205 research outputs found

    Multi-image-feature-based hierarchical concrete crack identification framework using optimized svm multi-classifiers and d–s fusion algorithm for bridge structures

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    Cracks in concrete can cause the degradation of stiffness, bearing capacity and durability of civil infrastructure. Hence, crack diagnosis is of great importance in concrete research. On the basis of multiple image features, this work presents a novel approach for crack identification of concrete structures. Firstly, the non-local means method is adopted to process the original image, which can effectively diminish the noise influence. Then, to extract the effective features sensitive to the crack, different filters are employed for crack edge detection, which are subsequently tackled by integral projection and principal component analysis (PCA) for optimal feature selection. Moreover, support vector machine (SVM) is used to design the classifiers for initial diagnosis of concrete surface based on extracted features. To raise the classification accuracy, enhanced salp swarm algorithm (ESSA) is applied to the SVM for meta-parameter optimization. The Dempster–Shafer (D–S) fusion algorithm is utilized to fuse the diagnostic results corresponding to different filters for decision making. Finally, to demonstrate the effectiveness of the proposed framework, a total of 1200 images are collected from a real concrete bridge including intact (without crack), longitudinal crack, transverse crack and oblique crack cases. The results validate the performance of proposed method with promising results of diagnosis accuracy as high as 96.25%

    Third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007) in Iran: methods and results on prevalence of diabetes, hypertension, obesity, central obesity, and dyslipidemia

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    <p>Abstract</p> <p>Background</p> <p>The burden of non-communicable diseases is rising globally. This trend seems to be faster in developing countries of the Middle East. In this study, we presented the latest prevalence rates of a number of important non-communicable diseases and their risk factors in the Iranian population.</p> <p>Methods</p> <p>The results of this study are extracted from the third national Surveillance of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007), conducted in 2007. A total of 5,287 Iranian citizens, aged 15–64 years, were included in this survey. Interviewer-administered questionnaires were applied to collect the data of participants including the demographics, diet, physical activity, smoking, history of hypertension, and history of diabetes. Anthropometric characteristics were measured and serum biochemistry profiles were determined on venous blood samples. Diabetes (fasting plasma glucose ≥ 126 mg/dl), hypertension (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg, or use of anti-hypertensive drugs), dyslipidemia (hypertriglyceridemia: triglycerides ≥ 150 mg/dl, hypercholesterolemia: total cholesterol ≥ 200 mg/dl), obesity (body mass index ≥ 30 kg/m<sup>2</sup>), and central obesity (waist circumference ≥ 80 cm in females and ≥ 94 cm in males) were identified and the national prevalence rates were estimated.</p> <p>Results</p> <p>The prevalence of diabetes, hypertension, obesity, and central obesity was 8.7% (95%CI = 7.4–10.2%), 26.6% (95%CI = 24.4–28.9%), 22.3% (95%CI = 20.2–24.5%), and 53.6% (95%CI = 50.4–56.8%), respectively. The prevalence of hypertriglyceridemia and hypercholesterolemia was 36.4% (95%CI = 34.1–38.9%) and 42.9% (95%CI = 40.4–45.4%), respectively. All of the mentioned prevalence rates were higher among females (except hypertriglyceridemia) and urban residents.</p> <p>Conclusion</p> <p>We documented a strikingly high prevalence of a number of chronic non-communicable diseases and their risk factors among Iranian adults. Urgent preventive interventions should be implemented to combat the growing public health problems in Iran.</p

    Path and Ridge Regression Analysis of Seed Yield and Seed Yield Components of Russian Wildrye (Psathyrostachys juncea Nevski) under Field Conditions

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    The correlations among seed yield components, and their direct and indirect effects on the seed yield (Z) of Russina wildrye (Psathyrostachys juncea Nevski) were investigated. The seed yield components: fertile tillers m-2 (Y1), spikelets per fertile tillers (Y2), florets per spikelet- (Y3), seed numbers per spikelet (Y4) and seed weight (Y5) were counted and the Z were determined in field experiments from 2003 to 2006 via big sample size. Y1 was the most important seed yield component describing the Z and Y2 was the least. The total direct effects of the Y1, Y3 and Y5 to the Z were positive while Y4 and Y2 were weakly negative. The total effects (directs plus indirects) of the components were positively contributed to the Z by path analyses. The seed yield components Y1, Y2, Y4 and Y5 were significantly (P<0.001) correlated with the Z for 4 years totally, while in the individual years, Y2 were not significant correlated with Y3, Y4 and Y5 by Peason correlation analyses in the five components in the plant seed production. Therefore, selection for high seed yield through direct selection for large Y1, Y2 and Y3 would be effective for breeding programs in grasses. Furthermore, it is the most important that, via ridge regression, a steady algorithm model between Z and the five yield components was founded, which can be closely estimated the seed yield via the components

