Robust and Communication-Efficient Collaborative Learning

We consider a decentralized learning problem, where a set of computing nodes aim at solving a non-convex optimization problem collaboratively. It is well-known that decentralized optimization schemes face two major system bottlenecks: stragglers' delay and communication overhead. In this paper, we tackle these bottlenecks by proposing a novel decentralized and gradient-based optimization algorithm named as QuanTimed-DSGD. Our algorithm stands on two main ideas: (i) we impose a deadline on the local gradient computations of each node at each iteration of the algorithm, and (ii) the nodes exchange quantized versions of their local models. The first idea robustifies to straggling nodes and the second alleviates communication efficiency. The key technical contribution of our work is to prove that with non-vanishing noises for quantization and stochastic gradients, the proposed method exactly converges to the global optimal for convex loss functions, and finds a first-order stationary point in non-convex scenarios. Our numerical evaluations of the QuanTimed-DSGD on training benchmark datasets, MNIST and CIFAR-10, demonstrate speedups of up to 3x in run-time, compared to state-of-the-art decentralized optimization methods

Molecular diagnosis of Mycoplasma spp. Arthritis by PCR

Background: Arthritis is one of the most common inflammatory diseases worldwide. It is characterized by symptoms such as systemic inflammation and autoantibody production. The molecular mechanisms in pathogenesis of arthritis are not fully understood. Studies show that many microorganisms, including Mycoplasmas, play a role in arthritis. The PCR method is a fast and accurate molecular method for the detection of Mycoplasma genus. The main objective of this study is the detection of Mycoplasma spp arthritis by PCR method.Methods: In this study, 70 samples of synovial fluid collected from Shariati hospital. DNA samples were extracted by phenol-chloroform standard method. Using several Mycoplasma standard strains and 16S rRNA gene target optimized PCR test of Mycoplasma spp. Sensitivity and specificity test were performed on the basis of standard methods and then performed on the DNA extracted of samples.Results: PCR product was amplified by 272 bp and was observed on 2% gel electrophoresis. Specificity test with DNA of other microorganisms showed 100% specificity of these primers. The limit of detection was evaluated 100 copy/reaction. From 70 samples of synovial fluid, 2 samples (3%) were positive and 68 cases (97%) were negative.Conclusion: This study showed that a number of infectious arthritis are Mycoplasma spp at the same time, and the PCR technique can be used as a sensitive and accurate way of early detection of Mycoplasma spp arthritis. 

Designing Mu Robust Controller in Wind Turbine in Cold Weather Conditions

Due to wind turbine is in class of complex nonlinear system so the precise model of this plant is not accessible, therefore it can be categorized as an uncertain model. So, controlling of this system is a demanding topic. Many of schemes which presented for controlling of wind turbines investigate these systems in a good weather condition. However, many turbines work in severe weather condition. In this study, wind turbine is suggested in cold weather, and in ice on turbine blades which they are considered as uncertainties in the model. A robust controller is designed for the wind turbine, to control the pitch angle

The trend of marriage, childbearing, and divorce and its determinants of socioeconomic factors on divorce in Yazd province 2016-2021: A cross-sectional study

Background: In recent decades, families and their stability as an important social institution have changed significantly. Objective: This study aimed to investigate the marriage trends, childbearing, and divorce changes in Yazd province from 2016 to 2021 to estimate the effect of socioeconomic factors on divorce. Materials and Methods: A cross-sectional study was done in 2 phases. In the first phase, an ecological (time trend) was conducted to investigate the 5 yr trend in the occurrence of marriage, childbearing, and divorce, as well as the factors affecting the occurrence of divorce in the second phase. For the second phase of the study, 600 participants were selected. 300 divorced and 300 married applicants were chosen between 2016 and 2021. A binary logistic regression model was used to find the related factors affecting the occurrence of divorce. Results: The results showed a declining marriage (p = 0.05) and childbearing trend (p = 0.84), as well as an increasing trend in divorces (p = 0.02) in Yazd. Logistic regression analysis showed that college education (OR = 0.22, CI: 0.116-0.430, p < 0.001) and being self-employed (OR = 0.48, CI: 0.255-0.934, p = 0.03) could reduce the odds of divorce. In addition, nonresidents (OR = 2.1, CI: 1.314-3.562, p < 0.001), with > 10-yr age differences (OR = 3.8, CI: 1.803-8.213, p < 0.001) or the woman being older than her husband (OR = 3.4, CI: 1.981-5.848, p < 0.001) could increase the odds of divorce. Conclusion: Our results confirmed that a combination of socioeconomic characteristics affects the stability of family institutions. Key words: Family, Marriage, Childbearing, Divorce, Socioeconomic factors

Hydropic leiomyoma, a considerable differential diagnosis: a case series

Uterine leiomyomas can show a wide variety of degenerative changes. In the actual work, we report two cases of hydropic leiomyomas. Hydropic leiomyomas are characterized by a massive intra-tumoral accumulation of watery edema. This variant is often associated to atypical clinical and radiological presentations, raising the possibility of aggressive neoplasms, particularly uterine sarcomas. Although imaging can be helpful to diagnose uterine neoplasms, in particular ultrasounds and MRI, the radiological features of Hydropic leiomyomas, as for other leiomyomas variants, are often atypical and worrisome for uterine sarcomas. The pathological evaluation is often needed to have a final diagnosis.

A promising approach to low electrical percolation threshold in PMMA nanocomposites by using MWCNT-PEO predispersions

Electrical conductive poly(methyl methacrylate) (PMMA) nanocomposites with low percolation threshold are very challenging to be prepared. Here, we show that the miscibility between poly(ethylene oxide) (PEO) as matrix for predispersions of multi-walled carbon nanotubes (MWCNTs) and PMMA represents an efficient approach to achieve very low electrical percolation threshold. PMMA/PEO-MWCNTs nanocomposites were prepared by a two-step solution casting method involving pre-mixing of MWCNTs with PEO and then mixing of PEO-MWCNTs with PMMA, resulting in a PMMA/PEO ratio of 80/20 wt%. The electrical percolation threshold (EPT) value was determined to be ~ 0.07 wt% which is significantly lower than most of the reported EPT values in the literature for PMMA/CNT composites. The very low electrical percolation threshold was attributed to the effectual role of PEO in self-assembly of secondary structures of nanotubes into an electrically conductive network. This was further confirmed by transmission electron microscopy and by comparing the obtained EPT value with the prediction of the excluded volume model in which statistical percolation threshold is defined based on uniform distribution of high-aspect ratio sticks in a matrix. Moreover, based on UV–Vis measurements and linear viscoelastic rheological measurements, optical and rheological percolation thresholds were obtained at nearly 0.01 wt% and 0.5 wt%, respectively