Stabilization of non-admissible curves for a class of nonholonomic systems

The problem of tracking an arbitrary curve in the state space is considered for underactuated driftless control-affine systems. This problem is formulated as the stabilization of a time-varying family of sets associated with a neighborhood of the reference curve. An explicit control design scheme is proposed for the class of controllable systems whose degree of nonholonomy is equal to 1. It is shown that the trajectories of the closed-loop system converge exponentially to any given neighborhood of the reference curve provided that the solutions are defined in the sense of sampling. This convergence property is also illustrated numerically by several examples of nonholonomic systems of degrees 1 and 2.Comment: This is the author's version of the manuscript accepted for publication in the Proceedings of the 2019 European Control Conference (ECC'19

The Investigation of WRAP53 rs2287499 Association with Thyroid Cancer Risk and Prognosis among the Azeri Population in Northwest Iran

Background: TP53 and the oncogene WRAP53 are adjoining genes, producing p53-WRAP53α sense-antisense RNA couples. WRAP53α is indispensable for p53 mRNA regulation and p53 induction following DNA damage. Up-regulated WRAP53β can induce neoplastic transformation and cancer cell survival. All these, along with the associations of WRAP53 single nucleotide polymorphisms with tumor incidence and prognosis, highlighted an impact in human cancers. Considering the importance of WRAP53 in modulating p53, and the frequent occurrence of thyroid cancer, we examined the association of a WRAP53 SNP (rs2287499) with thyroid cancer risk and prognosis among Iranian-Azeri population. Methods: This research was done in Tabriz-IRAN in 2014. DNA samples obtained from 106 patients and 196 controls were subjected to polymerase chain-reaction-based single-strand conformational polymorphism (PCR-SSCP) analysis. Genotypes were characterized by sequencing. Correlations of desired SNP with thyroid cancer as well as age, gender, involved thyroid lobe, lymph node metastasis, tumor type, stage, and size were estimated using Chi-square (χ2) or Fisher's exact tests with a P-value less than 0.05 as significant. Results: rs2287499 is not associated with thyroid cancer predisposition. Except for gender, none of the clinicopathologic factors were significantly linked to the examined genotypes. Conclusions: rs2287499 is not a genetic risk factor for thyroid cancer. Although rs2287499 is not assessable as a biomarker to predict prognosis based on clinicopathologic parameters, the considerable association with gender suggests that this SNP may indirectly be relevant to gender-associated disease manifestation. Further investigations on distinct types of thyroid tumors are needed to fully characterize the rs2287499 status in thyroid malignancies

The Lunar Lander Neutron and Dosimetry (LND) Experiment on Chang'E 4

Chang'E 4 is the first mission to the far side of the Moon and consists of a lander, a rover, and a relay spacecraft. Lander and rover were launched at 18:23 UTC on December 7, 2018 and landed in the von K\'arm\'an crater at 02:26 UTC on January 3, 2019. Here we describe the Lunar Lander Neutron \& Dosimetry experiment (LND) which is part of the Chang'E 4 Lander scientific payload. Its chief scientific goal is to obtain first active dosimetric measurements on the surface of the Moon. LND also provides observations of fast neutrons which are a result of the interaction of high-energy particle radiation with the lunar regolith and of their thermalized counterpart, thermal neutrons, which are a sensitive indicator of subsurface water content.Comment: 38 pages, submitted to Space Science Review

Long and Short-term Metformin Consumption as a Potential Therapy to Prevent Complications of COVID-19

Purpose: The aim of the study is to evaluate the effect of metformin in complication improvement of hospitalized patients with COVID-19. Methods: This was a randomized clinical trial that involved 189 patients with confirmed COVID-19 infection. Patients in the intervention group received metformin-500 mg twice daily. Patients who received metformin before admission were excluded from the control group. Patients who were discharged before taking at least 2000 mg of metformin were excluded from the study. Primary outcomes were vital signs, need for ICU admission, need for intubation, and mortality. Results: Data showed that patients with diabetes with previous metformin in their regimen had lower percentages of ICU admission and death in comparison with patients without diabetes (11.3% vs. 26.1% (P=0.014) and 4.9% vs. 23.9% (P≤0.001), respectively). Admission time characteristics were the same for both groups except for diabetes and hyperlipidemia, which were significantly different between the two groups. Observations of naproxen consumption on endpoints, duration of hospitalization, and the levels of spO2 did not show any significant differences between the intervention and the control group. The adjusted OR for intubation in the intervention group versus the control group was 0.21 [95% CI, 0.04-0.99 (P=0.047)]. Conclusion: In this trial, metformin consumption had no effect on mortality and ICU admission rates in non-diabetic patients. However, metformin improved COVID-19 complications in diabetic patients who had been receiving metformin prior to COVID-19 infection, and it significantly lowered the intubation rates

