Inelastic behavior of structural components

A more accurate procedure was developed for the determination of the inelastic behavior of structural components. The actual stress-strain curve for the mathematical of the structure was utilized to generate the force-deformation relationships for the structural elements, rather than using simplified models such as elastic-plastic, bilinear and trilinear approximations. relationships were generated for beam elements with various types of cross sections. In the generational of these curves, stress or load reversals, kinematic hardening and hysteretic behavior were taken into account. Intersections between loading and unloading branches were determined through an iterative process. Using the inelastic properties obtained, the plastic static response of some simple structural systems composed of beam elements was computed. Results were compared with known solutions, indicating a considerable improvement over response predictions obtained by means of simplified approximations used in previous investigations

ALEC: Active learning with ensemble of classifiers for clinical diagnosis of coronary artery disease

Invasive angiography is the reference standard for coronary artery disease (CAD) diagnosis but is expensive and associated with certain risks. Machine learning (ML) using clinical and noninvasive imaging parameters can be used for CAD diagnosis to avoid the side effects and cost of angiography. However, ML methods require labeled samples for efficient training. The labeled data scarcity and high labeling costs can be mitigated by active learning. This is achieved through selective query of challenging samples for labeling. To the best of our knowledge, active learning has not been used for CAD diagnosis yet. An Active Learning with Ensemble of Classifiers (ALEC) method is proposed for CAD diagnosis, consisting of four classifiers. Three of these classifiers determine whether a patient’s three main coronary arteries are stenotic or not. The fourth classifier predicts whether the patient has CAD or not. ALEC is first trained using labeled samples. For each unlabeled sample, if the outputs of the classifiers are consistent, the sample along with its predicted label is added to the pool of labeled samples. Inconsistent samples are manually labeled by medical experts before being added to the pool. The training is performed once more using the samples labeled so far. The interleaved phases of labeling and training are repeated until all samples are labeled. Compared with 19 other active learning algorithms, ALEC combined with a support vector machine classifier attained superior performance with 97.01% accuracy. Our method is justified mathematically as well. We also comprehensively analyze the CAD dataset used in this paper. As part of dataset analysis, features pairwise correlation is computed. The top 15 features contributing to CAD and stenosis of the three main coronary arteries are determined. The relationship between stenosis of the main arteries is presented using conditional probabilities. The effect of considering the number of stenotic arteries on sample discrimination is investigated. The discrimination power over dataset samples is visualized, assuming each of the three main coronary arteries as a sample label and considering the two remaining arteries as sample features

Thyroid Nodules in Children: A Single Institution's Experience

Thyroid nodules in children are uncommon but often present an increased risk of malignancy in comparison to their adult counterpart. Multiple diagnostic modalities are frequently employed to characterize these nodules including ultrasound, radionuclide scans, fine needle aspiration (FNA), thyroid function tests, and evaluation of patient demographics. We chose to evaluate if any of these modalities influence treatment or signify a tendency for a nodule to represent a malignant lesion. A retrospective review of patients <21 years of age who underwent partial or total thyroidectomy from 2004 to 2009 was performed (IRB no. 4695). Other than an FNA indicating a malignancy, there does not appear to be any value to extensive preoperative imaging, nor can patient risk be stratified based upon age. We conclude that there is minimal utility in an extensive preoperative workup in a child with a thyroid nodule

Synthesis of New Organometallic Polymers via Ring-Opening Polymerization of Strained Ferrocenophanes Containing Group 13, 14, or 15 Elements in Bridging Positions

