Predicting the effects of dimensional and material stiffness variations on a compliant bistable microrelay performance

In this paper we investigate the effects of dimensional and material stiffness variations on a microrelay performance. A linear displacement bistable micromechanism is modelled by pseudo-rigid-body model method and fully characterized. To find the effects of dimensional and material stiffness variation, an analysis of mechanical error is used. The method is a stochastic one and takes into account the random nature of variations. Variations of the contact force and required power of a microrelay example is obtained by the method introduced and the performance of the microrelay is determined. The method introduced is a simple, effective and general that may be used at the design level

Linear Thermal Instability and Formation of Clumpy Gas Clouds Including the Ambipolar Diffusion

Thermal instability is one of the most important processes in the formation of clumpy substructure in magnetic molecular clouds. On the other hand, ambipolar diffusion, or ion-neutral friction, has long been thought to be an important energy dissipation mechanism in these clouds. Thus, we would interested to investigate the effect of ambipolar diffusion on the thermal instability and formation of clumps in the magnetic molecular clouds. For this purpose, in the first step, we turn our attention to the linear perturbation stage. In this way, we obtain a non-dimensional characteristic equation which reduces to the prior characteristic equation in the absence of the magnetic field and ambipolar diffusion. With numerical manipulation of this characteristic equation, we conclude that there are solutions where the thermal instability allows compression along the magnetic field but not perpendicular to it. We infer that this aspect might be an evidence in formation of observed disc-like (oblate) clumps in magnetic molecular clouds.Comment: 20 pages, 11 figures. accepted by MNRA

Cell Cycle Regulation of Stem Cells by MicroRNAs

MicroRNAs (miRNAs) are a class of small non-coding RNA molecules involved in the regulation of gene expression. They are involved in the fine-tuning of fundamental biological processes such as proliferation, differentiation, survival and apoptosis in many cell types. Emerging evidence suggests that miRNAs regulate critical pathways involved in stem cell function. Several miRNAs have been suggested to target transcripts that directly or indirectly coordinate the cell cycle progression of stem cells. Moreover, previous studies have shown that altered expression levels of miRNAs can contribute to pathological conditions, such as cancer, due to the loss of cell cycle regulation. However, the precise mechanism underlying miRNA-mediated regulation of cell cycle in stem cells is still incompletely understood. In this review, we discuss current knowledge of miRNAs regulatory role in cell cycle progression of stem cells. We describe how specific miRNAs may control cell cycle associated molecules and checkpoints in embryonic, somatic and cancer stem cells. We further outline how these miRNAs could be regulated to influence cell cycle progression in stem cells as a potential clinical application

Classification of Compact Polarimetric Synthetic Aperture Radar Images

The RADARSAT Constellation Mission (RCM) was launched in June 2019. RCM, in addition to dual-polarization (DP) and fully quad-polarimetric (QP) imaging modes, provides compact polarimetric (CP) mode data. A CP synthetic aperture radar (SAR) is a coherent DP system in which a single circular polarization is transmitted followed by the reception in two orthogonal linear polarizations. A CP SAR fully characterizes the backscattered field using the Stokes parameters, or equivalently, the complex coherence matrix. This is the main advantage of a CP SAR over the traditional (non-coherent) DP SAR. Therefore, designing scene segmentation and classification methods using CP complex coherence matrix data is advocated in this thesis. Scene classification of remotely captured images is an important task in monitoring the Earth's surface. The high-resolution RCM CP SAR data can be used for land cover classification as well as sea-ice mapping. Mapping sea ice formed in ocean bodies is important for ship navigation and climate change modeling. The Canadian Ice Service (CIS) has expert ice analysts who manually generate sea-ice maps of Arctic areas on a daily basis. An automated sea-ice mapping process that can provide detailed yet reliable maps of ice types and water is desirable for CIS. In addition to linear DP SAR data in ScanSAR mode (500km), RCM wide-swath CP data (350km) can also be used in operational sea-ice mapping of the vast expanses in the Arctic areas. The smaller swath coverage of QP SAR data (50km) is the reason why the use of QP SAR data is limited for sea-ice mapping. This thesis involves the design and development of CP classification methods that consist of two steps: an unsupervised segmentation of CP data to identify homogeneous regions (superpixels) and a labeling step where a ground truth label is assigned to each super-pixel. An unsupervised segmentation algorithm is developed based on the existing Iterative Region Growing using Semantics (IRGS) for CP data and is called CP-IRGS. The constituents of feature model and spatial context model energy terms in CP-IRGS are developed based on the statistical properties of CP complex coherence matrix data. The superpixels generated by CP-IRGS are then used in a graph-based labeling method that incorporates the global spatial correlation among super-pixels in CP data. The classifications of sea-ice and land cover types using test scenes indicate that (a) CP scenes provide improved sea-ice classification than the linear DP scenes, (b) CP-IRGS performs more accurate segmentation than that using only CP channel intensity images, and (c) using global spatial information (provided by a graph-based labeling approach) provides an improvement in classification accuracy values over methods that do not exploit global spatial correlation

