975 research outputs found

    Nonlinear Racking Analysis of Nailed Walls

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    An energy formation of nonlinear analysis of racking resistance of nailed walls is presented. The analysis is dependent on the nonlinear load-slip relationship of nailed connections. The method permits the calculation of the racking force associated with a given horizontal displacement and uses as input data panel geometry, number and spacing of nails, and load distortion relationship of a single connection.Two 4 ft x 8 ft panels with two thicknesses of 1/2 in. and 5/8 in. plywood are analyzed using linear and nonlinear methods, and results of horizontal displacement versus racking force are displayed graphically. It is shown that while the two methods converge at ultimate loads, true representation of wall behavior at low levels of displacement is best described through nonlinear analysis. Good comparison is obtained with a finite element approach

    Arabic spam tweets classification using deep learning

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    With the increased use of social network sites, such as Twitter, attackers exploit these platforms to spread counterfeit content. Such content can be fake advertisements or illegal content. Classifying such content is a challenging task, especially in Arabic. The Arabic language has a complex structure and makes classification tasks more difficult. This paper presents an approach to classifying Arabic tweets using classical machine learning (non-deep machine learning) and deep learning techniques. Tweets corpus were collected through Twitter API and labelled manually to get a reliable dataset. For an efficient classifier, feature extraction is applied to the corpus dataset. Then, two learning techniques are used for each feature extraction technique on the created dataset using N-gram models (uni-gram, bi-gram, and char-gram). The applied classical machine learning algorithms are support vector machines, neural networks, logistics regression, and naïve Bayes. Global vector (GloVe) and fastText learning models are utilised for the deep learning approaches. The Precision, Recall, and F1-score are the suggested performance measures calculated in this paper. Afterwards, the dataset is increased using the synthetic minority oversampling technique class to create a balanced dataset. After applying the classical machine learning models, the experimental results show that the neural network algorithm outperforms the other algorithms. Moreover, the GloVe outperforms the fastText model for the deep learning approach

    A case study with breast cancer and brain metastasis encompassing acute onset of amnesia and altered mental status due to limbic encephalitis - biochemical and proteomic aspects

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    A biochemical case study is reported on a 50-year old lady known to have breast cancer. The woman was treated by mastectomy and this was followed by unraveling brain metastases three years post-diagnosis of the cancer, which was treated by radiation and chemotherapy. Two months after ending her treatment, she exhibited acute changes in her mental status manifested by severe amnesia and fever. A generalized analytical and biochemical assessment revealed the presence of paraneoplastic limbic encephalitis

    Induction of controlled hypoxic pregnancy in large mammalian species.

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    Progress in the study of pregnancy complicated by chronic hypoxia in large mammals has been held back by the inability to measure long-term significant reductions in fetal oxygenation at values similar to those measured in human pregnancy complicated by fetal growth restriction. Here, we introduce a technique for physiological research able to maintain chronically instrumented maternal and fetal sheep for prolonged periods of gestation under significant and controlled isolated chronic hypoxia beyond levels that can be achieved by habitable high altitude. This model of chronic hypoxia permits measurement of materno-fetal blood gases as the challenge is actually occurring. Chronic hypoxia of this magnitude and duration using this model recapitulates the significant asymmetric growth restriction, the pronounced cardiomyopathy, and the loss of endothelial function measured in offspring of high-risk pregnancy in humans, opening a new window of therapeutic research.This work was supported by The British Heart Foundation and The Royal Society. DG is Professor of Cardiovascular Physiology & Medicine at the Department of Physiology Development & Neuroscience at the University of Cambridge, Professorial Fellow and Director of Studies in Medicine at Gonville & Caius College, a Lister Institute Fellow and a Royal Society Wolfson Research Merit Award Holder.This is the final version of the article. It was first available from the American Physiological Society via http://dx.doi.org/10.14814/phy2.1261

    Sildenafil therapy for fetal cardiovascular dysfunction during hypoxic development: studies in the chick embryo.

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    KEY POINTS: Common complications of pregnancy, such as chronic fetal hypoxia, trigger a fetal origin of cardiovascular dysfunction and programme cardiovascular disease in later life. Sildenafil treatment protects placental perfusion and fetal growth, but whether the effects of sildenafil transcend the placenta to affect the fetus is unknown. Using the chick embryo model, here we show that sildenafil treatment directly protects the fetal cardiovascular system in hypoxic development, and that the mechanisms of sildenafil protection include reduced oxidative stress and increased nitric oxide bioavailability; Sildenafil does not protect against fetal growth restriction in the chick embryo, supporting the idea that the protective effect of sildenafil on fetal growth reported in mammalian studies, including humans, is secondary to improved placental perfusion. Therefore, sildenafil may be a good candidate for human translational antioxidant therapy to protect the chronically hypoxic fetus in adverse pregnancy. ABSTRACT: There is a need for developing clinically translatable therapy for preventing fetal origins of cardiovascular disease in pregnancy complicated by chronic fetal hypoxia. Evidence shows that sildenafil protects placental perfusion and fetal growth. However, whether beneficial effects of sildenafil transcend onto the fetal heart and circulation in complicated development is unknown. We isolated the direct effects of sildenafil on the fetus using the chick embryo and hypothesised that sildenafil also protects fetal cardiovascular function in hypoxic development. Chick embryos (n = 11 per group) were incubated in normoxia or hypoxia (14% O2 ) from day 1 and treated with sildenafil (4 mg kg-1  day-1 ) from day 13 of the 21-day incubation. Hypoxic incubation increased oxidative stress (4-hydroxynonenal, 141.1 ± 17.6% of normoxic control), reduced superoxide dismutase (60.7 ± 6.3%), increased phosphodiesterase type 5 expression (167 ± 13.7%) and decreased nitric oxide bioavailability (54.7 ± 6.1%) in the fetal heart, and promoted peripheral endothelial dysfunction (70.9 ± 5.6% AUC of normoxic control; all P < 0.05). Sildenafil treatment after onset of chronic hypoxia prevented the increase in phosphodiesterase expression (72.5 ± 22.4%), protected against oxidative stress (94.7 ± 6.2%) and normalised nitric oxide bioavailability (115.6 ± 22.3%) in the fetal heart, and restored endothelial function in the peripheral circulation (89.8 ± 2.9%). Sildenafil protects the fetal heart and circulation directly in hypoxic development via mechanisms including decreased oxidative stress and enhanced nitric oxide bioavailability. Sildenafil may be a good translational candidate for human antioxidant therapy to prevent fetal origins of cardiovascular dysfunction in adverse pregnancy.British Heart Foundation
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