The presence of transition metals in the main chain of synthetic polymers can give rise to unique properties which differ from those of organic polymers. Recently, our group developed a route to strained ferrocenophanes (FCPs) with planar chirality. Through ring-opening polymerization (ROP) of these chiral monomers, new metallopolymers with potentially interesting properties could be obtained. In addition, the chirality of [1]FCPs provided some insight into the mechanism of a ROP process. Following known “Ugi’s amine” chemistry, new dibromoferrocene derivatives with planar-chirality were prepared. The synthesis and characterization of two families of dibromoferrocene derivatives with C2 and C1 symmetry, respectively, are described. Dibromoferrocene derivatives (Sp,Sp)-1,1'-dibromo-2,2'-di(3-pentyl)ferrocene [(Sp,Sp)-107] and (R,R,Sp,Sp)-1,1'-dibromo-2,2'-di(2-butyl)ferrocene [(R,R,Sp,Sp)-108] with C2 symmetry were prepared and fully characterized. The molecular structure of (Sp,Sp)-107 was determined by single-crystal X-ray analysis. The synthesis and characterization of 1,1'-dibromo-2-isopropylferrocene (109) with C1 symmetry is reported in racemic (rac-109) as well as in enantiomerically pure form [(Sp)-109]. Salt-metathesis reactions of the dilithio derivative of (Sp,Sp)-107 with ArʹGaCl2 [Arʹ = 2-(Me2NCH2)C6H4] and Me2SiCl2 afforded novel gallium- and silicon-bridged [1]FCPs (Sp,Sp)-124 and (Sp,Sp)-125, respectively. Salt-metathesis reaction of the dilithio derivative of rac-109 and (Sp)-109 with Me2SiCl2 affords novel silicon-bridged [1]FCPs in both racemic and enantiomerically pure forms [rac-126 and (Sp)-126]. The molecular structure of rac-126 was determined by single-crystal X-ray analysis. Salt-metathesis reaction of the dilithio derivative of (Sp,Sp)-107 with tBuPCl2 yielded new phosphorus-bridged [1]FCPs (127). Compound 127 with C1 symmetry [(Sp,Sp)-127C1] isomerized in reaction mixture to give the Cs-symmetrical phosphorus-bridged [1]FCP meso-127Cs. The molecular structure of meso-127Cs was determined by single-crystal X-ray analysis. DFT calculations were performed to study the structure and understand the extra strain in (Sp,Sp)-127C1. The salt-metathesis reaction of the dilithio derivative of rac-109 and PhPCl2 afforded a mixture of cis and trans isomers of a phosphorus-bridged [1]FCP (rac-130), each present as a racemate. Experimental and theoretical data for the interconversion of cis and trans diastereomers of rac-130, which occurs through inversion at phosphorus, is reported. The molecular structure of the cis isomer rac-130cis was determined by single-crystal X-ray analysis. Differential scanning calorimetry (DSC) thermographs of rac-126, (Sp)-126, and rac-130 suggest that these are potential candidates for thermal ROP. Compounds rac-126 and (Sp)-126 were polymerized via thermal ROP and afforded polymers 132 and 133, respectively. The resulting polymers were characterized by gel permeation chromatography (GPC), nuclear magnetic resonance (NMR) spectroscopy, and carbon-hydrogen-nitrogen (CHN) elemental analysis. The high molecular weight and low polydispersity index (PDI) were determined by triple-detection GPC analysis for polymers 132 and 133. The thermal ROP of silicon-bridged [1]FCP with iPr groups on both Cp rings resulted in polymer 134 which due to solubility issues could not be fully characterized. Thermal ROP of rac-130 was performed and the resulting products were sulfurized for characterization. This ROP afforded both linear polymer (135) and several cyclic phosphines as side products. Polymer 136 was analyzed by GPC, NMR spectroscopy, and CHN analysis. Mass spectra of this mixture revealed the presence of cyclic phosphines from dimers to heptamers. Preparative thin layer chromatography (PTLC) was carried out in order to separate this mixture. Suitable crystals of three different dimers for X-ray analysis were obtained for complete structure determinations

Comparative Evaluation of the efficacy of Laser Therapy and Fibroblastic Growth Factor Injection on Mucosal Wound Healing in Rat Experimental Model

