2+ concentration ([Ca2+]i) via Ca2+ influx across the plasma membrane. Salinity stress, as well as other stresses, induces the production of reactive oxygen species (ROS), such as H2O2. It is well established that short-term H2O2 treatment also triggers a transient increase in [Ca2+]i. However, whether and how long-term NaCl and H2O2 treatments affect the basal levels of [Ca2+]i as well as plant responses to additional NaCl and H2O2 stresses remain poorly understood. Using an aequorin-based Ca2+ imaging assay, we found that the long-term treatment of Arabidopsis seedlings with both moderate NaCl and H2O2 in the growth media reduced the basal [Ca2+]i levels. Interestingly, we found that the long-term treatment with NaCl, but not H2O2, affected the responses of plants to additional NaCl stress, and remarkably the roots displayed enhanced responses while the leaves showed reduced responses. These findings suggest that plants adapt to the long-term NaCl stress, while H2O2 might be an integrator of many stresses