Modal analysis of a rectangular variable cross-section beam with multiple cracks under different temperatures

A new method is proposed to calculate natural frequencies of a rectangular variable cross-section beam with multiple cracks under different temperatures. The temperature module is introduced through the elastic modulus, and cracks are modelled by bending springs without mass. Based on the transfer matrix method, the characteristic equation of the cracked beam is derived by the implementation of different boundary conditions. Examples are presented on cantilever beams having different non-uniformity parameters, and the influence of the temperature, the number and geometric parameters of cracks on natural frequencies is also investigated. Compared with results obtained using the Patran FEM method, good agreements are obtained and this analytical method is demonstrated to be feasible

Laser-Ranging Transponders for Science Investigations of the Moon and Mars

An active laser was developed ranging in real-time with two terminals, emulating interplanetary distances, and with submillimeter accuracy. In order to overcome the limitations to ranging accuracy from jitters and delay drifts within the transponders, architecture was proposed based on asynchronous paired one-way ranging with local references. A portion of the transmitted light is directed, via a reference path, to the local detector. This allows for compensation of any jitter in the timing of the emitted laser pulse. The same detector is used to measure the time of the received pulses emitted from the remote terminal. This approach removes any change in the delay caused by the detector or its electronics. Two separate terminals using commercial off-the-shelf hardware were built to emulate active laser ranging over interplanetary distances. The communication link for the command to start recording pulse arrival times and data transfer from one terminal to the other was achieved using a standard wireless link, emulating free space laser communication. The deviation is well below the goal of 1-mm precision. This leaves enough margin to achieve 1-mm precision when including the fluctuations due to atmospheric turbulence while ranging to Mars through the Earth s atmosphere. The two terminals are mounted on translation stages, which can be moved freely on rails to yield a wide range of distances with fine adjustment. The two terminals were separated by approximately 16 meters

Spatial-temporal Graph Based Multi-channel Speaker Verification With Ad-hoc Microphone Arrays

The performance of speaker verification degrades significantly in adverse acoustic environments with strong reverberation and noise. To address this issue, this paper proposes a spatial-temporal graph convolutional network (GCN) method for the multi-channel speaker verification with ad-hoc microphone arrays. It includes a feature aggregation block and a channel selection block, both of which are built on graphs. The feature aggregation block fuses speaker features among different time and channels by a spatial-temporal GCN. The graph-based channel selection block discards the noisy channels that may contribute negatively to the system. The proposed method is flexible in incorporating various kinds of graphs and prior knowledge. We compared the proposed method with six representative methods in both real-world and simulated environments. Experimental results show that the proposed method achieves a relative equal error rate (EER) reduction of $\mathbf{15.39\%}$ lower than the strongest referenced method in the simulated datasets, and $\mathbf{17.70\%}$ lower than the latter in the real datasets. Moreover, its performance is robust across different signal-to-noise ratios and reverberation time

FCG-ASpredictor: An Approach for the Prediction of Average Speed of Road Segments with Floating Car GPS Data

The average speed (AS) of a road segment is an important factor for predicting traffic congestion, because the accuracy of AS can directly affect the implementation of traffic management. The traffic environment, spatiotemporal information, and the dynamic interaction between these two factors impact the predictive accuracy of AS in the existing literature, and floating car data comprehensively reflect the operation of urban road vehicles. In this paper, we proposed a novel road segment AS predictive model, which is based on floating car data. First, the impact of historical AS, weather, and date attributes on AS prediction has been analyzed. Then, through spatiotemporal correlations calculation based on the data from Global Positioning System (GPS), the predictive method utilizes the recursive least squares method to fuse the historical AS with other factors (such as weather, date attributes, etc.) and adopts an extended Kalman filter algorithm to accurately predict the AS of the target segment. Finally, we applied our approach on the traffic congestion prediction on four road segments in Chengdu, China. The results showed that the proposed predictive model is highly feasible and accurate. Document type: Articl

Genome architecture changes and major gene variations of Andrias davidianus ranavirus (ADRV)

Ranaviruses are emerging pathogens that have led to global impact and public concern. As a rarely endangered species and the largest amphibian in the world, the Chinese giant salamander, Andrias davidianus, has recently undergone outbreaks of epidemic diseases with high mortality. In this study, we isolated and identified a novel ranavirus from the Chinese giant salamanders that exhibited systemic hemorrhage and swelling syndrome with high death rate in China during May 2011 to August 2012. The isolate, designated Andrias davidianus ranavirus (ADRV), not only could induce cytopathic effects in different fish cell lines and yield high viral titers, but also caused severely hemorrhagic lesions and resulted in 100% mortality in experimental infections of salamanders. The complete genome of ADRV was sequenced and compared with other sequenced amphibian ranaviruses. Gene content and phylogenetic analyses revealed that ADRV should belong to an amphibian subgroup in genus Ranavirus, and is more closely related to frog ranaviruses than to other salamander ranaviruses. Homologous gene comparisons show that ADRV contains 99%, 97%, 94%, 93% and 85% homologues in RGV, FV3, CMTV, TFV and ATV genomes respectively. In addition, several variable major genes, such as duplicate US22 family-like genes, viral eukaryotic translation initiation factor 2 alpha gene and novel 75L gene with both motifs of nuclear localization signal (NLS) and nuclear export signal (NES), were predicted to contribute to pathogen virulence and host susceptibility. These findings confirm the etiologic role of ADRV in epidemic diseases of Chinese giant salamanders, and broaden our understanding of evolutionary emergence of ranaviruses

