Spectral Compressive Sensing with Model Selection

The performance of existing approaches to the recovery of frequency-sparse signals from compressed measurements is limited by the coherence of required sparsity dictionaries and the discretization of frequency parameter space. In this paper, we adopt a parametric joint recovery-estimation method based on model selection in spectral compressive sensing. Numerical experiments show that our approach outperforms most state-of-the-art spectral CS recovery approaches in fidelity, tolerance to noise and computation efficiency.Comment: 5 pages, 2 figures, 1 table, published in ICASSP 201

Drought Tolerance Dissection and Molecular Breeding in Alfalfa

Drought stress is one of the leading impediments that limit the productivity of global alfalfa (Medicago sativa). The underlying molecular and genetic mechanisms for drought tolerance in alfalfa remain largely unclear. In order to fully reveal the transcriptional changes of alfalfa in response to abiotic stress, the alfalfa transcriptome database under mannitol (simulated drought stress), NaCl (simulated salt stress), or exogenous ABA application was built via various RNA-seq technologies. Through further screening of the transcriptome database, a number of genes significantly induced by drought stress, such as the Nuclear Transport Factor 2-like (MsNTF2L), Drought-Induced Unknown Protein 1 (MsDIUP1), and MsNST1, were identified. These three genes were transferred into alfalfa by overexpression and RNAi techniques, and their physiological characteristics and transcriptional level response were synthetically studied. Alfalfa MsNTF2L-OE plants have been approved by the Ministry of Agriculture of China to carry out the field test in Gansu Province. Furthermore, we constructed a GWAS population and obtained 50 excellent plants with strong drought tolerance and high hay-yield. These studies provide a theoretical foundation for drought-tolerant molecular breeding of alfalfa

An experimental study on the effect of salt spray testing on the optical properties of solar selective absorber coatings produced with different manufacturing technologies

Solar selective absorber coating (SSAC) is one of the key components of a solar collector, with its optical properties having a significant impact on the collector’s thermal performance. The key parameters characterizing the optical properties of an SSAC are the solar absorptance (absorptance of solar radiation) and the thermal emittance (emittance for long-wave radiation). However, some of high-performing SSACs suffer from some drawbacks, such as lower durability, lower resistance to corrosion and abrasion, which is particularly harmful for SSACs, as, for example, chlorides in the atmosphere have become a main contributor to corrosion in coastal areas with the increasing trend of global warming. In this paper, salt spray tests have been conducted on the SSACs manufactured by three common manufacturing technologies, i.e., the anode oxidation (AO) technology, the vacuum magnetron sputtering (VMS) technology, and the black chromium plating (BCP) technology, over the testing durations of 12 h, 24 h, 36 h, and 48 h, respectively, to examine the effect of the salt spray testing on the optical properties of SSACs manufactured by different manufacturing technologies. The salt spray testing is an accelerated aging testing method for evaluating the SSAC’s resistance to corrosion when it is under an extended exposure to a saline, or salted, spray (fog). The experimental results show that, in general, the SSACs manufactured by the BCP technology have excellent resistance to salt spray (i.e., to corrosion) and those manufactured by the AO technology have only reasonable resistance to corrosion, whereas the SSACs manufactured by the VMS technology have very poor resistance to corrosion. The results also demonstrate that there are noticeable differences in the optical properties of the SSAC samples even manufactured by the same technology but by different manufacturers, with some having significant differences. The causes for the differences have been further examined through the inspection of the physical appearance of the selected SSAC samples and the experimentally measured distributions of the monochromatic reflectance of solar radiation of the samples over the solar spectrum before and after the salt spray testing over different durations

FeatureBooster: Boosting Feature Descriptors with a Lightweight Neural Network

We introduce a lightweight network to improve descriptors of keypoints within the same image. The network takes the original descriptors and the geometric properties of keypoints as the input, and uses an MLP-based self-boosting stage and a Transformer-based cross-boosting stage to enhance the descriptors. The enhanced descriptors can be either real-valued or binary ones. We use the proposed network to boost both hand-crafted (ORB, SIFT) and the state-of-the-art learning-based descriptors (SuperPoint, ALIKE) and evaluate them on image matching, visual localization, and structure-from-motion tasks. The results show that our method significantly improves the performance of each task, particularly in challenging cases such as large illumination changes or repetitive patterns. Our method requires only 3.2ms on desktop GPU and 27ms on embedded GPU to process 2000 features, which is fast enough to be applied to a practical system.Comment: 14 pages, 8 figures, 5 table

