•A deep learning-based phase reconstruction scheme is proposed for high-resolution multi-shot (MSH) DWI reconstruction.•Higher SNR (especially with high acceleration rates), fewer aliasing artifacts, ...lower ghost-to-signal-ratio (GSR), higher tracked fiber counts, and finer fiber delineation can be obtained with MSH-DWI reconstruction compared to conventional MUSE.•Single-shot (SSH) DWIs were used for training, making the proposed method readily applicable for routine clinical exams.
A phase correction method for high-resolution multi-shot (MSH) diffusion weighted imaging (DWI) is proposed. The efficacy and generalization capability of the method were validated on both healthy volunteers and patients.
Conventionally, inter-shot phase variations for MSH echo-planar imaging (EPI) DWI are corrected by model-based algorithms. However, many acquisition imperfections are hard to measure accurately for conventional model-based methods, making the phase estimation and artifacts suppression unreliable. We propose a deep learning multiplexed sensitivity-encoding (DL-MUSE) framework to improve the phase estimations based on convolutional neural network (CNN) reconstruction. Aliasing-free single-shot (SSH) DW images, which have been used routinely in clinical settings, were used for training before the aliasing correction of MSH-DWI images. A dual-channel U-net comprising multiple convolutional layers was used for the phase estimation of MSH-EPI. The network was trained on a dataset containing 30 healthy volunteers and tested on another dataset of 52 healthy subjects and 15 patients with lesions or tumors with different shot numbers (4, 6 and 8). To further validate the generalization capability of our network, we acquired a dataset with different numbers of shots, TEs, partial Fourier factors, resolutions, ETLs, FOVs, coil numbers, and image orientations from two sites. We also compared the reconstruction performance of our proposed method with that of the conventional MUSE and SSH-EPI qualitatively and quantitatively.
Our results show that DL-MUSE is capable of correcting inter-shot phase errors with high and robust performance. Compared to conventional model-based MUSE, our method, by applying deep learning-based phase corrections, showed reduced distortion, noise level, and signal loss in high b-value DWIs. The improvements of image quality become more evident as the shot number increases from 4 to 8, especially in those central regions of the images, where g-factor artifacts are severe. Furthermore, the proposed method could provide the information about the orientation of the white matter with better consistency and achieve finer fibers delineation compared to the SSH-EPI method. Besides, the experiments on volunteers and patients from two different sites demonstrated the generalizability of our proposed method preliminarily.
A deep learning-based reconstruction algorithm for MSH-EPI images, which helps improve image quality greatly, was proposed. Results from healthy volunteers and tumor patients demonstrated the feasibility and generalization performances of our method for high-resolution MSH-EPI DWI, which can be used for routine clinical applications as well as neuroimaging research.
Urban freeway traffic control is of great importance for traffic management and intelligent transportation systems. Various approaches have been proposed to relieve urban freeway traffic jam, among ...which, ALINEA, a ramp metering strategy, is commonly implemented with fixed triggering threshold and static controller parameter. However, such a strategy may not be able to effectively alleviate the traffic congestion while maintaining certain ramp throughput due to two reasons: i). the congestion threshold can be time-varying due to different factors, such as segment ID, weather condition, time, and etc. ii). The congestion evolution patterns are time-varying even for the same segment. In this paper, based on over 890 million records of vehicles collected on ramps in Hangzhou, China, we established dynamic congestion threshold for each road segment with external factors. Based on such dynamic congestion threshold, we further clustered the congestion evolution patterns, and designed adaptive ramp controller which could switch the controller parameter according to the predicted congestion evolution pattern. Finally, in order to show the performance among different strategies, we introduced three baseline groups, which are `without Controller', `ALINEA controller', and `Direct RBF(radial basis function)-neural network controller', respectively.The evaluation of proposed controller design over real large-scale data indicated that our method achieves 8.4%(7.2%), 4.62%(9.48%) efficiency improvement in terms of average speed in km/h (average traffic flow in veh/h) than the performance with normal ALINEA controller and RBF-neural network controller respectively.
