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- Höjer, Pontus, et al.
(författare)
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Identification of Major Immune Cell Lineages with DBS-Pro
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Proteins play a pivotal role in cellular function and heterogeneity. Understanding cellular diversity at the proteome level necessitates sensitive single-cell assays with high throughput. While current sequencing-based methods offer promise, they often face limitations, including reliance on expensive and inaccessible commercial platforms. Here, we have adopted the DBS-Pro method, utilizing site-specific oligonucleotide-conjugated antibodies, to analyze surface proteins in single cells. The method uses cheap degenerated barcode oligonucleotides and a simple microfluidics setup for cell encapsulation. A sample of PBMCs was examined using a panel targeting six separate immune cell markers. Using this panel we could quantify marker expression on 1,307 cells, identifying major immune cell lineages including CD4+ T-cells, CD8+ T-cells, monocytes, and B-cells. While recognizing the need for protocol improvements, our results present a promising approach for single-cell proteomics.
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| 5. |
- Wang, Jianfeng, et al.
(författare)
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Contrast Agent Quantification by Using Spatial Information in Dynamic Contrast Enhanced MRI
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The purpose of this study is to investigate a method, using simulations, to improve contrast agent quantification in Dynamic Contrast Enhanced MRI. Bayesian hierarchical models (BHMs) are applied to smaller images (10×10×10) such that spatial information can be incorporated. Then exploratory analysis is done for larger images (64×64×64) by using maximum a posteriori (MAP).For smaller images: the estimators of proposed BHMs show improvements in terms of the root mean squared error compared to the estimators in existing method for a noise level equivalent of a 12-channel head coil at 3T. Moreover, Leroux model outperforms Besag models. For larger images: MAP estimators also show improvements by assigning Leroux prior.
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| 6. |
- Wang, Jianfeng, 1984-, et al.
(författare)
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Effects of winter climate on high speed passenger trains in Botnia-Atlantica region
- 2020
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Harsh winter climate can cause various problems for both public and private sectors in Sweden, especially in the northern part for railway industry. To have a better understanding of winter climate impacts, this study investigates effects of the winter climate including atmospheric icing on the performance of high speed passenger trains in the Botnia-Atlantica region. The investigation is done with train operational data together with simulated weather data from the Weather Research and Forecast model over January - February 2017.Two different measurements of the train performance are analysed. One is cumulative delay which measures the increment in delay in terms of running time within two consecutive measuring spots, the other is current delay which is the delay in terms of arrival time at each measuring spot compared to the schedule. Cumulative delay is investigated through a Cox model and the current delay is studied using a Markov chain model.The results show that the weather factors have impacts on the train performance. Therein temperature and humidity have significant impacts on both the occurrence of cumulative delay and the transition probabilities between (current) delayed and non-delayed states.
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| 7. |
- Wang, Jianfeng, et al.
(författare)
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Sparsity estimation in compressive sensing with application to MR images
- 2017
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The theory of compressive sensing (CS) asserts that an unknown signal x in C^N canbe accurately recovered from m measurements with m << N provided that x is sparse. Most of the recovery algorithms need the sparsity s = ||x||_0 as an input. However,generally s is unknown, and directly estimating the sparsity has been an open problem.In this study, an estimator of sparsity is proposed by using Bayesian hierarchical model. Its statistical properties such as unbiasedness and asymptotic normality are proved. Inthe simulation study and real data study, magnetic resonance image data is used asinput signal, which becomes sparse after sparsified transformation. The results fromthe simulation study confirm the theoretical properties of the estimator. In practice, theestimate from a real MR image can be used for recovering future MR images under theframework of CS if they are believed to have the same sparsity level after sparsification.
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| 8. |
- Wang, Jianfeng, 1984-, et al.
(författare)
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Statistical inference for block sparsity of complex signals
- 2019
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Block sparsity is an important parameter in many algorithms to successfully recover block sparse signals under the framework of compressive sensing. However, it is often unknown and needs to beestimated. Recently there emerges a few research work about how to estimate block sparsity of real-valued signals, while there is, to the best of our knowledge, no investigation that has been conductedfor complex-valued signals. In this paper, we propose a new method to estimate the block sparsity of complex-valued signal. Its statistical properties are obtained and verified by simulations. In addition,we demonstrate the importance of accurately estimating the block sparsity in signal recovery through asensitivity analysis.
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| 9. |
- Wang, Wei, et al.
(författare)
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Enhanced Edge Detection for Polarimetric SAR Images Using Directional Span-Driven Adaptive Window
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Automatic edge detection for polarimetric synthetic aperture radar (PolSAR) images plays a fundamental role in various PolSAR applications. The classic methods apply the fixed-shape windows to detect the edges, whereas their performance is limited in heterogeneous areas. This paper presents an enhanced edge detection method for PolSAR data based on the directional span-driven adaptive (DSDA) window. The DSDA window has variable sizes and flexible shapes, and is constructed by adaptively selecting samples which follow the same statistical distribution. Therefore, it can overcome the limitation of classic fixed-shape windows. To obtain refined and reliable edge detection results in heterogeneous urban areas, we adopt the spherically invariant random vector (SIRV) product model, since the complex Wishart distribution is often not met. In addition, a span ratio is combined with the SIRV distance to highlight the dissimilarity measure and to improve the robustness of the proposed method. The simulated PolSAR data and three real data sets from ESAR, EMISAR and RADARSAT-2 systems are used to validate the performance of the enhanced edge detector. Both quantitative evaluation and visual presentation of the results demonstrate the effectiveness of the proposed method and its superiority over the classic edge detectors.
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| 10. |
- Wang, Wei, et al.
(författare)
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Superpixel-Based Segmentation of Polarimetric SAR Images through Two-Stage Merging
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a superpixel-based segmentation method for multilook polarimetric SAR (PolSAR) data. By exploring the PolSAR statistics, a two-stage merging strategy is proposed to improve the segmentation efficiency and accuracy. First, based on the initial superpixel partition, the Wishart-merging stage (WMS) simultaneously merges the regions in homogeneous areas, which can be modelled by the Wishart distribution. The Wishart energy loss together with the edge penalty is utilized so that the merged superpixels are from the same land cover and without ambiguity. In the second stage, the doubly flexible two-parameter KummerU distribution is applied to better characterize the resultant regions from the WMS, which are usually located in heterogeneous areas. This KummerU-merging stage (KUMS) iteratively merges the adjacent regions based on the KummerU energy loss. In addition, the edge penalty and the proposed homogeneity penalty are also adopted to guide the merging procedure, and prevent merging the regions from distinct land covers. Compared with the classical iterative merging methods, the two-stage merging strategy can improve the efficiency based on the WMS, and increase the segmentation accuracy through the KUMS. Two experimental PolSAR datasets acquired by ESAR and EMISAR system are used to demonstrate the effectiveness of the proposed segmentation method.
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