751 Quantitative changes in intracardiac vortices between patients with different ventricular geometry

Aims Over the past decades growing evidence have demonstrated the promising role of intracardiac fluid-dynamics in evaluating cardiac performance. To investigate quantitative changes in vortices parameters in patients with different ventricular geometry. Methods and results We enrolled 50 consecutive patients with one of the following: LV concentric hypertrophy (CH), eccentric hypertrophy (EH), concentric remodelling, and normal LV geometry (CTRL). They underwent a complete echocardiographic examination with intracardiac fluid-dynamic analysis by Color Vector Flow Mapping (Hyperdoppler). The following parameters were obtained: vortex area (VA); vortex length (VL); and vortex depth (VD). Bland Altman Plot has been used to assess intra and inter-observer variability. Mean VD was higher in CR, CH, and EH compared to CTRL (P = 0.013, P = 0.001, and P = 0.022, respectively). Moreover, CH showed higher VL (P = 0.006) and larger VA (P = 0.012) compared to CTRL. A similar trend was noticed in EH patients, despite did not reach statistical significance (P = 0.21 and P = 0.07 for VA and VL, respectively). No significative differences in vortices parameters have been observed between CH and EH. Conclusions This is the first study providing quantitative echocardiographic parameters of vortex location and morphology in different LV geometries. Quantitative fluid-dynamic assessment was feasible and reliable in the whole population.

Komputasi Budaya Untuk Pencarian Gambar Semantik Pada Lukisan Budaya Indonesia Dengan Deteksi Dan Informasi Aliran Lukisan

Lukisan merupakan salah satu gambaran kompleks yang mencerminkan pengamatan dan perasaan seniman terhadap lingkungan. Kondisi ini memperluas kebutuhan akan sistem pendeteksi citra budaya karena masyarakat awam yang kurang memiliki pengalaman artistik akan sulit mendapatkan kesan lukisannya. Oleh karena itu, peneliti menekankan penerapan lukisan budaya Indonesia ke dalam aplikasi mobile. Sistem yang diusulkan telah diimplementasikan pada 239 lukisan budaya Indonesia yang terdiri dari lima kategori gaya lukisan. Kategorinya adalah abstraksionisme, naturalisme, ekspresionisme, realisme, dan romantisme. Sistem mengekstrak 3 fitur, yaitu fitur warna, bentuk, dan tekstur. Ekstraksi ciri warna menggunakan Histogram 3D Color Vector Quantization. Ekstraksi fitur bentuk menggunakan Connected Component Labeling Algorithm (CCL) dengan menghitung nilai area, diameter setara, luas, convex hull, soliditas, eksentrisitas, dan perimeter masing-masing objek. Ekstraksi fitur tekstur menggunakan Gabor Transformation dengan 40 kernel. Sedangkan untuk ekstraksi impresi dilakukan survey terhadap beberapa orang tentang impresi lukisan budaya Indonesia. Survei ini dilakukan terhadap responden yang memahami seni lukis seperti pelukis, pemerhati lukisan, dan orang-orang yang berkecimpung di dunia seni rupa. Untuk menunjukkan gaya lukisan peneliti menggunakan proses klasifikasi menggunakan K-Nearest Neighbor. Hasil eksperimen menunjukan fitur warna sebagai fitur terbaik dalam impression query

An Automated Quantitative Method to Analyze Immunohistochemistry and Immunocytochemistry Images

Immunohistochemistry (IHC) plays an important role in target protein analysis. However, many researchers analyze IHC images by five/three-tier manual ranking methods based on stained area and density. Such manual scoring might be biased by the antibody amount, counterstaining density, overall brightness, and most importantly, researchers' ranking experience. The potential lack of reliability in manual approach drives us to develop an automatic tool to quantitatively analyze IHC, which can also be used for immunocytochemistry (ICC). We applied a “color deconvolution” method based on an red-green-blue (RGB) color vector matching the color of desired immunochemistry agent, 3,3′-diaminobenzidine (DAB) with haematoxylin in this case, to acquire pseudo-color images. Subsequently, Density, the product of integrating the single pixel staining density by area stained, is used as an index of immunostaining. We observed a strong correlation between the results by our automatic method and the manual scoring from experienced researchers, demonstrating the utility of this method in IHC and ICC. For IHC analysis, five-tier ranking based on density (n = 161) shows a high Spearman's coefficient (rho) of 0.80 (P < 0.0001) with the annotation given by two experienced scientists. However, the rho between experienced and inexperienced researchers' annotation (n = 154) is only 0.66 (P < 0.0001). In immunocytochemistry, the rho between density and experienced researchers' annotation is 0.80 (n = 44, P < 0.0001). In conclusion, our method can rank multiple protein targets in immunohistochemistry and may be also used in immunochemistry.