Gait disturbance is a manifestation of cerebral small vessel disease (CSVD). The posterolateral thalamus (PL), whose blood is mainly supplied by the P2 segment of posterior cerebral artery (P2-PCA), ...plays pivotal roles in gait regulation. We investigated the influence of the distance between P2-PCA and PL on gait with varying CSVD burden. 71 participants were divided into low and high CSVD burden groups. The distance from P2-PCA to PL was measured using 7 T TOF-MRA and categorized into an immediate or distant PCA-to-thalamus pattern. Functional connectivity (FC) and voxel-based morphometry were assessed to evaluate functional and structural alterations. In the low CSVD burden group, immediate PCA-to-thalamus supply strongly correlates with longer step length and higher wave phase time percent, and exhibited enhanced FCs in left supplementary motor area, right precentral cortex (PreCG.R). While in the high CSVD burden group, no association between PCA-to-thalamus pattern and gait was found, and we observed reduced FC in PreCG.R with immediate PCA-to-thalamus pattern. Higher CSVD burden was associated with decreased gray matter density in bilateral thalamus. However, no significant structural thalamic change was observed between the two types of PCA-to-thalamus patterns in all patients. Our study demonstrated patients with immediate PCA-to-thalamus supply exhibited better gait performance in low CSVD burden populations, which also correlated with enhanced FCs in motor-related cortex, indicating the beneficial effects of the immediate PCA-to-thalamus supply pattern. In the higher burden CSVD populations, the effects of PCA-to-thalamus pattern on gait are void, attributable to the CSVD-related thalamic destruction and impairment of thalamus-related FC.
This paper reports on the measurement of optical property mapping of apples at the wavelengths of 460, 527, 630, and 710 nm using spatial-frequency domain imaging (SFDI) technique, for assessing the ...soluble solid content (SSC), firmness, and color parameters. A laboratory-based multispectral SFDI system was developed for acquiring SFDI of 140 "Golden Delicious" apples, from which absorption coefficient (
) and reduced scattering coefficient (
) mappings were quantitatively determined using the three-phase demodulation coupled with curve-fitting method. There was no noticeable spatial variation in the optical property mapping based on the resulting effect of different sizes of the region of interest (ROI) on the average optical properties. Support vector machine (SVM), multiple linear regression (MLR), and partial least square (PLS) models were developed based on
,
and their combinations (
×
and
) for predicting apple qualities, among which SVM outperformed the best. Better prediction results for quality parameters based on the
were observed than those based on the
, and the combinations further improved the prediction performance, compared to the individual
or
. The best prediction models for SSC and firmness parameters slope, flesh firmness (FF), and maximum force (Max.F) were achieved based on the
×
, whereas those for color parameters of b* and C* were based on the
, with the correlation coefficients of prediction as 0.66, 0.68, 0.73, 0.79, 0.86, and 0.86, respectively.
Rheumatoid Arthritis (RA) is a chronic autoimmune disease that can lead to joint pain and disability, and seriously impact patients' quality of life. Strychni Semen combined with Atractylodes ...Macrocephala koidz (SA) have pronounced curative effect on RA, and there is no poisoning of Strychni Semen (SS). However, its pharmacological mechanisms are still unclear.
In this study, we aimed to investigate the pharmacological mechanisms of Strychni Semen combined with Atractylodes Macrocephala Koidz (SA) for the treatment of RA.
We used network pharmacology to screen the active components of SA and predict the targets and pathways involved. Results originating from network pharmacology were then verified by animal experiments.
Network pharmacology identified 81 active ingredients and 141 targets of SA; 2640 disease- related genes were also identified. The core targets of SA for the treatment of RA included ALB, IL-6, TNF and IL-1β. A total of 354 gene ontology terms were identified by Gene ontology (GO) enrichment analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis results showed that SA was closely associated with TNF signaling pathways in the treatment of RA. Furthermore, according to the predicted results of network pharmacology, we established a rat model of Adjuvant Arthritis (AA) for
experiments. Analysis showed that each treatment group led to an improvement in paw swelling, immune organ coefficient and synovial tissue morphology in AA rats to different degrees, inhibit the expression levels of IL-1β, TNF-α and IL-6, upregulated the levels of Fas, Bax and Caspase 3, down-regulated the expression levels of Fas-L, Bcl-2 and p53.
SA has an anti-RA effect, the mechanism underlying the therapeutic action of SA in AA rats was related to the regulation of apoptosis signaling pathways.