Introduction: The aim of present study was to compare the effects of laser and bFGF treatment on operative wound healing in a rat model.Methods: 66 male Wistar rats were employed in this study. 10millimeter surgical wound was created on buccal mucosa of each rat ,under anesthesia, and then the rats were divided into 3 groups of 22 each: 1- GF group (received subcutaneous injection of bFGF), 2- laser group (treated with low level laser irradiation) and 3- control group (received no treatment). On day 5 half of rats in each group and on day 10 the other half, were sacrificed. Then, samples were taken from rats' buccal mucosa for histological assay and scoring. The data was analyzed with Mann-Whitney test (α=5%).Results: On day5 there was not any significant difference between GF and control group; however laser group showed delayed wound coverage clinically, compared to other groups(p&lt;0.05). On day 10, histological examination demonstrated marked vascular granulation tissue in GF group. Collagen production was significantly prominent in laser group compared to GF treated samples (p=.004). Inflammation of granulation tissue in GF and laser groups was significantly less than that in control samples (p=.005 and .001, respectively). Conclusion: The components of wound matrix induced by GF and laser treatment were significantly different. Although bFGF or laser treatment of oral wounds, under conditions of present study, did not accelerated wound healing but showed some other notable effects on the quality of healing

The efficacy of photodynamic therapy in rat tongue dysplasia

Photodynamic therapy (PDT) using 5-aminolevulinic acid (ALA) has previously shown promising results in cancerous cell destruction. The present study was conducted to evaluate the efficacy of this treatment option on oral epithelial dysplasia in Wistar rats. Furthermore, microscopic effects of systemic versus topical administration of ALA before laser illumination was assessed. Thirty male Wistar rats (200- 250 grams) were used in the present study. Tongue dysplasia was induced by a daily delivery of a 20 ppm solution of 4-nitroquinoline -1- oxide (4NQO) for 3 months. Then, rats were divided into 3 groups of 10 including, group 1 that was received systemic ALA-based PDT (30 mg/kg ALA), group 2 that was received topical ALA-based PDT (20% ALA solution) and group 3 (control) which was left untreated. Tongue specimens were fixed for histopathological evaluation and dysplasia was graded at microscopic level. Data was compared between various treatment groups using Mann Whitney test (p<0.05). The rate of atypical dysplastic cells was decreased significantly in both topical (p= 0.006) and systemic (p= 0.001) treatment groups compared to control group. Furthermore, systemic use of ALA resulted in a remarkable destruction of dysplastic cells compared to its topical application (p=0.045). Nevertheless, some evidence of muscle destruction was documented in systemic ALA group. It seems that ALA mediated PDT is an effective treatment option for the destruction of dysplastic cells. However, the extent of this effect depends on the mode of ALA administration before light illumination

Standardization, certification, maintenance, and dissemination of large scale engineering software systems

A verbatim transcript of the discussion by panel members is presented

Medical Images Encryption Based on Adaptive-Robust Multi-Mode Synchronization of Chen Hyper-Chaotic Systems

In this paper, a novel medical image encryption method based on multi-mode synchronization of hyper-chaotic systems is presented. The synchronization of hyper-chaotic systems is of great significance in secure communication tasks such as encryption of images. Multi-mode synchronization is a novel and highly complex issue, especially if there is uncertainty and disturbance. In this work, an adaptive-robust controller is designed for multimode synchronized chaotic systems with variable and unknown parameters, despite the bounded disturbance and uncertainty with a known function in two modes. In the first case, it is a main system with some response systems, and in the second case, it is a circular synchronization. Using theorems it is proved that the two synchronization methods are equivalent. Our results show that, we are able to obtain the convergence of synchronization error and parameter estimation error to zero using Lyapunov’s method. The new laws to update time-varying parameters, estimating disturbance and uncertainty bounds are proposed such that stability of system is guaranteed. To assess the performance of the proposed synchronization method, various statistical analyzes were carried out on the encrypted medical images and standard benchmark images. The results show effective performance of the proposed synchronization technique in the medical images encryption for telemedicine application.MINECO/ FEDER under the RTI2018-098913-B100 CV20-45250 and A-TIC- 080-UGR18 project