Region of interest extraction for image quality assessment

Print quality (PQ) is most important in the printing industry. To detect and analyze print defects is an effective solution to improve print quality. As the different types of print defects appear in different regions of interest (ROI) in the digital image of a scanned page, extracting the different ROIs helps to detect and analyze the printer defect. This paper proposes a method to extract different ROIs based on the digital image object map [1], which includes three different labels: raster (images or pictures), vector (background and smooth gradient color areas), and symbol (symbols and texts). Our ROI extraction method will extract four kinds of ROIs based on these three labeled objects. So we need to distinguish the background area and smooth gradient color area (color vector) from other vector objects. The process of the ROI extraction method includes four parts; and each part will extract one kind of ROI. For the color vector and background ROI extraction part, we develop two approaches: one is to obtain the maximum area rectangular ROI; and the other approach is to extract the deepest rectangular ROI. With both of these two methods, we use a greedy algorithm to gather additional useful ROIs. In the final result of the ROI extraction process, we only save the left top and right bottom positions for each ROI. In the end, we design a Matlab GUI Tool and label the ROI ground truth manually. We calculate the intersection over union (IoU)) between the ROI extraction result and the ROI manually labeled ground truth to evaluate our ROI extraction algorithm, and check whether it is good enough to crop different ROIs from the image of the scanned page to detect and analyze print defects.

Application of Finite Element Power Flow and Visualization in Rolling Mill Vibration

The power flow harmonic responses of the upper roll system are obtained by combining the speed solution and stress solution, and compare with the traditional harmonic response, we find that the traditional vibration displacement, velocity and acceleration harmonic response spectrum can’t completely reflect the reality of the vibration energy. The power flow vectors of the mill can be obtained with a color vector program developed independently. Compared with the vibration displacement vectors, we found that the displacement vector distribution of the mill is quite different from that of the power flow vector with the frequency of 104Hz: the displacement vector amplitude gradually increases from the bottom to the top of the mill, and the displacement vector is transmitted from bottom to top vertically. The power flow vector amplitude of the working roll and the intermediate roll is larger than that of the other parts, and power flow vectors present complex transfer directions. Similarly, when the considering frequency is taken as other values, the distribution of vibration displacement vector and power flow vector are also variable.

Efficient Mutual Authentication Protocol between Hospital Internet of Things Devices Using Probabilistic Attribute Information

Wearable and portable medical devices are one of the fastest growing sectors in the Internet of Things (IoT) market. However, medical services specialize in the processing of personal health data, which carries issues that are not faced by other industries. In this paper, we propose a multi-dimensional color vector information based IoT device authentication protocol that can provide benefits for medical work, assuming that a hospital has the capability of integrating IoT devices and has access to patient information. The proposed protocol uses multi-dimensional color vectors to help users who use IoT devices to manage their condition in multiple groups, stochastically. In addition, the proposed protocol provides the health and medical service status of users to medical staff in real time using IoT authentication keys generated through the proposed multi-dimensional color vectors. The proposed protocol not only addresses health care problems yet to be tackled in the management of hospital and health services, but also minimizes administrative time and procedures for current medical services. As a result of the performance evaluation, the proposed protocol improved the efficiency of hospital IoT devices by an average of 31.1%, and the time delay for medical services was improved by 19.8%, compared to the existing protocol. By using the proposed protocol and IoT devices, the average overhead of healthcare providers could be reduced by as much as 15.3%.

Using a lentiviral Tet-regulated miR-E shRNA dual color vector to evaluate gene function in human leukemic stem cells in vivo

RNA interference is a powerful tool to study loss-of-gene function in leukemic cells. Still, in order to identify effective novel treatment strategies to target and eradicate leukemic stem cells (LSCs), it is critically important to study gene function in a well-controlled and time-dependent manner. We implemented a lentiviral Tet-regulated miR-E shRNA dual color vector in our in vitro and in vivo human leukemia models. Thus, we were able to efficiently introduce doxycycline-inducible and reversible gene repression and trace and isolate transduced miR-E shRNA expressing cells over time. As proof of concept we focused on the non-canonical PRC1.1 Polycomb complex, which we previously identified to be essential for LSCs (1). Here, we show that inducible downmodulation of PCGF1 strongly impaired the growth of primary MLL-AF9 cells. Next, a Tet-regulated miR-E PCGF1 human xenograft MLL-AF9 leukemia mouse model was established, which revealed that early knockdown of PCGF1 at the onset of leukemia development significantly reduced peripheral blood chimerism levels and improved overall survival. In contrast, knockdown of PCGF1 when leukemia was already firmly established in the bone marrow proved insufficient to enhance overall survival. Despite these findings, FACS analysis of MLL-AF9/miR-E PCGF1/CD45+/GFP+ populations suggested that particularly cells with inefficient PCGF1 knockdown contributed to leukemogenesis. In conclusion, by building in vivo xenograft leukemia inducible RNAi models, we show that timing of gene knockdown critically impacts on the efficacy of leukemia treatment and that clonal drift still plays a major role in the escape of LSCs.