Orchard plant protection machinery in China still has a low application efficiency. Air-blast sprayers represent the primary development direction of pesticide applications in orchards. The spray ...control parameters have to be matched to the tree canopy status to achieve precise results. In this study, a vertical patternator was used to determine the accuracy of spraying fruit trees. The influences of three control parameters (blower speed, spray angle, and spray distance) on the spray performance of the air-blast sprayer were analyzed, and the volume of the spray was measured in collection plates at different heights. The quantitative relationship between the overall collection volume and the critical height collection volume was obtained for different parameter values, and the combined effects of any two control parameters on the collection performance and the position of the optimum collection area were obtained. The regression model describing the relationship between the collection volume in the critical height range and the three factors was established, and the main effects of the control parameters were determined. The results showed that if one parameter remained constant, the correlation between the other two parameters was non-significant. The collection volume in the critical height range increased initially and then decreased as the spray distance increased. The maximum collection volume was obtained at a spray distance of 1.762 m. The regression model can be used to obtain the optimum values of the parameters.
Spatial-frequency domain imaging (SFDI) is a wide-field, noncontact, and label-free imaging modality that is currently being explored as a new means for estimating optical absorption and scattering ...properties of two-layered turbid materials. The accuracy of SFDI for optical property estimation, however, depends on light transfer model and inverse algorithm. This study was therefore aimed at providing theoretical analyses of the diffusion model and inverse algorithm through numerical simulation, so as to evaluate the potential for estimating optical absorption and reduced scattering coefficients of two-layered horticultural products. The effect of varying optical properties on reflectance prediction was first simulated, which indicated that there is good separation in diffuse reflectance over a large range of spatial frequencies for different reduced scattering values in the top layer, whereas there is less separation in diffuse reflectance for different values of absorption in the top layer, and even less separation for optical properties in the bottom layer. To implement the nonlinear least-square method for extracting the optical properties of two-layered samples from Monte Carlo-generated reflectance, five curve fitting strategies with different constrained parameters were conducted and compared. The results confirmed that estimation accuracy improved as fewer variables were to be estimated each time. A stepwise method was thus suggested for estimating optical properties of two-layered samples. Four factors influencing optical property estimation of the top layer, which is the basis for accurately implementing the stepwise method, were investigated by generating absolute error contour maps. Finally, the relationship between light penetration depth and spatial frequency was studied. The results showed that penetration depth decreased with the increased spatial frequency and also optical properties, suggesting that appropriate selection of spatial frequencies for a stepwise method to estimate optical properties from two-layered samples provides potential for estimation accuracy improvement. This work lays a foundation for improving optical property estimation of two-layered horticultural products using SFDI.
A 6-degree-of-freedom (DOF) model of a pilot's upper limb is established in this study. A kinematics analysis is performed by using the screw theory and the product of exponential formula. Kane's ...equation in screw form, which is a concise form with a definite physical meaning, is used to analyze the dynamic characteristics of a pilot's upper limb. In the Mathematica environment, the man-machine system consisting of a pilot and a joystick is taken as the analysis object to simulate the joystick pushing and pulling processes of a pilot at the 50th percentile of Chinese body dimensions. The analysis yields the angular velocity and angular acceleration curves of the joint, which indicate that the manipulation comfort is rather good. The actual posture data during the pilot manipulation process are measured. Through a comparison with the output data, the correctness of the simulation analysis is verified. The torque curve reflects that the torque of the shoulder joint is greater than that of the elbow joint, and the changing tendency conforms to the actual motion law. Therefore, the correctness of Kane's equation in screw form is verified. At the same time, the results can serve as a theoretical basis for evaluating a pilot's manipulation comfort and as an important reference for cockpit layout design.
As an innovative mobility strategy, public bike-sharing has grown dramatically worldwide. Though it provides convenient, low-cost, and environmental-friendly transportation, the unique features of ...bike-sharing systems give rise to problems for both users and operators. The primary issue is the uneven distribution of bikes caused by ever-changing usage and (available) supply. This imbalance necessitates efficient bike rebalancing strategies, which depends highly on bike mobility modeling and prediction. In this paper, a trace-driven simulation-based prediction approach is proposed by simultaneously taking user mobility demand and real-time status of stations into consideration. We extensively evaluate the performance of our design with the dataset from one of the world's largest public bike-sharing systems located in Hangzhou, China, which owns more than 2800 stations. The evaluation results show an 85 percentile relative error of 0.6 for checkout and 0.4 for checkin prediction. The preliminary results on how the predictions can be used for bike rebalancing are also provided. We believe that this new mobility modeling and prediction approach can improve the bike-sharing system operation algorithm design and pave the way for rapid deployment and adoption of bike-sharing systems across the globe.
PDF