Sensitivity of Four Various Candida Species to Photodynamic Therapy Mediated by Indocyanine Green, an in vitro Study

Statement of the Problem: Various species of candida contribute to oral candidiasis. It is the time to shift from conventional rigid antimicrobial therapies to more patient specific and safer ones. Purpose: The present study aimed to investigate antifungal effects of photodynamic therapy (PDT) using Indocyanine green as photosensitizer and low-power laser irradiation on the viability of candida albicans, candida tropicalis, candida glabrata and candida krusei, and to compare it with Nystatin as the conventional treatment. Materials and Method: In this in vitro study, 0.5 McFarland suspensions of candida's species were prepared (n=50, each). Each strain was then divided into five groups of 10 samples each, according to the following experimental interventions: (1) Nystatin, (2) photodynamic therapy: laser irradiation (wavelength= 808 nm, power= 100 mW, energy density= 10 J/cm2, exposure duration= 100 s) in the presence of the photosensitizer, (3) laser irradiation alone, (4) treatment with the PS alone and (5-control: no exposure to laser light or photosensitizer. Next, serial dilutions were prepared and seeded onto Sabouraud dextrose agar. The colonies were counted, and the values of log (CFU/ml) were analyzed by variance and the Tamhan test (p< 0.05). Results: Photodynamic therapy mediated indocyanine green is significantly effective in reducing the number of CFU/ml of all species of candida tested, compared to control group (p< .001). Nystatin, laser irradiation and photodynamic therapy, with respectively decreasing potency, have considerably reduced the number of candida's colonies in all four bacterial strains (p<. 05). Photosensitizer alone, showed impressive antimicrobial potency against all species of candida except candida albicans, in comparison to control group. Conclusion: It seems that laser therapy alone is more powerful than photodynamic therapy mediated indocyanine green; however, conventional treatment has still the top antimicrobial efficacy towards all candida species

Uncertainty-Aware Semi-supervised Method using Large Unlabelled and Limited Labeled COVID-19 Data

This work was partly supported by the MINECO/ FEDER under the RTI2018-098913-B100, CV20-45250 and A-TIC-080-UGR18 projects.The new coronavirus has caused more than 1 million deaths and continues to spread rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe. The X-ray or computed tomography (CT) images of lungs can reveal whether the patient is infected with COVID-19 or not. Many researchers are trying to improve COVID-19 detection using artificial intelligence. In this paper, relying on Generative Adversarial Networks (GAN), we propose a Semi-supervised Classification using Limited Labelled Data (SCLLD) for automated COVID-19 detection. Our motivation is to develop learning method which can cope with scenarios that preparing labelled data is time consuming or expensive. We further improved the detection accuracy of the proposed method by applying Sobel edge detection. The GAN discriminator output is a probability value which is used for classification in this work. The proposed system is trained using 10,000 CT scans collected from Omid hospital. Also, we validate our system using the public dataset. The proposed method is compared with other state of the art supervised methods such as Gaussian processes. To the best of our knowledge, this is the first time a COVID-19 semi-supervised detection method is presented. Our method is capable of learning from a mixture of limited labelled and unlabelled data where supervised learners fail due to lack of sufficient amount of labelled data. Our semi-supervised training method significantly outperforms the supervised training of Convolutional Neural Network (CNN) in case labelled training data is scarce. Our method has achieved an accuracy of 99.60%, sensitivity of 99.39%, and specificity of 99.80% where CNN (trained supervised) has achieved an accuracy of 69.87%, sensitivity of 94%, and specificity of 46.40%.Spanish Government RTI2018-098913-B100 CV20-45250 A-TIC-080UGR1