A Truncation Method Based on Hermite Expansion for Unknown Source in Space Fractional Diffusion Equation

In this paper we consider the problem for identifying an unknown steady source in a space fractional diffusion equation. A truncation method based on a Hermite function expansion is proposed, and the regularization parameter is chosen by a discrepancy principle. An error estimate between the exact solution and its approximation is given. A numerical implementation is discussed and corresponding results are presented to verify the effectiveness of the method

High Resolution and Fast Response of Humidity Sensor Based on AlN Cantilever with Two Groups of Segmented Electrodes

Resonant cantilever based on piezoelectric materials is one of the most promising platforms for real-time humidity sensing. In this letter, we propose a humidity sensor based on an AlN piezoelectric microcantilever with a high-order resonant mode and a sensing layer of MoS2. The top electrode of cantilever is designed into two groups of segmented electrodes in order to achieve a high intensity of the resonance peak of the cantilever resonator operated at a high-order mode. Compared with the humidity sensor based on a standard cantilever with the same dimension, the sensitivity of the newly proposed humidity sensor is increased from 5.99 to 778 Hz/%RH when the humidity is about 80%RH. The resolution is increased from 0.21%RH to 0.025%RH because of the improvement of the ratio of sensitivity to noise, which cannot be achieved simply by increasing the frequency. The sensor shows a low hysteresis (5.8%) in a wide humidity sensing range from 10%RH to 90%RH. Moreover, the proposed humidity sensor has good short-term repeatability, fast response (0.6 s) and recovery (8 s) to humidity changes, indicating its great potential for fast-response detection

Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing

<p>Abstract</p> <p>Background</p> <p>In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.</p> <p>This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain.</p> <p>Methods</p> <p>The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT) on a pixel level. Overall data were then evaluated using a quantified system.</p> <p>Results</p> <p>The quantified parameters, including the "percent match" (PM) and "correlation ratio" (CR), suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain.</p> <p>Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related.</p> <p>Conclusions</p> <p>Results indicated that, even when using only two sets of non-contrasted MR images, the system is a reliable and efficient method of brain-tumor detection. With further development the system demonstrates high potential for practical clinical use.</p

Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision

A high precision geometric method for automated shoreline detection from Landsat TM and ETM+ imagery is presented. The methodology is based on the application of an algorithm that ensures accurate image geometric registration and the use of a new algorithm for sub-pixel shoreline extraction, both at the sub-pixel level. The analysis of the initial errors shows the influence that differences in reflectance of land cover types have over shoreline detection, allowing us to create a model to substantially reduce these errors. Three correction models were defined according to the type of gain used in the acquisition of the original Landsat images. Error assessment tests were applied on three artificially stabilised coastal segments that have a constant and well-defined land-water boundary. A testing set of 45 images (28 TM, 10 ETM high-gain and 7 ETM low-gain) was used. The mean error obtained in shoreline location ranges from 1.22 to 1.63. m, and the RMSE from 4.69 to 5.47. m. Since the errors follow a normal distribution, then the maximum error at a given probability can be estimated. The results confirm that the use of Landsat imagery for detection of instantaneous coastlines yields accuracy comparable to high-resolution techniques, showing the potential of Landsat TM and ETM images in those applications where the instantaneous lines are a good geomorphological descriptor. © 2012 Elsevier Inc.The authors appreciate the financial support provided by the Spanish Ministerio de Ciencia e Innovacion and the Spanish Plan E in the framework of the Projects CGL2009-14220-C02-01 and CGL2010-19591.Pardo Pascual, JE.; Almonacid Caballer, J.; Ruiz Fernández, LÁ.; Palomar-Vázquez, J. (2012). Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision. Remote Sensing of Environment. 123:1-11. doi:10.1016/j.rse.2012.02.024S11112

Study of e+e−→ppˉe^+e^- \rightarrow p\bar{p} in the vicinity of ψ(3770)\psi(3770)