    Covalent modification of reduced graphene oxide with piperazine as a novel nanoadsorbent for removal of H2S gas

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    In the present research, piperazine grafted-reduced graphene oxide RGO-N-(piperazine) was synthesized through a three-step reaction and employed as a highly efficient nanoadsorbent for H2S gas removal. Temperature optimization within the range of 30–90 °C was set which significantly improved the adsorption capacity of the nanoadsorbent. The operational conditions including the initial concentration of H2S (60,000 ppm) with CH4 (15 vol%), H2O (10 vol%), O2 (3 vol%) and the rest by helium gas and gas hour space velocity (GHSV) 4000–6000 h−1 were examined on adsorption capacity. The results of the removal of H2S after 180 min by RGO-N-(piperazine), reduced graphene oxide (RGO), and graphene oxide (GO) were reported as 99.71, 99.18, and 99.38, respectively. Also, the output concentration of H2S after 180 min by RGO-N-(piperazine), RGO, and GO was found to be 170, 488, and 369 ppm, respectively. Both chemisorption and physisorption are suggested as mechanism in which the chemisorption is based on an acid–base reaction between H2S and amine, epoxy, hydroxyl functional groups on the surface of RGO-N-(piperazine), GO, and RGO. The piperazine augmentation of removal percentage can be attributed to the presence of amine functional groups in the case of RGO-N-(piperazine) versus RGO and GO. Finally, analyses of the equilibrium models used to describe the experimental data showed that the three-parameter isotherm equations Toth and Sips provided slightly better fits compared to the three-parameter isotherms

    Liver cell therapy: is this the end of the beginning?

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    The prevalence of liver diseases is increasing globally. Orthotopic liver transplantation is widely used to treat liver disease upon organ failure. The complexity of this procedure and finite numbers of healthy organ donors have prompted research into alternative therapeutic options to treat liver disease. This includes the transplantation of liver cells to promote regeneration. While successful, the routine supply of good quality human liver cells is limited. Therefore, renewable and scalable sources of these cells are sought. Liver progenitor and pluripotent stem cells offer potential cell sources that could be used clinically. This review discusses recent approaches in liver cell transplantation and requirements to improve the process, with the ultimate goal being efficient organ regeneration. We also discuss the potential off-target effects of cell-based therapies, and the advantages and drawbacks of current pre-clinical animal models used to study organ senescence, repopulation and regeneration

    Role of Cancer Microenvironment in Metastasis: Focus on Colon Cancer

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    One person on three will receive a diagnostic of cancer during his life. About one third of them will die of the disease. In most cases, death will result from the formation of distal secondary sites called metastases. Several events that lead to cancer are under genetic control. In particular, cancer initiation is tightly associated with specific mutations that affect proto-oncogenes and tumour suppressor genes. These mutations lead to unrestrained growth of the primary neoplasm and a propensity to detach and to progress through the subsequent steps of metastatic dissemination. This process depends tightly on the surrounding microenvironment. In fact, several studies support the point that tumour development relies on a continuous cross-talk between cancer cells and their cellular and extracellular microenvironments. This signaling cross-talk is mediated by transmembrane receptors expressed on cancer cells and stromal cells. The aim of this manuscript is to review how the cancer microenvironment influences the journey of a metastatic cell taking liver invasion by colorectal cancer cells as a model

    The global burden of cancer attributable to risk factors, 2010-19: a systematic analysis for the Global Burden of Disease Study 2019

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    Perturbation and numerical study of double-diffusive dissipative reactive convective flow in an open vertical duct containing a non-darcy porous medium with robin boundary conditions

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    A mathematical model for thermosolutal convection flow in an open two-dimensional vertical channel containing a porous medium saturated with reactive Newtonian fluid is developed and studied. Robin boundary conditions are prescribed, and a first-order homogenous chemical reaction is considered. The Darcy–Forchheimer model is used to simulate both the first- and second-order porous mediums’ drag effects. For the general non-Darcy-case, a numerical solution is presented using the Runge–Kutta quadrature and a shooting method. The influences of thermal (0≤λ1≤15) and solute Grashof numbers (0≤λ2≤20) , Biot numbers (1≤Bi1≤10,Bi2=10) , Brinkman number (0≤Br≤0.5) , first-order chemical reaction parameter (2≤α≤8) , porous medium parameter (2≤σ≤8) and Forchheimer (inertial drag) parameter (0≤I≤12) on the evolutions of velocity, temperature and concentration (species) distributions are visualized graphically. Nusselt number and skin friction at the walls are also computed for specific values of selected parameters. The study is relevant to the analysis of geothermal energy systems with chemical reaction
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