Characterization Of Inpaint Residuals In Interferometric Measurements of the Epoch Of Reionization

Radio Frequency Interference (RFI) is one of the systematic challenges preventing 21cm interferometric instruments from detecting the Epoch of Reionization. To mitigate the effects of RFI on data analysis pipelines, numerous inpaint techniques have been developed to restore RFI corrupted data. We examine the qualitative and quantitative errors introduced into the visibilities and power spectrum due to inpainting. We perform our analysis on simulated data as well as real data from the Hydrogen Epoch of Reionization Array (HERA) Phase 1 upper limits. We also introduce a convolutional neural network that capable of inpainting RFI corrupted data in interferometric instruments. We train our network on simulated data and show that our network is capable at inpainting real data without requiring to be retrained. We find that techniques that incorporate high wavenumbers in delay space in their modeling are best suited for inpainting over narrowband RFI. We also show that with our fiducial parameters Discrete Prolate Spheroidal Sequences (DPSS) and CLEAN provide the best performance for intermittent ``narrowband'' RFI while Gaussian Progress Regression (GPR) and Least Squares Spectral Analysis (LSSA) provide the best performance for larger RFI gaps. However we caution that these qualitative conclusions are sensitive to the chosen hyperparameters of each inpainting technique. We find these results to be consistent in both simulated and real visibilities. We show that all inpainting techniques reliably reproduce foreground dominated modes in the power spectrum. Since the inpainting techniques should not be capable of reproducing noise realizations, we find that the largest errors occur in the noise dominated delay modes. We show that in the future, as the noise level of the data comes down, CLEAN and DPSS are most capable of reproducing the fine frequency structure in the visibilities of HERA data.Comment: 26 pages, 18 figure

Characterization of inpaint residuals in interferometric measurements of the epoch of reionization

To mitigate the effects of Radio Frequency Interference (RFI) on the data analysis pipelines of 21 cm interferometric instruments, numerous inpaint techniques have been developed. In this paper, we examine the qualitative and quantitative errors introduced into the visibilities and power spectrum due to inpainting. We perform our analysis on simulated data as well as real data from the Hydrogen Epoch of Reionization Array (HERA) Phase 1 upper limits. We also introduce a convolutional neural network that is capable of inpainting RFI corrupted data. We train our network on simulated data and show that our network is capable of inpainting real data without requiring to be retrained. We find that techniques that incorporate high wavenumbers in delay space in their modelling are best suited for inpainting over narrowband RFI. We show that with our fiducial parameters discrete prolate spheroidal sequences (DPSS) and CLEAN provide the best performance for intermittent RFI while Gaussian progress regression (GPR) and least squares spectral analysis (LSSA) provide the best performance for larger RFI gaps. However, we caution that these qualitative conclusions are sensitive to the chosen hyperparameters of each inpainting technique. We show that all inpainting techniques reliably reproduce foreground dominated modes in the power spectrum. Since the inpainting techniques should not be capable of reproducing noise realizations, we find that the largest errors occur in the noise dominated delay modes. We show that as the noise level of the data comes down, CLEAN and DPSS are most capable of reproducing the fine frequency structure in the visibilities

Crude and standardized prevalences of cataract and related factors in the elderly people in Northern Iran