Using 2917 $\rm{pb}^{-1}$ of data accumulated at 3.773~$\rm{GeV}$, 44.5~$\rm{pb}^{-1}$ of data accumulated at 3.65~$\rm{GeV}$ and data accumulated during a $\psi(3770)$ line-shape scan with the BESIII detector, the reaction $e^+e^-\rightarrow p\bar{p}$ is studied considering a possible interference between resonant and continuum amplitudes. The cross section of $e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p}$, $\sigma(e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p})$, is found to have two solutions, determined to be ($0.059\pm0.032\pm0.012$) pb with the phase angle $\phi = (255.8\pm37.9\pm4.8)^\circ$ ($<$0.11 pb at the 90% confidence level), or $\sigma(e^+e^-\rightarrow\psi(3770)\rightarrow p\bar{p}) = (2.57\pm0.12\pm0.12$) pb with $\phi = (266.9\pm6.1\pm0.9)^\circ$ both of which agree with a destructive interference. Using the obtained cross section of $\psi(3770)\rightarrow p\bar{p}$, the cross section of $p\bar{p}\rightarrow \psi(3770)$, which is useful information for the future PANDA experiment, is estimated to be either ($9.8\pm5.7$) nb ($<17.2$ nb at 90% C.L.) or $(425.6\pm42.9)$ nb

Asymmetric adjustment, non-linearity and housing price bubbles: New international evidence

[[abstract]]In this paper, we detect the housing price bubbles of eighteen OECD countries under assumptions of asymmetric adjustment and non-linearity. To this end, we adopt the momentum threshold autoregressive (MTAR) and exponential smooth transition (ESTR) approaches in this study. In order to consider the possibility of asymmetry between regimes of positive and negative changes in the price-rent ratio, we modify the Kilic (2011) and Park and Shintani (2005, 2016) tests and provide their critical values, finite sample size and power via Monte Carlo simulations. Among the main results, first, it is found that the price-rent ratios of eighteen OECD nations are integrated processes of order one by using the traditional unit root tests. Second, the property of asymmetric adjustment is empirically justified for the housing markets of Belgium, Germany and the US by using the MTAR unit root test. Third, the results of the ESTR-type unit root tests point to the conclusion that the housing markets of thirteen countries are globally stationary ESTR processes, implying that the further the price-rent ratio deviates from its fundamental, the faster will be the speed of mean reversion. Finally, the results of the modified Kilic (2011) and Park and Shintani (2005, 2016) tests are in line with the ESTR unit root tests, indicating that the bubble hypothesis is not accepted.[[notice]]補正完

Pttg1 Promotes Growth of Breast Cancer through P27 Nuclear Exclusion

Background/Aims: A role of Pituitary Tumor Transforming Gene 1 (Pttg1) in the carcinogenesis has been shown in some cancers, but not in BC (BC). Methods: We compared the levels of Pttg1 in the resected BC tissue with the adjacent normal breast tissue from the same patient. We modified Pttg1 levels in a BC cell line, MCF7, by either a Pttg1 transgene, or a Pttg1 shRNA. The cell growth was measured in an MTT assay. The cell apoptosis was measured by apoptosis assay. The nuclear protein of cell-cycle-related genes was examined in Pttg1-modifed BC cells. Co-immunoprecipitation was performed to examine the association of Pttg1 and p27. Results: We detected significantly higher levels of Pttg1 in the resected BC tissue, compared to the adjacent normal breast tissue from the same patient. Overexpression or depletion of Pttg1 in MCF7 significantly increased or inhibited cell growth, respectively. Changes in Pttg1 levels, however, did not alter cell apoptosis, suggesting that Pttg1 increases cell growth through augmented cell proliferation, rather than decreased cell apoptosis. Among all examined cell-cycle-related proteins in Pttg1-modifed BC cells, only nuclear p27 levels were significantly affected. Further, co-immunoprecipitation showed that Pttg1 directly associated with p27. Conclusion: Pttg1 may increase BC cell growth through nuclear exclusion of p27, which highlights a novel molecular regulatory machinery in tumorigenesis of BC