With the serious impact of fossil fuels on the environment and the rapid development of the global economy, the development of clean and usable energy storage devices has become one of the most ...important themes of sustainable development in the world today. Supercapacitors are a new type of green energy storage device, with high power density, long cycle life, wide temperature range, and both economic and environmental advantages. In many industries, they have enormous application prospects. Electrode materials are an important factor affecting the performance of supercapacitors. MnO2‐based materials are widely investigated for supercapacitors because of their high theoretical capacitance, good chemical stability, low cost, and environmental friendliness. To achieve high specific capacitance and high rate capability, the current best solution is to use MnO2 and carbon composite materials. Herein, MnO2–carbon composite as supercapacitor electrode materials is reviewed including the synthesis method and research status in recent years. Finally, the challenges and future development directions of an MnO2–carbon based supercapacitor are summarized.
In this paper, the mechanism of MnO2‐based supercapacitors is summarized, and the synthesis method and research status of MnO2‐carbon based supercapacitor electrode materials in recent years are reviewed. Finally, the challenges and future development directions of MnO2‐carbon based supercapacitors are discussed.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Owing to its powerful adaptability and robustness to the weak light, the infrared camera equipped on the unmanned aerial vehicle is more and more applied for aerial photography. Nowadays, how to make ...full use of the aerial infrared image sequences for the moving vehicle detection has attracted widespread attention. However, due to the low-resolution, low contrast, and few texture features of the infrared image, it is extremely difficult to detect the moving vehicles. In our work, an effective and efficient moving vehicle detection approach in the aerial infrared image sequences is proposed via fast image registration and You Only Look Once Version 3 (YOLOv3) network. First, to compensate for the motion of the aerial infrared camera, a fast infrared image registration method is put forward. To improve the accuracy and efficiency of image registration, we construct a multi-screening based mechanism for screening out the incorrect and redundant feature points. For feature description, the low-level and high-level descriptors are combined to further improve the registration accuracy. Then, the 2-frame difference and image masking are introduced to acquire the frame mask images, where only the region-of-interest is reserved, and the remaining regions are masked. Next, we construct a new structure of an improved YOLOv3 network with only 23 layers. Due to the insufficiency of the infrared vehicle samples, transfer learning is introduced to train the improved YOLOv3 network. Finally, the proposed approach is evaluated on the Defence Advanced Research Projects Agency (DARPA) Video verification of Identify (VIVID) and Northwest Polytechnical University (NPU) data sets. Experiments and comprehensive analyses show that the proposed approach can achieve satisfactory and competitive moving vehicle detection results.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
In order to deal with the problems of low evaluation accuracy and long evaluation time in the traditional English classroom teaching quality monitoring and evaluation methods, this study proposes an ...English classroom teaching quality monitoring and evaluation method based on big data. According to the selection principle of English classroom teaching quality monitoring factors, this study analyzes the English classroom teaching quality monitoring factors, constructs the English classroom teaching quality monitoring index system, obtains the monitoring index data, filters and compresses the monitoring data, and takes the preprocessed English classroom teaching quality monitoring data as the evaluation index. This study uses the principal component analysis method to calculate the weight of the English classroom teaching quality evaluation index and constructs an English classroom teaching quality evaluation model. The simulation results show that the proposed method has high accuracy and short evaluation time.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Seismic design principles advocate for simple and regular structures to minimize earthquake damage. However, this frequently does not lead to unique and aesthetically pleasing designs, leading some ...engineers to select irregular structures despite the potential risks. The primary aim of this investigation is to achieve the optimal design of torsional irregularity coefficients for planar irregular reinforced concrete (RC) frames under static and dynamic loads, utilizing a 3D 6-layer model. Structural ground vibration analysis was conducted using the ETABS software. By imposing limits on the torsional irregularity coefficients for each layer of the frame layout, we subsequently applied the combination of artificial neural networks (ANN) with the particle swarm optimization (PSO) algorithm, namely ANN-PSO, to address the size distribution issue across the structure. The design variables included the dimensions of the columns located in each layer of the layout. The results demonstrate that the ANN-PSO algorithm optimizes the cross-sectional area of columns with significant variations. The coefficients of the torsion inequality rule in the optimized solution closely approach the minimum values. The dimensions and orientations of the optimized columns slightly differ from the pre-optimized scheme. In the optimized scheme, the coefficients of the torsional irregularity in the Y-direction meet the requirements, preventing any torsional irregularities from occurring. The research presented an effective method, including an innovative combination of ANN-PSO and the finite element method (FEM), for designing RC structures. The findings of the research provided a practical solution to fulfill torsional regularity criteria, indicating the proposed approach is an effective method for the economical and safe design of RC structures in earthquake-prone areas. The outcomes of the present study highlighted the innovative framework to achieve optimal and safe designs for irregular RC structures while minimizing torsional damage during earthquakes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Compromised endothelial barrier function is a hallmark of inflammation. Rho family GTPases are critical in regulating endothelial barrier function, yet their precise roles, particularly in ...sphingosine-1-phosphate (S1P)-induced endothelial barrier enhancement, remain elusive. Confluent cultures of human umbilical vein endothelial cells (HUVEC) or human dermal microvascular endothelial cells (HDMEC) were used to model the endothelial barrier. Barrier function was assessed by determining the transendothelial electrical resistance (TER) using an electrical cell-substrate impedance sensor (ECIS). The roles of Rac1 and RhoA were tested in S1P-induced barrier enhancement. The results show that pharmacologic inhibition of Rac1 with Z62954982 failed to block S1P-induced barrier enhancement. Likewise, expression of a dominant negative form of Rac1, or knockdown of native Rac1 with siRNA, failed to block S1P-induced elevations in TER. In contrast, blockade of RhoA with the combination of the inhibitors Rhosin and Y16 significantly reduced S1P-induced increases in TER. Assessment of RhoA activation in real time using a fluorescence resonance energy transfer (FRET) biosensor showed that S1P increased RhoA activation primarily at the edges of cells, near junctions. This was complemented by myosin light chain-2 phosphorylation at cell edges, and increased F-actin and vinculin near intercellular junctions, which could all be blocked with pharmacologic inhibition of RhoA. The results suggest that S1P causes activation of RhoA at the cell periphery, stimulating local activation of the actin cytoskeleton and focal adhesions, and resulting in endothelial barrier enhancement. S1P-induced Rac1 activation, however, does not appear to have a significant role in this process.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Gliomas are the common type of brain tumors originating from glial cells. Epidemiologically, gliomas occur among all ages, more often seen in adults, which males are more susceptible than females. ...According to the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5), standard of care and prognosis of gliomas can be dramatically different. Generally, circumscribed gliomas are usually benign and recommended to early complete resection, with chemotherapy if necessary. Diffuse gliomas and other high-grade gliomas according to their molecule subtype are slightly intractable, with necessity of chemotherapy. However, for glioblastoma, feasible resection followed by radiotherapy plus temozolomide chemotherapy define the current standard of care. Here, we discuss novel feasible or potential targets for treatment of gliomas, especially IDH-wild type glioblastoma. Classic targets such as the p53 and retinoblastoma (RB) pathway and epidermal growth factor receptor (EGFR) gene alteration have met failure due to complex regulatory network. There is ever-increasing interest in immunotherapy (immune checkpoint molecule, tumor associated macrophage, dendritic cell vaccine, CAR-T), tumor microenvironment, and combination of several efficacious methods. With many targeted therapy options emerging, biomarkers guiding the prescription of a particular targeted therapy are also attractive. More pre-clinical and clinical trials are urgently needed to explore and evaluate the feasibility of targeted therapy with the corresponding biomarkers for effective personalized treatment options.
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MEG3 noncoding RNA: a tumor suppressor Zhou, Yunli; Zhang, Xun; Klibanski, Anne
Journal of molecular endocrinology,
06/2012, Volume:
48, Issue:
3
Journal Article
Peer reviewed
Open access
Maternally expressed gene 3 (MEG3) is an imprinted gene belonging to the imprinted DLK1–MEG3 locus located at chromosome 14q32.3 in humans. Its mouse ortholog, Meg3, also known as gene trap locus 2 ...(Gtl2), is located at distal chromosome 12. The MEG3 gene encodes a long noncoding RNA (lncRNA) and is expressed in many normal tissues. MEG3 gene expression is lost in an expanding list of primary human tumors and tumor cell lines. Multiple mechanisms contribute to the loss of MEG3 expression in tumors, including gene deletion, promoter hypermethylation, and hypermethylation of the intergenic differentially methylated region. Re-expression of MEG3 inhibits tumor cell proliferation in culture and colony formation in soft agar. This growth inhibition is partly the result of apoptosis induced by MEG3. MEG3 induces accumulation of p53 (TP53) protein, stimulates transcription from a p53-dependent promoter, and selectively regulates p53 target gene expression. Maternal deletion of the Meg3 gene in mice results in skeletal muscle defects and perinatal death. Inactivation of Meg3 leads to a significant increase in expression of angiogenesis-promoting genes and microvessel formation in the brain. These lines of evidence strongly suggest that MEG3 functions as a novel lncRNA tumor suppressor.
Owing to the strong complementarity between visible and infra-red thermal (RGB-T) images, the two types of images receive the increased application of vehicle detection in traffic monitoring. Now, ...how to take full advantage of the two kinds of images for vehicle fusion detection has drawn wide publicity. Nevertheless, due to the requirement of high quality and high precision on vehicle fusion detection, and insufficiency of the infra-red thermal dataset, it is extremely hard to realize the vehicle fusion detection in RGB-T images. In our work, a complementary and precise vehicle fusion detection approach in RGB-T images is put forward, which combines the detection results of both visible and infra-red thermal images based on a decision-level fusion strategy. For vehicle detection in visible images, an effective and shallow network is constructed. For vehicle detection in infra-red thermal images, we do not directly train an effective network because of the insufficiency of the infra-red thermal vehicle samples. Instead, semi-supervised transfer learning is applied to combine the trained visible network for vehicle detection in infra-red thermal images. Next, for the decision-level fusion, we propose a novel fusion algorithm. It not only retains the vehicle results detected only in the visible images or only the infra-red thermal images but also fuses the detection results of the same vehicle in both visible and infra-red thermal images. Finally, VOT2019 and RGBT234 data sets are introduced to evaluate the proposed vehicle fusion detection approach. Compared with the main trend of current, it is indicated that the proposed approach can obtain competitive and superior vehicle fusion detection results in RGB-T images.
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Abstract
Our society is pursuing chemically recyclable polymers to accelerate the green revolution in plastics. Here, we develop a recyclable polyester library from the alternating copolymerization ...of aldehyde and cyclic anhydride. Although these two monomer sets have little or no thermodynamic driving force for homopolymerization, their copolymerization demonstrates the unexpected alternating characteristics. In addition to readily available monomers, the method is performed under mild conditions, uses common Lewis/Brønsted acids as catalysts, achieves the facile tuning of polyester structure using two distinct monomer sets, and yields 60 polyesters. Interestingly, the copolymerization exhibits the chemical reversibility attributed to its relatively low enthalpy, which makes the resulting polyesters perform closed-loop recycling to monomers at high temperatures. This study provides a modular, efficient, and facile synthesis of recyclable polyesters using sustainable monomers.
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