Approximation solution for steel concrete beam accounting high-order shear deformation using trigonometric-series

Steel concrete beams have a reasonable structure in terms of using material and high load carrying capacity. This paper deals with an approximate solution based on a trigonometric series for the static of steel concrete beams. The displacement field is based on the higher-order theory using Reddy’s hypothesis. The governing equations are derived from variation principles. An approximate solution based on the representation of displacement fields by trigonometric series is developed to solve the static problem of steel concrete beams. In order to verify the accuracy of the present approximate solution, numerical results are compared with those of exact solutions using classical beam theory. The displacements and nominal stress distributions in the depth direction are obtained with various high of beams. The present approximate approach can accurately predict the displacements and stresses of steel concrete beams

Approximation solution for steel concrete beam accounting high-order shear deformation using trigonometric-series

Steel concrete beams have a reasonable structure in terms of using material and high load carrying capacity. This paper deals with an approximate solution based on a trigonometric series for the static of steel concrete beams. The displacement field is based on the higher-order theory using Reddy’s hypothesis. The governing equations are derived from variation principles. An approximate solution based on the representation of displacement fields by trigonometric series is developed to solve the static problem of steel concrete beams. In order to verify the accuracy of the present approximate solution, numerical results are compared with those of exact solutions using classical beam theory. The displacements and nominal stress distributions in the depth direction are obtained with various high of beams. The present approximate approach can accurately predict the displacements and stresses of steel concrete beams

Gene Family Abundance Visualization based on Feature Selection Combined Deep Learning to Improve Disease Diagnosis

Advancements in machine learning in general and in deep learning in particular have achieved great success in numerous fields. For personalized medicine approaches, frameworks derived from learning algorithms play an important role in supporting scientists to investigate and explore novel data sources such as metagenomic data to develop and examine methodologies to improve human healthcare. Some challenges when processing this data type include its very high dimensionality and the complexity of diseases. Metagenomic data that include gene families often have millions of features. This leads to a further increase of complexity in processing and requires a huge amount of time for computation. In this study, we propose a method combining feature selection using perceptron weight-based filters and synthetic image generation to leverage deep-learning advancements in order to predict various diseases based on gene family abundance data. An experiment was conducted using gene family datasets of five diseases, i.e. liver cirrhosis, obesity, inflammatory bowel diseases, type 2 diabetes, and colorectal cancer. The proposed method provides not only visualization for gene family abundance data but also achieved a promising performance level

Kinetic modeling of essential oil hydro-distillation from peels of pomelo (Citrus grandis L.) fruit grown in Southern Vietnam

Thorough understanding of kinetics plays a key role in improving existing industrial processes. In this study, we attempted to model the kinetics of the hydro-distillation process that produces essential oil from peels of pomelo (Citrus grandis L.) fruit, which is a product with high economic value and a wide range of applications. We first determined the optimal water-to-material ratio for attaining maximal oil yield. Then, further experimental attempts were carried out at different distillation rates to generate experimental data to fit three kinetic models, namely first-order kinetics model, instantaneous washing, followed by diffusion model and simultaneous washing and diffusion model. Overall, the three models have well described the experimental kinetic data on hydro-distillation (R2> 90%). Of which, the simultaneous washing and diffusion model attaining the R2 of 99.97% was chosen as the most suitable to describe the kinetics of the extraction process. Estimated parameters also shown that the washing stage occurs more rapidly than the later, diffusion stage. GC-MS results showed that the obtained oil sample was characterized by the dominance of the D-Limonene compound (97.873%)

Cider Production from King Mandarin (Citrus nobilis Lour.) and Its Antioxidant Activity

With the necessity of diversifying alcoholic beverages, cider has become a kind of drink that can fulfill this demand. This is because the cider will be diversified depending on the kinds of fruit that are chosen to be used for the cider fermentation. Therefore, this study aims to investigate the effects of dilution ratio, Brix, pH, and yeast concentration on the production of cider from king mandarin (Citrus nobilis Lour.), and to evaluate the analytical characteristics and antioxidant activity of the product. After the investigation, it can be claimed that the dilution of the juice causes the ethanol content to decrease, whereas the increase of Brix, pH, and yeast concentration makes the ethanol content increase. However, the proportional increase in the ethanol content with Brix, pH, and yeast concentration has its limitations. Specifically, when the Brix and the yeast concentrations were, respectively, higher than 16°Brix and 0.04%, the ethanol content tended to maintain the same. This is also the same when the pH was lower than 4.5. In addition, by using the DPPH and ABTS●+ methods, the antioxidant activity of cider is estimated to be lower than the one of the juice before fermentation, which is smaller than 3.78 times for the DPPH method and 3.76 times for the ABTS●+ method

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Effects of ultrasound support and carboxymethyl cellulose on the physicochemical properties, sensory evaluation and total microbiology of cloudy juice from soursop (

This study investigated the influence of the carboxymethyl cellulose (CMC) addition on several quality indicators of soursop juice, including pH, dissolved solids, Lab* criteria, vitamin C, total plate count (TPC) content, microbiology, and sensory qualities. The content of CMC was allowed to vary from 0.01-0.05 to 0.2% under sonication. The addition of CMC seemed to induce color changes, with total difference color (TDC) being proportionally related to CMC content. Oxidant resistance in fresh samples was 0.62 ± 0.04 mg GAE / mL and then increased at 0.05% CMC. A similar trend was also observed with the vitamin C values of the product. Visual qualities of the product were evaluated with a focus on appearance, color, and flavor with descriptive terms in a typical white liquid and odorless. Comparison with ISO quality standard indicates that the final product met with microbiological requirements

BRAZILIAN ARCHIVES OF BIOLOGY AND TECHNOLOGY A N I N T E R N A T I O N A L J O U R N A L Cloning and Overexpression of GmDREB2 Gene from a Vietnamese Drought-resistant Soybean Variety

ABSTRACT This work studied the amplification, cloning and determination of the GmDREB2 gene from the soybean cultivar DT2008 and five Vietnamese local soybean cultivars (DT26, DT51, DVN5, CB, CBD) and designed the vector carrying the structure containing GmDREB2 gene from cultivar DT2008 (best drought tolerant). The coding region of GmDREB2 gene isolated from six soybean cultivars was 480 nucleotides in length, encoding 159 amino acids. The recombinant structure was designed as 35S-GmDREB2-c-myc and its expression was analysed in transgenic tobacco plants. Recombinant DREB2 protein was expressed in five transgenic tobacco lines with molecular weights close to 20 kDa. During the drought conditions, the proline accumulation of the transgenic tobacco lines was higher than on wild-type (WT) plant