Seismic Behavior of Asphaltic Concrete Core Dams

In current years the use of asphaltic concrete core dams are increased especially in some areas with shortage of clayey materials. These dams also have less earth work in comparison with clay core dams. Despite of many advantages of this kind of dam in compression of other types, the behavior of these dams against earthquakes and seismic condition isn\u27t clearly specified. In this research using CA2 program (Finite difference Code) Some numerical studies about the behavior of asphaltic concrete core dams with various height and slopes to understand the influence of dam geometry on behavior of these dams under earthquake condition were done. Application of dams with asphalt concrete core is a relatively novel method especially in Iran. Iran is among regions with high seismicity risk. Therefore, investigation and studying the behavior of such types of dams in earthquake conditions is of more importance considering the novelty of implementing asphaltic core dams. In this research, behavior of asphaltic core dams have been studied under earthquake loading using nonlinear dynamic analysis method and a method is presented for assessment of seismic stability of these types of dams in earthquake conditions based on nonlinear dynamic analysis. Results of the proposed method in this research beside other existing methods can assist designers of asphaltic core dams in judgment about dam stability during earthquake occurrence

Methodology for artificial microswimming using magnetic actuation

We propose a methodology for swimming at low-Reynolds-number flows based on ciliary motion of a microswimmer using magnetic actuation of artificial cilia.By solving the coupled magnetic-elastic-hydrodynamic problem, we demonstrate nonreciprocal effective and recovery strokes for cilia that nicely mimic natural cilia beating. Cilia drag forces, microswimmer net displacement, velocity, and efficiency are calculated, and we show the model can swim using a prespecified magnetic actuation. The proposed methodology can be used for devising biomedical microdevices that swim in viscous flows inside the human body

Single-dose Intravitreal Bevacizumab after Complete Panretinal Photocoagulation in Proliferative Diabetic Retinopathy: an Effective Adjunctive Treatment

Patients with proliferative diabetic retinopathy (PDR) who are refractory to complete panretinal photocoagulation (PRP) have a high risk of severe vision loss. The aim of this study was to evaluate the effectiveness of single-dose intravitreal bevacizumab (IVB) after complete PRP in patients with refractory PDR. Patients with retinal neovascularization (NV) secondary to diabetes mellitus and refractory to complete PRP were enrolled in this study. All patients received a single dose of 1.25 mg IVB at 3 months after completing the PRP. Patients underwent complete ophthalmic evaluation and fluorescein angiography (FA) at baseline and 1 month after injection. The main outcome measure was a reduction in the areas of leakage (mm2) on FA. All patients were evaluated at baseline and on every visit at 1 day, 1 week, and 1 month after the injection. A total of 21 consecutive patients (32 eyes) with PDR completed this study. Thirteen (61.9%) patients were female. The mean ± standard deviation (SD) age was 64.1 ± 5.6 years. Complete and partial response of angiographic leakage of NV was noted in 7 (21.9%) and 18 (56.2%) of 32 eyes after a single IVB injection, respectively. No satisfactory response of retinal NV was observed in 7 eyes (21.9%) at 1 month after the injection. There was a significant difference in age between response groups (partial and complete; 61.9 ± 4.4 years) versus the no-satisfactory response group (67.7 ± 5.9 years) (P = 0.007). No significant ocular or systemic adverse events were observed. A single-dose of IVB could be associated with a satisfactory response of retinal NV, secondary to PDR, in patients who are refractory to complete PRP.Â

Exploring Metabolomic Patterns in Type 2 Diabetes Mellitus and Response to Glucose-Lowering Medications—Review

The spectrum of information related to precision medicine in diabetes generally includes clinical data, genetics, and omics-based biomarkers that can guide personalized decisions on diabetes care. Given the remarkable progress in patient risk characterization, there is particular interest in using molecular biomarkers to guide diabetes management. Metabolomics is an emerging molecular approach that helps better understand the etiology and promises the identification of novel biomarkers for complex diseases. Both targeted or untargeted metabolites extracted from cells, biofluids, or tissues can be investigated by established high-throughput platforms, like nuclear magnetic resonance (NMR) and mass spectrometry (MS) techniques. Metabolomics is proposed as a valuable tool in precision diabetes medicine to discover biomarkers for diagnosis, prognosis, and management of the progress of diabetes through personalized phenotyping and individualized drug-response monitoring. This review offers an overview of metabolomics knowledge as potential biomarkers in type 2 diabetes mellitus (T2D) diagnosis and the response to glucose-lowering medications.</p