We present 855 cataclysmic variable candidates detected by the Catalina Real-time Transient Survey (CRTS) of which at least 137 have been spectroscopically confirmed and 705 are new discoveries. The ...sources were identified from the analysis of five years of data, and come from an area covering three quarters of the sky. We study the amplitude distribution of the dwarf novae cataclysmic variables (CVs) discovered by CRTS during outburst, and find that in quiescence they are typically 2 mag fainter compared to the spectroscopic CV sample identified by the Sloan Digital Sky Survey. However, almost all CRTS CVs in the SDSS footprint have ugriz photometry. We analyse the spatial distribution of the CVs and find evidence that many of the systems lie at scale heights beyond those expected for a Galactic thin disc population. We compare the outburst rates of newly discovered CRTS CVs with the previously known CV population, and find no evidence for a difference between them. However, we find significant evidence for a systematic difference in orbital period distribution. We discuss the CVs found below the orbital period minimum and argue that many more are yet to be identified among the full CRTS CV sample. We cross-match the CVs with archival X-ray catalogues and find that most of the systems are dwarf novae rather than magnetic CVs.
CO2 capture from the atmosphere and concentration by cyclic adsorption–desorption processes are studied for the first time. New high microporosity materials, zeolite types Li-LSX and K-LSX, are ...compared to zeolite NaX and amine-grafted SBA-15 with low amine content. Breakthrough performance showed low silica type X (LSX) to have the most promise for application in dry conditions and capable of high space velocities of at least 63 000 h–1, with minimal spreading of the CO2 breakthrough curve. Amine-grafted silica was the only adsorbent able to operate in wet conditions, but at a lower space velocity of 1500 h–1, due to slower uptake rates. The results illustrate that the uptake rate is as important as the equilibrium adsorbed amount in determining the cyclic process performance. Li-LSX was found to have double the capacity of zeolite NaX at atmospheric conditions, also higher than all other reported zeolites. It is further demonstrated that by using a combined temperature and vacuum swing cycle, the CO2 concentration in the desorption product is >90% for all adsorbents in pellet form. This is the first report of such high CO2 product concentrations from a single cycle, using atmospheric air.
Background
The aim of this study was to investigate the prevalence of epidemiologic and physician‐diagnosed pollen‐induced AR (PiAR) in the grasslands of northern China and to study the impact of the ...intensity and time of pollen exposure on PiAR prevalence.
Methods
A multistage, clustered and proportionately stratified random sampling with a field interviewer‐administered survey study was performed together with skin prick tests (SPT) and measurements of the daily pollen count.
Results
A total of 6043 subjects completed the study, with a proportion of 32.4% epidemiologic AR and 18.5% PiAR. The prevalence was higher in males than females (19.6% vs 17.4%, P = .024), but no difference between the two major residential and ethnic groups (Han and Mongolian) was observed. Subjects from urban areas showed higher prevalence of PiAR than rural areas (23.1% vs 14.0%, P < .001). Most PiAR patients were sensitized to two or more pollens (79.4%) with artemisia, chenopodium, and humulus scandens being the most common pollen types, which were similarly found as the top three sensitizing pollen allergens by SPT. There were significant regional differences in the prevalence of epidemiologic AR (from 18.6% to 52.9%) and PiAR (from 10.5% to 31.4%) among the six areas investigated. PiAR symptoms were positively associated with pollen counts, temperature, and precipitation (P < .05), but negatively with wind speed and pressure P < .05).
Conclusion
Pollen‐induced AR (PiAR) prevalence in the investigated region is extremely high due to high seasonal pollen exposure, which was influenced by local environmental and climate conditions.
Predicting mutation-induced changes in protein thermodynamic stability (ΔΔG) is of great interest in protein engineering, variant interpretation, and protein biophysics. We introduce ThermoNet, a ...deep, 3D-convolutional neural network (3D-CNN) designed for structure-based prediction of ΔΔGs upon point mutation. To leverage the image-processing power inherent in CNNs, we treat protein structures as if they were multi-channel 3D images. In particular, the inputs to ThermoNet are uniformly constructed as multi-channel voxel grids based on biophysical properties derived from raw atom coordinates. We train and evaluate ThermoNet with a curated data set that accounts for protein homology and is balanced with direct and reverse mutations; this provides a framework for addressing biases that have likely influenced many previous ΔΔG prediction methods. ThermoNet demonstrates performance comparable to the best available methods on the widely used Ssym test set. In addition, ThermoNet accurately predicts the effects of both stabilizing and destabilizing mutations, while most other methods exhibit a strong bias towards predicting destabilization. We further show that homology between Ssym and widely used training sets like S2648 and VariBench has likely led to overestimated performance in previous studies. Finally, we demonstrate the practical utility of ThermoNet in predicting the ΔΔGs for two clinically relevant proteins, p53 and myoglobin, and for pathogenic and benign missense variants from ClinVar. Overall, our results suggest that 3D-CNNs can model the complex, non-linear interactions perturbed by mutations, directly from biophysical properties of atoms.