Climate change impact on China food security in 2050

Climate change is now affecting global agriculture and food production worldwide. Nonetheless the direct link between climate change and food security at the national scale is poorly understood. Here we simulated the effect of climate change on food security in China using the CERES crop models and the IPCC SRES A2 and B2 scenarios including CO2 fertilization effect. Models took into account population size, urbanization rate, cropland area, cropping intensity and technology development. Our results predict that food crop yield will increase +3-11 % under A2 scenario and +4 % under B2 scenario during 2030-2050, despite disparities among individual crops. As a consequence China will be able to achieve a production of 572 and 615 MT in 2030, then 635 and 646 MT in 2050 under A2 and B2 scenarios, respectively. In 2030 the food security index (FSI) will drop from +24 % in 2009 to -4.5 % and +10.2 % under A2 and B2 scenarios, respectively. In 2050, however, the FSI is predicted to increase to +7.1 % and +20.0 % under A2 and B2 scenarios, respectively, but this increase will be achieved only with the projected decrease of Chinese population. We conclude that 1) the proposed food security index is a simple yet powerful tool for food security analysis; (2) yield growth rate is a much better indicator of food security than yield per se; and (3) climate change only has a moderate positive effect on food security as compared to other factors such as cropland area, population growth, socio-economic pathway and technology development. Relevant policy options and research topics are suggested accordingly

What is valued most by patients with type 2 diabetes mellitus when selecting second-line antihyperglycemic medications in China

Objective: To estimate patient preferences for second-line antihyperglycemic medications in China. Methods: A face to face survey with the best-worst scaling (BWS) choices was administered in patients with diagnosed type 2 diabetes mellitus (T2DM). Study participants were asked to indicate which attribute they valued most and which attribute they valued least in 11 choice sets, each of which consisted of five alternatives out of 11 antihyperglycemic medication-specific attributes (treatment efficacy, weight change, hypoglycemic events, gastrointestinal side effects, cardiovascular health, urinary tract infection and genital infection side effects, edema, mode of administration, bone fracture, dosing frequency and out-of-pocket cost). A counting approach, a conditional logit model, and K-means clustering were used to estimate the relative importance of items and preference heterogeneity. Results: A total of 362 participants were included with a mean age of 63.6 (standard deviation: 11.8) years. There were 56.4% of participants were women, and 56.3% being diagnosed with diabetes for at least 5 years. Efficacy, cardiovascular health and hypoglycemic events were valued most, while dosing frequency, mode of administration and bone fracture were valued least. The K-means clustering further showed preference heterogeneity in out-of-pocket cost across the participants. Conclusion: Our study suggests that treatment efficacy, cardiovascular health and hypoglycemic events are valued most by Chinese patients with T2DM when selecting second-line antihyperglycemic medications. The study improves the understanding of patients’ preferences for second-line antihyperglycemic medications in China

Consistent Targets Provide Better Supervision in Semi-supervised Object Detection

In this study, we dive deep into the inconsistency of pseudo targets in semi-supervised object detection (SSOD). Our core observation is that the oscillating pseudo targets undermine the training of an accurate semi-supervised detector. It not only inject noise into student training but also lead to severe overfitting on the classification task. Therefore, we propose a systematic solution, termed Consistent-Teacher, to reduce the inconsistency. First, adaptive anchor assignment~(ASA) substitutes the static IoU-based strategy, which enables the student network to be resistant to noisy pseudo bounding boxes; Then we calibrate the subtask predictions by designing a 3D feature alignment module~(FAM-3D). It allows each classification feature to adaptively query the optimal feature vector for the regression task at arbitrary scales and locations. Lastly, a Gaussian Mixture Model (GMM) dynamically revises the score threshold of the pseudo-bboxes, which stabilizes the number of ground-truths at an early stage and remedies the unreliable supervision signal during training. Consistent-Teacher provides strong results on a large range of SSOD evaluations. It achieves 40.0 mAP with ResNet-50 backbone given only 10\% of annotated MS-COCO data, which surpasses previous baselines using pseudo labels by around 3 mAP. When trained on fully annotated MS-COCO with additional unlabeled data, the performance further increases to 47.2 mAP. Our code will be open-sourced soon