Experimental and numerical studies on indoor thermal comfort in fluid flow: a case study on primary school classrooms

Indoor thermal comfort in primary classrooms is important to students' learning and health. The studies focusing on it, especially under the subtropical plateau monsoon climate, are scarce. In this study, the indoor thermal comfort surveys and parameter measurements were made over the period from October 2018 to December 2018 in Kunming, China. A series of indoor thermal comfort and outdoor parameters were measured each 1 h and subjective questionnaire surveys were performed on the selected 20 students every week except on holidays. A series of three-dimensional numerical simulations were carried out using ANSYS Fluent

AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection

The short-form videos have explosive popularity and have dominated the new social media trends. Prevailing short-video platforms,~\textit{e.g.}, Kuaishou (Kwai), TikTok, Instagram Reels, and YouTube Shorts, have changed the way we consume and create content. For video content creation and understanding, the shot boundary detection (SBD) is one of the most essential components in various scenarios. In this work, we release a new public Short video sHot bOundary deTection dataset, named SHOT, consisting of 853 complete short videos and 11,606 shot annotations, with 2,716 high quality shot boundary annotations in 200 test videos. Leveraging this new data wealth, we propose to optimize the model design for video SBD, by conducting neural architecture search in a search space encapsulating various advanced 3D ConvNets and Transformers. Our proposed approach, named AutoShot, achieves higher F1 scores than previous state-of-the-art approaches, e.g., outperforming TransNetV2 by 4.2%, when being derived and evaluated on our newly constructed SHOT dataset. Moreover, to validate the generalizability of the AutoShot architecture, we directly evaluate it on another three public datasets: ClipShots, BBC and RAI, and the F1 scores of AutoShot outperform previous state-of-the-art approaches by 1.1%, 0.9% and 1.2%, respectively. The SHOT dataset and code can be found in https://github.com/wentaozhu/AutoShot.git .Comment: 10 pages, 5 figures, 3 tables, in CVPR 2023; Top-1 solution for scene / shot boundary detection https://paperswithcode.com/paper/autoshot-a-short-video-dataset-and-state-o

MRI signal intensity differentiation of brainstem encephalitis induced by Enterovirus 71: a classification approach for acute and convalescence stages

Additional file 3. After tick the segment region, Medflovan show the segmentation region of lesion

Ku80 cooperates with CBP to promote COX-2 expression and tumor growth.

Cyclooxygenase-2 (COX-2) plays an important role in lung cancer development and progression. Using streptavidin-agarose pulldown and proteomics assay, we identified and validated Ku80, a dimer of Ku participating in the repair of broken DNA double strands, as a new binding protein of the COX-2 gene promoter. Overexpression of Ku80 up-regulated COX-2 promoter activation and COX-2 expression in lung cancer cells. Silencing of Ku80 by siRNA down-regulated COX-2 expression and inhibited tumor cell growth in vitro and in a xenograft mouse model. Ku80 knockdown suppressed phosphorylation of ERK, resulting in an inactivation of the MAPK pathway. Moreover, CBP, a transcription co-activator, interacted with and acetylated Ku80 to co-regulate the activation of COX-2 promoter. Overexpression of CBP increased Ku80 acetylation, thereby promoting COX-2 expression and cell growth. Suppression of CBP by a CBP-specific inhibitor or siRNA inhibited COX-2 expression as well as tumor cell growth. Tissue microarray immunohistochemical analysis of lung adenocarcinomas revealed a strong positive correlation between levels of Ku80 and COX-2 and clinicopathologic variables. Overexpression of Ku80 was associated with poor prognosis in patients with lung cancers. We conclude that Ku80 promotes COX-2 expression and tumor growth and is a potential therapeutic target in lung cancer