In this paper, a novel accurate and economical 3D computer vision‐based framework is proposed to quantify out‐of‐plane displacements of steel plate structures. First, a sequence of image frames of ...the steel plate structures of interest is collected. Second, using image association, structure‐from‐motion, and multi‐view stereo algorithms, a 3D point cloud of the steel plate structures and their surroundings is created. Third, an efficient 3D object detection method based on convolutional neural networks is developed and implemented to identify the steel plate structures in the 3D point cloud. Last, the out‐of‐plane displacements of the steel plate structures are quantified using point cloud postprocessing algorithms. The proposed framework has been implemented on a steel plate damper and a full‐scale steel corrugated plate wall panel, which are commonly used in structural and earthquake engineering applications. The results indicate the developed framework can successfully localize the steel plate components in the 3D scene and accurately quantify the out‐of‐plane structural displacements with an average accuracy of ∼1 mm. The implementation shows the proposed framework can accurately and efficiently quantify the out‐of‐plane displacements of steel plate structures in realistic engineering applications.
Propofol is a frequently used intravenous anesthetic agent. Recent studies show that propofol exerts a number of non-anesthetic effects. The present study aimed to investigate the effects of propofol ...on lung cancer cell lines H1299 and H1792 and functional role of microRNA (miR)-486 in these effects. H1299 and/or H1792 cells were treated with or without propofol and transfected or not with miR-486 inhibitor, and then cell viability and apoptosis were analyzed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and flow cytometry. The expression of miR-486 was determined by quantitative real-time polymerase chain reaction (qRT-PCR) with or without propofol treatment. Western blot was performed to analyze the protein expression of Forkhead box, class O (FOXO) 1 and 3, Bcl-2 interacting mediator of cell death (Bim), and pro- and activated caspases-3. Results showed that propofol significantly increased the miR-486 levels in both H1299 and H1792 cells compared to untreated cells in a dose-dependent manner (P<0.05 or P<0.01). Propofol statistically decreased cell viability but increased the percentages of apoptotic cells and protein expressions of FOXO1, FOXO3, Bim, and pro- and activated caspases-3; however, miR-486 inhibitor reversed the effects of propofol on cell viability, apoptosis, and protein expression (P<0.05 or P<0.01). In conclusion, propofol might be an ideal anesthetic for lung cancer surgery by effectively inhibiting lung cancer cell viability and inducing cell apoptosis. Modulation of miR-486 might contribute to the anti-tumor activity of propofol.
Abstract
Earlier identification of bolt loosening is crucial to maintain structural integrity and prevent system‐level collapse. In this study, a novel drone‐based 3D vision methodology has been ...proposed for autonomous bolt loosening assessment. First, a low‐cost micro aerial vehicle with various types of sensors is designed. Second, a drone‐based autonomous image collection method is proposed. Third, a 3D point cloud of the bolted connection is generated using the acquired images. Fourth, 3D point cloud processing methods are proposed to localize and quantify bolt loosening. The proposed method has been implemented on structural beam–column connections. The results show that the proposed drone‐based data collection method can effectively acquire images for 3D reconstruction. The 3D point cloud processing methods can reliably localize and quantify bolt loosening at high accuracy. The proposed method provides a more robust and comprehensive evaluation of bolt loosening, compared to existing 2D vision methods, which process 2D images captured at a specific camera view.
Earthquake-induced building collapses and casualties have been effectively controlled in the last two decades. However, earthquake-induced economic losses have continued to rise. Following the ...objective and procedure of next-generation performance-based seismic design, the economic loss prediction method proposed by FEMA-P58 is extended to regional earthquake loss prediction in this study. The engineering demand parameters for a large number of buildings within a region are efficiently obtained through nonlinear time history analysis using multi-story concentrated-mass shear models. The building data, including structural and nonstructural components, are obtained through field investigation, structural and architectural drawings, and default database published in the FEMA-P58 document. A case study of Tsinghua University campus in Beijing is performed to demonstrate the implementation and advantage using proposed FEMA-P58 method for regional earthquake loss prediction. The results show the advancement in loss simulation for a region, and in identifying the influence of the different ground motion characteristics (e.g., velocity pulse) on the regional loss.
PDF