Purpose: This study aims to estimate the crude and standardized prevalences of cataract and its related factors among old people in northern parts of Iran. Methods: This cross-sectional study was carried out among 397 people aged 60 and older in northern Iran. Required information about treated and nontreated cataract was collected using a standard checklist. The World Standard Population was applied for direct standardization. Results: The standardized prevalence (95% confidence interval) of cataract among men, women, and all people were 27.5% (21.2–33.8), 30.9% (24.5–37.4), and 29.1% (24.6–33.6), respectively. Based on multivariate logistic regression models, age over 75 years (OR = 3.03, 95% CI: 1.21–7.59), living alone (OR = 4.89, 95% CI: 1.86‒12.86), diabetes mellitus (odds ratio = 19.10, 95% confidence interval: 8.13–44.89), rheumatoid arthritis (OR = 7.76, 95% CI: 2.32–25.99), history of infectious diseases (OR = 4.02, 95% CI: 1.35‒11.98), hypertension (OR = 3.19, 95% CI: 1.59–6.42), history of ophthalmic surgery (OR = 2.83, 95% CI: 1.29–6.16), history of sedative drug use (OR = 2.71, 95% CI: 1.35–5.47), history of vitamin supplementation use (OR = 0.21, 95% CI: 0.08–0.55), and familial history of cataract (OR = 2.81, 95% confidence interval: 1.38–5.72) increased the odds of cataract. Our multiple logistic regression model explained 53% of the variation in developing cataract. Conclusion: Our study showed that the prevalence of cataract in the study population was relatively high. We also found that aging, living alone, diabetes mellitus, rheumatoid arthritis, hypertension, infectious diseases, ophthalmic surgery, sedative drugs and familial history of cataract were the risk factors of cataract and vitamin supplementations were its protective factors

Phytoremediation of hydrocarbon-contaminated soils with emphasis on the effect of petroleum hydrocarbons on the growth of plant species

To date, many developing countries such as Iran have almost completely abandoned the idea of decontaminating oil-polluted soils due to the high costs of conventional (physical/chemical) soil remediation methods. Phytoremediation is an emerging green technology that can become a promising solution to the problem of decontaminating hydrocarbon-polluted soils. Screening the capacity of native tolerant plant species to grow on aged, petroleum hydrocarbon-contaminated soils is a key factor for successful phytoremediation. This study investigated the effect of hydrocarbon pollution with an initial concentration of 40 000 ppm on growth characteristics of sorghum (Sorghum bicolor) and common flax (Linum usitatissumum). At the end of the experiment, soil samples in which plant species had grown well were analyzed for total petroleum hydrocarbons (TPHs) removal by GC-FID. Common flax was used for the first time in the history of phytoremediation of oil-contaminated soil. Both species showed promising remediation efficiency in highly contaminated soil; however, petroleum hydrocarbon contamination reduced the growth of the surveyed plants significantly. Sorghum and common flax reduced TPHs concentration by 9500 and 18500 mg kg‑1, respectively, compared with the control treatment.À ce jour, plusieurs pays en voie de développement, comme l’Iran, ont presque complètement abandonné l’idée de décontaminer les sols pollués par le pétrole à cause des coûts élevés reliés aux méthodes conventionnelles (physiques/chimiques) de décontamination des sols. La phytoremédiation est une nouvelle technologie verte qui peut s’avérer une solution prometteuse au problème posé par la décontamination des sols pollués par des hydrocarbures. Évaluer la capacité d’espèces indigènes tolérantes à croître sur des sols âgés et pollués par des hydrocarbures de pétrole représente l’une des étapes clé de la phytoremédiation. Au cours de la présente étude, l’effet de la pollution aux hydrocarbures sur les caractéristiques de croissance du sorgho (Sorghum bicolor) et du lin cultivé (Linum usitatissumum) a été évalué à partir d’une concentration initiale de 40 000 ppm. À la fin de d’étude, des échantillons de sols dans lesquels des plantes avaient obtenu un bon taux de croissance ont été analysés à l’aide d’un appareil CG-DIF afin de déterminer les taux d’hydrocarbures pétroliers (THP) totaux enrayés des sols. Le lin cultivé a été utilisé pour la première fois dans l’histoire de la phytoremédiation de sols contaminés par le pétrole. Les deux espèces ont fait preuve d’une efficacité prometteuse dans les sols fortement pollués. Cependant, la pollution par les hydrocarbures de pétrole a réduit de façon significative la croissance des plantes à l’étude. Le sorgho et le lin cultivé ont réduit la concentration en THP de 9 500 et 18 500 mg kg‑1, respectivement, comparativement au traitement témoin